@Article{ TheisBFRRBETB2016, title = {Benchmarking Spike Rate Inference in Population Calcium Imaging}, journal = {Neuron}, year = {2016}, month = {5}, volume = {90}, number = {3}, pages = {471–482}, abstract = {A fundamental challenge in calcium imaging has been to infer spike rates of neurons from the measured noisy fluorescence traces. We systematically evaluate different spike inference algorithms on a large benchmark dataset (>100,000 spikes) recorded from varying neural tissue (V1 and retina) using different calcium indicators (OGB-1 and GCaMP6). In addition, we introduce a new algorithm based on supervised learning in flexible probabilistic models and find that it performs better than other published techniques. Importantly, it outperforms other algorithms even when applied to entirely new datasets for which no simultaneously recorded data is available. Future data acquired in new experimental conditions can be used to further improve the spike prediction accuracy and generalization performance of the model. Finally, we show that comparing algorithms on artificial data is not informative about performance on real data, suggesting that benchmarking different methods with real-world datasets may greatly facilitate future algorithmic developments in neuroscience.}, web_url = {http://www.sciencedirect.com/science/article/pii/S0896627316300733}, state = {published}, DOI = {10.1016/j.neuron.2016.04.014}, author = {Theis L{lucas}{Research Group Computational Vision and Neuroscience}; Berens P{berens}{Research Group Computational Vision and Neuroscience}; Froudarakis E; Reimer J; Rom{\'a}n Ros{\'o}n M; Baden T; Euler T; Tolias AS{atolias}; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}} } @Article{ CadwellPJBDYRSBTST2015, title = {Electrophysiological, transcriptomic and morphologic profiling of single neurons using Patch-seq}, journal = {Nature Biotechnology}, year = {2016}, month = {2}, volume = {34}, number = {2}, pages = {199–203}, abstract = {Despite the importance of the mammalian neocortex for complex cognitive processes, we still lack a comprehensive description of its cellular components. To improve the classification of neuronal cell types and the functional characterization of single neurons, we present Patch-seq, a method that combines whole-cell electrophysiological patch-clamp recordings, single-cell RNA-sequencing and morphological characterization. Following electrophysiological characterization, cell contents are aspirated through the patch-clamp pipette and prepared for RNA-sequencing. Using this approach, we generate electrophysiological and molecular profiles of 58 neocortical cells and show that gene expression patterns can be used to infer the morphological and physiological properties such as axonal arborization and action potential amplitude of individual neurons. Our results shed light on the molecular underpinnings of neuronal diversity and suggest that Patch-seq can facilitate the classification of cell types in the nervous system.}, web_url = {http://www.nature.com/nbt/journal/v34/n2/pdf/nbt.3445.pdf}, state = {published}, DOI = {10.1038/nbt.3445}, author = {Cadwell CR; Palasantza A; Jiang X; Berens P{berens}{Research Group Computational Vision and Neuroscience}; Deng Q; Yilmaz M; Reimer J; Shen S; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}; Tolias KF; Sandberg R; Tolias AS{atolias}} } @Article{ EckerDBT2016, title = {On the Structure of Neuronal Population Activity under Fluctuations in Attentional State}, journal = {Journal of Neuroscience}, year = {2016}, month = {2}, volume = {36}, number = {5}, pages = {1775-1789}, abstract = {Attention is commonly thought to improve behavioral performance by increasing response gain and suppressing shared variability in neuronal populations. However, both the focus and the strength of attention are likely to vary from one experimental trial to the next, thereby inducing response variability unknown to the experimenter. Here we study analytically how fluctuations in attentional state affect the structure of population responses in a simple model of spatial and feature attention. In our model, attention acts on the neural response exclusively by modulating each neuron's gain. Neurons are conditionally independent given the stimulus and the attentional gain, and correlated activity arises only from trial-to-trial fluctuations of the attentional state, which are unknown to the experimenter. We find that this simple model can readily explain many aspects of neural response modulation under attention, such as increased response gain, reduced individual and shared variability, increased correlations with firing rates, limited range correlations, and differential correlations. We therefore suggest that attention may act primarily by increasing response gain of individual neurons without affecting their correlation structure. The experimentally observed reduction in correlations may instead result from reduced variability of the attentional gain when a stimulus is attended. Moreover, we show that attentional gain fluctuations, even if unknown to a downstream readout, do not impair the readout accuracy despite inducing limited-range correlations, whereas fluctuations of the attended feature can in principle limit behavioral performance.}, web_url = {http://www.jneurosci.org/content/36/5/1775.full.pdf+html}, state = {published}, DOI = {10.1523/JNEUROSCI.2044-15.2016}, author = {Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Denfield GH; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Article{ JiangSCBSEPT2015, title = {Principles of connectivity among morphologically defined cell types in adult neocortex}, journal = {Science}, year = {2015}, month = {11}, volume = {350}, number = {6264}, pages = {1055: 1-10}, abstract = {Since the work of Ramón y Cajal in the late 19th and early 20th centuries, neuroscientists have speculated that a complete understanding of neuronal cell types and their connections is key to explaining complex brain functions. However, a complete census of the constituent cell types and their wiring diagram in mature neocortex remains elusive. By combining octuple whole-cell recordings with an optimized avidin-biotin-peroxidase staining technique, we carried out a morphological and electrophysiological census of neuronal types in layers 1, 2/3, and 5 of mature neocortex and mapped the connectivity between more than 11,000 pairs of identified neurons. We categorized 15 types of interneurons, and each exhibited a characteristic pattern of connectivity with other interneuron types and pyramidal cells. The essential connectivity structure of the neocortical microcircuit could be captured by only a few connectivity motifs.}, web_url = {http://www.sciencemag.org/content/350/6264/aac9462.full.pdf}, state = {published}, DOI = {10.1126/science.aac9462}, EPUB = {aac9462}, author = {Jiang X; Shen S; Cadwell CR; Berens P{berens}; Sinz F{fabee}; Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Patel S; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Article{ YatsenkoJEFCT2015, title = {Improved Estimation and Interpretation of Correlations in Neural Circuits}, journal = {PLoS Computational Biology}, year = {2015}, month = {3}, volume = {11}, number = {3}, pages = {1-28}, abstract = {Ambitious projects aim to record the activity of ever larger and denser neuronal populations in vivo. Correlations in neural activity measured in such recordings can reveal important aspects of neural circuit organization. However, estimating and interpreting large correlation matrices is statistically challenging. Estimation can be improved by regularization, i.e. by imposing a structure on the estimate. The amount of improvement depends on how closely the assumed structure represents dependencies in the data. Therefore, the selection of the most efficient correlation matrix estimator for a given neural circuit must be determined empirically. Importantly, the identity and structure of the most efficient estimator informs about the types of dominant dependencies governing the system. We sought statistically efficient estimators of neural correlation matrices in recordings from large, dense groups of cortical neurons. Using fast 3D random-access laser scanning microscopy of calcium signals, we recorded the activity of nearly every neuron in volumes 200 μm wide and 100 μm deep (150–350 cells) in mouse visual cortex. We hypothesized that in these densely sampled recordings, the correlation matrix should be best modeled as the combination of a sparse graph of pairwise partial correlations representing local interactions and a low-rank component representing common fluctuations and external inputs. Indeed, in cross-validation tests, the covariance matrix estimator with this structure consistently outperformed other regularized estimators. The sparse component of the estimate defined a graph of interactions. These interactions reflected the physical distances and orientation tuning properties of cells: The density of positive ‘excitatory’ interactions decreased rapidly with geometric distances and with differences in orientation preference whereas negative ‘inhibitory’ interactions were less selective. Because of its superior performance, this ‘sparse+latent’ estimator likely provides a more physiologically relevant representation of the functional connectivity in densely sampled recordings than the sample correlation matrix.}, web_url = {http://www.ploscompbiol.org/article/fetchObject.action?uri=info:doi/10.1371/journal.pcbi.1004083&representation=PDF}, state = {published}, DOI = {10.1371/journal.pcbi.1004083}, EPUB = {e1004083}, author = {Yatsenko D; Josić K; Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Froudarakis E; Cotton RJ; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Article{ EckerT2014, title = {Is there signal in the noise?}, journal = {Nature Neuroscience}, year = {2014}, month = {6}, volume = {17}, number = {6}, pages = {750-751}, abstract = {A study now shows that variability in neuronal responses in the visual system mainly arises from slow fluctuations in excitability, presumably caused by factors of nonsensory origin, such as arousal, attention or anesthesia.}, web_url = {http://www.nature.com/neuro/journal/v17/n6/pdf/nn.3722.pdf}, state = {published}, DOI = {10.1038/nn.3722}, author = {Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Article{ FroudarakisBECSYSBT2014, title = {Population code in mouse V1 facilitates readout of natural scenes through increased sparseness}, journal = {Nature Neuroscience}, year = {2014}, month = {6}, volume = {17}, number = {6}, pages = {851–857}, abstract = {Neural codes are believed to have adapted to the statistical properties of the natural environment. However, the principles that govern the organization of ensemble activity in the visual cortex during natural visual input are unknown. We recorded populations of up to 500 neurons in the mouse primary visual cortex and characterized the structure of their activity, comparing responses to natural movies with those to control stimuli. We found that higher order correlations in natural scenes induced a sparser code, in which information is encoded by reliable activation of a smaller set of neurons and can be read out more easily. This computationally advantageous encoding for natural scenes was state-dependent and apparent only in anesthetized and active awake animals, but not during quiet wakefulness. Our results argue for a functional benefit of sparsification that could be a general principle governing the structure of the population activity throughout cortical microcircuits.}, web_url = {http://www.nature.com/neuro/journal/v17/n6/pdf/nn.3707.pdf}, state = {published}, DOI = {10.1038/nn.3707}, author = {Froudarakis E; Berens P{berens}{Research Group Computational Vision and Neuroscience}; Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Cotton RJ; Sinz FH{fabee}{Research Group Computational Vision and Neuroscience}{Research Group Computational Vision and Neuroscience}; Yatsenko D; Saggau P; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Article{ EckerBCSDCSBT2014, title = {State Dependence of Noise Correlations in Macaque Primary Visual Cortex}, journal = {Neuron}, year = {2014}, month = {4}, volume = {82}, number = {1}, pages = {235–248}, abstract = {Shared, trial-to-trial variability in neuronal populations has a strong impact on the accuracy of information processing in the brain. Estimates of the level of such noise correlations are diverse, ranging from 0.01 to 0.4, with little consensus on which factors account for these differences. Here we addressed one important factor that varied across studies, asking how anesthesia affects the population activity structure in macaque primary visual cortex. We found that under opioid anesthesia, activity was dominated by strong coordinated fluctuations on a timescale of 1–2 Hz, which were mostly absent in awake, fixating monkeys. Accounting for these global fluctuations markedly reduced correlations under anesthesia, matching those observed during wakefulness and reconciling earlier studies conducted under anesthesia and in awake animals. Our results show that internal signals, such as brain state transitions under anesthesia, can induce noise correlations but can also be estimated and accounted for based on neuronal population activity.}, web_url = {http://www.sciencedirect.com/science/article/pii/S0896627314001044}, state = {published}, DOI = {10.1016/j.neuron.2014.02.006}, author = {Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Berens P{berens}{Research Group Computational Vision and Neuroscience}; Cotton RJ; Subramaniyan M; Denfield GH; Cadwell CR; Smirnakis SM{ssmirnakis}{Department Physiology of Cognitive Processes}; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Article{ SubramaniyanEBT2013, title = {Macaque Monkeys Perceive the Flash Lag Illusion}, journal = {PLoS ONE}, year = {2013}, month = {3}, volume = {8}, number = {3}, pages = {1-10}, abstract = {Transmission of neural signals in the brain takes time due to the slow biological mechanisms that mediate it. During such delays, the position of moving objects can change substantially. The brain could use statistical regularities in the natural world to compensate neural delays and represent moving stimuli closer to real time. This possibility has been explored in the context of the flash lag illusion, where a briefly flashed stimulus in alignment with a moving one appears to lag behind the moving stimulus. Despite numerous psychophysical studies, the neural mechanisms underlying the flash lag illusion remain poorly understood, partly because it has never been studied electrophysiologically in behaving animals. Macaques are a prime model for such studies, but it is unknown if they perceive the illusion. By training monkeys to report their percepts unbiased by reward, we show that they indeed perceive the illusion qualitatively similar to humans. Importantly, the magnitude of the illusion is smaller in monkeys than in humans, but it increases linearly with the speed of the moving stimulus in both species. These results provide further evidence for the similarity of sensory information processing in macaques and humans and pave the way for detailed neurophysiological investigations of the flash lag illusion in behaving macaques.}, web_url = {http://www.plosone.org/article/fetchObject.action?uri=info%3Adoi%2F10.1371%2Fjournal.pone.0058788&representation=PDF}, state = {published}, DOI = {10.1371/journal.pone.0058788}, EPUB = {e58788}, author = {Subramaniyan M; Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Berens P{berens}{Research Group Computational Vision and Neuroscience}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Article{ BerensECMBT2012, title = {A Fast and Simple Population Code for Orientation in Primate V1}, journal = {Journal of Neuroscience}, year = {2012}, month = {8}, volume = {32}, number = {31}, pages = {10618-10626}, abstract = {Orientation tuning has been a classic model for understanding single-neuron computation in the neocortex. However, little is known about how orientation can be read out from the activity of neural populations, in particular in alert animals. Our study is a first step toward that goal. We recorded from up to 20 well isolated single neurons in the primary visual cortex of alert macaques simultaneously and applied a simple, neurally plausible decoder to read out the population code. We focus on two questions: First, what are the time course and the timescale at which orientation can be read out from the population response? Second, how complex does the decoding mechanism in a downstream neuron have to be to reliably discriminate between visual stimuli with different orientations? We show that the neural ensembles in primary visual cortex of awake macaques represent orientation in a way that facilitates a fast and simple readout mechanism: With an average latency of 30–80 ms, the population code can be read out instantaneously with a short integration time of only tens of milliseconds, and neither stimulus contrast nor correlations need to be taken into account to compute the optimal synaptic weight pattern. Our study shows that—similar to the case of single-neuron computation—the representation of orientation in the spike patterns of neural populations can serve as an exemplary case for understanding the computations performed by neural ensembles underlying visual processing during behavior.}, web_url = {http://www.jneurosci.org/content/32/31/10618.full.pdf+html}, state = {published}, DOI = {10.1523/​JNEUROSCI.1335-12.2012}, author = {Berens P; Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Cotton RJ; Ma WJ; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Article{ EckerBTB2011, title = {The effect of noise correlations in populations of diversely tuned neurons}, journal = {Journal of Neuroscience}, year = {2011}, month = {10}, volume = {31}, number = {40}, pages = {14272-14283}, abstract = {The amount of information encoded by networks of neurons critically depends on the correlation structure of their activity. Neurons with similar stimulus preferences tend to have higher noise correlations than others. In homogeneous populations of neurons, this limited range correlation structure is highly detrimental to the accuracy of a population code. Therefore, reduced spike count correlations under attention, after adaptation, or after learning have been interpreted as evidence for a more efficient population code. Here, we analyze the role of limited range correlations in more realistic, heterogeneous population models. We use Fisher information and maximum-likelihood decoding to show that reduced correlations do not necessarily improve encoding accuracy. In fact, in populations with more than a few hundred neurons, increasing the level of limited range correlations can substantially improve encoding accuracy. We found that this improvement results from a decrease in noise entropy that is associated with increasing correlations if the marginal distributions are unchanged. Surprisingly, for constant noise entropy and in the limit of large populations, the encoding accuracy is independent of both structure and magnitude of noise correlations.}, web_url = {http://www.jneurosci.org/content/31/40/14272.full.pdf+html}, state = {published}, DOI = {10.1523/​JNEUROSCI.2539-11.2011}, author = {Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Berens P{berens}{Research Group Computational Vision and Neuroscience}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}} } @Article{ KuTLG2011, title = {fMRI of the Face-Processing Network in the Ventral Temporal Lobe of Awake and Anesthetized Macaques}, journal = {Neuron}, year = {2011}, month = {4}, volume = {70}, number = {2}, pages = {352-362}, abstract = {The primate brain features specialized areas devoted to processing of faces, which human imaging studies localized in the superior temporal sulcus (STS) and ventral temporal cortex. Studies in macaque monkeys, in contrast, revealed face selectivity predominantly in the STS. While this discrepancy could result from a true species difference, it may simply be the consequence of technical difficulties in obtaining high-quality MR images from the ventral temporal lobe. By using an optimized fMRI protocol we here report face-selective areas in ventral TE, the parahippocampal cortex, the entorhinal cortex, and the hippocampus of awake macaques, in addition to those already known in the STS. Notably, the face-selective activation of these memory-related areas was observed although the animals were passively viewing and it was preserved even under anesthesia. These results point to similarly extensive cortical networks for face processing in humans and monkeys and highlight potential homologs of the human fusiform face area.}, web_url = {http://www.sciencedirect.com/science?_ob=MImg&_imagekey=B6WSS-52R37RY-C-S&_cdi=7054&_user=29041&_pii=S0896627311002054&_origin=gateway&_coverDate=04%2F28%2F2011&_sk=999299997&view=c&wchp=dGLbVtz-zSkWb&md5=b6710cd9134892714e88e07b1c5ccd35&ie=/sdarticle.pdf}, state = {published}, DOI = {10.1016/j.neuron.2011.02.048}, author = {Ku SP{shihpi}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}; Goense J{jozien}{Department Physiology of Cognitive Processes}} } @Article{ BerensEGTB2011, title = {Reassessing optimal neural population codes with neurometric functions}, journal = {Proceedings of the National Academy of Sciences of the United States of America}, year = {2011}, month = {3}, volume = {108}, number = {11}, pages = {4423-4428}, abstract = {Cortical circuits perform the computations underlying rapid perceptual decisions within a few dozen milliseconds with each neuron emitting only a few spikes. Under these conditions, the theoretical analysis of neural population codes is challenging, as the most commonly used theoretical tool—Fisher information—can lead to erroneous conclusions about the optimality of different coding schemes. Here we revisit the effect of tuning function width and correlation structure on neural population codes based on ideal observer analysis in both a discrimination and a reconstruction task. We show that the optimal tuning function width and the optimal correlation structure in both paradigms strongly depend on the available decoding time in a very similar way. In contrast, population codes optimized for Fisher information do not depend on decoding time and are severely suboptimal when only few spikes are available. In addition, we use the neurometric functions of the ideal observer in the classification task to investigate the differential coding properties of these Fisher-optimal codes for fine and coarse discrimination. We find that the discrimination error for these codes does not decrease to zero with increasing population size, even in simple coarse discrimination tasks. Our results suggest that quite different population codes may be optimal for rapid decoding in cortical computations than those inferred from the optimization of Fisher information.}, web_url = {http://www.pnas.org/content/108/11/4423.full.pdf+html}, state = {published}, DOI = {10.1073/pnas.1015904108}, author = {Berens P{berens}{Research Group Computational Vision and Neuroscience}; Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Gerwinn S{sgerwinn}{Research Group Computational Vision and Neuroscience}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}} } @Article{ 6855, title = {Local field potentials, BOLD and spiking activity: Relationships and physiological mechanisms}, journal = {Nature Precedings}, year = {2010}, month = {11}, volume = {2010}, pages = {1-27}, abstract = {Extracellular voltage fluctuations (local field potentials, LFPs) reflecting neural mass action are ubiquitous across species and brain regions. Numerous studies have characterized the properties of LFP signals in the cortex to study sensory and motor computations as well as cognitive processes like attention, perception and memory. In addition, its extracranial counterpart – the electroencephalogram – is widely used in clinical applications. However, the link between LFP signals and the underlying activity of local populations of neurons is still largely elusive. For the LFP to aid our understanding of cortical computation, however, we need to know as precisely as possible what aspects of neural mass action it reflects. In this chapter, we examine recent advances and results regarding the origin, the feature selectivity and the spatial resolution of the local field potential and discuss its relationship to local spiking activity as well as the BOLD signal used in fMRI. We place particular focus on the gamm a-band of the local field potential since it has long been implicated to play an important role in sensory processing. We conclude that in contrast to spikes, the local field potential does not measure the output of the computation performed by a cortical circuit, but are rather indicative of the synaptic and dendritic processes, as well as the dynamics of cortical computation.}, file_url = {/fileadmin/user_upload/files/publications/BerensEtAl2010_LFP_[0].pdf}, web_url = {http://precedings.nature.com/documents/5216/version/1/files/npre20105216-1.pdf}, state = {published}, DOI = {10101/npre.2010.5216.1}, author = {Berens P{berens}{Research Group Computational Vision and Neuroscience}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Article{ 6683, title = {The Role of the Primary Visual Cortex in Perceptual Suppression of Salient Visual Stimuli}, journal = {Journal of Neuroscience}, year = {2010}, month = {9}, volume = {30}, number = {37}, pages = {12353-12365}, abstract = {The role of primary visual cortex (area V1) in subjective perception has intrigued students of vision for decades. Specifically, the extent to which the activity of different types of cells (monocular versus binocular) and electrophysiological signals (i.e. local field potentials versus spiking activity) reflect perception is still debated. To address these questions we recorded from area V1 of the macaque using tetrodes during the paradigm of binocular flash suppression, where incongruent images presented dichoptically compete for perceptual dominance. We found that the activity of a minority (20%) of neurons reflect the perceived visual stimulus and these cells exhibited perceptual modulations substantially weaker in comparison to their sensory modulation induced by congruent stimuli. Importantly, perceptual modulations were found equally often for monocular and binocular cells, demonstrating that perceptual competition in V1 involves mechanisms across both types of neurons. The power of the local field pot ential (LFP) also showed moderate perceptual modulations with similar percentages of sites showing significant effects across frequency bands (18-22%). The possibility remains that perception may be strongly reflected in more elaborate aspects of activity in V1 circuits (e.g. specific neuronal subtypes) or perceptual states might have a modulatory role on more intricate aspects of V1 firing patterns (e.g. synchronization), not necessarily altering the firing rates of single cells or the LFP power dramatically.}, web_url = {http://www.jneurosci.org/cgi/reprint/30/37/12353}, state = {published}, DOI = {10.1523/JNEUROSCI.0677-10.2010}, author = {Keliris GA{george}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Article{ 6257, title = {Decorrelated Neuronal Firing in Cortical Microcircuits}, journal = {Science}, year = {2010}, month = {1}, volume = {327}, number = {5965}, pages = {584-587}, abstract = {Correlated trial-to-trial variability in the activity of cortical neurons is thought to reflect the functional connectivity of the circuit. Many cortical areas are organized into functional columns, in which neurons are believed to be densely connected and to share common input. Numerous studies report a high degree of correlated variability between nearby cells. We developed chronically implanted multitetrode arrays offering unprecedented recording quality to reexamine this question in the primary visual cortex of awake macaques. We found that even nearby neurons with similar orientation tuning show virtually no correlated variability. Our findings suggest a refinement of current models of cortical microcircuit architecture and function: Either adjacent neurons share only a few percent of their inputs or, alternatively, their activity is actively decorrelated.