Zeitschriftenartikel (94)

  1. 1.
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    Cadena, S.; Denfield, G.; Walker, E.; Gatys, L.; Tolias, A.; Bethge, M.; Ecker, A.: Deep convolutional models improve predictions of macaque V1 responses to natural images. PLoS Computational Biology 15 (4) (2019)
  2. 2.
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    Wallis, T.; Funke, C.; Ecker, A.; Gatys, L.; Wichmann, F.; Bethge, M.: Image content is more important than Bouma’s Law for scene metamers. eLife 8 (2019)
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    Subramaniyan, M.; Ecker, A.; Patel, S.; Cottonq, R.; Bethge, M.; Pitkow, X.; Berens, P.; Tolias, A.: Faster processing of moving compared with flashed bars in awake macaque V1 provides a neural correlate of the flash lag illusion. Journal of Neurophysiology 120 (5), S. 2430 - 2452 (2018)
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    Mathis, A.; Mamidanna, P.; Cury, A.; Abe, T.; Murthy, V.; Mathis, M.; Bethge, M.: DeepLabCut: markerless pose estimation of user-defined body parts with deep learning. Nature Neuroscience 21 (9), S. 1281 - 1289 (2018)
  5. 5.
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    Denfield, G.; Ecker, A.; Shinn, T.; Bethge, M.; Tolias, A.: Attentional fluctuations induce shared variability in macaque primary visual cortex. Nature Communications 9, 2654, S. 1 - 14 (2018)
  6. 6.
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    Wallis, T.; Funke, C.; Ecker, A.; Gatys, L.; Wichmann, F.; Bethge, M.: Image content is more important than Bouma's Law for scene metamers. (eingereicht)
  7. 7.
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    Mathis, A.; Mamidanna, P.; Abe, T.; Cury, K.; Murthy, V.; Mathis, M.; Bethge, M.: Markerless tracking of user-defined features with deep learning. (eingereicht)
  8. 8.
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    Gatys, L.; Ecker, A.; Bethge, M.: Texture and art with deep neural networks. Current Opinion in Neurobiology 46, S. 178 - 186 (2017)
  9. 9.
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    Nonnenmacher, M.; Behrens, C.; Berens, P.; Bethge, M.; Macke, J.: Signatures of criticality arise from random subsampling in simple population models. PLoS Computational Biology 13 (10) (2017)
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    Wallis, T.; Tobias, S.; Bethge, M.; Wichmann, F.: Detecting distortions of peripherally presented letter stimuli under crowded conditions. Attention, Perception, Psychophysics 79 (3), S. 850 - 862 (2017)
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    Franke, K.; Berens, P.; Schubert, T.; Bethge, M.; Euler, T.; Baden, T.: Inhibition decorrelates visual feature representations in the inner retina. Nature 542 (7642), S. 439 - 444 (2017)
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    Hosseini, R.; Sra, S.; Theis, L.; Bethge, M.: Inference and mixture modeling with the Elliptical Gamma Distribution. Computational Statistics Data Analysis 101, S. 29 - 43 (2016)
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    Mathis, A.; Rokni, D.; Kapoor, V.; Bethge, M.; Murthy, V.: Reading Out Olfactory Receptors: Feedforward Circuits Detect Odors in Mixtures without Demixing. Neuron 91 (5), S. 1110 - 1123 (2016)
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    Theis, L.; Berens, P.; Froudarakis, E.; Reimer, J.; Román Rosón, M.; Baden, T.; Euler, T.; Tolias, A.; Bethge, M.: Benchmarking Spike Rate Inference in Population Calcium Imaging. Neuron 90 (3), S. 471 - 482 (2016)
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    Wallis, T.; Bethge, M.; Wichmann, F.: Testing models of peripheral encoding using metamerism in an oddity paradigm. Journal of Vision 16 (2), 4, S. 1 - 30 (2016)
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    Cadwell, C.; Palasantza, A.; Jiang, X.; Berens, P.; Deng, Q.; Yilmaz, M.; Reimer, J.; Shen, S.; Bethge, M.; Tolias, K. et al.; Sandberg, R.; Tolias, A.: Electrophysiological, transcriptomic and morphologic profiling of single neurons using Patch-seq. Nature Biotechnology 34 (2), S. 199 - 203 (2016)
  17. 17.
