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--- Timezone: CEST
Creation date: 2013-05-25
Creation time: 19-33-25
--- Number of references
7
article
6403
Sensory information in local field potentials and spikes from visual and auditory cortices: time scales and frequency bands
Journal of Computational Neuroscience
2010
12
29
3
533-545
http://www.kyb.tuebingen.mpg.de/fileadmin/user_upload/files/publications/Belitski_JCompNeurosci_10_6403[0].pdf
http://www.kyb.tuebingen.mpg.de
http://www.kyb.tuebingen.mpg.de
Department Logothetis
Research Group Kayser
http://www.springerlink.com/content/a7731565r9828434/fulltext.pdf
Biologische Kybernetik
Max-Planck-Gesellschaft
en
10.1007/s10827-010-0230-y
belitskiABelitski
stefanoSPanzeri
cmagriCMagri
nikosNKLogothetis
kayserCKayser
article
5249
Low-frequency Local Field Potentials and Spikes in Primary Visual Cortex Convey Independent Visual Information
Journal of Neuroscience
2008
5
28
22
5696-5709
Local field potentials (LFPs) reflect subthreshold integrative processes that complement spike train measures. However, little is yet known about the differences between how LFPs and spikes encode rich naturalistic sensory stimuli. We addressed this question by recording LFPs and spikes from the primary visual cortex of anesthetized macaques while presenting a color movie. We then determined how the power of LFPs and spikes at different frequencies represents the visual features in the movie. We found that the most informative LFP frequency ranges were 1–8 and 60–100 Hz. LFPs in the range of 12–40 Hz carried little information about the stimulus, and may primarily reflect neuromodulatory inputs. Spike power was informative only at frequencies <12 Hz. We further quantified "signal correlations" (correlations in the trial-averaged power response to differen
t stimuli) and "
noise correlatio
ns" (trial-by-tr
ial correlations
in the fluctuations around the average) of LFPs and spikes recorded from the same electrode. We found positive signal correlation between high-gamma LFPs (60–100 Hz) and spikes, as well as strong positive signal correlation within high-gamma LFPs, suggesting that high-gamma LFPs and spikes are generated within the same network. LFPs <24 Hz shared strong positive noise correlations, indicating that they are influenced by a common source, such as a diffuse neuromodulatory input. LFPs <40 Hz showed very little signal and noise correlations with LFPs >40 Hz and with spikes, suggesting that low-frequency LFPs reflect neural processes that in natural conditions are fully decoupled from those giving rise to spikes and to high-gamma LFPs.
http://www.kyb.tuebingen.mpg.de
http://www.kyb.tuebingen.mpg.de
http://www.kyb.tuebingen.mpg.de
Department Logothetis
http://www.jneurosci.org/cgi/reprint/28/22/5696
Biologische Kybernetik
Max-Planck-Gesellschaft
en
10.1523/JNEUROSCI.0009-08.2008
belitskiABelitski
arthurAGretton
cmagriCMagri
yusukeYMurayama
MAMontemurro
nikosNKLogothetis
stefanoSPanzeri
article
3989
The Effect of Artifacts on Dependence Measurement in fMRI
Magnetic Resonance Imaging
2006
4
24
4
401-409
http://www.kyb.tuebingen.mpg.de/fileadmin/user_upload/files/publications/artifactFmri_3989[0].pdf
http://www.kyb.tuebingen.mpg.de
http://www.kyb.tuebingen.mpg.de
Department Schölkopf
Department Logothetis
http://www.sciencedirect.com/science?_ob=MImg&_imagekey=B6T9D-4JS20BB-1-S&_cdi=5112&_user=29041&_orig=browse&_coverDate=05%2F31%2F2006&_sk=999759995&am
Biologische Kybernetik
Max-Planck-Gesellschaft
en
10.1016/j.mri.2005.12.036
arthurAGretton
belitskiABelitski
yusukeYMurayama
bsBSchölkopf
nikosNKLogothetis
inproceedings
3174
Kernel Constrained Covariance for Dependence Measurement
AISTATS 2005
2005
1
112-119
We discuss reproducing kernel Hilbert space (RKHS)-based measures of statistical dependence, with emphasis on constrained covariance (COCO), a novel criterion to test dependence of random variables. We show that COCO is a test for independence if and only if the associated RKHSs are universal. That said, no independence test exists that can distinguish dependent and independent random variables in all circumstances. Dependent random variables can result in a COCO which is arbitrarily close to zero when the source densities are highly non-smooth. All current kernel-based independence tests share this behaviour. We demonstrate exponential convergence between the population and empirical COCO. Finally, we use COCO as a measure of joint neural activity between voxels in MRI recordings of the macaque monkey, and compare the results to the mutual information and the correlation. We also show the effect of removing breathing artefacts from the MRI recording.