}, web_url = {http://www.sciencemag.org/cgi/reprint/327/5965/584.pdf}, state = {published}, DOI = {10.1126/science.1179867}, author = {Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Berens P{berens}{Research Group Computational Vision and Neuroscience}; Keliris GA{george}{Department Physiology of Cognitive Processes}; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Article{ 5157, title = {Generating Spike Trains with Specified Correlation Coefficients}, journal = {Neural Computation}, year = {2009}, month = {2}, volume = {21}, number = {2}, pages = {397-423}, abstract = {Spike trains recorded from populations of neurons can exhibit substantial pairwise correlations between neurons and rich temporal structure. Thus, for the realistic simulation and analysis of neural systems, it is essential to have efficient methods for generating artificial spike trains with specified correlation structure. Here we show how correlated binary spike trains can be simulated by means of a latent multivariate gaussian model. Sampling from the model is computationally very efficient and, in particular, feasible even for large populations of neurons. The entropy of the model is close to the theoretical maximum for a wide range of parameters. In addition, this framework naturally extends to correlations over time and offers an elegant way to model correlated neural spike counts with arbitrary marginal distributions.}, file_url = {/fileadmin/user_upload/files/publications/macke2009_5157[0].pdf}, web_url = {http://www.mitpressjournals.org/doi/pdf/10.1162/neco.2008.02-08-713}, state = {published}, DOI = {10.1162/neco.2008.02-08-713}, author = {Macke JH{jakob}; Berens P{berens}{Research Group Computational Vision and Neuroscience}; Ecker AS{aecker}; Tolias AS{atolias}; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}} } @Article{ 5614, title = {Feature selectivity of the gamma-band of the local field potential in primate primary visual cortex}, journal = {Frontiers in Neuroscience}, year = {2008}, month = {12}, volume = {2}, number = {2}, pages = {199-207}, abstract = {Extra-cellular voltage fluctuations (local field potentials; LFPs) reflecting neural mass action are ubiquitous across species and brain regions. Numerous studies have characterized the properties of LFP signals in the cortex to study sensory and motor computations as well as cognitive processes like attention, perception and memory. In addition, its extracranial counterpart – the electroencelphalogram (EEG) – is widely used in clinical applications. However, the link between LFP signals and the underlying activity of local populations of neurons remains largely elusive. Here, we review recent work elucidating the relationship between spiking activity of local neural populations and LFP signals. We focus on oscillations in the gamma-band (30-90Hz) of the local field potential in the primary visual cortex (V1) of the macaque that dominate during visual stimulation. Given that in area V1 much is known about the properties of single neurons and the cortical architecture, it provides an excellent opportunity to study the mechanisms underlying the generation of the local field potential.}, web_url = {http://frontiersin.org/neuroscience/paper/10.3389/neuro.01/037.2008/pdf/}, state = {published}, DOI = {10.3389/neuro.01.037.2008}, author = {Berens P{berens}{Research Group Computational Vision and Neuroscience}; Keliris GA{george}{Department Physiology of Cognitive Processes}; Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Article{ 5205, title = {Comparing the feature selectivity of the gamma-band of the local field potential and the underlying spiking activity in primate visual cortex}, journal = {Frontiers in Systems Neuroscience}, year = {2008}, month = {6}, volume = {2}, number = {2}, pages = {1-11}, abstract = {The local field potential (LFP), comprised of low-frequency extra-cellular voltage fluctuations, has been used extensively to study the mechanisms of brain function. In particular, oscillations in the gamma-band (30–90 Hz) are ubiquitous in the cortex of many species during various cognitive processes. Surprisingly little is known about the underlying biophysical processes generating this signal. Here, we examine the relationship of the local field potential to the activity of localized populations of neurons by simultaneously recording spiking activity and LFP from the primary visual cortex (V1) of awake, behaving macaques. The spatial organization of orientation tuning and ocular dominance in this area provides an excellent opportunity to study this question, because orientation tuning is organized at a scale around one order of magnitude finer than the size of ocular dominance columns. While we find a surprisingly weak correlation between the preferred orientation of multi-unit activity and gamma-band LFP recorded on the same tetrode, there is a strong correlation between the ocular preferences of both signals. Given the spatial arrangement of orientation tuning and ocular dominance, this leads us to conclude that the gamma-band of the LFP seems to sample an area considerably larger than orientation columns. Rather, its spatial resolution lies at the scale of ocular dominance columns.}, web_url = {http://www.frontiersin.org/systemsneuroscience/paper/10.3389/neuro.06/002.2008/pdf/}, state = {published}, DOI = {10.3389/neuro.06.002.2008}, author = {Berens P{berens}{Research Group Computational Vision and Neuroscience}; Keliris GA{george}{Department Physiology of Cognitive Processes}; Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Article{ 4824, title = {fMRI of the temporal lobe of the awake monkey at 7 T}, journal = {NeuroImage}, year = {2008}, month = {2}, volume = {39}, number = {3}, pages = {1081-1093}, abstract = {Increasingly 7 T scanners are used for fMRI of humans and non-human primates, promising improvements in signal-to-noise, spatial resolution and specificity. A disadvantage of fMRI at 7 T, but already at 3 T, is that susceptibility artifacts from air-filled cavities like the ear canal and nasal cavity cause signal loss and distortion. This limits the applicability of fMRI in these areas, thereby limiting study of these areas, but it also limits study of processes that span large-scale cortical networks or the entire brain. Our goal is to study the inferior temporal (IT) lobe in awake monkeys because of its importance in object perception and recognition, but the functional signal is degraded by strong susceptibility gradients. To allow fMRI of this region, we used an optimized SE-EPI, which recovers signal lost with GE-EPI and we corrected for susceptibility-induced image distortion. SE-EPI has the added advantage that, in contrast to GE-EPI, where the functional signal derives to a large extent from veins, th e SE-EPI signal arises from the microvasculature, and hence it better represents the neural activation. We show fMRI at 7 T of the entire visual pathway in the awake primate with robust and widespread activation in all ventral areas of the brain, including areas adjacent to the ear canal. This allows fMRI of areas that normally suffer from artifact and thus more reliable whole-brain studies.}, web_url = {http://www.sciencedirect.com/science?_ob=MImg&_imagekey=B6WNP-4PT2960-1-S&_cdi=6968&_user=29041&_orig=search&_coverDate=10%2F01%2F2007&_sk=999999999&view=c&wchp=dGLbVzb-zSkWA&md5=f951a759c6655f02492ab5f09f1a9e42&ie=}, state = {published}, DOI = {10.1016/j.neuroimage.2007.09.038}, author = {Goense JBM{jozien}{Department Physiology of Cognitive Processes}; Ku S-P{shihpi}{Department Physiology of Cognitive Processes}; Merkle H{hellmut}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Article{ 4788, title = {Recording Chronically from the same Neurons in Awake, Behaving Primates}, journal = {Journal of Neurophysiology}, year = {2007}, month = {12}, volume = {98}, number = {6}, pages = {3780-3790}, abstract = {Understanding the mechanisms of learning requires characterizing how the response properties of individual neurons and interactions across populations of neurons change over time. In order to study learning in-vivo, we need the ability to track an electrophysiological signature that uniquely identifies each recorded neuron for extended periods of time. We have identified such an extracellular signature using a statistical framework which allows quantification of the accuracy by which stable neurons can be identified across successive recording sessions. Our statistical framework uses spike waveform information recorded on a tetrode’s four channels in order to define a measure of similarity between neurons recorded across time. We use this framework to quantitatively demonstrate for the first time the ability to record from the same neurons across multiple consecutive days and weeks. The chronic recording techniques and methods of analyses we report can be used to characterize the changes in brain circuits du e to learning.}, web_url = {http://jn.physiology.org/cgi/reprint/00260.2007v1}, state = {published}, DOI = {10.1152/jn.00260.2007}, author = {Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Siapas AG; Hoenselaar A{hoenselaar}{Department Physiology of Cognitive Processes}; Keliris GA{george}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Article{ 4775, title = {A method for generating a “purely first-order” dichoptic motion stimulus}, journal = {Journal of Vision}, year = {2007}, month = {6}, volume = {7}, number = {8:7}, pages = {1-10}, abstract = {In the present technical article, we describe a method for generating a new dichoptic motion stimulus, the monocular components of which are dynamic random noise without constant figural cues for feature-tracking-based motion. Our dichoptic motion stimulus adds a new line of evidence, which supports the original conclusion of M. Shadlen and T. Carney (1986) that motion detection can be solely derived from early binocular motion processing. Further, we describe novel motion displays in which monocular motion and binocular motion are in opposite directions with variable intensity ratios. Our dichoptic stimuli will serve as a useful tool to investigate the interaction between low-level binocular motion detectors and monocular motion detectors without requiring feature extraction before motion detection.}, web_url = {http://www.journalofvision.org/7/8/7/Hayashi-2007-jov-7-8-7.pdf}, state = {published}, DOI = {10.1167/7.8.7}, author = {Hayashi R{hayashi}{Department Physiology of Cognitive Processes}; Nishida S; Tolias A{atolias}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Article{ 3827, title = {Spatial specificity of BOLD versus cerebral blood volume fMRI for mapping cortical organization}, journal = {Journal of Cerebral Blood Flow and Metabolism}, year = {2007}, month = {1}, volume = {27}, number = {6}, pages = {1248-1261}, abstract = {Intravascular contrast agents are used in functional magnetic resonance imaging to obtain cerebral blood volume (CBV) maps of cortical activity. Cerebral blood volume imaging with MION (monocrystalline-iron-oxide-nanoparticles) increases the sensitivity of functional imaging compared with the blood oxygenation level-dependent (BOLD) signal (Leite et al, 2002; Mandeville et al, 1998; Vanduffel et al, 2001). It therefore represents an attractive method for obtaining detailed maps of cortical organization (Vanduffel et al, 2001; Zhao et al, 2005). However, it remains to be determined how the spatial profile of CBV maps of cortical activity derived with MION compares with the profile of BOLD activation maps under a variety of different stimulation conditions. We used several stimulation paradigms to compare the spatial specificity of CBV versus BOLD activation maps in macaque area V1 at 4.7 T. We observed that: (1) CBV modulation is relatively stronger in deep cortical layers compared with BOLD, in agreement with studies in cats (Harel et al, 2006) and rodents (Lu et al, 2004; Mandeville and Marota, 1999) and (2) surprisingly, under large surround stimulation conditions, CBV maps extend along the cortical surface to cover large (&gt;10 mm) regions of the cortex that are devoid of significant BOLD modulation. We conclude that the spatial profiles of BOLD and CBV activity maps do not coregister across all stimulus conditions, and therefore do not necessarily represent equivalent transforms of the neural response. Cerebral blood volume maps should be interpreted with care, in the context of the particular experimental paradigm applied.}, web_url = {http://www.nature.com/jcbfm/journal/v27/n6/pdf/9600434a.pdf}, state = {published}, DOI = {10.1038/sj.jcbfm.9600434}, author = {Smirnakis SM{ssmirnakis}{Department Physiology of Cognitive Processes}; Schmid MC{mschmid}; Weber B{bweber}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Augath M{mark}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Article{ 4379, title = {Direct and Indirect Activation of Cortical Neurons by Electrical Microstimulation}, journal = {Journal of Neurophysiology}, year = {2006}, month = {4}, volume = {96}, number = {2}, pages = {512-521}, abstract = {Electrical microstimulation has been used to elucidate cortical function. This review discusses neuronal excitability and effective current spread estimated by using three different methods: 1) single-cell recording, 2) behavioral methods, and 3) functional magnetic resonance imaging (fMRI). The excitability properties of the stimulated elements in neocortex obtained using these methods were found to be comparable. These properties suggested that microstimulation activates the most excitable elements in cortex, that is, by and large the fibers of the pyramidal cells. Effective current spread within neocortex was found to be greater when measured with fMRI compared with measures based on single-cell recording or behavioral methods. The spread of activity based on behavioral methods is in close agreement with the spread based on the direct activation of neurons (as opposed to those activated synaptically). We argue that the greater activation with imaging is attributed to transynaptic spread, which includes sub threshold activation of sites connected to the site of stimulation. The definition of effective current spread therefore depends on the neural event being measured.}, web_url = {http://jn.physiology.org/cgi/reprint/96/2/512}, state = {published}, DOI = {10.1152/jn.00126.2006}, author = {Tehovnik EJ; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Sultan F; Slocum WM; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Article{ 4479, title = {Mapping Cortical Activity Elicited with Electrical Microstimulation Using fMRI in the Macaque}, journal = {Neuron}, year = {2005}, month = {12}, volume = {48}, number = {6}, pages = {901-911}, abstract = {Over the last two centuries, electrical microstimulation has been used to demonstrate causal links between neural activity and specific behaviors and cognitive functions. However, to establish these links it is imperative to characterize the cortical activity patterns that are elicited by stimulation locally around the electrode and in other functionally connected areas. We have developed a technique to record brain activity using the blood oxygen level dependent (BOLD) signal while applying electrical microstimulation to the primate brain. We find that the spread of activity around the electrode tip in macaque area V1 was larger than expected from calculations based on passive spread of current and therefore may reflect functional spread by way of horizontal connections. Consistent with this functional transynaptic spread we also obtained activation in expected projection sites in extrastriate visual areas, demonstrating the utility of our technique in uncovering in vivo functional connectivity maps.}, web_url = {http://www.sciencedirect.com/science?_ob=MImg&_imagekey=B6WSS-4HVMT2J-7-2&_cdi=7054&_user=29041&_orig=browse&_coverDate=12%2F22%2F2005&_sk=999519993&view=c&wchp=dGLbVzb-zSkWz&md5=72ecd52a491258a743a50f885045465e&ie=/sdarticle.pdf}, state = {published}, DOI = {10.1016/j.neuron.2005.11.034}, author = {Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Sultan F; Augath MA{mark}{Department Physiology of Cognitive Processes}; Oeltermann A{axel}; Tehovnik EJ; Schiller PH; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Article{ 3726, title = {Neuroscience: Rewiring the adult brain (Reply)}, journal = {Nature}, year = {2005}, month = {11}, volume = {438}, number = {7065}, pages = {E3-E4}, abstract = {We disagree with Calford et al. that there is a consensus on adult plasticity in primate V1 cortex: for example, macaque area V1 cytochrome oxidase levels remained depressed for several months after binocular retinal lesions; no reorganization in macaque V1 after monocular retinal lesions was found; and no area V1 reorganization in a patient with macular degeneration was detected.}, web_url = {http://www.nature.com/nature/journal/v438/n7065/abs/nature04360.html}, state = {published}, DOI = {10.1038/nature04360}, author = {Smirnakis SM{ssmirnakis}{Department Physiology of Cognitive Processes}; Schmid MC{mschmid}; Brewer AA; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Sch\"uz A{schuez}{Department Physiology of Cognitive Processes}; Augath MA{mark}{Department Physiology of Cognitive Processes}; Inhoffen W; Wandell BA; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Article{ 4480, title = {Reply to "Motion processing in macaque V4"}, journal = {Nature Neuroscience}, year = {2005}, month = {9}, volume = {8}, number = {9}, pages = {1125-1125}, web_url = {http://www.nature.com/neuro/journal/v8/n9/pdf/nn0905-1125b.pdf}, state = {published}, DOI = {10.1038/nn0905-1125b}, author = {Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Keliris GA{george}{Department Physiology of Cognitive Processes}; Smirnakis SM{ssmirnakis}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Article{ 3325, title = {Lack of long-term cortical reorganization after macaque retinal lesions}, journal = {Nature}, year = {2005}, month = {5}, volume = {435}, number = {7040}, pages = {300-307}, abstract = {Several aspects of cortical organization are thought to remain plastic into adulthood, allowing cortical sensorimotor maps to be modified continuously by experience. This dynamic nature of cortical circuitry is important for learning, as well as for repair after injury to the nervous system. Electrophysiology studies suggest that adult macaque primary visual cortex (V1) undergoes large-scale reorganization within a few months after retinal lesioning, but this issue has not been conclusively settled. Here we applied the technique of functional magnetic resonance imaging (fMRI) to detect changes in the cortical topography of macaque area V1 after binocular retinal lesions. fMRI allows non-invasive, in vivo, long-term monitoring of cortical activity with a wide field of view, sampling signals from multiple neurons per unit cortical area. We show that, in contrast with previous studies, adult macaque V1 does not approach normal responsivity during 7.5 months of follow-up after retinal lesions, and its topography does not change. Electrophysiology experiments corroborated the fMRI results. This indicates that adult macaque V1 has limited potential for reorganization in the months following retinal injury.}, web_url = {http://www.nature.com/nature/journal/v435/n7040/abs/nature03495.html;jsessionid=2A77D316DEC3A65D47341EF03D079D49}, state = {published}, DOI = {10.1038/nature03495}, author = {Smirnakis SM{ssmirnakis}{Department Physiology of Cognitive Processes}; Brewer AA; Schmid MC{mschmid}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Sch\"uz A{schuez}{Department Physiology of Cognitive Processes}; Augath M{mark}{Department Physiology of Cognitive Processes}; Inhoffen W; Wandell BA; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Article{ 3329, title = {Neurons in macaque area V4 acquire directional tuning after adaptation to motion stimuli}, journal = {Nature Neuroscience}, year = {2005}, month = {5}, volume = {8}, number = {5}, pages = {591-593}, abstract = {Macaque area V4 neurons are generally not selective for direction of motion, as judged from their response to directional stimuli presented after a baseline condition devoid of movement (classical paradigm). We used a motion-adaptation paradigm to investigate whether stimulation history influences direction-of-motion selectivity. We found that classically non-directional V4 neurons develop direction-of-motion selectivity after adaptation. This underscores the dynamic nature of functional cortical architecture.}, web_url = {http://www.nature.com/neuro/journal/v8/n5/pdf/nn1446.pdf}, state = {published}, DOI = {10.1038/nn1446}, author = {Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Keliris GA{george}{Department Physiology of Cognitive Processes}; Smirnakis SM{ssmirnakis}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Article{ 4481, title = {Are express saccades generated under natural viewing conditions?}, journal = {European Journal of Neuroscience}, year = {2004}, month = {11}, volume = {20}, number = {9}, pages = {2467-2473}, abstract = {To assess whether express saccades are generated under everyday conditions, we collected eye movement data from Rhesus monkeys engaged in free viewing under a variety of conditions. The durations of the fixation periods that occurred between saccades were calculated. The results show that while short-duration fixations within the range of express saccades occur quite commonly, the overall distribution is unimodal. This is the case even when all the object elements in the visual scene have the same contrast. The findings suggest that while saccades that fall within the express range occur commonly under natural viewing conditions, bimodal distributions of saccadic latencies are obtainable only under laboratory conditions.}, web_url = {http://www.blackwell-synergy.com/doi/pdf/10.1111/j.1460-9568.2004.03663.x}, state = {published}, DOI = {10.1111/j.1460-9568.2004.03663.x}, author = {Schiller PH; Slocum WM; Carvey C; Tolias AS{atolias}} } @Article{ 2067, title = {Integration of Local Features into Global Shapes: Monkey and Human fMRI Studies}, journal = {Neuron}, year = {2003}, month = {1}, volume = {37}, number = {2}, pages = {333-346}, abstract = {The integration of local image features into global shapes was investigated in monkeys and humans using fMRI. An adaptation paradigm was used, in which stimulus selectivity was deduced by changes in the course of adaptation of a pattern of randomly oriented elements. Accordingly, we observed stronger activity when orientation changes in the adapting stimulus resulted in a collinear contour than a different random pattern. This selectivity to collinear contours was observed not only in higher visual areas that are implicated in shape processing, but also in early visual areas where selectivity depended on the receptive field size. These findings suggest that unified shape perception in both monkeys and humans involves multiple visual areas that may integrate local elements to global shapes at different spatial scales.}, file_url = {/fileadmin/user_upload/files/publications/pdf2067.pdf}, web_url = {http://www.sciencedirect.com/science?_ob=MImg&_imagekey=B6WSS-47STJPB-K-H&_cdi=7054&_user=29041&_orig=browse&_coverDate=01%2F23%2F2003&_sk=999629997&view=c&wchp=dGLbVlz-zSkzS&md5=456e08b25ca9888e6292a3139f0e3102&ie=/sdarticle.pdf}, state = {published}, DOI = {10.1016/S0896-6273(02)01174-1}, author = {Kourtzi Z{zoe}{Department Human Perception, Cognition and Action}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Altmann CF{altmann}{Department Human Perception, Cognition and Action}; Augath M{mark}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Article{ 53, title = {Motion Processing in the Macaque: Revisited with Functional Magnetic Resonance Imaging}, journal = {Journal of Neuroscience}, year = {2001}, month = {11}, volume = {21}, number = {21}, pages = {8594-8601}, abstract = {A great deal is known about the response properties of single neurons processing sensory information. In contrast, less is understood about the collective characteristics of networks of neurons that may underlie sensory capacities of animals. We used functional magnetic resonance imaging to study the emergent properties of populations of neurons processing motion across different brain areas. Using a visual adaptation paradigm, we localized a distributed network of visual areas that process information about the direction of motion as expected from single-cell recording studies. However, we found an apparent discrepancy between the directional signals in certain visual areas as measured with blood oxygenation level-dependent imaging compared with an estimate based on the spiking of single neurons. We propose a hypothesis that may account for this difference based on the postulate that neuronal selectivity is a function of the state of adaptation. Consequently, neurons classically thought to lack information about certain attributes of the visual scene may nevertheless receive and process this information. We further hypothesize that this adaptation-dependent selectivity may arise from intra- or inter-area cellular connections, such as feedback from higher areas. This network property may be a universal principle the computational goal of which is to enhance the ability of neurons in earlier visual areas to adapt to statistical regularities of the input and therefore increase their sensitivity to detect changes along these stimulus dimensions.}, web_url = {http://www.jneurosci.org/content/21/21/8594.long}, state = {published}, author = {Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Smirnakis SM{ssmirnakis}{Department Physiology of Cognitive Processes}; Augath MA{mark}{Department Physiology of Cognitive Processes}; Trinath T{torsten}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Article{ 4482, title = {Eye Movements Modulate Visual Receptive Fields of V4 Neurons}, journal = {Neuron}, year = {2001}, month = {3}, volume = {29}, number = {3}, pages = {757-767}, abstract = {The receptive field, defined as the spatiotemporal selectivity of neurons to sensory stimuli, is central to our understanding of the neuronal mechanisms of perception. However, despite the fact that eye movements are critical during normal vision, the influence of eye movements on the structure of receptive fields has never been characterized. Here, we map the receptive fields of macaque area V4 neurons during saccadic eye movements and find that receptive fields are remarkably dynamic. Specifically, before the initiation of a saccadic eye movement, receptive fields shrink and shift towards the saccade target. These spatiotemporal dynamics may enhance information processing of relevant stimuli during the scanning of a visual scene, thereby assisting the selection of saccade targets and accelerating the analysis of the visual scene during free viewing.}, web_url = {http://www.sciencedirect.com/science?_ob=MImg&_imagekey=B6WSS-4CC2XVR-11-1G&_cdi=7054&_user=29041&_orig=browse&_coverDate=03%2F31%2F2001&_sk=999709996&view=c&wchp=dGLbVzb-zSkzS&md5=fc30470f6f315c4ff1d0a0a9b3764f4a&ie=/sdarticle.pdf}, state = {published}, author = {Tolias AS{atolias}; Moore T; Smirnakis SM{ssmirnakis}; Tehovnik EJ; Siapas AG; Schiller PH} } @Article{ 4484, title = {Visual representations during saccadic eye movements}, journal = {Proceedings of the National Academy of Sciences of the United States of America}, year = {1998}, month = {7}, volume = {95}, number = {15}, pages = {8981-8984}, abstract = {n normal vision, shifts of attention are usually followed by saccadic eye movements. Neurons in extrastriate area V4 are modulated by focal attention when eye movements are withheld, but they also respond in advance of visually guided saccadic eye movements. We have examined the visual selectivity of saccade-related responses of area V4 neurons in monkeys making delayed eye movements to receptive field stimuli of varying orientation. This task did not require the monkey to attend to orientation per se but merely to foveate the receptive field stimulus. We present evidence that the presaccadic enhancement exhibited by V4 neurons, quite separate from the response at stimulus onset, is a resurgent visual representation that seems as selective as the response is when the stimulus first appears. The presaccadic enhancement appears to provide a strengthening of a decaying featural representation immediately before an eye movement is directed to visual targets. We suggest that this reactivation provides a mechanism by which a clear perception of the saccade goal can be maintained during the execution of the saccade, perhaps for the purpose of establishing continuity across eye movements.}, web_url = {http://www.pubmedcentral.nih.gov/picrender.fcgi?artid=21188&blobtype=pdf}, state = {published}, author = {Moore T; Tolias AS{atolias}; Schiller PH} } @Article{ 4483, title = {Saccades induced electrically from the dorsomedial frontal cortex: evidence for a head-centered representation}, journal = {Brain Research}, year = {1998}, month = {6}, volume = {795}, number = {1-2}, pages = {287-291}, abstract = {The amplitude and direction of saccadic eye movements evoked electrically from the dorsomedial frontal cortex (DMFC) of monkeys vary with starting eye position. This observation has been used to argue that the DMFC codes saccadic eye movements in head-centered coordinates. Whether the amplitude and direction of the evoked saccades are also affected by changes in head position has never been demonstrated. Such a result would argue against a head-centered representation, and instead would suggest a representation anchored to another body part. Tests were conducted on rhesus monkeys to determine whether changing the position of the head with respect to the trunk or changing the position of the head with respect to the gravitational axis alters saccadic parameters. The amplitude and direction of saccadic eye movements remained invariant to such manipulations. These findings confirm the claim that the DMFC encodes saccadic eye movements in head-centered coordinates.