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    Ecker, A.; Denfield, G.; Bethge, M.; Tolias, A.: On the Structure of Neuronal Population Activity under Fluctuations in Attentional State. Journal of Neuroscience 36 (5), S. 1775 - 1789 (2016)
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    Baden, T.; Berens, P.; Franke, K.; Román Rosón, M.; Bethge, M.; Euler, T.: The functional diversity of retinal ganglion cells in the mouse. Nature 529 (7586), S. 345 - 350 (2016)
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    Kümmerer, M.; Wallis, T.; Bethge, M.: Information-theoretic model comparison unifies saliency metrics. Proceedings of the National Academy of Sciences of the United States of America 112 (52), S. 16054 - 16059 (2015)
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    Jiang, X.; Shen, S.; Cadwell, C.; Berens, P.; Sinz, F.; Ecker, A.; Patel, S.; Tolias, A.: Principles of connectivity among morphologically defined cell types in adult neocortex. Science 350 (6264), S. aac9462-1 - aac9462-10 (2015)
  21. 21.
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    Gatys, L.; Ecker, A.; Bethge, M.: A Neural Algorithm of Artistic Style. Nature Communications submitted (2015)
  22. 22.
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    Gatys, L.; Ecker, A.; Tchumatchenko, T.; Bethge, M.: Synaptic unreliability facilitates information transmission in balanced cortical populations. Physical Review E 91, 062707, S. 1 - 7 (2015)
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    Lüdtke, N.; Das, D.; Theis, L.; Bethge, M.: A Generative Model of Natural Texture Surrogates. - submitted (2015)
  24. 24.
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    Panzeri, S.; Macke, J.; Gross, J.; Kayser, C.: Neural population coding: combining insights from microscopic and mass signals. Trends in Cognitive Sciences 19 (3), S. 162 - 172 (2015)
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    Yatsenko, D.; Josić, K.; Ecker, A.; Froudarakis, E.; Cotton, R.; Tolias, A.: Improved Estimation and Interpretation of Correlations in Neural Circuits. PLoS Computational Biology 11 (3) (2015)
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    Küffner, R.; Zach, N.; Norel, R.; Hawe, J.; Schoenfeld, D.; Wang, L.; Li, G.; Fang, L.; Mackey, L.; Hardiman, O. et al.; Cudkowicz, M.; Sherman, A.; Ertaylan, G.; Grosse-Wentrup, M.; Hothorn, T.; van Ligtenberg, J.; Macke, J.; Meyer, T.; Schölkopf, B.; Tran, L.; Vaughan, R.; Stolovitzky, G.; Leitner, M.: Crowdsourced analysis of clinical trial data to predict amyotrophic lateral sclerosis progression. Nature Biotechnology 33 (1), S. 51 - 57 (2015)
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    Park, M.; Macke, J.: Hierarchical models for neural population dynamics in the presence of non-stationarity. - submitted (2015)
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    Ecker, A.; Tolias, A.: Is there signal in the noise? Nature Neuroscience 17 (6), S. 750 - 751 (2014)
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    Froudarakis, E.; Berens, P.; Ecker, A.; Cotton, R.; Sinz, F.; Yatsenko, D.; Saggau, P.; Bethge, M.; Tolias, A.: Population code in mouse V1 facilitates readout of natural scenes through increased sparseness. Nature Neuroscience 17 (6), S. 851 - 857 (2014)
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    Fründ, I.; Wichmann, F.; Macke, J.: Quantifying the effect of intertrial dependence on perceptual decisions. Journal of Vision 14 (7:9), S. 1 - 16 (2014)
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    Ecker, A.; Berens, P.; Cotton, R.; Subramaniyan, M.; Denfield, G.; Cadwell, C.; Smirnakis, S.; Bethge, M.; Tolias, A.: State Dependence of Noise Correlations in Macaque Primary Visual Cortex. Neuron 82 (1), S. 235 - 248 (2014)
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    Lies, J.-P.; Häfner, R.; Bethge, M.: Slowness and sparseness have diverging effects on complex cell learning. PLoS Computational Biology 10 (3) (2014)
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    Gerhard, H.; Bethge, M.: Towards Rigorous Study of Artistic Style: A New Psychophysical Paradigm. Art & Perception 2 (1-2), S. 23 - 44 (2014)
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    Chagas, A.; Theis, L.; Sengupta, B.; Stüttgen, M.; Bethge, M.; Schwarz, C.: Functional analysis of ultra high information rates conveyed by rat vibrissal primary afferents. Frontiers in Neural Circuits 7 (2013)
  35. 35.