http://www.kyb.tuebingen.mpg.de/fileadmin/user_upload/files/publications/pdf3174.pdf
http://www.kyb.tuebingen.mpg.de
http://www.kyb.tuebingen.mpg.de
Department Schölkopf
Department Logothetis
http://www.gatsby.ucl.ac.uk/aistats/proceedings.htm
Cowell, R. , Z. Ghahramani
AISTATS 2005
Biologische Kybernetik
Max-Planck-Gesellschaft
MPI for Biological Cybernetics, Spemannstr 38 72076 Tuebingen
Barbados
Tenth International Workshop on Artificial Intelligence and Statistics (AI & Statistics 2005)
en
0-9727358-1-X
arthurAGretton
smolaAJSmola
bousquetOBousquet
RHerbrich
belitskiABelitski
markMAugath
yusukeYMurayama
jpaulsJPauls
bsBSchölkopf
nikosNKLogothetis
poster
5695
A comparison of the information about rich naturalistic stimuli carried by phase and power of LFP recordings
2008
11
38
397.7
Local field potentials (LFPs) reflect sub-threshold integrative processes that complement spike train measures. Here we investigate how LFPs encode rich naturalistic sensory stimuli. We addressed this question by recording LFPs from the primary visual cortex of anesthetized macaques with an array of electrodes while presenting binocularly a color movie. The electrodes were arranged in a 4 by 4 matrix and interelectrode spacing varied from 1 to 2.5 mm. We decomposed the LFP into narrow frequency bands (1-4Hz, 4-8Hz, 8-12Hz and up to 100Hz in 4-Hz wide non-overlapping frequency intervals by using standard bandpassing techniques. We then computed the amount of information about the movie that is carried by the phase or by the instantaneous power of the bandpassed LFP obtained from each individual electrode. When considering the information in LFP power, we found that the instantaneous power was most informative in the low frequency range (< 8 Hz) and in the high gamma frequency range (60-100 Hz). When considering the LFP phase, we found that only the phase of low frequency LFPs (< 12 Hz) was informative about the movie. We found that phase was more informative about the movie than power was. On average across all recording sites and experimental animals, the maximum across LFP frequencies of information about the movie that could be extracted from LFP phase was approximately 0.4 bits, whereas the maximum across LFP frequencies of information about the movie that could be extracted from LFP power was approximately 0.2 bits. We finally investigated whether the phase or power or LFPs recorded from different electrodes convey similar or different information about the movie. Our preliminary results suggest that the informative parts of the LFP signal, i.e. low frequency phases, low frequency power and high gamma power have stimulus selectivity that remains largely similar (though not identical) across the range of distances covered by the electrode grid. Currently we are investigating how phase and power of LFPs encodes stimuli in auditory cortex.
http://www.kyb.tuebingen.mpg.de
http://www.kyb.tuebingen.mpg.de
http://www.kyb.tuebingen.mpg.de
Department Logothetis
Research Group Kayser
http://www.sfn.org/am2008/
Biologische Kybernetik
Max-Planck-Gesellschaft
Washington, DC, USA
38th Annual Meeting of the Society for Neuroscience (Neuroscience 2008)
en
belitskiABelitski
MMontemurro
kayserCKayser
nikosNKLogothetis
stefanoSPanzeri
poster
4996
A time/frequency decomposition of information transmission by LFPs and spikes in the primary visual cortex
2007
11
37
103.18
Local Field Potentials (LFP) and Multiple Unit Activity (MUA) are indicators of perisynaptic and spiking activity respectively. An analysis of changes in dependence between these two types of signals may help us understand computations at the level of small networks and characterize the type of processing carried out by a cortical area. The goal of our research is to develop a principled and theoretically sound approach to measuring the information content of electrical signals in the brain (LFPs and spikes), as it relates to stimulus. Traditionally, the LFP has been broken up into a series of well established bands from the EEG literature (delta, alpha, beta), however it is not clear that this decomposition is maximally informative in relating the stimulus and response.