}, web_url = {http://www.sciencedirect.com/science?_ob=MImg&_imagekey=B6SYR-4BRCN5H-1W-7&_cdi=4841&_user=29041&_orig=browse&_coverDate=06%2F08%2F1998&_sk=992049998&view=c&wchp=dGLbVzW-zSkzV&md5=9ff681401acf297b996b43837b6c523b&ie=/sdarticle.pdf}, state = {published}, DOI = {10.1016/S0006-8993(98)00302-3}, author = {Tehovnik EJ; Slocum WM; Tolias AS{atolias}; Schiller PH} } @Article{ 4485, title = {Colour adaptation modifies the long-wave versus middle-wave cone weights and temporal phases in human luminance (but not red-green) mechanism}, journal = {Journal of Physiology}, year = {1997}, month = {2}, volume = {499}, number = {1}, pages = {227-254}, web_url = {http://jp.physoc.org/cgi/reprint/499/Pt_1/227}, state = {published}, author = {Stromeyer CF; Chaparro A; Tolias AS{atolias}; Kronauer RE} } @Inproceedings{ SultanAMTL2011, title = {esfMRI of the upper STS: further evidence for the lack of electrically induced polysynaptic propagation of activity in the neocortex}, journal = {Magnetic Resonance Imaging}, year = {2011}, month = {12}, volume = {29}, number = {10}, pages = {1374-1381}, abstract = {Combining electrical stimulation with fMRI (esfMRI) has proven to be an important tool to study the global effects of electrical stimulation on neural networks in the brain. Here we extend our previous studies to stimulating the upper superior temporal sulcus (STS) in the anesthetized monkey. Our results show that stimulating area V5/MT and surrounding areas leads to positive BOLD responses in the majority of cortical areas known to receive direct/monosynaptic connections from the stimulation site. We confirm our previous results from stimulating primary visual cortex that the propagation of electrically induced activity is limited in its transsynaptic propagation to the first synapse also for extrastriate areas.}, web_url = {http://www.sciencedirect.com/science?_ob=MiamiImageURL&_cid=271222&_user=29041&_pii=S0730725X11001354&_check=y&_origin=&_coverDate=31-Dec-2011&view=c&wchp=dGLzVBA-zSkWz&md5=1ebff3056d9b781fb0d326346e0f58f1/1-s2.0-S0730725X11001354-main.pdf}, event_name = {9th Workshop of the International School on Magnetic Resonance and Brain Function}, event_place = {Erice, Italy}, state = {published}, DOI = {10.1016/j.mri.2011.04.005}, author = {Sultan F; Augath M{mark}{Department Physiology of Cognitive Processes}; Murayama Y{yusuke}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Inproceedings{ 2646, title = {Modelling Spikes with Mixtures of Factor Analysers}, year = {2004}, month = {9}, pages = {391-398}, abstract = {Identifying the action potentials of individual neurons from extracellular recordings, known as spike sorting, is a challenging problem. We consider the spike sorting problem using a generative model,mixtures of factor analysers, which concurrently performs clustering and feature extraction. The most important advantage of this method is that it quantifies the certainty with which the spikes are classified. This can be used as a means for evaluating the quality of clustering and therefore spike isolation. Using this method, nearly simultaneously occurring spikes can also be modelled which is a hard task for many of the spike sorting methods. Furthermore, modelling the data with a generative model allows us to generate simulated data.}, file_url = {/fileadmin/user_upload/files/publications/pdf2646.pdf}, web_url = {http://link.springer.com/content/pdf/10.1007%2F978-3-540-28649-3_48.pdf}, editor = {Rasmussen, C. E. , H.H. Bülthoff, B. Schölkopf, M.A. Giese}, publisher = {Springer}, address = {Berlin, Germany}, series = {Lecture Notes in Computer Science ; 3175}, booktitle = {Pattern Recognition}, event_name = {26th Annual Symposium of the German Association for Pattern Recognition (DAGM 2004)}, event_place = {Tübingen, Germany}, state = {published}, ISBN = {978-3-540-22945-2}, DOI = {10.1007/978-3-540-28649-3_48}, author = {G\"or\"ur D{dilan}{Department Empirical Inference}; Rasmussen CE{carl}{Department Empirical Inference}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Sinz F{fabee}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Inproceedings{ 2483, title = {Prediction on Spike Data Using Kernel Algorithms}, year = {2004}, month = {6}, pages = {1367-1374}, abstract = {We report and compare the performance of different learning algorithms based on data from cortical recordings. The task is to predict the orientation of visual stimuli from the activity of a population of simultaneously recorded neurons. We compare several ways of improving the coding of the input (i.e., the spike data) as well as of the output (i.e., the orientation), and report the results obtained using different kernel algorithms.}, file_url = {/fileadmin/user_upload/files/publications/pdf2483.pdf}, web_url = {http://books.nips.cc/nips16.html}, editor = {Thrun, S. , L.K. Saul, B. Schölkopf}, publisher = {MIT Press}, address = {Cambridge, MA, USA}, booktitle = {Advances in Neural Information Processing Systems 16}, event_name = {Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003)}, event_place = {Vancouver, BC, Canada}, state = {published}, ISBN = {0-262-20152-6}, author = {Eichhorn J{je}{Department Empirical Inference}; Tolias AS{atolias}; Zien A{zien}{Department Empirical Inference}; Kuss M{kuss}{Department Empirical Inference}; Rasmussen CE{carl}{Department Empirical Inference}; Weston J{weston}{Department Empirical Inference}; Logothetis NK{nikos}; Sch\"olkopf B{bs}{Department Empirical Inference}} } @Inbook{ 7051, title = {Local Field Potentials, BOLD, and Spiking Activity: Relationsships and Physiological Mechanisms}, year = {2012}, pages = {599-624}, abstract = {Extracellular voltage fluctuations (local field potentials, LFPs) reflecting neural mass action are ubiquitous across species and brain regions. Numerous studies have characterized the properties of LFP signals in the cortex to study sensory and motor computations as well as cognitive processes like attention, perception and memory. In addition, its extracranial counterpart – the electroencephalogram – is widely used in clinical applications. However, the link between LFP signals and the underlying activity of local populations of neurons is still largely elusive. For the LFP to aid our understanding of cortical computation, however, we need to know as precisely as possible what aspects of neural mass action it reflects. In this chapter, we examine recent advances and results regarding the origin, the feature selectivity and the spatial resolution of the local field potential and discuss its relationship to local spiking activity as well as the BOLD signal used in fMRI. We place particular focus on the gamma-band of the local field potential since it has long been implicated to play an important role in sensory processing. We conclude that in contrast to spikes, the local field potential does not measure the output of the computation performed by a cortical circuit, but are rather indicative of the synaptic and dendritic processes, as well as the dynamics of cortical computation.}, web_url = {https://mitpress.mit.edu/books/visual-population-codes}, web_url2 = {http://precedings.nature.com/documents/5216/version/1}, editor = {Kriegeskorte, N. , G. Kreiman}, publisher = {MIT Press}, address = {Cambridge, MA, USA}, booktitle = {Visual population codes: toward a common multivariate framework for cell recording and functional imaging}, state = {published}, ISBN = {978-0-26201-624-7}, author = {Berens P{berens}{Research Group Computational Vision and Neuroscience}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Inbook{ 3969, title = {Motion Perception}, year = {2004}, pages = {100-115}, editor = {Adelman, G. , B.H. Smith}, publisher = {Elsevier}, address = {Amsterdam, The Netherlands}, booktitle = {Encyclopedia of Neuroscience}, state = {published}, ISBN = {0-444-51432-5}, author = {Smirnakis SM{ssmirnakis}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Inbook{ 4499, title = {Functional magnetic resonance imaging adaptation: a technique for studying the properties of neuronal networks}, year = {2003}, pages = {109-125}, abstract = {Functional magnetic resonance imaging can be used to study the networks of neurons that underline different behaviors. The blood oxygenation level-dependent signal though, measures the activity averaged across heterogeneous population of neurons with different response characteristics. It is therefore often impossible to infer the properties of the underlying imaged neural populations by simply examining the fMRI signal. Here, we describe the use of an adaptation paradigm to study the properties of neuronal populations beyond the spatial resolution of fMRI.}, web_url = {http://dl.acm.org/citation.cfm?id=949832&CFID=779594081&CFTOKEN=98730659}, editor = {Sommer, F.T. , A. Wicher}, publisher = {MIT Press}, address = {Cambridge, MA, USA}, series = {Neural information processing series}, booktitle = {Exploratory analysis and data modeling in functional neuroimaging}, state = {published}, ISBN = {0-262-19481-3}, author = {Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Kourtzi Z{zoe}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ CadenaEDWTB2017, title = {A goal-driven deep learning approach for V1 system identification}, year = {2017}, month = {2}, day = {23}, pages = {74}, abstract = {Understanding sensory processing in the visual system results from accurate predictions of its neural responses to arbitrary stimuli. Despite great efforts over the last decades, we still lack a full characterization of the computations in primary visual cortex (V1) and their role in higher cognitive functional tasks (e.g. object recognition). Recent goal-driven deep learning models have provided unprecedented predictive performance on the visual ventral stream and revealed a hierarchical correspondence. However, we still have to assess if their learned representations can also be used to predict single cell responses in V1. Here, we leverage these learned representations to build a model that predicts responses to natural images across layers of monkey V1. We use the internal representations of a high-performing convolutional neural network (CNN) trained on object recognition as a non-linear feature space for a Generalized Linear Model. We found that intermediate early layers in the CNN provided the best predictive performance on held out data. Our model significantly outperformed classical and current state-of-the-art methods on V1 identification. When exploring the properties of the best predictive layers in the CNN, we found striking similarities with known V1 computation. Our model is not only interpretable, but also interpolates between recent subunit-based hierarchical models and goal-driven deep learning models, leading to results that argue in favor of shared representations in the brain.}, web_url = {http://www.cosyne.org/c/index.php?title=Cosyne2017_posters_1}, event_name = {Computational and Systems Neuroscience Meeting (COSYNE 2017)}, event_place = {Salt Lake City, UT, USA}, state = {published}, author = {Cadena S; Ecker A{aecker}; Denfield G; Walker E; Tolias A{atolias}; Bethge M{mbethge}} } @Poster{ BerensTSSTBF2017, title = {Standardizing and benchmarking data analysis for calcium imaging}, year = {2017}, month = {2}, day = {23}, pages = {66}, abstract = {Two-photon laser scanning microscopy with fluorescent calcium indicators is used widely to measure the activity of large populations of neurons. Extracting biologically relevant signals of interest without manual intervention remains a challenge. Two key problems are identifying image regions corresponding to individual neurons, and then detecting the timing of individual spikes from their derived fluorescence traces. The neuroscience community still lacks automated and agreed-upon solutions to these problems. Motivated by algorithm benchmarking efforts in computer vision and machine learning, we built two web-based benchmarking systems, Neurofinder (http://neurofinder.codeneuro.org) and Spikefinder (http://spikefinder.codeneuro.org), to compare algorithm performance on standardized datasets. Both were built with modular and modern open-source tools, allowing easy reuse for other data analysis problems. Neurofinder considers the problem of identifying neuron somata in fluorescence movies. We assembled a collection of training datasets from multiple labs in a standardized format, each with labeled regions defined manually, in some cases guided by activity-independent anatomical markers. Algorithm results are submitted through a web application and evaluated on independent test data, for which labels have not been made public. Evaluation metrics separately assess accuracy of neuronal locations and shapes. Submitted results are stored in a database and metrics are presented in a leaderboard. Spikefinder considers the problem of detecting spike times from fluorescence traces, building on a recent quantitative comparison of existing spike inference algorithms (Theis et al. 2016). Here, we assembled training data with simultaneously measured calcium traces and electrophysiologically-recorded action potentials. Performance of submitted algorithms is evaluated on a test dataset using several metrics including correlation, information gain, and standard measures from signal detection. Both challenges are currently running with publicly contributed algorithms. We hope this approach will both improve our understanding of how current algorithms perform, and generate new crowd-sourced solutions to current and future analysis problems.}, web_url = {http://www.cosyne.org/c/index.php?title=Cosyne2017_posters_1}, event_name = {Computational and Systems Neuroscience Meeting (COSYNE 2017)}, event_place = {Salt Lake City, UT, USA}, state = {published}, author = {Berens P{berens}; Theis L{lucas}; Stone J; Sofroniew N; Tolias A{atolias}; Bethge M{mbethge}; Freeman J} } @Poster{ DenfieldET2017, title = {The Role of Internal Signals in Structuring V1 Population Activity}, year = {2017}, month = {2}, pages = {31}, abstract = {Neuronal responses to repeated presentations of identical visual stimuli are variable. The source of this variability is unknown, but it is commonly treated as noise. We argue that this variability reflects, and is due to, computations internal to the brain. Relatively little research has examined the effect on neuronal responses of fluctuations in internal signals such as cortical state and attention, leaving a number of uncontrolled parameters that may contribute to neuronal variability. Attention increases neuronal response gain in a spatial and feature selective manner. We hypothesize that fluctuations in the strength and focus of attention are a major source of neuronal response variability and covariability. We first examine a simple model of a gain-modulating signal acting on a population of neurons and show that fluctuations in attention can increase individual and shared variability. To test our model’s predictions experimentally, we devised a cued-spatial attention, change-detection task to induce varying degrees of fluctuation in the subject’s attentional signal. We use multi-electrode recordings in primary visual cortex of macaques performing this task. We demonstrate that attention gain-modulates responses of V1 neurons in a manner consistent with results from higher-order areas. Our results also indicate neuronal covariability is elevated in conditions in which attention fluctuates. Overall, our results suggest that attentional fluctuations are an important contributor to neuronal variability and open the door to the use of statistical methods for inferring the state of these signals on behaviorally relevant timescales.}, web_url = {https://media.bcm.edu/documents/2017/ec/abstract-book-complete.pdf}, event_name = {27th Annual Rush and Helen Record Neuroscience Forum}, event_place = {Galveston, TX, USA}, state = {published}, author = {Denfield GH; Ecker A{aecker}{Department Physiology of Cognitive Processes}; Tolias A{atolias}{Department Physiology of Cognitive Processes}} } @Poster{ CadenaEDWTB2016, title = {A goal-driven deep learning approach for V1 system identification}, year = {2016}, month = {9}, day = {21}, pages = {40-41}, abstract = {Understanding sensory processing in the visual system results from accurate predictions of its neural responses to any kind of stimulus. Although great effort has been devoted to the task, we still lack a full characterization of primary visual cortex (V1) computations and their role in higher cognitive functional tasks (e.g. object recognition) in response to naturalistic stimuli. While previous goal-driven deep learning models have provided unprecedented performance on visual ventral stream predictions and revealed hierarchical correspondence, no study has used the representations learned by those models to predict single cell spike counts in V1. We introduce a novel model (Fig. 1A) that leverages these learned representations to build a linearized model with Poisson noise. We separately use the representations of each convolutional layer of a near-state of the art convolutional neural network (CNN) trained on object recognition to fit a model that predicts V1 responses to naturalistic stimuli. When fitted to data collected from neurons across cortical layers in V1 from an awake, fixating monkey, we found that, as we expected, intermediate early layers in the CNN provided better performance on held out data (Fig. 1B). Additionally we show that, using the best predictive layers, our model significantly outperforms classical and current state-of-the-art methods on V1 identification (Fig. 1C). When exploring the properties of the best predictive layers in the CNN, we found striking similarities with known V1 computation. Our model is not only interpretable, but also interpolates between recent subunit-based hierarchical models and goal-driven deep learning models leading to results that argue in favor of shared representations in the brain.}, web_url = {https://abstracts.g-node.org/conference/BC16/abstracts#/uuid/d1f4edcc-aa10-43ec-9b49-588e3e884e8e}, event_name = {Bernstein Conference 2016}, event_place = {Berlin, Germany}, state = {published}, DOI = {10.12751/nncn.bc2016.0029}, author = {Cadena SA; Ecker AS{aecker}; Denfield GH; Walker EY; Tolias AS{atolias}; Bethge M{mbethge}} } @Poster{ CadwellJSBFYFECT2016, title = {Cell Lineage Directs teh Precise Assembly of Excitatory Neocortical Circuits}, year = {2016}, month = {6}, pages = {60}, abstract = {The neocortex carries out complex mental processes such as perception and cognition through the interactions of billions of neurons connected by trillions of synapses. Recent studies suggest that excitatory cortical neurons with a shared developmental lineage are more likely to be synaptically connected to each other than to nearby, unrelated neurons [1, 2]. However, the precise wiring diagram between clonally related neurons is unknown, and the impact of cell lineage on neural computation remains controversial. Here we show that vertical connections linking neurons across cortical layers are specifically enhanced between clonally related neurons (Fig. 1). In contrast, lateral connections within a cortical layer preferentially occur between unrelated neurons (Fig. 1). Importantly, we observed these connection biases for distantly related cousin cells, suggesting that cell lineage influences a larger fraction of connections than previously thought. A simple quantitative model of cortical connectivity based on our empirically measured connection probabilities reveals that both increased vertical connectivity and decreased lateral connectivity between cousins promote the convergence of shared input onto clonally related neurons, providing a novel circuit-level mechanism by which clonal units form functional cell assemblies with similar tuning properties [3, 4]. Taken together, our data suggest that the integration of feedforward, intra-columnar input with lateral, inter-columnar information may represent a fundamental principle of cortical computation that is established, at least initially, by developmental programs.}, web_url = {http://areadne.org/2016/pezaris-hatsopoulos-2016-areadne.pdf}, event_name = {AREADNE 2016: Research in Encoding And Decoding of Neural Ensembles}, event_place = {Santorini, Greece}, state = {published}, author = {Cadwell CR; Jiang X; Sinz FH{fabee}; Berens P{berens}; Fahey PG; Yatsenko D; Froudarakis E; Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Cotton RJ; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Poster{ DenfieldEBT2016, title = {Correlated Variability in Population Activity: Noise or Signature of Internal Computations}, year = {2016}, month = {6}, pages = {63}, abstract = {Neuronal responses to repeated presentations of identical visual stimuli are variable. The source of this variability is unknown, but it is commonly treated as noise and seen as an obstacle to understanding neuronal activity. We argue that this variability is not noise but reflects, and is due to, computations internal to the brain. Internal signals such as cortical state or attention interact with sensory information processing in early sensory areas. However, little research has examined the effect of fluctuations in these signals on neuronal responses, leaving a number of uncontrolled parameters that may contribute to neuronal variability. One such variable is attention, which increases neuronal response gain in a spatial and feature selective manner. Both the strength of this modulation and the focus of attention are likely to vary from trial to trial, and we hypothesize that these fluctuations are a major source of neuronal response variability and covariability. We first examine a simple model of a gain-modulating signal acting on a population of neurons and show that fluctuations in attention can increase individual and shared variability and generate a variety of correlation structures relevant to population coding, including limited range and differential correlations. To test our model’s predictions experimentally, we devised a cued-spatial attention, change-detection task to induce varying degrees of fluctuation in the subject’s attentional signal by changing whether the subject must attend to one stimulus location while ignoring another, or attempt to attend to multiple locations simultaneously. We use multi-electrode recordings with laminar probes in primary visual cortex of macaques performing this task. We demonstrate that attention gain-modulates responses of V1 neurons in a manner consistent with results from higher-order areas. Consistent with our model’s predictions, our preliminary results indicate neuronal covariability is elevated in conditions in which attention fluctuates and that neurons are nearly independent when attention is focused. Overall, our results suggest that attentional fluctuations are an important contributor to neuronal variability and open the door to the use of statistical methods for inferring the state of these signals on behaviorally relevant timescales.}, web_url = {http://areadne.org/2016/pezaris-hatsopoulos-2016-areadne.pdf}, event_name = {AREADNE 2016: Research in Encoding And Decoding of Neural Ensembles}, event_place = {Santorini, Greece}, state = {published}, author = {Denfield GH; Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Poster{ ReimerYEWSBHCST2016, title = {DataJoint: Managing Big Scientific Data Using Matlab or Python}, year = {2016}, month = {6}, pages = {99}, abstract = {The rise of big data in modern research poses serious challenges for data management: Large and intricate datasets from diverse instrumentation must be precisely aligned, annotated, and organized in a flexible way that allows swift exploration and analysis. Data management should guarantee consistency of intermediate results in subsequent multi-step processing pipelines such that changes in one part automatically propagate to all downstream results. Finally, data organization should be self-documenting to ensure that lab members and collaborators can access the data with minimal effort, even years after it was collected. While high levels of data integrity are expected, research teams have diverse backgrounds, are geographically dispersed, and rarely possess a primary interest in data science. While the challenges associated with large, complex data sets may be new to biologists, they have been addressed quite successfully in other contexts by relational databases, which provide a principled approach for effective data management. DataJoint is an open-source framework that provides a clean implementation of core concepts of the relational data model to facilitate multi-user access, effcient queries, distributed computing, and cascading dependencies across multiple data modalities. Critically, while DataJoint relies on an established relational database management system (MySQL) as its backend, data access and manipulation are performed transparently in the commonly-used languages MATLAB or Python, and DataJoint can be integrated into new and existing analyses written in these languages with minimal effort or additional training. DataJoint is not limited to particular file formats, acquisition systems, or data modalities and can be quickly adapted to new experimental designs. DataJoint and related resources are available at http://datajoint.github.com.}, web_url = {http://areadne.org/2016/pezaris-hatsopoulos-2016-areadne.pdf}, event_name = {AREADNE 2016: Research in Encoding And Decoding of Neural Ensembles}, event_place = {Santorini, Greece}, state = {published}, author = {Reimer J; Yatsenko D; Ecker A{aecker}{Department Physiology of Cognitive Processes}; Walker EY; Sinz F{fabee}; Berens P{berens}; Hoenselaar A; Cotton RJ; Siapas AG; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Poster{ YatsenkoFERJT2016, title = {Strong functional connectivity of parvalbumin-expressing cortical interneurons}, year = {2016}, month = {2}, day = {27}, pages = {221}, abstract = {The morphological and electrophysiological properties of parvalbumin-expressing inhibitory interneurons (PV+ neurons) suggest their role as synchronizers and normalizers of the local cortical microcircuit. PV+ cells are thought to average the local activity and dynamically regulate its overall level. In apparent agreement with this model, previous studies have shown stable patterns of correlations of the spiking activity of the PV+ neurons among themselves and with the local excitatory cells. However, we have previously shown that, in sufficiently dense recordings, estimates of the partial pairwise correlations of the spiking activity can yield a more insightful picture of interactions in the circuit, or its functional connectivity. Using high-speed 3D two-photon imaging of calcium signals and genetically encoded fluorescent markers of PV+ neurons, we recorded the activity of the majority of neurons in 200 um x 200 um x 100 um volumes in layers 2/3 and 4 of mouse visual cortex during visual stimulation. If PV+ neurons simply pooled the activity of the local circuit, their activity would be predicted from the local circuit and the partial correlations among the PV+ neurons would all but vanish. Surprisingly, we found that the partial pairwise correlations among the PV+ cells were exceptionally high. In fact, the partial pairwise correlations enhanced the differentiation of PV+ neurons from other cell types. The average partial pairwise correlation between PV+/PV+ pairs was 4.9 times higher than between PV-/PV- pairs whereas the average noise correlations differed by the factor of 1.5. This effect was insensitive to the choice of the temporal scales of correlation analysis. Although other explanations cannot yet be excluded, the present finding may suggest that the correlations among the PV+ neurons are shaped predominantly by structured input from outside the local circuit such as, for example, by input from layer 5.}, web_url = {http://www.cosyne.org/c/index.php?title=Cosyne_16}, event_name = {Computational and Systems Neuroscience Meeting (COSYNE 2016)}, event_place = {Salt Lake City, UT, USA}, state = {published}, author = {Yatsenko D; Froudarakis E; Ecker A{aecker}; Rosenbaum R; Josic K; Tolias A{atolias}} } @Poster{ BethgeTBFRRBET2016, title = {Supervised learning sets benchmark for robust spike rate inference from calcium imaging signals}, year = {2016}, month = {2}, day = {26}, pages = {163}, abstract = {A fundamental challenge in calcium imaging has been to infer spike rates of neurons from the measured noisy calcium fluorescence traces. We collected a large benchmark dataset (>100.000 spikes, 73 neurons) recorded from varying neural tissue (V1 and retina) using different calcium indicators (OGB-1 and GCaMP6s). We introduce a new algorithm based on supervised learning in flexible probabilistic models and systematically compare it against a range of spike inference algorithms published previously. We show that our new supervised algorithm outperforms all previously published techniques. Importantly, it even performs better than other algorithms when applied to entirely new datasets for which no simultaneously recorded data is available. Future data acquired in new experimental conditions can easily be used to further improve its spike prediction accuracy and generalization performance. Finally, we show that comparing algorithms on artificial data is not informative about performance on real data, suggesting that benchmark datasets such as the one we provide may greatly facilitate future algorithmic developments.