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    Theis, L.; Chagas , A.; Arnstein, D.; Schwarz, C.; Bethge, M.: Beyond GLMs: A Generative Mixture Modeling Approach to Neural System Identification. PLoS Computational Biology 9 (11) (2013)
  36. 36.
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    Watanabe, M.; Bartels, A.; Macke, J.; Murayama, Y.; Logothetis, N.: Temporal Jitter of the BOLD Signal Reveals a Reliable Initial Dip and Improved Spatial Resolution. Current Biology 23 (21), S. 2146 - 2150 (2013)
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    Macke, J.; Murray, I.; Latham, P.: Estimation bias in maximum entropy models. Entropy 15 (8), S. 3109 - 3219 (2013)
  38. 38.
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    Subramaniyan, M.; Ecker, A.; Berens, P.; Tolias, A.: Macaque Monkeys Perceive the Flash Lag Illusion. PLoS One 8 (3) (2013)
  39. 39.
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    Baden, T.; Berens, P.; Bethge, M.; Euler, T.: Spikes in Mammalian Bipolar Cells Support Temporal Layering of the Inner Retina. Current Biology 23 (1), S. 48 - 52 (2013)
  40. 40.
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    Gerhard, H.; Wichmann, F.; Bethge, M.: How sensitive is the human visual system to the local statistics of natural images? PLoS Computational Biology 9 (1) (2013)
  41. 41.
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    Berens, P.; Ecker, A.; Cotton, R.; Ma, W.; Bethge, M.; Tolias, A.: A Fast and Simple Population Code for Orientation in Primate V1. Journal of Neuroscience 32 (31), S. 10618 - 10626 (2012)
  42. 42.
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    Schwartz, G.; Macke, J.; Amodei, D.; Tang, H.; Berry II, M.: Low Error Discrimination using a Correlated Population Code. Journal of Neurophysiology 108 (4), S. 1069 - 1088 (2012)
  43. 43.
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    Theis, L.; Hosseini, R.; Bethge, M.: Mixtures of Conditional Gaussian Scale Mixtures Applied to Multiscale Image Representations. PLoS One 7 (7) (2012)
  44. 44.
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    Putzeys, T.; Bethge, M.; Wichmann, F.; Wagemans, J.; Goris, R.: A New Perceptual Bias Reveals Suboptimal Population Decoding of Sensory Responses. PLoS Computational Biology 8 (4) (2012)
  45. 45.
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    Theis, L.; Gerwinn, S.; Sinz, F.; Bethge, M.: In All Likelihood, Deep Belief Is Not Enough. The Journal of Machine Learning Research 12, S. 3071 - 3096 (2011)
  46. 46.
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    Ecker, A.; Berens, P.; Tolias, A.; Bethge, M.: The effect of noise correlations in populations of diversely tuned neurons. The Journal of Neuroscience 31 (40), S. 14272 - 14283 (2011)
  47. 47.
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    Kitching, T.; Amara, A.; Gill, M.; Harmeling, S.; Heymans, C.; Massey, R.; Rowe, B.; Schrabback, T.; Voigt, L.; Balan, S. et al.; Bernstein, G.; Bethge, M.; Bridle, S.; Courbin, F.; Gentile, M.; Heavens, A.; Hirsch, M.; Hosseini, R.; Kiessling, A.; Kirk, D.; Kuijken, K.; Mandelbaum, R.; Moghaddam, B.; Nurbaeva, G.; Paulin-Henriksson , S.; Rassat, A.; Rhodes, J.; Schölkopf, B.; Shawe-Taylor, J.; Shmakova , M.; Taylor, A.; Velander, M.; van Waerbeke, L.; Witherick, D.; Wittman, D.: Gravitational Lensing Accuracy Testing 2010 (GREAT10) Challenge Handbook. Annals of Applied Statistics 5 (3), S. 2231 - 2263 (2011)
  48. 48.
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    Macke, J.; Berens, P.; Bethge, M.: Statistical analysis of multi-cell recordings: linking population coding models to experimental data. Frontiers in Computational Neuroscience 5 (2011)
  49. 49.
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    Fleming, R.; Jäkel, F.; Maloney, L.: Visual Perception of Thick Transparent Materials. Psychological Science 22 (6), S. 812 - 820 (2011)
  50. 50.
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    Macke, J.; Opper, M.; Bethge, M.: Common Input Explains Higher-Order Correlations and Entropy in a Simple Model of Neural Population Activity. Physical Review Letters 106 (20), 208102, S. 1 - 4 (2011)
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