To better understand this issue we analyze multiple electrode recordings from the macaque primary visual cortex (V1), under stimulation by continuous natural movies. We first decompose the information about the stimulus, contained in the LFPs and spikes, into different frequency bands, so as to determine which parts of the signal carry the most stimulus content. We also determine the interaction between different LFP and spike frequencies, and test the extent to which these interactions are stimulus driven. In this way, we are able to determine whether bands are synergistic (contain more information jointly than if viewed separately), independent, or redundant. This analysis leads to a frequency decomposition methodology for the LFP that follows the signal structure, rather than prior beliefs; clarifies the dependence between different LFP frequencies and spikes; and gives insight into the neurophysiological mechanisms for stimulus encoding. We further measure the effect of temporal resolution on these information theoretic quantities, to determine the timescale over which information transfer occurs.
It is also possible to extract component features from the input stimulus, using image processing methods: examples include flow fields, frame-to-frame per-pixel differences, contrast, luminance, and low and high frequency power in each frame. We investigate the extent to which neural activity is driven by particular stimulus features, and find the fraction of total information transmission associated with each of these.
Finally, we investigate the information between neural signals as a function of separation between recording sites. In particular, it can be determined, as a function of signal frequency, the distance at which no significant dependence of any kind exists between signals; this may then be compared to known anatomical features (e.g column width) of the cortex.
http://www.kyb.tuebingen.mpg.de
http://www.kyb.tuebingen.mpg.de
http://www.kyb.tuebingen.mpg.de
Department Schölkopf
Department Logothetis
http://www.sfn.org/am2007/
Biologische Kybernetik
Max-Planck-Gesellschaft
San Diego, CA, USA
37th Annual Meeting of the Society for Neuroscience (Neuroscience 2007)
en
belitskiABelitski
arthurAGretton
cmagriCMagri
yusukeYMurayama
MMontemurro
nikosNKLogothetis
stefanoSPanzeri
poster
GrettonBMSL2005
Kernel methods for dependence testing in LFP-MUA
2005
11
35
689.17
A fundamental problem in neuroscience is determining whether or not particular neural signals are dependent. The correlation is the most straightforward basis for such tests, but considerable work also focuses on the mutual information (MI), which is capable of revealing dependence of higher orders that the correlation cannot detect. That said, there are other measures of dependence that share with the MI an ability to detect dependence of any order, but which can be easier to compute in practice. We focus in particular on tests based on the functional covariance, which derive from work originally accomplished in 1959 by Renyi. Conceptually, our dependence tests work by computing the covariance between (infinite dimensional) vectors of nonlinear mappings of the observations being tested, and then determining whether this covariance is zero - we call this measure the constrained covariance (COCO). When these vectors are members of universal reproducing kernel Hilbert spaces, we can prove this covariance to be zero only when the variables being tested are independent. The greatest advantage of these tests, compared with the mutual information, is their simplicity – when comparing two signals, we need only take the largest eigenvalue (or the trace) of a product of two matrices of nonlinearities, where these matrices are generally much smaller than the number of observations (and are very simple to construct). We compare the mutual information, the COCO, and the correlation in the context of finding changes in dependence between the LFP and MUA signals in the primary visual cortex of the anaesthetized macaque, during the presentation of dynamic natural stimuli. We demonstrate that the MI and COCO reveal dependence which is not detected by the correlation alone (which we prove by artificially removing all correlation between the signals, and then testing their dependence with COCO and the MI); and that COCO and the MI give results consistent with each other on our data.
http://www.kyb.tuebingen.mpg.de
http://www.kyb.tuebingen.mpg.de
http://www.kyb.tuebingen.mpg.de
Department Schölkopf
Department Logothetis
http://www.sfn.org/absarchive/
Washington, DC, USA
35th Annual Meeting of the Society for Neuroscience (Neuroscience 2005)
arthurAGretton
belitskiABelitski
yusukeYMurayama
bsBSchölkopf
nikosNKLogothetis