}, web_url = {http://www.cosyne.org/c/index.php?title=Cosyne_16}, event_name = {Computational and Systems Neuroscience Meeting (COSYNE 2016)}, event_place = {Salt Lake City, UT, USA}, state = {published}, author = {Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}; Theis L{lucas}{Research Group Computational Vision and Neuroscience}; Berens P{berens}{Research Group Computational Vision and Neuroscience}; Froudarakis E; Reimer J; Roman-Roson M; Baden T; Euler T; Tolias A{atolias}} } @Poster{ CottonEFBBST2015, title = {Scaling of information in large sensory neuronal populations}, year = {2015}, month = {10}, day = {19}, volume = {45}, number = {331.01}, abstract = {Individual neurons are noisy. Therefore, it seems necessary to pool the activity of many neurons to obtain an accurate representation of the environment. However, it is widely believed that shared noise in the activity of nearby neurons renders such pooling ineffective, limiting the accuracy of the population code and, ultimately, behavior. However, these predictions are based on extrapolating models fit to small numbers of neurons and have not been tested experimentally. Using a novel high-speed 3D-microscope we densely recorded from hundreds of neurons in the mouse visual cortex and measured the amount of information encoded. We find that the information in this sensory population increases approximately linearly with population size and does not saturate, even for several hundred neurons. This information growth is facilitated by a correlation structure that is not aligned with the tuning, making it less harmful than would be predicted from pairwise measurements. Accordingly, a decoder that accounts for the correlation structure outperforms one that does not. Our findings suggest that sensory representations may be more accurate than previously thought and therefore that psychophysical limitations may arise from downstream neural processes rather than limitations in the sensory encoding.}, web_url = {http://www.sfn.org/am2015/}, event_name = {45th Annual Meeting of the Society for Neuroscience (Neuroscience 2015)}, event_place = {Chicago, IL, USA}, state = {published}, author = {Cotton JR; Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Froudarakis E; Berens P{berens}{Research Group Computational Vision and Neuroscience}; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}; Saggau P; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Poster{ CadwellJBFYFET2015, title = {Sibling rivalry and cooperation among excitatory neurons in the neocortex}, year = {2015}, month = {10}, day = {17}, volume = {45}, number = {59.13}, abstract = {The mammalian neocortex carries out complex mental processes such as cognition, perception and decision-making through the interactions of billions of neurons connected by trillions of synapses. We are just beginning to understand how networks of neurons become wired together during development to give rise to cortical computations. Recent studies have shown that excitatory cortical neurons with a shared ontogenetic lineage form vertical columns spanning multiple cortical layers and that these “sister cells” are more likely to be synaptically connected to each other than to nearby, unrelated neurons. However, the precise wiring diagram between sister cells is unknown. Here we show that connectivity between sister cells depends on the laminar position of the pre- and post-synaptic neurons. In contrast to previous studies, we find that although sister cells residing in different cortical layers are more likely to be connected, sister cells located within the same layer are less likely to be connected to each other compared to distance-matched controls. Avoidance of cells that receive common input may be a fundamental principle of information processing within a cortical column. Our findings challenge the prevailing hypothesis that shared developmental lineage is always associated with an increase in connectivity, and suggest that both attraction and repulsion play an important role in shaping cortical circuits.}, web_url = {http://www.sfn.org/am2015/}, event_name = {45th Annual Meeting of the Society for Neuroscience (Neuroscience 2015)}, event_place = {Chicago, IL, USA}, state = {published}, author = {Cadwell CR; Jiang X; Berens P{berens}{Research Group Computational Vision and Neuroscience}; Fahey PG; Yatsenko D; Froudarakis E; Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Poster{ EckerDTB2015, title = {On the structure of population activity under fluctuations in attentional state}, year = {2015}, month = {9}, day = {16}, pages = {185}, abstract = {Attention is commonly thought to improve behavioral performance by increasing response gain and suppressing shared variability in neuronal populations. However, both the focus and the strength of attention are likely to vary from one experimental trial to the next, thereby inducing response variability unknown to the experimenter. Here we study analytically how fluctuations in attentional state affect the structure of population responses in a simple model of spatial and feature attention. In our model, attention acts on the neural response exclusively by modulating each neuron’s gain. Neurons are conditionally independent given the stimulus and the attentional gain, and correlated activity arises only from trial-to-trial fluctuations of the attentional state, which are unknown to the experimenter. We find that this simple model can readily explain many aspects of neural response modulation under attention, such as increased response gain, reduced individual and shared variability, increased correlations with firing rates, limited range correlations, and differential correlations. We therefore suggest that attention may act primarily by increasing response gain of individual neurons without affecting their correlation structure. The experimentally observed reduction in correlations may instead result from reduced variability of the attentional gain when a stimulus is attended. Moreover, we show that attentional gain fluctuations – even if unknown to a downstream readout – do not impair the readout accuracy despite inducing limited-range correlations.}, web_url = {http://www.nncn.de/de/bernstein-conference/2015/program}, event_name = {Bernstein Conference 2015}, event_place = {Heidelberg, Germany}, state = {published}, DOI = {10.12751/nncn.bc2015.0179}, author = {Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Denfield GH; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}} } @Poster{ FroudarakisBECSYSBT2014_2, title = {Population Code in Mouse V1 Facilities Read-out of Natural Scenes through Increased Sparseness}, year = {2014}, month = {6}, pages = {69}, abstract = {The neural code is believed to have adapted to the statistical properties of the natural environment. However, the principles that govern the organization of ensemble activity in the visual cortex during natural visual input are unknown. We recorded populations of up to 500 neurons in the mouse primary visual cortex and characterized the structure of their activity, comparing responses to natural movies with those to control stimuli. We found that higher-order correlations in natural scenes induce a sparser code, in which information is encoded by reliable activation of a smaller set of neurons and can be read-out more easily. This computationally advantageous encoding for natural scenes was state-dependent and apparent only in anesthetized and active, awake animals, but not during quiet wakefulness. Our results argue for a functional benefit of sparsification that could be a general principle governing the structure of the population activity throughout cortical microcircuits.}, web_url = {http://areadne.org/2014/home.html}, event_name = {AREADNE 2014: Research in Encoding and Decoding of Neural Ensembles}, event_place = {Santorini, Greece}, state = {published}, author = {Froudarakis A; Berens P{berens}{Research Group Computational Vision and Neuroscience}; Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Cotton RJ; Sinz FH{fabee}{Research Group Computational Vision and Neuroscience}{Research Group Computational Vision and Neuroscience}; Yatsenko D; Saggau P; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Poster{ CottonFEBST2014, title = {Scaling of Information in Large Sensory Neuronal Populations}, year = {2014}, month = {6}, pages = {60}, abstract = {Although we know a lot about how individual neurons in the brain represent the sensory environment, we are far from understanding how neural populations represent sensory information. Because individual neurons are noisy, pooling the activity of many neurons with similar response properties seems necessary to obtain an accurate representation of the sensory environment. However, it is widely believed that shared noise (or, noise correlations) in the activity of nearby neurons renders such pooling ineffective, profoundly limiting the accuracy of any population code and, ultimately, behavior. This belief is based on model-based extrapolations from correlations measured in individual pairs of neurons, as it has been impossible to record simultaneously from complete neuronal populations. Here, we use a novel 3D high-speed in vivo two-photon microscope to record nearly all of the hundreds of neurons in a small volume of the mouse primary visual cortex and directly measure the amount of information encoded by these local populations. In contrast to previous predictions, we find that the information in a sensory population increases approximately linearly with population size and does not saturate even for several hundred neurons. Moreover, even a decoder ignoring correlations between neurons can decode 80% of the information in the population. Our results suggest that sensory neural populations represent information in a truly distributed manner and pooling of neural activity within local circuits is much more effective than previously anticipated. Thus, the representation in early sensory areas does not appear to be impaired substantially by shared sensory noise and limitations in behavioral performance in psychophysical tasks may need to be attributed to processes downstream of the sensory population.}, web_url = {http://areadne.org/2014/home.html}, event_name = {AREADNE 2014: Research in Encoding and Decoding of Neural Ensembles}, event_place = {Santorini, Greece}, state = {published}, author = {Cotton RJ; Froudarakis E; Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Berens P{berens}{Research Group Computational Vision and Neuroscience}; Saggau P; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Poster{ EckerBCSDCSBT2014_2, title = {State Dependence of Noise Correlation in Macaque Primary Visual Cortex}, year = {2014}, month = {6}, pages = {64}, abstract = {Shared, trial-to-trial variability in neuronal populations has a strong impact on the accuracy of information processing in the brain. Estimates of the level of such noise correlations are diverse, ranging from 0.01 to 0.4, with little consensus on which factors account for these differences. Here we addressed one important factor that varied across studies, asking how anesthesia affects the population activity structure in macaque primary visual cortex. We found that under opioid anesthesia, activity was dominated by strong coordinated fluctuations on a timescale of 1–2 Hz, which were mostly absent in awake, fixating monkeys. Accounting for these global fluctuations markedly reduced correlations under anesthesia, matching those observed during wakefulness and reconciling earlier studies conducted under anesthesia and in awake animals. Our results show that internal signals, such as brain state transitions under anesthesia, can induce noise correlations, but can also be estimated and accounted for based on neuronal population activity.}, web_url = {http://areadne.org/2014/home.html}, event_name = {AREADNE 2014: Research in Encoding and Decoding of Neural Ensembles}, event_place = {Santorini, Greece}, state = {published}, author = {Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Berens P{berens}{Research Group Computational Vision and Neuroscience}; Cotton RJ; Subramaniyan M; Denfield GH; Cadwell CR; Smirnakis SM{ssmirnakis}{Department Physiology of Cognitive Processes}; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Poster{ FroudarakisBCESBT2013, title = {Encoding of natural scene statistics in the primary visual cortex of the mouse}, year = {2013}, month = {3}, number = {II-76}, web_url = {http://www.cosyne.org/c/index.php?title=Cosyne_13}, event_name = {Computational and Systems Neuroscience Meeting (COSYNE 2013)}, event_place = {Salt Lake City, UT, USA}, state = {published}, author = {Froudarakis E; Berens P{berens}{Research Group Computational Vision and Neuroscience}; Cotton JR; Ecker AS{aecker}; Saggau P; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}; Tolias A{atolias}} } @Poster{ EckerBTB2012_2, title = {The correlation structure induced by fluctuations in attention}, year = {2012}, month = {6}, pages = {56}, abstract = {How attention shapes the structure of population activity has attracted substantial interest over the past decades. Attention has traditionally been associated with an increase in firing rates, reflecting a change in the gain of the population. More recent studies also report a change in noise correlations, which is thought to reflect changes in functional connectivity. However, since the degree of attention can vary substantially from trial to trial even within one experimental condition, the measured correlations could actually reflect fluctuations in the attention-related feedback signal (gain) rather than feed-forward noise, as often assumed. To gain insights into this issue we analytically analyzed the standard model of spatial attention, where directing attention to the receptive field of a neuron increases its response gain. We assumed conditionally independent neurons (no noise correlations) and asked how uncontrolled fluctuations in attention affect the correlation structure. First, we found that this simple model of spatial attention explains the empirically measured correlation structure quite well. In addition to a positive average level of correlations, it predicts both an increase in correlations with firing rates, as observed in many studies, and a decrease in correlations with the difference of two neurons’ tuning functions — a structure generally referred to as limited range correlations. Second, we asked how fluctuations in attention would affect the accuracy of a population code, if treated as noise by a downstream readout. Based on previous theoretical results, it would be expected that they negatively affect readout accuracy because of the limited range correlations they induce. Surprisingly, we found that this is not the case: correlations due to random gain fluctuations do not affect readout accuracy because their major axis is orthogonal to changes in the stimulus orientation. Our results can be readily generalized to include feature-based attention. The model has very few free parameters and can potentially account for a large fraction of the experimentally observed spike count (co-)variance.}, web_url = {http://areadne.org/2012/home.html}, event_name = {AREADNE 2012: Research in Encoding and Decoding of Neural Ensembles}, event_place = {Santorini, Greece}, state = {published}, author = {Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Berens P{berens}{Research Group Computational Vision and Neuroscience}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}} } @Poster{ BesserveBPCKTPL2012, title = {Identifying endogenous rhythmic spatio-temporal patterns in micro-electrode array recordings}, year = {2012}, month = {2}, volume = {9}, pages = {114-115}, abstract = {Microelectrode arrays are a privileged recording modality to study neural processes with a very fine spatial and temporal resolution. They capture the activity of small populations and permit assessment of synergistic interactions between cells. Patterns of rhythmic ongoing activity are of particular interest because they reflect the intrinsic dynamics of neural populations and the way such dynamics may optimize the processing of incoming information. In this study, we identify the various coherent spatio-temporal patterns of rhythmic activity occurring across time using a two steps approach. First, signals were bandpass filtered in a relevant frequency band and subsequently Hilbert-transformed. Second, the complex patterns of activity occurring across time were clustered using a graph cut algorithm based on a phase shift invariant similarity measure. This invariance is a key-property of our approach to isolate wave propagation phenomena. We apply our method to Local Field Potentials recorded in the inferior convexity of the Prefrontal Cortex (icPFC) in two anesthetized macaques using a multi electrode array. We found a dominant travelling wave pattern in the beta band (15-25Hz), propagating along the ventral-dorsal plane, emerging and vanishing across time both in the absence of visual stimulation (spontaneous activity) and during binocular stimulation with movie clips. By computing mutual information, we showed that the amplitude of this wave actually carries sensory information during the presentation of several movies. Altogether, our analysis provides evidence for travelling wave phenomena reflecting the distributed computation in icPFC, which is known to be involved in higher order sensory processing. More generally, our approach enables the unsupervised analysis of the complex spatio-temporal neural dynamics in ongoing signals, providing key information to understand cooperative mechanisms in spatially distributed neural populations.}, web_url = {http://www.cosyne.org/c/index.php?title=Cosyne_12}, event_name = {9th Annual Computational and Systems Neuroscience Meeting (Cosyne 2012)}, event_place = {Salt Lake City, UT, USA}, state = {published}, author = {Besserve M{besserve}{Department Empirical Inference}{Department Physiology of Cognitive Processes}; Panagiotaropoulos T{theofanis}{Department Physiology of Cognitive Processes}; Crocker B{bcrocker}{Department Physiology of Cognitive Processes}; Kapoor V{vishal}{Department Physiology of Cognitive Processes}; Tolias A{atolias}{Department Physiology of Cognitive Processes}; Panzeri S{stefano}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ EckerBTB2012, title = {The correlation structure induced by fluctuations in attention}, year = {2012}, month = {2}, volume = {9}, pages = {180}, abstract = {Attention has traditionally been associated with an increase in firing rates, reflecting a change in the gain of the population. More recent studies also report a change in noise correlations, which is thought to reflect changes in functional connectivity. However, since the degree of attention can vary substantially from trial to trial even within one experimental condition, the measured correlations could actually reflect fluctuations in the attentionrelated feedback signal (gain) rather than feed-forward noise, as often assumed. To gain insights into this issue we analytically analyzed the standard model of spatial attention, where directing attention to the receptive field of a neuron increases its response gain. We assumed conditionally independent neurons (no noise correlations) and asked how uncontrolled fluctuations in attention affect the correlation structure. First, we found that this simple model of spatial attention explains the empirically measured correlation structure quite well. In addition to a positive average level of correlations, it predicts both an increase in correlations with firing rates, as observed in many studies, and a decrease in correlations with the difference of two neurons’ tuning functions—a structure generally referred to as limited range correlations. Second, we asked how fluctuations in attention would affect the accuracy of a population code, if treated as noise by a downstream readout. Based on previous theoretical results, it would be expected that they negatively affect readout accuracy because of the limited range correlations they induce. Surprisingly, we found that this is not the case: correlations due to random gain fluctuations do not affect readout accuracy because their major axis is orthogonal to changes in the stimulus orientation. Our results can be readily generalized to include feature-based attention. The model has very few free parameters and can potentially account for a large fraction of the observed spike count (co-)variance.}, web_url = {http://www.cosyne.org/c/index.php?title=Cosyne_12}, event_name = {9th Annual Computational and Systems Neuroscience Meeting (Cosyne 2012)}, event_place = {Salt Lake City, UT, USA}, state = {published}, author = {Ecker A{aecker}; Berens P{berens}{Research Group Computational Vision and Neuroscience}; Tolias A{atolias}; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}} } @Poster{ PanagiotaropoulosBCKTPL2011, title = {Spatiotemporal mapping of rhythmic activity in the inferior convexity of the macaque prefrontal cortex}, year = {2011}, month = {11}, volume = {41}, number = {239.15}, abstract = {The inferior convexity of the macaque prefrontal cortex (icPFC) is known to be involved in higher order processing of sensory information mediating stimulus selection, attention and working memory. Until now, the vast majority of electrophysiological investigations of the icPFC employed single electrode recordings. As a result, relatively little is known about the spatiotemporal structure of neuronal activity in this cortical area. Here we study in detail the spatiotemporal properties of local field potentials (LFP's) in the icPFC using multi electrode recordings during anesthesia. We computed the LFP-LFP coherence as a function of frequency for thousands of pairs of simultaneously recorded sites anterior to the arcuate and inferior to the principal sulcus. We observed two distinct peaks of coherent oscillatory activity between approximately 4-10 and 15-25 Hz. We then quantified the instantaneous phase of these frequency bands using the Hilbert transform and found robust phase gradients across recording sites. The dependency of the phase on the spatial location reflects the existence of traveling waves of electrical activity in the icPFC. The dominant axis of these traveling waves roughly followed the ventral-dorsal plane. Preliminary results show that repeated visual stimulation with a 10s movie had no dramatic effect on the spatial structure of the traveling waves. Traveling waves of electrical activity in the icPFC could reflect highly organized cortical processing in this area of prefrontal cortex.}, web_url = {http://www.sfn.org/am2011/}, event_name = {41st Annual Meeting of the Society for Neuroscience (Neuroscience 2011)}, event_place = {Washington, DC, USA}, state = {published}, author = {Panagiotaropoulos T{theofanis}{Department Physiology of Cognitive Processes}; Besserve M{besserve}{Department Empirical Inference}{Department Physiology of Cognitive Processes}; Crocker B{bcrocker}{Department Physiology of Cognitive Processes}; Kapoor V{vishal}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Panzeri S{stefano}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ BerensEGTB2011_2, title = {Optimal Population Coding, Revisited}, year = {2011}, month = {2}, number = {III-67}, abstract = {Cortical circuits perform computations within few dozens of milliseconds with each neuron emitting only a few spikes. In this regime conclusions based on Fisher information, which is commonly used to assess the quality of population codes, are not always valid. Here we revisit the effect of tuning function width and correlation structure on neural population codes for angular variables using ideal observer analysis in both reconstruction and classification tasks employing Monte-Carlo simulations and analytical derivations. We show that the optimal tuning width of individual neurons and the optimal correlation structure of the population depend on the signal-to-noise ratio for both the reconstruction and the classification task. Strikingly, both ideal observers lead to very similar conclusions at low signal-to-noise ratio. In contrast, Fisher information favors severely suboptimal coding schemes in this regime. To further investigate the coding properties of Fisher-optimal codes, we compute the full neurometric functions of an ideal observer in the stimulus discrimination task, which allows us to evaluate population codes separately for fine and coarse discrimination. We find that codes with Fisher-optimal tuning width show strikingly bad performance for simple coarse discrimination tasks with a ëpedestal errorí, which is independent of population size. We show analytically that this is a necessary consequence of the fact that in such codes only few neurons are activated by each stimulus, irrespective of the population size. Further we show that the initial region of the neurometric function goes to zero with increasing population size. As a consequence, the overall error achieved by Fisher-optimal ensembles saturates for large populations. In summary, based on exact ideal observer analysis for both stimulus reconstruction and discrimination tasks we obtained (1) an accurate assessment of neural population codes at all signal-to-noise ratios and (2) analytical insights into the suboptimal behavior of Fisher-optimal population codes.}, web_url = {http://www.cosyne.org/c/index.php?title=Cosyne_11_posters3}, event_name = {Computational and Systems Neuroscience Meeting (COSYNE 2011)}, event_place = {Salt Lake City, UT, USA}, state = {published}, author = {Berens P{berens}{Research Group Computational Vision and Neuroscience}; Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Gerwinn S{sgerwinn}{Department Empirical Inference}{Research Group Computational Vision and Neuroscience}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}} } @Poster{ 7055, title = {Decorrelated neuronal firing in cortical microcircuits}, year = {2010}, month = {11}, volume = {40}, number = {73.20}, abstract = {Correlated trial-to-trial variability in the activity of cortical neurons is thought to reflect the functional connectivity of the circuit. Many cortical areas are organized into functional columns, in which neurons are believed to be densely connected and share common input. Numerous studies report a high degree of correlated variability between nearby cells. We developed chronically implanted multi-tetrode arrays offering unprecedented recording quality to re-examine this question in primary visual cortex of awake macaques. We found that even nearby neurons with similar orientation tuning show virtually no correlated variability. In a total of 46 recording sessions from two monkeys, we presented either static or drifting sine-wave gratings at eight different orientations. We recorded from 407 well isolated, visually responsive and orientation-tuned neurons, resulting in 1907 simultaneously recorded pairs of neurons. In 406 of these pairs both neurons were recorded by the same tetrode. Despite being physically close to each other and having highly overlapping receptive fields, neurons recorded from the same tetrode had exceedingly low spike count correlations (rsc = 0.005 ± 0.004; mean ± SEM). Even cells with similar preferred orientations (rsignal > 0.5) had very weak correlations (rsc = 0.028 ± 0.010). This was also true if pairs were strongly driven by gratings with orientations close to the cells’ preferred orientations. Correlations between neurons recorded by different tetrodes showed a similar pattern. They were low on average (rsc = 0.010 ± 0.002) with a weak relation between tuning similarity and spike count correlations (two-sample t test, rsignal < 0.5 versus rsignal > 0.5: P = 0.003, n = 1907). To investigate whether low correlations also occur under more naturalistic stimulus conditions, we presented natural images to one of the monkeys. The average rsc was close to zero (rsc = 0.001 ± 0.005, n = 329) with no relation between receptive field overlap and spike count correlations. We obtained a similar result during stimulation with moving bars in a third monkey (rsc = 0.014 ± 0.011, n = 56). Our findings suggest a refinement of current models of cortical microcircuit architecture and function: either adjacent neurons share only a few percent of their inputs or, alternatively, their activity is actively decorrelated.}, web_url = {http://www.sfn.org/am2010/index.aspx?pagename=abstracts_main}, event_name = {40th Annual Meeting of the Society for Neuroscience (Neuroscience 2010)}, event_place = {San Diego, CA, USA}, state = {published}, author = {Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Berens P{berens}{Research Group Computational Vision and Neuroscience}; Keliris GA{george}{Department Physiology of Cognitive Processes}; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Poster{ 7073, title = {The face selective activity in ventral temporal lobe in macaques}, year = {2010}, month = {11}, volume = {40}, number = {834.2}, abstract = {Face perception is one of the most crucial abilities for social animals like humans and nonhuman primates. fMRI-, lesion- and electrophysiology studies in humans and monkeys have indicated the existence of a dedicated and wide-spread face-processing network. In humans the most robust face-selective brain areas are fusiform face area (FFA), occipital face area (OFA) and superior temporal sulcus (STS). However, in monkeys the strongest face selectivity is found predominantly in STS, and no reliable face selectivity has been reported in fusiform gyrus and occipital temporal region. These differences may be a species difference, or they may be due to technical difficulties, because in monkeys the fusiform gyrus and ventral occipital-temporal area are located in regions that are difficult to map with fMRI due to susceptibility artifacts from the ear canal. Here we used an optimized imaging protocol at 7T, which does not suffer from the usual signal loss in inferior temporal areas. We investigated the functional organization of face processing in 5 awake or anesthetized macaques while the subjects viewed faces, fruit, houses and fractal patterns. We found face-specific BOLD responses in STS, anterior medial temporal sulcus (AMTS), the regions anterior and lateral to AMTS and amygdala, consistent with previous fMRI and electrophysiology results. But in addition, entorhinal cortex (EC), ventral TE (posterior to AMTS), and hippocampus also contain face selective patches. These areas have not been reported to be face-selective in monkeys before, although they were shown to be responsive to faces with fMRI or intracortical recording in humans. The results indicate that there is much more extensive face selective brain activity than earlier studies have found in monkey ventral temporal lobe and suggests a large degree of similarity between the human and monkey face-processing network.}, web_url = {http://www.sfn.org/am2010/index.aspx?pagename=abstracts_main}, event_name = {40th Annual Meeting of the Society for Neuroscience (Neuroscience 2010)}, event_place = {San Diego, CA, USA}, state = {published}, author = {Ku S-P{shihpi}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}; Goense J{jozien}{Department Physiology of Cognitive Processes}} } @Poster{ 6810, title = {Decorrelated Firing in Cortical Microcircuits}, year = {2010}, month = {6}, volume = {2010}, pages = {58}, abstract = {Correlated trial-to-trial variability in the activity of cortical neurons is thought to reflect the functional connectivity of the circuit. Many cortical areas are organized into functional columns, in which neurons are believed to be densely connected and share common input. Numerous studies report a high degree of correlated variability between nearby cells. We developed chronically implanted multi-tetrode arrays offering unprecedented recording quality to re-examine this question in primary visual cortex of awake macaques. We found that even nearby neurons with similar orientation tuning show virtually no correlated variability. In a total of 46 recording sessions from two monkeys, we presented either static or drifting sine-wave gratings at eight different orientations. We recorded from 407 well isolated, visually responsive and orientation-tuned neurons, resulting in 1907 simultaneously recorded pairs of neurons. In 406 of these pairs both neurons were recorded by the same tetrode. Despite being physically close to each other and having highly overlapping receptive fields, neurons recorded from the same tetrode had exceedingly low spike count correlations (rsc = 0.005 ± 0.004; mean ± SEM). Even cells with similar preferred orientations (rsignal > 0.5) had very weak correlations (rsc = 0.028 ± 0.010). This was also true if pairs were strongly driven by gratings with orientations close to the cells’ preferred orientations. Correlations between neurons recorded by different tetrodes showed a similar pattern. They were low on average (rsc = 0.010 ± 0.002) with a weak relation between tuning similarity and spike count correlations (two-sample t test, rsignal < 0.5 versus rsignal > 0.5: P = 0.003, n = 1907). To investigate whether low correlations also occur under more naturalistic stimulus conditions, we presented natural images to one of the monkeys. The average rsc was close to zero (rsc = 0.001 ± 0.005, n = 329) with no relation between receptive field overlap and spike count correlations. We obtained a similar result during stimulation with moving bars in a third monkey (rsc = 0.014 ± 0.011, n = 56). Our findings suggest a refinement of current models of cortical microcircuit architecture and function: either adjacent neurons share only a few percent of their inputs or, alternatively, their activity is actively decorrelated.}, web_url = {http://www.areadne.org/2010/home.html}, editor = {Hatsopoulos, N. G., S. Pezaris}, event_name = {AREADNE 2010: Research in Encoding And Decoding of Neural Ensembles}, event_place = {Santorini, Greece}, state = {published}, author = {Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Berens P{berens}{Research Group Computational Vision and Neuroscience}; Keliris GA{george}{Department Physiology of Cognitive Processes}; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Poster{ 6290, title = {Primary visual cortex contributions in perceptual supppression}, year = {2009}, month = {10}, volume = {39}, number = {805.4}, abstract = {Understanding the neural underpinnings of conscious perception has long intrigued the students of the brain from philosophers to modern neuroscientists. In the visual domain, the primary visual cortex (V1) is by far the most extensively studied cortical area. It entails the main gateway of visual information to higher cortical areas and we understand a lot about its function in sensory processing. Nevertheless, the role of V1 in perceptual awareness remains intensely debated. Under certain stimulus conditions perception alternates between two or multiple stimulus interpretations. Notably such perceptual alternations happen while the sensory input is kept constant, offering thus a clear dissociation of sensory stimulation and subjective awareness. A celebrated example of such a perceptual phenomenon is binocular rivalry (BR). It involves the dichoptic presentation of two different stimuli at corresponding retinal locations and results in the perceptual suppression of one of the two stimuli at different times. A slight variant of BR, binocular flash suppression (BFS), ensures excellent control over the subjects’ perceptual state by intermittent presentation of monocular and binocular stimuli. We have trained rhesus macaques to report their perception during BFS and BR to study the effects of perceptual suppression in V1. We have recorded the spiking activity of a large number of well isolated single units (SUA) and acquired simultaneous local field potentials (LFPs) during the dichoptic presentation of orthogonal orientation gratings. We found that during BFS, 20% of the single units modulated their activities in consonance with the perceptual state. Furthermore, the magnitude of the perceptual effect was small (15%) in comparison to the sensory preference of the neurons. Analysis of the ocularity preferences demonstrated that both monocular and binocular classes of cells show perceptual modulations with equal probability. In addition, cells modulating during perceptual suppression encode information matching their sensory preferences and therefore can be used for decoding both the orientation and/or the eye of presentation of the perceived grating. Results of the LFPs were very similar to the single units showing a similar percentage of sites modulating with perception in all analyzed frequency bands. We conclude that footprints of perception are evident in both the SUA and LFP signals in V1 but in a much smaller degree than their corresponding sensory selectivity. Perceptual states might have a modulatory role on more intricate aspects of V1 firing patterns, not necessarily altering the firing rates of single cells or the LFP power dramatically.}, web_url = {http://www.abstractsonline.com/Plan/ViewAbstract.aspx?sKey=b32a2863-3104-401e-a2e7-5263bb970bc4&cKey=32ca0e40-6724-42ff-90dd-e00783866960}, event_name = {39th Annual Meeting of the Society for Neuroscience (Neuroscience 2009)}, event_place = {Chicago, IL, USA}, state = {published}, author = {Keliris GA{george}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ PanagiotaropoulosKKTL2009, title = {High frequency local field potentials and multi unit activity reflect visual awareness in the macaque prefrontal cortex}, journal = {Frontiers in Behavioral Neuroscience}, year = {2009}, month = {9}, volume = {Conference Abstract: 41st European Brain and Behaviour Society Meeting}, abstract = {Binocular rivalry (BR) has been successfully combined with extracellular electrophysiological recordings in awake, behaving macaques to study the cortical mechanisms of subjective visual perception. Here we used binocular flash suppression (BFS), a highly controlled variant of BR, to explore the neuronal correlates of visual awareness in the inferior prefrontal convexity (icPFC) of the macaque brain while simultaneously recording multi unit activity (MUA) and local field potentials (LFP). We found that MUA was perceptually modulated in 67% of the visually selective recording sites. During BFS in 92% of MUA modulated sites we observed higher firing rates when the preferred stimulus was perceived. An explicit representation of the perceptually dominant stimulus was also provided by the power modulation of high frequency LFP’s only at the MUA modulated sites. Specifically, sensory selectivity of the LFP power increased as a function of frequency with the highest selectivity observed between 150 and 450Hz. The same pattern in LFP power selectivity was observed when the preferred stimulus was perceived during BFS. A correlation analysis between MUA and LFP power selectivity showed significant correlation in sensory selectivity for frequencies >60Hz that saturated at 150Hz and followed the same pattern during BFS. While spikes measure cortical output, LFP’s are thought to reflect input and intracortical processing in a given cortical area. According to this scheme our results suggest that icPFC sites providing perceptually modulated output are also the sites that receive and process a representation of the perceived stimulus during BFS. Inferior temporal cortex (IT) output is also known to reflect the perceived stimulus during ambiguous visual stimulation and could thus be the source of the modulated icPFC input reflected in the LFP’s. Our results suggest a highly organized network involving IT and icPFC that mediates visual awareness during subjective visual perception.}, web_url = {http://www.frontiersin.org/10.3389/conf.neuro.08.2009.09.251/event_abstract}, event_name = {41st European Brain and Behaviour Society Meeting}, event_place = {Rhodos, Greece}, state = {published}, DOI = {10.3389/conf.neuro.08.2009.09.251}, author = {Panagiotaropoulos T{theofanis}{Department Physiology of Cognitive Processes}; Kapoor V{vishal}{Department Physiology of Cognitive Processes}; Keliris GA{george}{Department Physiology of Cognitive Processes}; Tolias A{atolias}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ 5844, title = {Sensory input statistics and network mechanisms in primate primary visual cortex}, journal = {Frontiers in Systems Neuroscience}, year = {2009}, month = {3}, volume = {2009}, number = {Conference Abstracts: Computational and Systems Neuroscience}, abstract = {Understanding the structure of multi-neuronal firing patterns in ensembles of cortical neurons is a major challenge for systems neuroscience. The dependence of network properties on the statistics of the sensory input can provide important insights into the computations performed by neural ensembles. Here, we study the functional properties of neural populations in the primary visual cortex of awake, behaving macaques by varying visual input statistics in a controlled way. Using arrays of chronically implanted tetrodes, we record simultaneously from up to thirty well-isolated neurons while presenting sets of images with three different correlation structures: spatially uncorrelated white noise (whn), images matching the second-order correlations of natural images (phs) and natural images including higher-order correlations (nat). We find that groups of six nearby cortical neurons show little redundancy in their firing patterns (represented as binary vectors, 10ms bins) but rather act almost independently (mean multi-information 0.85 bits/s, range 0.16 - 1.90 bits/s, mean fraction of marginal entropy 0.34 %, N=46). Although network correlations are weak, they are statistically significant. While relatively few groups showed significant redundancies under stimulation with white noise (67.4 ± 3.2%; mean fraction of groups ± S.E.M.), many more did so in the other two conditions (phs: 95.7 ± 0.6%; nat: 89.1 ± 1.4%). Additional higher-order correlations in natural images compared to phase scrambled images did not increase but rather decrease the redundancy in the cortical representation: Network correlations are significantly higher in phs than in nat, as is the number of significantly correlated groups. Multi-information measures the reduction in entropy due to any form of correlation. By using second order maximum entropy modeling, we find that a large fraction of multi-information is accounted for by pairwise correlations (whn: 75.0 ± 3.3%; phs: 82.8 ± 2.1%; nat: 80.8 ± 2.4%; groups with significant redundancy). Importantly, stimulation with natural images containing higher-order correlations only lead to a slight increase in the fraction of redundancy due to higher-order correlations in the cortical representation (mean difference 2.26 %, p=0.054, Sign test). While our results suggest that population activity in V1 may be modeled well using pairwise correlations only, they leave roughly 20-25 % of the multi-information unexplained. Therefore, choosing a particular form of higher-order interactions may improve model quality. Thus, in addition to the independent model, we evaluated the quality of three different models: (a) The second-order maximum entropy model, which minimizes higher-order correlations, (b) a model which assumes that correlations are a product of common inputs (Dichotomized Gaussian) and (c) a mixture model in which correlations are induced by a discrete number of latent states. We find that an independent model is sufficient for the white noise condition but neither for phs or nat. In contrast, all of the correlation models (a-c) perform similarly well for the conditions with correlated stimuli. Our results suggest that under natural stimulation redundancies in cortical neurons are relatively weak. Higher-order correlations in natural images do not increase but rather decrease the redundancies in the cortical representation.}, web_url = {http://www.cosyne.org/c/index.php?title=Cosyne_09}, event_name = {Computational and Systems Neuroscience Meeting (COSYNE 2009)}, event_place = {Salt Lake City, UT, USA}, state = {published}, DOI = {10.3389/conf.neuro.06.2009.03.298}, author = {Berens P{berens}{Research Group Computational Vision and Neuroscience}; Macke JH{jakob}; Ecker AS{aecker}; Cotton RJ; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}; Tolias AS{atolias}} } @Poster{ 5359, title = {Towards the neural basis of the flash-lag effect}, year = {2008}, month = {9}, event_name = {International Workshop: Aspects of Adaptive Cortex Dynamics}, event_place = {Delmenhorst, Germany}, state = {published}, author = {Ecker AS{aecker}; Berens P{berens}{Research Group Computational Vision and Neuroscience}; Hoenselaar A{hoenselaar}; Subramaniyan M; Tolias AS{atolias}; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}} } @Poster{ MackeBEOTB2008, title = {Modeling populations of spiking neurons with the Dichotomized Gaussian distribution}, year = {2008}, month = {7}, web_url = {http://www.theswartzfoundation.org/summer-meeting-2008.asp}, event_name = {Annual Meeting 2008 of Sloan-Swartz Centers for Theoretical Neurobiology}, event_place = {Princeton, NJ, USA}, state = {published}, author = {Macke JH{jakob}; Berens P{berens}{Research Group Computational Vision and Neuroscience}; Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Opper M; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}} } @Poster{ 5443, title = {Neurophysiological substrates of visual awareness in the macaque prefrontal cortex}, year = {2008}, month = {7}, volume = {6}, number = {220.12}, abstract = {Human fMRI studies during binocular rivalry have demonstrated an involvement of prefrontal cortex (PFC) in the processing of subjective visual perception. In this study we used binocular flash suppression, a version of binocular rivalry that permits the robust induction of a visual percept, to study the neuronal correlates of visual awareness in the macaque prefrontal cortex (PFC) and specifically in the inferior prefrontal convexity. We found that the firing rate of almost 70% of the visually selective neurons closely followed the induced visual percept. This percentage is significantly higher than the respective percentage of perceptually modulated cells found in the striate and extrastriate visual cortex (V1, V2 and V4) but smaller than that found in the inferior temporal cortex (IT) (almost 90%). Interestingly, we observed that the neuronal responses following a perceptual alternation were transient, similar to the transient BOLD response observed during perceptual transitions in the human binocular rivalry fMRI studies. Our finding provides further evidence in support of a role of higher brain areas in processing an explicit perceptual representation during ambiguous visual stimulation. In addition, it points to a potential neuronal network consisting of perceptually modulated cells in IT and PFC that process an explicit representation of a visual percept. The existence of such a network is not surprising since area TE of inferior temporal cortex is anatomically connected to the inferior convexity (areas 12/45) through feedforward and feedback pathways. Finally, in an effort to explore whether the perceptual modulation observed in primary visual cortex (V1) is influenced by a feedback signal from PFC we will also present data from simultaneous PFC and V1 neurophysiological recordings during binocular flash suppression.}, web_url = {http://fens2008.neurosciences.asso.fr/}, event_name = {6th Forum of European Neuroscience (FENS 2008)}, event_place = {Geneva, Switzerland}, state = {published}, author = {Panagiotaropoulos T{theofanis}{Department Physiology of Cognitive Processes}; Kapoor V{vishal}{Department Physiology of Cognitive Processes}; Keliris GA{george}{Department Physiology of Cognitive Processes}; Tolias A{atolias}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ 5511, title = {The Role of Primary Visual Cortex (V1) in Perceptual Suppression}, year = {2008}, month = {7}, volume = {6}, number = {220.8}, abstract = {When two incongruent stimuli are presented simultaneously at corresponding retinal locations in the two eyes, one typically experiences a perceptual alternation of the two stimuli; a phenomenon known as binocular rivalry. Binocular flash suppression (BFS) is a variant of binocular rivalry and refers to the sudden and persistent perceptual suppression resulting when two rivalrous patterns are presented dichoptically and asynchronously to the two eyes. Under these conditions, the latter pattern dominates perceptually over the first. The binocular flash suppression paradigm ensures excellent control over the subject’s perceptual state without the need for subjective reports which involve decision making, action preparation and action execution. The role of primary visual cortex (V1) in perceptual suppression remains controversial. In this study, we assessed quantitatively the effects of perceptual suppression on neural activity in V1 of the macaque using BFS. We have analyzed both the spiking activity of a large number of single neurons (SUA) and different frequency bands of the local field potentials (LFPs). The main result for SUA was that only a small minority (~20%) modulates in consonance with the perceptual suppression of static orientation gratings. Furthermore, the magnitude of the perceptual effect was small (~15%) in comparison to the sensory preference of the neurons. LFPs showed comparable percentages. The amplitude of LFP modulations was independent of frequency although gamma frequencies showed greater selectivity during physical alternation of the stimuli. Our results provide evidence against the hypothesis that competition is happening at the level of monocular neurons at the input layers of primary visual cortex.}, web_url = {http://fens2008.neurosciences.asso.fr/}, event_name = {6th Forum of European Neuroscience (FENS 2008)}, event_place = {Geneva, Switzerland}, state = {published}, author = {Keliris GA{george}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ 5857, title = {Analysis of Pattern Recognition Methods in Classifying Bold Signals in Monkeys at 7-Tesla}, year = {2008}, month = {6}, pages = {67}, abstract = {Pattern recognition methods have shown that fMRI data can reveal significant information about brain activity. For example, in the debate of how object-categories are represented in the brain, multivariate analysis has been used to provide evidence of distributed encoding schemes. Many follow-up studies have employed different methods to analyze human fMRI data with varying degrees of success. In this study we compare four popular pattern recognition methods: correlation analysis, support-vector machines (SVM), linear discriminant analysis and Gaussian naïve Bayes (GNB), using data collected at high field (7T) with higher resolution than usual fMRI studies. We investigate prediction performance on single trials and for averages across varying numbers of stimulus presentations. The performance of the various algorithms depends on the nature of the brain activity being categorized: for several tasks, many of the methods work well, whereas for others, no methods perform above chance level. An important factor in overall classification performance is careful preprocessing of the data, including dimensionality reduction, voxel selection, and outlier elimination.}, web_url = {http://www.areadne.org/2008/home.html}, event_name = {AREADNE 2008: Research in Encoding and Decoding of Neural Ensembles}, event_place = {Santorini, Greece}, state = {published}, author = {Ku S-P{shihpi}{Department Physiology of Cognitive Processes}; Gretton A{arthur}{Department Empirical Inference}; Macke J{jakob}; Tolias AT{atolias}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ 5101, title = {Flexible Models for Population Spike Trains}, year = {2008}, month = {6}, pages = {48}, abstract = {In order to understand how neural systems perform computations and process sensory information, we need to understand the structure of firing patterns in large populations of neurons. Spike trains recorded from populations of neurons can exhibit substantial pair wise correlations between neurons and rich temporal structure. Thus, efficient methods for generating artificial spike trains with specified correlation structure are essential for the realistic simulation and analysis of neural systems. Here we show how correlated binary spike trains can be modeled by means of a latent multivariate Gaussian model. Sampling from our model is computationally very efficient, and in particular, feasible even for large populations of neurons. We show empirically that the spike trains generated with this method have entropy close to the theoretical maximum. They are therefore consistent with specified pair-wise correlations without exhibiting systematic higher-order correlations. We compare our model to alternative approaches and discuss its limitations and advantages. In addition, we demonstrate its use for modeling temporal correlations in a neuron recorded in macaque primary visual cortex. Neural activity is often summarized by discarding the exact timing of spikes, and only counting the total number of spikes that a neuron (or population) fires in a given time window. In modeling studies, these spike counts have often been assumed to be Poisson distributed and neurons to be independent. However, correlations between spike counts have been reported in various visual areas. We show how both temporal and inter-neuron correlations shape the structure of spike counts, and how our model can be used to generate spike counts with arbitrary marginal distributions and correlation structure. We demonstrate its capabilities by modeling a population of simultaneously recorded neurons from the primary visual cortex of a macaque, and we show how a model with correlations accounts for the data far better than a model that assumes independence.}, web_url = {http://www.areadne.org/2008/home.html}, event_name = {AREADNE 2008: Research in Encoding and Decoding of Neural Ensembles}, event_place = {Santorini, Greece}, state = {published}, author = {Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}; Macke JH{jakob}; Berens P{berens}{Research Group Computational Vision and Neuroscience}; Ecker AS{aecker}; Tolias AS{atolias}} } @Poster{ 5100, title = {Pairwise Correlations and Multineuronal Firing Patterns in the Primary Visual Cortex of the Awake, Behaving Macaque}, year = {2008}, month = {6}, pages = {46}, abstract = {Understanding the structure of multi-neuronal firing patterns has been a central quest and major challenge for systems neuroscience. In particular, how do pairwise interactions between neurons shape the firing patterns of neuronal ensembles in the cortex? To study this question, we recorded simultaneously from multiple single neurons in the primary visual cortex of an awake, behaving macaque using an array of chronically implanted tetrodes1. High contrast flashed and moving bars were used for stimulation, while the monkey was required to maintain fixation. In a similar vein to recent studies of in vitro preparations 2,3,5, we applied maximum entropy analysis for the first time to the binary spiking patterns of populations of cortical neurons recorded in vivo from the awake macaque. We employed the Dichotomized Gaussian distribution, which can be seen as a close approximation to the pairwise maximum-entropy model for binary data4. Surprisingly, we find that even pairs of neurons with nearby receptive fields (receptive field center distance < 0.15°) have only weak correlations between their binary responses computed in bins of 10 ms (median absolute correlation coefficient: 0.014, 0.010-0.019, 95% confidence intervals, N=95 pairs; positive correlations: 0.015, N=59; negative correlations: -0.013, N=36). Accordingly, the distribution of spiking patterns of groups of 10 neurons is described well with a model that assumes independence between individual neurons (Jensen-Shannon-Divergence: 1.06×10-2 independent model, 0.96×10-2 approximate second-order maximum-entropy model4; H/H1=0.992). These results suggest that the distribution of firing patterns of small cortical networks in the awake animal is predominantly determined by the mean activity of the participating cells, not by their interactions. Meaningful computations, however, are performed by neuronal populations much larger than 10 neurons. Therefore, we investigated how weak pairwise correlations affect the firing patterns of artificial populations4 of up to 1000 cells with the same correlation structure as experimentally measured. We find that in neuronal ensembles of this size firing patterns with many active or silent neurons occur considerably more often than expected from a fully independent population (e.g. 130 or more out of 1000 neurons are active simultaneously roughly every 300 ms in the correlated model and only once every 3-4 seconds in the independent model). These results suggest that the firing patterns of cortical networks comparable in size to several minicolumns exhibit a rich structure, even if most pairs appear relatively independent when studying small subgroups thereof.}, web_url = {http://www.areadne.org/2008/home.html}, event_name = {AREADNE 2008: Research in Encoding and Decoding of Neural Ensembles}, event_place = {Santorini, Greece}, state = {published}, author = {Berens P{berens}{Research Group Computational Vision and Neuroscience}; Ecker AS{aecker}; Subramaniyan M; Macke JH{jakob}; Hauck P; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}; Tolias AS{atolias}} } @Poster{ 5442, title = {Single units reflect visual awareness in the macaque prefrontal cortex}, year = {2008}, month = {6}, pages = {80}, web_url = {http://www.areadne.org/2008/home.html}, event_name = {AREADNE 2008: Research in Encoding and Decoding of Neural Ensembles}, event_place = {Santorini, Greece}, state = {published}, author = {Panagiotaropoulos T{theofanis}{Department Physiology of Cognitive Processes}; Kapoor V{vishal}{Department Physiology of Cognitive Processes}; Keliris GA{george}{Department Physiology of Cognitive Processes}; Tolias A{atolias}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ 5510, title = {The Role of Primary Visual Cortex in Perceptual Awareness}, year = {2008}, month = {6}, pages = {61}, abstract = {Under certain stimulus conditions a single interpretation of the external world cannot be unambiguously designated. When the brain is presented with such stimuli typically only one possible interpretation is perceived and after a few seconds the percept switches abruptly to another. Notably such perceptual alternations happen while the sensory input is kept constant, offering thus a clear dissociation of sensory stimulation and subjective awareness. A celebrated example of such a perceptual phenomenon is binocular rivalry (BR). It involves alternations of visual perception between two different images presented dichoptically at corresponding retinal locations. Based on many psychophysical studies over decades the primary visual cortex (V1) was implicated as an important candidate for the site of perceptual suppression. However, the first neurophysiological evidence performed in monkeys did not corroborate this but instead found only a small percentage of neurons modulating their activity with the subjective awareness reported by the animals. On the contrary, studies using human functional magnetic resonance imaging (fMRI), have found V1 to be modulating to a large extent, creating an apparent controversy. Therefore, the role of primary visual cortex (V1) in subjective perception remains controversial. In this study, we studied the effects of perceptual suppression on neural activity in V1 of the macaque. We have used the binocular flash suppression (BFS) paradigm, a variant of BR which ensures excellent control over the subject’s perceptual state. We have recorded the spiking activity of a large number of well isolated single units (SUA) and acquired simultaneous local field potentials (LFPs) during the dichoptic presentation of orthogonal orientation gratings. Our design enabled us to determine a) which neurons and LFP bands are correlated with the percept and b) how this is related to their orientation and ocularity preferences. We find that only a small minority of about 20% of the single units modulate in consonance with the perceptual suppression. Furthermore, the magnitude of the perceptual effect was small (~15%) in comparison to the sensory preference of the neurons. Results of the LFPs were very similar to the single units showing a similar percentage of sites modulating with perception. Analysis of the orientation and ocularity preference of neurons did not show a particular class of cells to be having a greater probability to show perceptual modulations.}, web_url = {http://www.areadne.org/2008/home.html}, event_name = {AREADNE 2008: Research in Encoding and Decoding of Neural Ensembles}, event_place = {Santorini, Greece}, state = {published}, author = {Keliris GA{george}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ 5512, title = {Binocular Flash Suppression in area V1 of the macaque}, year = {2008}, month = {2}, event_name = {First Annual inter-Science of Learning Center (iSLC): Student and Postdoc Conference}, event_place = {Pittsburgh, PA, USA}, state = {published}, author = {Keliris GA{george}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ 4591, title = {On the spatial scale of the local field potential - orientation and ocularity tuning of the local field potential in the primary visual cortex of the macaque}, year = {2007}, month = {11}, volume = {37}, number = {176.7}, abstract = {The local field potential (LFP) and, in particular, the gamma-band frequency range (30-90 Hz) have recently received much attention, as numerous studies have shown correlations between LFP and sensory, motor and cognitive variables in various cortical regions. However, the extent to which it reflects the activity of local populations of neurons remains elusive. The issue of spatial scale is central for understanding the origins of the LFP and how this signal can be used to study the functional organization of the brain. We addressed this question by simultaneously recording multi-unit spiking activity (MUA) and LFP from the primary visual cortex (V1) of awake, behaving macaques using arrays of tetrodes. Oriented gratings were used for visual stimulation, applied either binocular or monocular. The columnar organization of stimulus orientation and ocularity in V1 provides an excellent opportunity to study the spatial precision of the LFP signal, because neurons with similar orientation preference are organized at the fine spatial scale of cortical microcolumns (50-100 μm), whereas ocular dominance columns span around 450 μm. As shown before, we find that the increase of LFP gamma-band power is a function of orientation and ocularity of the stimulus. However, the power of the gamma-band contains much less information about the orientation of the stimulus than the MUA recorded at the same site. The average discriminability d' between preferred and orthogonal orientation was 2.46±0.15 for MUA and 1.01±0.05 for LFP (mean ±std). Moreover, we find only a weak correlation between the preferred orientation of the MUA tuning function and that of the LFP (r=0.21, p<0.05). In contrast, we find a strong correlation between the preferred ocularity of the two signals (r=0.53, p<1e-9). We therefore conclude that the gamma-power of the LFP does not reflect well the local activity on the scale of orientation columns but does capture the ocular dominance structure of V1. We suggest that gamma-band activity is generated by ensembles of neurons larger than 50-100 μm. In agreement with a previous study (Liu & Newsome, 2006) we find that it more likely resembles the activity of neurons from an area spanning a few hundred micrometers.}, web_url = {http://www.sfn.org/am2007/}, event_name = {37th Annual Meeting of the Society for Neuroscience (Neuroscience 2007)}, event_place = {San Diego, CA, USA}, state = {published}, author = {Berens P{berens}; Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Keliris GA{george}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Poster{ 4733, title = {Recording chronically from the same neurons in awake, behaving primates}, year = {2007}, month = {11}, volume = {37}, number = {176.8}, abstract = {Understanding the mechanisms of learning and memory consolidation requires characterizing how the response properties of individual neurons and interactions across populations of neurons change over time, during periods spanning multiple days. We used multiple chronically implanted tetrodes to record single unit activity from area V1 of the awake, behaving macaque and developed a method to quantitatively determine recording stability. Our method is based on a statistical framework which uses similarity of action potential waveforms to detect stable recordings given a pre-defined type I error rate. The similarity measure that was used takes into account both the shape of the action potential waveform and the amplitude ratio across channels, which depends on the location of the neuron relative to the tetrode. 271 well-isolated single units were recorded from 7 tetrodes during two periods of up to 23 days. We computed the distribution of pairwise similarities of average waveforms recorded on consecutive recording sessions during the first 34 days after implantation of the chronic drive. During this period, there was no recording stability due to regular adjustments of the tetrodes. We used this distribution as an empirical null distribution for hypothesis testing. Using this statistical procedure and a type I error rate of alpha = 0.05, we find that of all single units recorded on a given day, 51% could be recorded for at least 2 days, 40% for at least 3 days, and 25% for at least 7 days. In addition, we adapted a recently proposed multivariate statistical test (Gretton et al., 2007) to test whether the waveforms obtained at consecutive days come from the same underlying probability distribution. Using this test we obtained qualitatively similar results. To validate these results, we compared orientation tuning functions of neurons that were tracked across days. Consistent with the claim that the same neurons were recorded across days and the fact that the monkey was not performing a learning task, the distribution of tuning differences of stable and orientation-tuned neurons across days was highly significantly different (Wilcoxon rank sum test, n1 = 79, n2 = 582, p < 10^-34) from the distribution of tuning differences across different neurons. Our results show that using only waveform information it is possible to reliably track stable neurons across days with a limited type I error probability. This statistical approach is particularly important since, in a learning experiment, properties of neurons such as orientation tuning are potentially changed and therefore cannot be used to evaluate stability.}, web_url = {http://www.sfn.org/am2007/}, event_name = {37th Annual Meeting of the Society for Neuroscience (Neuroscience 2007)}, event_place = {San Diego, CA, USA}, state = {published}, author = {Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Siapas AG; Hoenselaar A{hoenselaar}{Department Physiology of Cognitive Processes}; Berens P{berens}; Keliris GA{george}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Poster{ 4998, title = {Using SE-EPI to measure visual responses in temporal lobe of awake macaque at 7 Tesla}, year = {2007}, month = {11}, volume = {37}, number = {396.3}, abstract = {In contrast to electrophysiological studies, the advantage of fMRI is that it allows simultaneous mapping of the functional organization of multiple cortical areas. FMRI of awake monkey has benefit of combining behavioral studies with BOLD-measurement to be used to precisely localize functional specific cortical areas for further invasive studies such as detailed electrophysiological single unit recordings. Although high magnetic field offers the benefit of increased signal-to-noise ratios and higher specificity, a drawback is the higher sensitivity to susceptibility gradients caused by the air-tissue interfaces. This can be particularly problematic in the lower floor of temporal lobe, because the large macroscopic susceptibility gradients near the ear canal result in distortion and loss of signal when the standard GE-EPI is used. For fMRI of such areas using spin-echo EPI (SE-EPI) is advantageous because it is less sensitive than GE-EPI to susceptibility artifacts, and does not suffer from signal dropout in these regions. Another advantage is that SE-EPI is less affected by frequency-changes in the main magnetic field, which are caused by movement of the animal. In this study, we compared SE-EPI and gradient-echo fMRI in the awake monkey (Macaca mulatta), using a vertical bore 7T MR system. A saddle coil optimized for temporal cortex was used to allow imaging of the major visual areas. The imaging parameters and slice orientation were optimized to minimize susceptibility effects. Resolution was typically 1.5x2x2mm, TE was 40 ms, TR was 1-2 s. In contrast to the GE-EPI images, which showed very large signal dropout in the temporal lobe, SE images showed minimal or no distortion or signal loss. Any remaining distortions were corrected using field-map correction to ensure matching of the functional map to the high-resolution T1-weighted anatomical images. Using movie- stimuli, we confirmed that reliable functional activation could be obtained with SE-EPI at high field, and we show robust activation in the temporal lobe and early visual areas. Using monkey faces, objects and fractal patterns we were also able to obtain functional activities in specific visual object sensitive areas in inferior temporal cortex. The reliability and specificity of the obtained activations with SE-EPI ensures the application of the method in our on-going visual perception studies.}, web_url = {http://www.sfn.org/am2007/}, event_name = {37th Annual Meeting of the Society for Neuroscience (Neuroscience 2007)}, event_place = {San Diego, CA, USA}, state = {published}, author = {Ku S-P{shihpi}{Department Physiology of Cognitive Processes}; Goense J{jozien}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ 4731, title = {Studying the effects of noise correlations on population coding using a sampling method}, year = {2007}, month = {9}, pages = {21-22}, abstract = {Responses of single neurons to a fixed stimulus are usually both variable and highly ambiguous. Therefore, it is widely assumed that stimulus parameters are encoded by populations of neurons. An important aspect in population coding that has received much interest in the past is the effect of correlated noise on the accuracy of the neural code. Theoretical studies have investigated the effects of different correlation structures on the amount of information that can be encoded by a population of neurons based on Fisher Information. Unfortunately, to be analytically tractable, these studies usually have to make certain simplifying assumptions such as high firing rates and Gaussian noise. Therefore, it remains open if these results also hold in the more realistic scenario of low firing rates and discrete, Poisson-distributed spike counts. In order to address this question we have developed a straightforward and efficient method to draw samples from a multivariate near-maximum entropy Poisson distribution with arbitrary mean and covariance matrix based on the dichotomized Gaussian distribution [1]. The ability to extensively sample data from this class of distributions enables us to study the effects of different types of correlation structures and tuning functions on the information encoded by populations of neurons under more realistic assumptions than analytically tractable methods. Specifically, we studied how limited range correlations (neurons with similar tuning functions and low spatial distance are more correlated than others) affect the accuracy of a downstream decoder compared to uniform correlations (correlations between neurons are independent of their properties and locations). Using a set of neurons with equally spaced orientation tuning functions, we computed the error of an optimal linear estimator (OLE) reconstructing stimulus orientation from the neurons firing rates. We findsupporting previous theoretical resultsthat irrespective of tuning width and the number of neurons in the network, limited range correlations decrease decoding accuracy while uniform correlations facilitate accurate decoding. The optimal tuning width, however, did not change as a function of either the correlation structure or the number of neurons in the network. These results are particularly interesting since a number of experimental studies report limited range correlation structures (starting at around 0.1 to 0.2 for similar neurons) while experiments carried out in our own lab suggest that correlations are generally low (on the order of 0.01) and uniform.}, web_url = {http://www.gatsby.ucl.ac.uk/nccd/nccd07/abstract_book.pdf}, event_name = {Neural Coding, Computation and Dynamics (NCCD 07)}, event_place = {Hossegor, France}, state = {published}, author = {Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Berens P{berens}{Research Group Computational Vision and Neuroscience}; Bethge M{mbethge}{Research Group Computational Vision and Neuroscience}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Poster{ 5488, title = {Spin-echo fMRI of the temporal lobe in awake, behaving monkeys at 7T}, year = {2007}, month = {5}, day = {23}, volume = {2007}, pages = {399}, abstract = {Susceptibility gradients from the ear canal result in distortion and signal loss in GE-EPI, resulting in loss of functional activation in areas adjacent to the ear canal. Although susceptibility-related signal loss also occurs at low field, at 7T it is so severe that no functional activation is seen in these areas. We are interested in fMRI of the entire visual ventral stream in awake monkeys, because the ventral pathway is crucial for object recognition. To overcome the susceptibility problem in the temporal lobes, we used SE-EPI, which allowed us to recover functional activation in areas affected by susceptibility gradients.}, web_url = {http://www.ismrm.org/07/}, event_name = {2007 Joint Annual Meeting ISMRM-ESMRMB}, event_place = {Berlin, Germany}, state = {published}, author = {Goense JBM{jozien}{Department Physiology of Cognitive Processes}; Ku S-P{shihpi}{Department Physiology of Cognitive Processes}; Merkle H{hellmut}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ 4272, title = {A Data Management System for Electrophysiological Data Analysis}, journal = {Neuroforum}, year = {2007}, month = {4}, volume = {13}, number = {Supplement}, pages = {1222}, abstract = {Recent advances in both electrophysiological recording techniques and hardware capabilities have enabled researchers to simultaneously record from a large number of neurons in different areas of the brain. This opens the door for a wide range of complex analyses potentially leading to a better understanding of the principles underlying neural network computations. At the same time, due to the increasing amount of data with increasing complexity, significantly more emphasis has to be put on the data analysis task. Although high-level scripting languages such as Matlab can speed up the development of analysis tools, in our experience, a too large amount of time is still spent on (re)structuring and (re)organizing data for specific analyses. Therefore, our goal was to develop a system which enables experimental neuroscientists to spend less time on organizing their data and more on data collection and creative analysis. We developed an object oriented Matlab toolbox which supplies the user with basic data types and functions to organize and structure various types of electrophysiological data. By using an object oriented, hierarchical layout, basic functionality, such as integration of metadata, or storage and retrieval of data and results, is implemented independent of specific data formats or experimental designs. This provides maximal flexibility and compatibility with future experiments and new data formats. All data and experimental results are stored in a database, so the experimenter can choose which data to keep in memory for faster access and which to save to disk to save resources. Additionally, we have created an extensive library of basic analysis and visualization tools that can be used to get an overview of the data.}, file_url = {/fileadmin/user_upload/files/publications/EckerTolias_2007_ADataManagement_4272[0].pdf}, web_url = {http://nwg.glia.mdc-berlin.de/media/pdf/conference/Proceedings-Goettingen2007.pdf}, event_name = {7th Meeting of the German Neuroscience Society, 31st Göttingen Neurobiology Conference}, event_place = {Göttingen, Germany}, state = {published}, author = {Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Berens P{berens}; Keliris GA{george}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Poster{ 4273, title = {Orientation tuning of the local field potential and multi-unit activity in the primary visual cortex of the macaque}, journal = {Neuroforum}, year = {2007}, month = {4}, volume = {13}, number = {Supplement}, pages = {735}, abstract = {Oscillations in the local field potential (LFP) are abundant across species and brain regions. The possible relationship of these low-frequency extracelluar voltage fluctuations with the activity of the underlying local population of neurons remains largely elusive. To study this relationship, we used an array of chronically implanted tetrodes spanning a distance of 700 μm and simultaneously recorded action potentials from multiple well-isolated single units, multi unit activity (MUA) and LFP from area V1 of the awake, behaving macaque. Moving and static gratings of different orientations were used for visual stimulation. In agreement with previous studies we find that the increase of LFP gamma-band power is a function of the orientation of the stimulus. However, the power of the gamma-band contains much less information about the orientation of the stimulus than the MUA and SUA recorded at the same site (Figure 1A). The average discriminability d‘ between preferred and orthogonal orientation was 2.46 for MUA, 2.45 for SUA and 1.01 for the LFP. Moreover, in contrast to recent results from area MT (Liu and Newsome, 2006) we find only a weak correlation between the preferred orientation of the MUA tuning function and that of the LFP (Figure 1B, different colors indicate different animals). Interestingly, all nearby LFP recording sites in our array were tuned to a similar orientation while the preferred orientations of MUA tuning functions were widely scattered. These results suggest that the power of LFP signals does not capture local population activity at the scale of orientation columns in area V1.}, file_url = {/fileadmin/user_upload/files/publications/T16-4C_[0].pdf}, web_url = {http://nwg.glia.mdc-berlin.de/media/pdf/conference/Proceedings-Goettingen2007.pdf}, event_name = {7th Meeting of the German Neuroscience Society, 31st Göttingen Neurobiology Conference}, event_place = {Göttingen, Germany}, state = {published}, author = {Berens P{berens}; Keliris GA{george}{Department Physiology of Cognitive Processes}; Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Poster{ KuGTL2007, title = {Using SE-EPI to Measure Visual Responses in the Awake Macaque at 7 Tesla}, journal = {Neuroforum}, year = {2007}, month = {4}, volume = {13}, number = {Supplement}, pages = {765}, abstract = {In contrast to electrophysiological studies, the advantage of fMRI is that it allows simultaneous mapping of the functional organization of multiple cortical areas. FMRI of awake monkey has benefit of combining behavioral studies with BOLD-measurement to be used to precisely localize functional specific cortical areas for further invasive studies such as detailed electrophysiological single unit recordings. Although high magnetic field offers the benefit of increased signal-to-noise ratios and higher specificity, a drawback is the higher sensitivity to susceptibility gradients caused by the air-tissue interfaces. This can be particularly problematic in the lower floor of temporal lobe because the large macroscopic susceptibility gradients near the ear canal result in distortion and loss of signal when the standard GE-EPI is used. For fMRI of such areas using spin-echo EPI (SE-EPI) is advantageous because it is less sensitive than GE-EPI to susceptibility artifacts, and does not suffer from signal dropout in these regions. Another advantage is that SE-EPI is less affected by frequency-changes in the main magnetic field, which are caused by movement of the animal. In this study, we compared SE-EPI and gradient-echo fMRI in the awake monkey (Macaca mulatta), using a vertical bore 7T MR system. A saddle coil optimized for temporal cortex was used to allow imaging of the major visual areas. The imaging parameters and slice orientation were optimized to minimize susceptibility effects. Resolution was typically 1.5x2x2mm, TE was 40 ms, TR was 1-2 s. In contrast to the GE-EPI images, which showed very large signal dropout in the temporal lobe, SE images showed minimal or no distortion or signal losses. Any remaining distortions were corrected using field-map correction to ensure perfect matching of the functional map to the high-resolution T1-weighted anatomical images. Using movie- stimuli, we confirmed that reliable functional activation could be obtained with SE-EPI at high field, and we show robust activation in the temporal lobe and early visual areas. Using random-dot kinematograms of various coherences we were also able to obtain functional activities in specific visual motion sensitive areas such as MT, MST and an area located within the lower bank of superior temporal sulcus by contract of high coherence (80%) and zero-coherence random dot stimuli. The reliability and specificity of the obtained activations with SE-EPI ensures the application of the method in our on-going visual perception studies.}, web_url = {http://nwg.glia.mdc-berlin.de/media/pdf/conference/Proceedings-Goettingen2007.pdf}, event_name = {7th Meeting of the German Neuroscience Society, 31st Göttingen Neurobiology Conference}, event_place = {Göttingen, Germany}, state = {published}, author = {Ku S-P{shipi}; Goense J{jozien}{Department Physiology of Cognitive Processes}; Tolias A{atolias}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ 4360, title = {Perceptual Suppression in area V1 of the Macaque}, year = {2006}, month = {6}, pages = {58}, abstract = {Under certain stimulus conditions we encounter pronounced perceptual suppression of suprathreshold visual stimuli. The brain mechanisms underlying these phenomena are poorly understood. Binocular rivalry (BR) and Binocular Flash Suppression (BFS) provide us excellent behavioural tools to study this phenomenon. During these paradigms visual stimuli are completely extinguished from our awareness for a substantial amount of time despite being physically present on our retinas. Therefore, we can study the dissociation between the neural responses that underlie a mere sensory representation of the visual input and what is perceived. Primary visual cortex (V1) has been implicated as an important candidate for the site of perceptual suppression. However, interestingly electrophysiological studies in V1 have found only a very small percentage of neurons to be correlated with the percept[1]. In contrast, human fMRI studies[2,3] have shown that the BOLD signal during such perceptual alternations modulates almost as much as when the stimuli are non-ambiguously presented separately. These contradicting results led to the speculation that the local field potential (LFP) signals, which have been shown to correlate with the BOLD signal, will also show correlations with perception in agreement with the BOLD results and thus potentially solve the apparent controversy. To this end, a recent study[4] claimed that low frequency (<30Hz) LFP signals in V1 correlate well with the subjective experience of macaques during BR. We have used BFS and recorded neural activity from large populations of well-isolated single neurons (SUA) from V1 using chronically implanted and non-chronic tetrodes in awake behaving macaques. In addition to the SUA we also simultaneously recorded multi-unit (MUA) and LFP signals. In agreement with previous electrophysiology experiments we find a very small percentage of single neurons (12%, t-test: p<0.05) as well as MUA sites (15%) to be correlated with the animals¹ percept during the binocular presentation of two gratings of orthogonal orientations. Interestingly, an even smaller percentage (7%) of gamma-band LFP sites show a significant modulation and no other LFP band (e.g. alfa or beta-bands) showed stronger perceptually related modulation. In addition, the amplitude of the normalized population response in all three signals shows a small fractional modulation in comparison with the monocular presentation of the gratings (see figure). We therefore conclude that the activity in V1 is not a good predictor of the perceptual alternations at least using the classical simple measures of firing rate and power modulations of the signals.}, web_url = {http://www.areadne.org/2006/}, event_name = {AREADNE 2006: Research in Encoding and Decoding of Neural Ensembles}, event_place = {Santorini, Greece}, state = {published}, author = {Keliris GA{george}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}; Tolias A{atolias}{Department Physiology of Cognitive Processes}} } @Poster{ 3949, title = {Spikes are phase locked to the gamma-band of the local field potential oscillations in the primary visual cortex of the macaque}, year = {2006}, month = {6}, pages = {39}, abstract = {Oscillations in the local field potential (LFP) are abundant across species and brain regions. The possible role of these oscillations in information processing in the primary visual cortex (V1) of the macaque still remains largely elusive despite that V1 is one of the most extensively studied brain areas. To this end, we used chronically implanted, multiple tetrodes and recorded the spiking activity of single neurons and LFPs from area V1 of the awake, behaving macaque. Moving and static gratings of different orientations were used for visual stimulation. In agreement with previous reports we find that the increase of the LFP gamma-band power is a function of the orientation of the stimulus. Surprisingly though, there is only a weak correlation between the peak of the multi-unit spiking activity orientation tuning functions and the peak of the orientation tuning function of the gamma-band power of the LFP. There is however a different kind of relationship between spikes and LFP. Namely, the timing of the spikes is not randomly distributed in time but instead is locked to the phase of the gamma-band of the LFP. Specifically, the spikes of 60 out of 151 well-isolated single units showed significant phase locking to the LFP (P<0.05, circular Rayleigh test). On average, the spikes occurred on the downward slope of the LFP oscillation. In contrast to the presence of phase precession reported in the rat hippocampus, the phase tuning in V1 is stable over time. Specifically, the preferred phase of the spikes does not seem to change over time during the presentation of the stimulus. Moreover, the preferred phase is not significantly modulated as a function of the orientation of the stimulus (Figure A). This temporal structuring of the spiking activity of neurons in V1 could allow coding of information in the temporal regime (Panzeri & Schultz, 2001). In addition it could also potentially synchronize populations of neurons (Fries 2005). We are currently investigating these conjectures.}, web_url = {http://www.areadne.org/2006/}, event_name = {AREADNE 2006: Research in Encoding and Decoding of Neural Ensembles}, event_place = {Santorini, Greece}, state = {published}, author = {Berens P{berens}; Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Hoenselaar A{hoenselaar}{Department Physiology of Cognitive Processes}; Keliris GA{george}{Department Physiology of Cognitive Processes}; Siapas AG; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Poster{ ToliasEKSSL2006, title = {Structure of interneuronal correlations in the primary visual cortex of the rhesus macaque}, year = {2006}, month = {3}, pages = {13}, abstract = {Despite recent progress in systems neuroscience, basic properties of the neural code still remain obscure. For instance, the responses of single neurons are both highly variable and ambiguous (similar responses can be elicited by different types of stimuli). This variability/ambiguity has to be resolved by considering the joint pattern of firing of multiple single units responding simultaneously to a stimulus. Therefore, in order to understand the underlying principles of the neural code it is important to characterize the correlations between neurons and the impact that these correlations have on the amount of information that can be encoded by populations of neurons. Here we applied the technique of chronically implanted, multiple tetrodes to record simultaneously from a number of neurons in the primary visual cortex (V1) of the awake behaving macaque, and to measure the correlations in the trial-to-trial fluctuations of their firing rates under the same stimulation conditions (noise correlations). We find that, contrary to widespread belief, noise correlations in V1 are very small (around 0.01) and do not change systematically neither as a function of cortical distance (up to 600 um) nor as a function of the similarity in stimulus preference between the neurons (uniform correlation structure). Interestingly, a uniform correlation structure is predicted by theory to increase the achievable encoding accuracy of a neuronal population and may reflect a universal principle for population coding throughout the cortex.}, web_url = {http://www.cosyne.org/c/index.php?title=Cosyne_06}, event_name = {Computational and Systems Neuroscience Meeting (COSYNE 2006)}, event_place = {Salt Lake City, UT, USA}, state = {published}, author = {Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Ecker A{aecker}{Department Physiology of Cognitive Processes}; Keliris GA{george}{Department Physiology of Cognitive Processes}; Siapas TG; Smirnakis SM{ssmirnakis}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ 3722, title = {Directional selectivity of human visual areas after adaptation to motion stimuli: an fMRI study}, year = {2005}, month = {11}, volume = {35}, number = {619.12}, abstract = {Motion processing is a fundamental property of the visual system. Classical electrophysiology studies in the macaque as well as fMRI studies in the human have revealed an extensive network of visual areas that contain neurons selective for direction of motion. Recent evidence from macaque fMRI (Tolias et al., J Neurosci 2001) and electrophysiology (Tolias et al. Nat Neurosci 2005) suggests that the direction-of-motion selectivity of macaque visual areas is not a fixed property but can change dynamically as a function of the state of adaptation to a moving stimulus. Here we used a visual motion adaptation paradigm to study the direction-of-motion selectivity of human visual areas with functional magnetic resonance imaging (fMRI). The visual stimuli we used consisted of expanding/contracting dot kinematograms at 100% coherence. These were presented passively while the subject performed an attentionally demanding task at the fovea. After moving unidirectionally (expanding or contracting) for about 160 sec the kinematogram abruptly reversed direction of motion. By measuring the blood oxygen level dependent (BOLD) signal response elicited by the direction of motion reversal and comparing it to the initial response elicited when the adapting stimulus turns on, we were able to assess the degree of direction-of-motion selectivity in the various visual areas. We found that an extensive network of visual areas shows BOLD rebound when the direction of motion reverses after adaptation, including areas that according to classical electrophysiology do not show strong direction-of-motion selectivity (for example area V4). Our results agree qualitatively with the findings in the macaque (Tolias et al., J Neurosci 2001), and together underscore the dynamic nature of functional cortical architecture.}, web_url = {http://www.sfn.org/absarchive/}, event_name = {35th Annual Meeting of the Society for Neuroscience (Neuroscience 2005)}, event_place = {Washington, DC, USA}, state = {published}, author = {Keliris GA{george}{Department Physiology of Cognitive Processes}; Smirnakis SM{ssmirnakis}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ 3835, title = {fMRI of the temporal lobe of the awake macaque at 7T}, year = {2005}, month = {11}, volume = {35}, number = {620.5}, abstract = {The temporal lobe of the primate brain is thought to be important in high-level object recognition and learning. In contrast to electrophysiological studies, fMRI has the advantage that it allows simultaneous mapping of the functional organization of multiple cortical areas. However, there are few fMRI studies of the inferior temporal lobe in the non-human primate, because gradient-echo echo-planar-imaging (GE-EPI), which is commonly used, suffers from susceptibility related signal losses due to the ear canal and the cancellous nature of the temporal bone. The large macroscopic susceptibility gradients caused by air-tissue interfaces result in distortion and reduced signal-to-noise in affected areas. At high magnetic fields this is especially problematic, because in addition to increases in the BOLD signal, the susceptibility artifacts also increase. In areas of high susceptibility, using spin-echo EPI (SE-EPI) may be advantageous because it is less sensitive than GE-EPI to susceptibility artifacts, and does not suffer from signal dropout in these regions. In this study, we compare SE-EPI and gradient-echo fMRI in the awake monkey (Macaca mulatta), using a vertical bore 7T MR system. An 8 cm surface coil was positioned over the monkey’s ear, which covers one hemisphere, allowing imaging of the major visual areas. The imaging parameters and slice orientation were optimized to minimize susceptibility effects. Resolution was typically 1.5x2x2mm, TE was 40 ms, TR was 1-2 s. In contrast to the GE-EPI images, which showed very large signal dropout in the temporal lobe, SE images showed minimal or no distortion or signal losses. Using movies as a stimulus, reliable functional activation was obtained in the inferior temporal lobe (as well as in other visual areas). The reliability and specificity of the obtained activations with SE-EPI ensures the application of the method in our on-going visual perception and learning studies.}, web_url = {http://www.sfn.org/absarchive/}, event_name = {35th Annual Meeting of the Society for Neuroscience (Neuroscience 2005)}, event_place = {Washington, DC, USA}, state = {published}, author = {Goense J{jozien}{Department Physiology of Cognitive Processes}; Ku S-P{shihpi}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ 4505, title = {Macaque visual cortex organization probed by fMRI after area V1 lesions}, year = {2005}, month = {11}, volume = {35}, number = {979.10}, abstract = {Under certain conditions, lesions of the adult central nervous system can induce reorganization of cortical sensory representations in the brain. This capacity of cortical circuitry for reorganization can potentially contribute in accelerating recovery after nervous system injury, such as stroke. In the visual system, extrastriate cortex has been shown to reorganize in an adult human subject with an extensive lesion of the primary visual cortex (Baseler et al., J Neurosci 1999). However, the extent and time course of the process of reorganization after focal area V1 lesions remains incompletely characterized. Here we use functional magnetic resonance imaging (fMRI) to characterize how the topography of early macaque visual areas changes following V1 lesions. After creating a ~1.2 cm x 1.2 cm lesion in area V1 by aspiration, we used 4.7 T fMRI in the anesthetised macaque preparation (Logothetis et al. Nat Neurosci 1999) to monitor changes in the topographic maps of early visual areas (V2, V3) as a function of time. The stimuli we used to map the topography of visual areas were a standard ring/wedge retinotopic stimulation paradigm (Brewer et al. J Neurosci, 2002) as well as a ~20 degree x 27 degree rotating checkerboard stimulus alternating with uniform background illumination. Both stimuli have been previously shown to activate reliably early visual areas (Smirnakis et al., Nature, 2005). Preliminary results revealed a localized cortical region within area V2/V3 whose visual modulation was strongly diminished following the V1 lesion. By monitoring how the strength of the visual modulation inside this region evolves in time we will quantify the degree of reorganization seen in area V2/V3.}, web_url = {http://www.sfn.org/absarchive/}, event_name = {35th Annual Meeting of the Society for Neuroscience (Neuroscience 2005)}, event_place = {Washington, DC, USA}, state = {published}, author = {Smirnakis SM{ssmirnakis}{Department Physiology of Cognitive Processes}; Schmid MC{mschmid}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Augath M{mark}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ 3327, title = {Motion processing in area V4 revealed with adaptation: Tetrode recordings in the awake, behaving macaque}, year = {2004}, month = {10}, volume = {34}, number = {301.4}, abstract = {The ability to detect motion in our environment is a crucial function of the visual system. Motion processing is usually studied by comparing the activity elicited by various motion stimuli relative to a baseline (“no-movement”) condition. However, during natural vision the sensory input is not broken into a series of discrete presentations that are simply switched on and off. By using a motion adaptation paradigm we studied how stimulation history influences the directional selectivity of single neurons in area V4. We found that V4 neurons which classically would be thought as non-directionally selective can in fact acquire directional selectivity after adaptation. We recorded from area V4 of two monkeys using tetrodes and characterized the directional tuning properties of single units using drifting coherent random dot patterns. In agreement with previous studies we find that the majority of area V4 neurons are weakly tuned to the direction of motion when their properties are characterized using the classical stimulation paradigm. The same neurons though, express stronger directional tuning if previously adapted to a moving stimulus for a period of one second. To quantify the amount of directional information present in the activity of V4 neurons we used a Bayesian population decoding method to predict the direction of motion of the stimulus trial by trial using the activity of a population of neurons in a four hundred millisecond window. The average test error dropped significantly when computed after adaptation. It is important to characterize the properties of neuronal circuits under adaptation to better understand the mechanisms of natural vision.}, web_url = {http://www.sfn.org/absarchive/}, event_name = {34th Annual Meeting of the Society for Neuroscience (Neuroscience 2004)}, event_place = {San Diego, CA, USA}, state = {published}, author = {Keliris GA{george}{Department Physiology of Cognitive Processes}; Smirnakis SM{ssmirnakis}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}} } @Poster{ 4504, title = {Spatial specificty of BOLD versus MION in a macaque fMRI preparation at 47T}, year = {2004}, month = {10}, volume = {34}, number = {646.10}, abstract = {Most macaque functional magnetic resonance imaging (fMRI) studies are based on monitoring the intrinsic blood oxygen level dependent signal (BOLD) or, alternatively, on measuring changes in cerebral blood volume (CBV) after injection of the intravascular contrast agent MION (monocrystalline iron oxide nanoparticles). In comparison to BOLD, imaging using MION results in higher contrast to noise ratios (CNR) (Leite et al., 2002; Vanduffel et al., 2001). However, the spatial specificity of MION is not well understood. In order to directly compare the spatial resolution of BOLD versus MION, we conducted a series of experiments in the anaesthetized macaque monkey preparation (macaca mulatta) at a magnetic field strength of 4.7 T. We acquired data using 8-segment multishot EPI with flip angle = 40 deg, TE = 20 ms, TR = 805 ms, for both BOLD and MION experiments. We typically injected 8mg/kg MION which is known to give near optimal CNR (Mandeville et al., 1998; Vanduffel et al., 2001). We measured the distribution of BOLD/MION as a function of gray matter depth in the primary visual cortex (V1) during stimulation with a full-field rotating polar checkerboard pattern alternating with uniform illumination (blank). Functional activation for MION peaked deeper in gray matter compared to BOLD, and appeared to sometimes even extend into white matter. To compare the extent of spatial activation of BOLD versus MION along the cortical surface, we used a rotating polar checkerboard pattern containing a 3.7○ diameter blank area we refer to as an ¨artificial scotoma¨. Functional activity spread inside the cortical area corresponding to the artificial scotoma (where there is no visual stimulation) appeared to be markedly greater for MION than for BOLD. On-going experiments aim to directly compare the fMRI findings to single unit responses inside the artificial scotoma.}, web_url = {http://www.sfn.org/absarchive/}, event_name = {34th Annual Meeting of the Society for Neuroscience (Neuroscience 2004)}, event_place = {San Diego, CA, USA}, state = {published}, author = {Schmid M{mschmid}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Augath MA{mark}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}; Smirnakis SM{ssmirnakis}{Department Physiology of Cognitive Processes}} } @Poster{ SchmidTALS2004, title = {Spatial resolution of BOLD versus MION in a macaque fMRI paradigm at 4.7 T}, journal = {NeuroImage}, year = {2004}, month = {6}, volume = {22}, number = {Supplement 1}, pages = {e2449-2450}, abstract = {Most macaque functional magnetic resonance imaging (fMRI) studies are based on monitoring the intrinsic blood oxygen level dependent signal (BOLD) or, alternatively, on measuring changes in cerebral blood volume (CBV) after injection of a contrast agent. The intravascular contrast agent MION (monocrystalline iron oxide nanoparticles) has been recently applied in a number of studies (Dubowitz et al., 2001; Leite et al., 2002; Mandeville et al., 1997; Mandeville et al., 1998; Mandeville and Marota, 1999; Tsao et al., 2003a; Tsao et al., 2003b; Vanduffel et al., 2001). In comparison to BOLD, imaging with MION results in higher contrast to noise ratios (CNR) (Leite et al., 2002;Vanduffel et al., 2001) which may provide improved fMRI sensitivity, making MION especially appealing at low to moderate magnetic field strengths. Moreover, it has been suggested that MION may result in improved spatial specificity, since it appears to arise primarily from small parenchymal vessels (Mandeville et al., 1998; Mandeville and Marota, 1999) as opposed to BOLD which, at low magnetic fields, is known to be influenced by larger vessels that run along the cortical surface (Gati, Menon, et al., 1997). In order to directly compare the spatial resolution of BOLD versus MION, we conducted a series of experiments in the anaesthetized macaque monkey preparation (macaca mulatta) at a magnetic field strength of 4.7 T. We acquired data using 8-segment multishot EPI with flip angle = 40 deg, TE = 20 ms, TR = 805 ms, for both BOLD and MION experiments. We typically injected 8mg/kg MION which is known to give near optimal CNR (Mandeville, Marota, et al., 1998; Vanduffel, Fize, et al., 2001). In a first set of experiments we measured the distribution of BOLD/MION as a function of gray matter depth in macaque primary visual cortex (V1). Stimulation was done by alternating a rotating polar checkerboard with a field of uniform light intensity. Voxel size was 0.2 x 0.2 x 1mm 3 . Correlation coefficients were computed voxel by voxel and then averaged for voxels lying at the same cortical depth. Figure 1 plots the average correlation coefficients for BOLD (blue) versus MION (red) as a function of depth in the primary visual cortex (V1) of one macaque. Note that the correlation coefficients for MION appear to peak deeper in gray matter as compared to BOLD. To compare the spatial extent of functional activation seen with BOLD versus MION along the cortical surface, we used a similar stimulation paradigm as before, except that now the rotating polar checkerboard pattern contained a 6 deg diameter occluder (artificial scotoma) centered at 6 deg from the fovea. This assured that the corresponding cortical area in V1 received no direct visual stimulation. Figure 2 shows the correlation maps obtained with BOLD and MION under these stimulation conditions in a slice through the left V1 of one macaque (voxel resolution: 1 x 1 x 2 mm 3 ). Note that the spread of functional activity into the cortical area corresponding to the artificial scotoma (i.e. where there is no visual stimulation) appears to be markedly greater for MION than for BOLD.}, web_url = {http://www.sciencedirect.com/science/article/pii/S1053811905700203}, event_name = {Tenth Annual Meeting of the Organization for Human Brain Mapping (HBM 2004)}, event_place = {Budapest, Hungary}, state = {published}, DOI = {10.1016/S1053-8119(05)70020-3}, author = {Schmid MC{mschmid}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Augath MA{mark}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}; Smirnakis SM{ssmirnakis}{Department Physiology of Cognitive Processes}} } @Poster{ 4502, title = {Simultaneous electrical microstimulation and fMRI in the macaque}, year = {2003}, month = {11}, volume = {33}, number = {69.20}, abstract = {Electrical microstimulation has been used extensively to study both neuronal connectivity and the behavioral effects of focal neural excitation. Yet most behaviors involve concurrent activation of several structures that are directly or indirectly interconnected with the stimulated site. Microstimulation performed simultaneously with fMRI offers a unique opportunity to investigate the network of structures eliciting certain behaviors. Recently, simultaneous recording of neural activity and BOLD responses in the monkey has been developed to study the correlation between the fMRI signals and electrical activity in the brain (Logothetis et al., 2001). This work has also enabled us to carry out simultaneous electrical microstimulation and fMRI. The specific goal of the current study is to determine the electrical parameters which elicit activity in the brain similar to that generated by focal visual stimulation. We compared visual stimulation with constant-current charge-balanced biphasic electrical pulses delivered via monopolar microelectrodes placed in area V1. We find that under certain microstimulation parameters we obtain focal activity around the electrode tip in area V1 as well the corresponding retinotopic location in area V2, V3, and MT. Ongoing research examines the activity patterns elicited by stimulating at different cortical layers of V1. This study paves the way to incorporate the much needed anatomical information in the analysis of the electrical signals obtained in trained, awake animals.}, web_url = {http://www.sfn.org/index.aspx?pagename=annualmeeting_futureandpast}, event_name = {33rd Annual Meeting of the Society for Neuroscience (Neuroscience 2003)}, event_place = {New Orleans, LA, USA}, state = {published}, author = {Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Augath M{mark}{Department Physiology of Cognitive Processes}; Pauls J{jpauls}{Department Physiology of Cognitive Processes}; Oeltermann A{axel}; Tehovnik EJ; Schiller PH; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ KourtziTAAL2003, title = {Integration of local features into global shapes: monkey and human fMRI studies}, journal = {Journal of Vision}, year = {2003}, month = {10}, volume = {3}, number = {9}, pages = {191}, abstract = {The perception of global visual shapes entails the integration of local image features into global configurations. Traditionally, the visual system is thought to be hierarchically organized in early visual areas (V1, V2, V3, V4) that are involved in the analysis of simple local features and higher visual areas (regions in the inferotemporal cortex) that are implicated in the processing of complex global shapes. We investigated the integration of local image features into global shapes across visual areas in the monkey and the human brain using fMRI. An adaptation paradigm was used, in which stimulus selectivity was deduced by changes in the course of adaptation of a pattern of randomly oriented elements. Accordingly, we observed stronger activity after adaptation when orientation changes in the adapting stimulus resulted in a collinear shape than a different random pattern. This selectivity to collinear shapes was observed not only in higher visual areas, but also in early visual areas where selectivity depended on the receptive field size. These findings suggest that unified shape perception in both monkeys and humans involves multiple visual areas that may integrate local elements to global shapes at different spatial scales.}, web_url = {http://www.journalofvision.org/content/3/9/191.abstract}, event_name = {Third Annual Meeting of the Vision Sciences Society (VSS 2003)}, event_place = {Sarasota, FL, USA}, state = {published}, DOI = {10.1167/3.9.191}, author = {Kourtzi Z{zoe}{Department Human Perception, Cognition and Action}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Altmann CF{altmann}{Department Human Perception, Cognition and Action}; Augath M{mark}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ 4501, title = {Coding visual information at the level of populations of neurons}, year = {2002}, month = {11}, volume = {32}, number = {557.5}, abstract = {Information conveyed through the firing of individual neurons is inherently ambiguous. For instance, different combinations of visual attributes such as orientation, contrast, and motion direction may result in the same rate of firing of a given cell. It is generally assumed that this ambiguity is resolved at the level of populations of neurons; yet the specific coding principles at the network level remain elusive. To examine these principles, we have recorded simultaneously from multiple well-isolated neurons in area V1/V2 of the macaque using a 12 tetrode chronically implanted array. We trained monkeys to report the direction of motion of a random dot display in which the strength of the motion signal was determined by the proportion of coherently moving dots. Since neurons in V1 have relatively small receptive fields, under these motion conditions we find that the mean firing rate of individual neurons does not predict the direction of motion of the stimulus, even when the psychophysical performance of th e animal was optimal. The coding principles underlying this performance are currently analyzed by the explicit characterization of the relationship between activity patterns across multiple neurons and the direction and coherence of the motion stimulus.}, web_url = {http://www.sfn.org/annual-meeting/past-and-future-annual-meetings}, event_name = {32nd Annual Meeting of the Society for Neuroscience (Neuroscience 2002)}, event_place = {Orlando, FL, USA}, state = {published}, author = {Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Siapas AG; Smirnakis SM{ssmirnakis}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ 2730, title = {FMRI Correlates of Perceptual Filling-in in a Moving Random Dot Paradigm}, year = {2002}, month = {11}, volume = {32}, number = {457.7}, abstract = {Perceptual filling-in refers to the fading of stabilized retinal patterns and their replacement by non-stabilized surrounding patterns. We used functional magnetic resonance imaging (fMRI) to investigate neuronal correlates of perceptual filling-in induced by a dynamic random dot pattern. The stimulus consisted of a moving random dot pattern on dark background surrounding a region devoid of dots (artificial scotoma). The subjects fixated at an eccentrically located spot, and they reported the time of onset of filling-in by button press. We controlled for attention by dimming the fixation spot at random points in time, which the subjects reported via a separate button press. Catch trials in which the stimulus physically filled the artificial scotoma were interspersed with filling-in trials to gauge the subjects’ performance. General linear model techniques with appropriate predictors were used to define areas of interest for analysis. Filling-in trials for each subject were divided in two groups of 30 trial s each, based on whether filling in occurred earlier (<8 s) or later (8-24 s) in a trial. The stimulus was identical for all trials. Preliminary results suggest that the fMRI signal from area V1 rises initially in both groups but then dips and remains low for the group with early filling-in. This suggests that filling-in is associated with a relative suppression of cortical activity. Other interpretations will be discussed.}, web_url = {http://www.sfn.org/annual-meeting/past-and-future-annual-meetings}, event_name = {32nd Annual Meeting of the Society for Neuroscience (Neuroscience 2002)}, event_place = {Orlando, FL, USA}, state = {published}, author = {Keliris GA{george}{Department Physiology of Cognitive Processes}; Smirnakis SM{ssmirnakis}{Department Physiology of Cognitive Processes}; Kourtzi Z{zoe}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ 1561, title = {fMRI responses to visual shapes at different spatial scales}, year = {2002}, month = {11}, volume = {32}, number = {260.16}, abstract = {The aim of the study is to understand the perception of global shapes from local image features. Specifically, we tested the role of various visual areas that are characterized by neural populations with different receptive field size in the integration of local features into global shapes at different spatial scales. To this end, we used fMRI in the anesthetized monkey and employed an adaptation paradigm. The paradigm entails prolonged presentation of a stimulus, resulting in decreased fMRI response, after which a change in a stimulus dimension elicits rebound of activity. The magnitude of the rebound correlates with the selectivity of an area to the changed dimension. The adapting stimulus was a rectangular area filled with randomly oriented line segments, followed by one of three test stimuli: a pattern identical to the adapting stimulus; a pattern where 1/3 of the line segments changed orientation randomly; a pattern in which change of line segment orientation resulted in a colinear shape. Spatial scale was manipulated by changing the size and the distance between the line segments. Differential responses to colinear shapes and random patterns indicated areas (V1,V2/V3) with neural populations that are selective for the global configuration of shapes, rather than local features. Rebound was observed in peripheral and central V1 for collinear shapes at large and small scales respectively. These findings suggest, that in the processing of global shapes from local features different visual areas are involved at different spatial scales.}, web_url = {http://www.sfn.org/annual-meeting/past-and-future-annual-meetings}, event_name = {32nd Annual Meeting of the Society for Neuroscience (Neuroscience 2002)}, event_place = {Orlando, FL, USA}, state = {published}, author = {Kourtzi Z{zoe}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Augath M{mark}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ 1921, title = {Macaque visual cortex reorganisation after homonymous retinal scotoma probed by fMRI}, year = {2002}, month = {11}, volume = {32}, number = {760.2}, abstract = {Visual cortex has the capacity to reorganize in response to changes in sensory input. Early studies of visual deprivation (Blakemore, Hubel, LeVay) suggested that stimulus driven reorganization occurs only during a critical period in early development. Recent electrophysiological studies (Gilbert, Kaas, Chino, Rosa, Heinen) suggest that the visual system of adult mammals may undergo significant reorganization after de-afferentiation. There is an ongoing debate regarding the nature and extent of this reorganization (Horton, DeAngelis). Here we describe measurements of cortical reorganization after inducing a 5-8o homonymous scotoma in the retinas of adult rhesus macaques with a photocoagulation laser (GYC-2000, NIDEK). We used 4.7T functional magnetic resonance imaging (fMRI) in the anesthetized macaque preparation (Logothetis et al., Nat Neurosci 1999) to track the changes in visual field maps in early cortical areas. FMRI is appealing as it is noninvasive, provides global coverage of the visual areas, and facilitates comparison with human studies. By comparing the activation patterns seen as a function of time after induction of the scotoma we aim to outline the temporal course of cortical reorganization. Preliminary results, based on one monkey, reveal a localized cortical region within V1 (~1.2x2.5cm2) whose signal response is strongly diminished by the lesion. Further, it appears that the fraction of area V1 silenced by the scotoma changes in time.}, web_url = {http://www.sfn.org/annual-meeting/past-and-future-annual-meetings}, event_name = {32nd Annual Meeting of the Society for Neuroscience (Neuroscience 2002)}, event_place = {Orlando, FL, USA}, state = {published}, author = {Smirnakis SM{ssmirnakis}{Department Physiology of Cognitive Processes}; Brewer AA; Schmid M{mschmid}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Augath M{mark}{Department Physiology of Cognitive Processes}; Inhoffen W; Wandell BA; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ 1920, title = {Mapping Macaque Visual Cortex Organization with BOLD and MION fMRI}, year = {2002}, month = {11}, volume = {32}, number = {759.5}, abstract = {Our research aims to use high field (4.7T) functional magnetic resonance imaging (fMRI) to map changes in cortical organization as a function of time after de-afferenting part of the primary visual cortex by inducing homonymous retinal lesions (Smirnakis et al., Neuroscience 2002). In order to obtain detailed maps of cortical organization by fMRI it is essential to use a strategy that maximizes spatiotemporal resolution. The contrast agent monocrystalline iron oxide nanoparticle (MION) has recently been used in the rat (Mandeville et al., Magn Res Med 1998,99) as well as in the awake behaving macaque (W. Vanduffel et al., Neuron 2001) to increase the sensitivity of fMRI imaging as compared to imaging based on the blood oxygenation level dependent (BOLD) signal. It is unclear, however, to what degree the advantage persists at higher field strengths, as well as whether the spatiotemporal profile of the MION (blood volume) induced signal provides adequate resolution to map cortical organization. Here we looked at the benefit of MION versus BOLD at 4.7 Tesla in the anesthesized macaque preparation (Logothetis at al., Nat Neurosci 1999). Visual stimuli of various sizes were presented in block design against background illumination, as well as retinotopic mapping was performed, with and without MION. Preliminary results suggest that MION invariably increased the sensitivity of the technique at 4.7T, boosting the modulation of the signal by a factor of 3-7 above that seen with the BOLD. The effect of MION on the spatial resolution is under investigation.}, web_url = {http://www.sfn.org/annual-meeting/past-and-future-annual-meetings}, event_name = {32nd Annual Meeting of the Society for Neuroscience (Neuroscience 2002)}, event_place = {Orlando, FL, USA}, state = {published}, author = {Schmid M{mschmid}; Smirnakis SM{ssmirnakis}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Augath M{mark}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ 1063, title = {fMRI adaptation for visual forms in the monkey brain}, year = {2001}, month = {11}, volume = {31}, number = {399.11}, abstract = {The aim of the study is to understand how local image features are integrated into configurations that may represent visual forms. We used fMRI in the anesthetized monkey and employed an adaptation paradigm (sufficiently prolonged presentation of a stimulus resulting in decreased fMRI responses over time) to test the role of various visual areas into such an integration process. The stimuli consisted of target-shapes embedded in a background of randomly oriented lines. The target-shapes were defined by collinearly arranged lines of the same height and width as the background lines. Following the presentation of an adapting stimulus, three conditions were tested:(A)presentation of a pattern identical to the adapting stimulus, (B) presentation of the same target-shape as the adapting stimulus but embedded in a different background (i.e. the background lines were rotated 90 deg), and (C) presentation of a different target-shape (orientation-changes of target rather than background lines). The selection of these conditions was motivated by the hypothesis that increased responses in the test phase for a new pattern are likely to indicate areas with neural populations that are selective for the global configuration of shapes, rather than local features. Initial experiments show that the time course of the fMRI signal varies in different visual areas. Not surprisingly, early visual areas failed to show shape selective adaptation, suggesting that the neural populations in these areas primarily encode local features. Differences in the time course of adaptation in higher visual areas are currently studied using a variety of visual patterns.}, web_url = {http://www.sfn.org/index.aspx?pagename=abstracts_ampublications}, event_name = {31st Annual Meeting of the Society for Neuroscience (Neuroscience 2001)}, event_place = {San Diego, CA, USA}, state = {published}, author = {Kourtzi Z{zoe}{Department Physiology of Cognitive Processes}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Prause BA{bprause}{Department Physiology of Cognitive Processes}; Augath M{mark}{Department Physiology of Cognitive Processes}; Trinath T{torsten}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ 4511, title = {Computations by networks of neurons: fMRI adaptation studies in monkeys}, year = {2001}, month = {3}, abstract = {A great deal is understood about the properties of single neurons processing visual information. In contrast, less is known about the collective characteristics of networks of cells that may underlie sensory capacities of animals. By measuring the blood oxygenation level-dependent (BOLD) signal in the macaque cortex we studied the emergent properties of populations of neurons processing motion across different brain areas. We used a visual adaptation paradigm to localize a distributed network of visual areas which process information about direction of motion, and also studied the dynamics of adaptation of the bold signal elicited by moving stimuli. We found that the BOLD signal in areas MT and V2/V3 adapted faster than in V1 reflecting the difference in motion processing between these areas. Moreover, the strength of the directionally selective bold signal in V1 was much greater than the one estimated on the basis of established facts from single cell electrophysiology. We propose an hypothesis that may account for this difference based on the postulate that neuronal selectivity is a function of the state of adaptation and therefore neurons classically thought to lack information about certain attributes of the visual scene, may nevertheless receive and process this information. The implementation of this hypothesis can arise as a result of intra- and inter-area cellular connections, such as feedback from higher areas. This network property may be a universal principle whose computational goal is to enhance the ability of neurons in earlier visual areas to adapt to statistical regularities of the input and therefore increase their sensitivity to detect changes along these stimulus dimensions.}, web_url = {http://zadorlab.cshl.edu/NIC.html}, event_name = {Neural Information and Coding Workshop (NIC 2001)}, event_place = {Big Sky, MT, USA}, state = {published}, author = {Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Smirnakis SM{ssmirnakis}{Department Physiology of Cognitive Processes}; Augath M{mark}{Department Physiology of Cognitive Processes}; Trinath T{torsten}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Poster{ 1040, title = {Functionally linked neuronal assemblies: fMRI adaptation studies in monkeys}, year = {2000}, month = {11}, volume = {30}, number = {448.13}, abstract = {A great deal is known about the properties of single neurons processing visual information. In contrast, less is known about the collective properties of contiguous or distributed neuronal assemblies that may underlie sensory or perceptual capacities of animals. We are studying the activation properties of functionally linked neural populations using fMRI adaptation experiments. Using this paradigm we have investigated the spatial distribution of motion-induced neural activity in cortical and subcortical visual structures in anesthetized monkeys. A black and white foveally-centered rotating polar pattern was used, which consistently activated the LGN, V1 and extrastriate areas including area MT (Logothetis et al., 1999). During the first presentation phase, lasting a few minutes, the polar rotated in one direction (i.e. clockwise). Then, abruptly, the direction of rotation was reversed (second phase). The first phase was long enough for the fMRI signal to show adaptation. We hypothesize that activity in brain areas carrying direction of motion information increases immediately following the reversal due to release from adaptation to the opposite direction of motion, occurring prior to the reversal. Initial experiments, reveal that the time course of adaptation to rotating polar patterns can be monitored in several visual areas using fMRI. Preliminary results suggest that activity in several areas (cortical and subcortical) increased after the direction of motion reversal. These initial results suggest that the global-network properties of brain areas carry stimulus specific information beyond that typically measured in single unit recordings.}, web_url = {http://www.sfn.org/absarchive/}, event_name = {30th Annual Meeting of the Society for Neuroscience (Neuroscience 2000)}, event_place = {New Orleans, LA, USA}, state = {published}, author = {Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Smirnakis SM{ssmirnakis}{Department Physiology of Cognitive Processes}; Augath M{mark}{Department Physiology of Cognitive Processes}; Trinath T{torsten}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Conference{ DenfieldET2015, title = {Correlated variability in population activity: noise or signature of internal computations?}, year = {2015}, month = {10}, day = {19}, volume = {45}, number = {372.05}, abstract = {Neuronal responses to repeated presentations of identical visual stimuli are variable. The source of this variability is unknown, but it is commonly treated as noise and seen as an obstacle to understanding neuronal activity. We argue that this variability is not noise but reflects, and is due to, computations internal to the brain. Internal signals such as cortical state or attention interact with sensory information processing in early sensory areas. However, little research has examined the effect of fluctuations in these signals on neuronal responses, leaving a number of uncontrolled parameters that may contribute to neuronal variability. One such variable is attention, which increases neuronal response gain in a spatial and feature selective manner. Both the strength of this modulation and the focus of attention are likely to vary from trial to trial, and we hypothesize that these fluctuations are a major source of neuronal response variability and covariability. We first examine a simple model of a gain-modulating signal acting on a population of neurons and show that fluctuations in attention can increase individual and shared variability and generate a variety of correlation structures that are relevant to population coding, including limited range and differential correlations. To test our model’s predictions experimentally, we devised a cued-spatial attention, change-detection task to induce varying degrees of fluctuation in the subject’s attentional signal by changing whether the subject must attend to one stimulus location while ignoring another, or attempt to attend to multiple locations simultaneously. We use multi-electrode recordings with laminar probes in primary visual cortex of macaques performing this task. We demonstrate that attention gain-modulates responses of V1 neurons in a manner that is consistent with results from higher-order areas. Consistent with our model’s predictions, our preliminary results indicate neuronal covariability is elevated in conditions in which attention fluctuates and that neurons are nearly independent when attention is focused. Overall, our results suggest that attentional fluctuations are an important contributor to neuronal variability and open the door to the use of statistical methods for inferring the state of these signals on a trial-by-trial basis.}, web_url = {http://www.sfn.org/am2015/}, event_name = {45th Annual Meeting of the Society for Neuroscience (Neuroscience 2015)}, event_place = {Chicago, IL, USA}, state = {published}, author = {Denfield G; Ecker A{aecker}{Department Physiology of Cognitive Processes}; Tolias A{atolias}{Department Physiology of Cognitive Processes}} } @Conference{ Tolias2015, title = {Structure and function of cortical microcircuits}, year = {2015}, month = {6}, day = {11}, web_url = {http://www.nncn.de/en/news/events/bernstein-sparks-workshop-decision-making}, event_name = {5th Bernstein Sparks Workshop: Neural models of decision making in natural inference tasks - from theory to experiment}, event_place = {Tübingen, Germany}, state = {published}, author = {Tolias A{atolias}} } @Conference{ DenfieldET2015_2, title = {The Role of Internal Signals in Structuring V1 Population Activity}, year = {2015}, month = {2}, pages = {19}, abstract = {Neuronal responses to repeated presentations of identical visual stimuli are variable. The cause of this variability is unknown, but it is commonly treated as noise and seen as an obstacle to understanding neuronal activity. We offer an alternative explanation: this variability is not noise but reflects, and is due to, computations internal to the brain. Internal signals such as cortical state or attention interact with sensory information processing in early sensory areas. However, little research has examined the effect of fluctuations in these signals on neuronal responses, leaving a number of uncontrolled parameters that may contribute to neuronal variability. One such variable is attention. We hypothesize that fluctuations in attentional signals contribute to neuronal response variability and that controlling for such fluctuations will reduce this variability. To study this interaction, we use multi-electrode recordings with laminar probes in primary visual cortex of macaques while subjects perform a cued-spatial attention, change-detection task. We induce varying degrees of fluctuation in the subject’s attentional signal by changing whether the subject must attend to one stimulus location while ignoring another, or attempt to attend to both locations simultaneously. We demonstrate that attention increases stimulusevoked firing rates and gain-modulates the tuning curves of V1 neurons in a manner that is consistent with results from higher order areas. Future experiments will examine the effect of attentional fluctuations on neuronal response variability and interneuronal correlations as well as the laminar profile of these effects. Under this hypothesis, this variability can aid, rather than hinder, our understanding of brain function.}, web_url = {https://media.bcm.edu/documents/2015/93/neuroscienceabstractbook2015.pdf}, event_name = {25th Annual Rush and Helen Record Neuroscience Forum}, event_place = {Houston, TX, USA}, state = {published}, author = {Denfield GH; Ecker A{aecker}{Department Physiology of Cognitive Processes}; Tolias A{atolias}{Department Physiology of Cognitive Processes}} } @Conference{ ToliasEKPPL2007, title = {Population codes, correlations and coding uncertainty}, year = {2007}, month = {9}, pages = {16}, abstract = {Despite progress in systems neuroscience the neural code still remains elusive. For instance, the responses of single neurons are both highly variable and ambiguous (similar responses can be elicited by different types of stimuli). This variability/ambiguity has to be resolved by considering the joint pattern of firing of multiple single units responding simultaneously to a stimulus. Therefore, in order to understand the underlying principles of the neural code it is imperative to characterize the correlations between neurons and the impact that these correlations have on the amount of information encoded by populations of neurons. We use chronically implanted tetrode arrays to record simultaneously from many neurons in the primary visual cortex (V1) of awake, behaving macaques. We find that the correlations in the trial-to-trial fluctuations of their firing rates between neurons under the same stimulation conditions (noise correlations) in V1 were very small (around 0.01 in 500 ms bin window) during passive viewing of sinusoidal grating stimuli. We are also measuring correlations in extrastriate visual areas and investigating the impact of correlations on encoding stimulus uncertainty by neuronal populations, under different stimulus and behavioral conditions.}, web_url = {http://www.gatsby.ucl.ac.uk/nccd/nccd07/abstract_book.pdf}, event_name = {Neural Coding, Computation and Dynamics (NCCD 07)}, event_place = {Hossegor, France}, state = {published}, author = {Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Ecker A{aecker}{Department Physiology of Cognitive Processes}; Keliris GA{george}{Department Physiology of Cognitive Processes}; Panagiotaropolulos F{theofanis}{Department Physiology of Cognitive Processes}; Panzeri S{stefano}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Conference{ SultanAOTL2006, title = {Microstimulation of the upper posterior bank of the STS}, year = {2006}, month = {10}, volume = {36}, number = {114.9}, abstract = {In the macaque the extrastriate area V5/MT is located within the dorsal half and on the posterior bank of the superior temporal sulcus. Neurons in V5/MT show directional tuning to moving stimuli. Furthermore, these neurons are organized in a retinotopic fashion with those responding to stimuli located at the center of gaze being more lateral and ventral within V5/MT (Gattass and Gross, 1981). We have now extended the technique of combined electrical microstimulation and fMRI from the striate cortex (Tolias et al., 2005) to this well-studied extrastriate region to further probe this technique as a tool to map the functional connectivity of the brain. We electrically stimulated V5/MT in the anaesthetized macaque in a 4.7T scanner with biphasic charge-balanced pulses (up to 1mA and 200us pulse width per phase) and evoked BOLD responses consistently in a number of brain areas known to be directly connected to V5/MT. BOLD responses were observed in ipsilateral V2, V3, V4, V4t, PO, MST, in the anterior and posterior banks of the IPS (corresponding to LIP) and in the superior colliculus. Two types of projection patterns could be discerned by stimulation of either the peripheral or the foveal retinal representation of area V5/MT. The latter showed activation of regions located on the lateral surface of the occipital cortex while the former showed activity in mesial occiptio-parietal cortex. BOLD responses were surprisingly rather difficult to evoke in V1 with our current stimulation paradigms. V1 responses were largely seen in peripheral V1 regions. This could indicate that the evoked BOLD responses are dominated by orthodromic vs antidromic pathway activation, however, electrical stimulation of the pulvinar in contrast to V5/MT evoked excellent BOLD responses in V1. Since the V1-pulvinar connectivity is mainly feedforeward, this then proves that antidromic pathway activation is well detected by our method. Hence the different activation patterns that we observe in V1 after MT/V5 and pulvinar stimulation are rather related to the different pathways characteristics, possibly related to differences in the type of synaptic connectivity. Thus microstimulation combined with fMRI may well prove to be a novel technique suited to reveal different characteristics of the brains functional connectivity.}, web_url = {http://www.sfn.org/index.aspx?pagename=abstracts_ampublications}, event_name = {36th Annual Meeting of the Society for Neuroscience (Neuroscience 2006)}, event_place = {Atlanta, GA, USA}, state = {published}, author = {Sultan FR; Augath M{mark}{Department Physiology of Cognitive Processes}; Oeltermann A{axel}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Conference{ 3723, title = {Structure of interneuronal correlations in the primary visual cortex of the Rhesus macaque}, year = {2005}, month = {11}, volume = {35}, number = {591.12}, abstract = {Despite recent progress in systems neuroscience, basic properties of the neural code still remain obscure. For instance, the responses of single neurons are both highly variable and ambiguous (similar responses can be elicited by different types of stimuli). This variability/ambiguity has to be resolved by considering the joint pattern of firing of multiple single units responding simultaneously to a stimulus. Therefore, in order to understand the underlying principles of the neural code it is important to characterize the correlations between neurons and the impact that these correlations have on the amount of information that can be encoded by populations of neurons. Here we applied the technique of chronically implanted, multiple tetrodes to record simultaneously from a number of neurons in the primary visual cortex (V1) of the awake behaving macaque, and to measure the correlations in the trial-to-trial fluctuations of their firing rates under the same stimulation conditions (noise correlations). We find that, contrary to widespread belief, noise correlations in V1 are very small (around 0.01) and do not change systematically neither as a function of cortical distance (up to 600 m) nor as a function of the similarity in stimulus preference between the neurons (uniform correlation structure). Interestingly, a uniform correlation structure is predicted by theory to increase the achievable encoding accuracy of a neuronal population and may reflect a universal principle for population coding throughout the cortex. Support Contributed By: MPI, NEI(NIH)}, web_url = {http://www.sfn.org/absarchive/}, event_name = {35th Annual Meeting of the Society for Neuroscience (Neuroscience 2005)}, event_place = {Washington, DC, USA}, state = {published}, author = {Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Keliris GA{george}{Department Physiology of Cognitive Processes}; Ecker AS{aecker}{Department Physiology of Cognitive Processes}; Siapas AG; Smirnakis SM{ssmirnakis}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Conference{ 4503, title = {V1 cortical reorganization revisited: fMRI and electrophysiology in macaque following retinal lesions}, year = {2004}, month = {10}, volume = {34}, number = {605.3}, abstract = {ntroduction. Electrophysiological studies (Chino, Calford, Heinen, Gilbert, Kaas, Rosa) suggest that adult V1 visual field maps reorganize after de-afferentiation. The reported electrophysiological reorganization appears inconsistent with cytochrome oxidase staining patterns after similar de-afferentiation (Horton &amp; Hocking, J Neurosci 1998). We are measuring macaque V1 responses with functional magnetic resonance imaging (fMRI) and electrophysiology to clarify the extent of V1 reorganization. Methods. A retinal photocoagulation laser (GYC-2000, NIDEK) was used to lesion 5-8 degree homonymous visual field locations in four adult rhesus macaques. The retinal lesion creates a de-afferentiated V1 zone referred to as the lesion projection zone, or LPZ (Schmid et al., Cerebral Cortex 1996). As expected, following the lesion we found little or no response to visual stimulation inside the LPZ using functional magnetic resonance imaging (fMRI) at 4.7T in the anesthetized macaque preparation (Logothetis et al., Nat Neurosci 1999). The extent of V1 reorganization was quantified by repeatedly measuring the visual modulation in the BOLD signal near the border of the LPZ. Results. Over the course of seven months, we found very little, if any, increase in BOLD activity within the LPZ apart from that expected by reduced retinal swelling. The boundary of the LPZ remained stable to within 1 mm. The stable scotoma persisted in the BOLD response in all four animals tested. Parallel electrophysiological experiments are in progress in these animals, allowing direct comparison between BOLD measurements and single unit responses.}, web_url = {http://www.sfn.org/absarchive/}, event_name = {34th Annual Meeting of the Society for Neuroscience (Neuroscience 2004)}, event_place = {San Diego, CA, USA}, state = {published}, author = {Smirnakis SM{ssmirnakis}{Department Physiology of Cognitive Processes}; Brewer AA; Schmid M{mschmid}; Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Augath M{mark}{Department Physiology of Cognitive Processes}; Inhoffen W; Sch\"uz A{schuez}{Department Physiology of Cognitive Processes}; Wandell BA; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} } @Conference{ 1057, title = {Studying networks of neurons: recordings with multiple, adjustable, chronically-implanted tetrodes in the awake macaque}, year = {2001}, month = {11}, volume = {31}, number = {123.5}, abstract = {To date, the neuronal mechanisms of brain processes have been primarily studied by analyzing the activity of neurons recorded one at a time. Further understanding of brain mechanisms is likely to come from studies involving the simultaneous recording of large numbers of single neurons. This has recently become possible with the development of the technique of large-scale chronic tetrode recordings. This technique provides a powerful tool for studying networks of neurons since it allows (a) the reliable isolation of single neuron activity through triangulation of action potentials across the four channels of a tetrode, (b) significant yield, enabling the simultaneous monitoring of large numbers of neurons, and (c) long-term stability of individual neuron recordings over several days, a property critical for studying the neuronal basis of learning. This technique has been successfully used to record the simultaneous activity of on the order of 100 well-isolated neurons in freely behaving rodents (Wilson & McNaughton, 1993). We have developed a recording chamber design that allows the chronic implantation of multi-tetrode arrays in awake behaving macaque monkeys. Using this design we have obtained high quality chronic recordings of single neurons from area V1 of a behaving macaque using a 12 tetrode array. These recordings allow the study of how visual information is processed in V1 at the level of networks of single neurons and the investigation of how the interactions across such networks change with learning.}, web_url = {http://www.sfn.org/index.aspx?pagename=abstracts_ampublications}, event_name = {31st Annual Meeting of the Society for Neuroscience (Neuroscience 2001)}, event_place = {San Diego, CA, USA}, state = {published}, author = {Tolias AS{atolias}{Department Physiology of Cognitive Processes}; Siapas AG; Smirnakis SM{ssmirnakis}{Department Physiology of Cognitive Processes}; Logothetis NK{nikos}{Department Physiology of Cognitive Processes}} }