Prof. Alexandre POUGET
Computational neurosciencepping






                                                                                                           Archive Unige




International Brain Initiative. International Brain Initiative: an innovative framework for coordinating global brain research efforts. Neuron. 105:212-216. 2020.

Mendonca , A., Drugowitsch, J.,Vicente, M., DeWitt, E., Pouget, A., Mainen, Z. Reinforcement learning limits performance in categorical decision-making. Nature Communication. In press. Code on github.

Dehaene, G., Ruben Coen-Cagli, R., Pouget A. Representing uncertainty in neuronal circuits: auditory localization as a test case. PLOS Computational Biology.  In press.


Drugowitsch, J., Mendonca , Mainen, Z. Pouget, A. Learning optimal decisions with confidence. PNAS. 2019. Supplementary Information.

Hou H, Zheng Q, Zhao Y, Pouget A, Gu Y. Neural Correlates of Optimal Multisensory Decision Making under Time-Varying Reliabilities with an Invariant Linear Probabilistic Population Code. Neuron. 2019 Sep 23. pii: S0896-6273(19)30744-5. doi: 10.1016/j.neuron.2019.08.038. [Epub ahead of print]. Supplementary Information.

Tajima, S., Drugowitsch, J., Patel, N., and Pouget, A. Optimal policy for multi-alternative decisions. Nature Neuroscience. Aug 5. doi: 10.1038/s41593-019-0453-9. 2019. Supplementary Information.


Lakshminarasimhan, K.J., Liu, S., Gu,Y., Pouget, A., DeAngelis, G.C., Angelaki, D.E., Pitkow, X. Inferring decoding strategies for multiple correlated neural populations. PLoS Computational Biology 14(9):e1006371. doi: 10.1371/journal.pcbi.1006371. eCollection 2018. 

Mendonca, A.G., Jan Drugowitsch, J. Maria I Vicente, M.I., DeWitt, E., Pouget, A. and Mainen, Z.F. The impact of learning on perceptual decisions and its implication for speed-accuracy tradeoffs. BioRxiv 501858; doi: 2018.

Hou, H., Zheng, Q., Zhao. Y., Pouget, A. and Gu, Y. Neural Correlates of Optimal Multisensory Decision Making. BioRxiv. doi: 2018.

Drugowitsch, J. And Pouget, A. Learning optimal decisions with confidence. BioRxiv . doi: 2018.



 Coen-Cagli,  R., Kanitscheider, I., Pouget, A. A method to estimate the number of neurons supporting visual orientation discrimination in primates. F1000Research. 6:1752 (doi: 10.12688/f1000research.12398.1). 2017.

International Brain Laboratory. An International Laboratory for Systems and Computational Neuroscience. Neuron. Volume 96, Issue 6, 20 December 2017, Pages 1213–1218

Grabska-Barwinska A, Barthelme S, Beck J, Mainen ZF, Pouget A, Latham PE. A probabilistic approach to demixing odors. Nature Neuroscience 2017;20(1):98-106.

Zylberberg J, Pouget A, Latham PE, Shea-Brown E. Robust information propagation through noisy neural circuits. PLOS Computational Biology 2017;13(4):e1005497.

Yamada, Y., Bhaukaurally, K., Madarasz, T.J., Pouget, A., Rodriguez, I. and Carleton, A. Context- and output layer-dependent long-term ensemble plasticity in a sensory circuit. Neuron. 93(5):1198-1212.e5. doi: 10.1016/j.neuron.2017.02.006. 2017.


Mainen, Z., Hausser, M. and Pouget A. A better way to crack the brain. Nature. 539, 159–161. 2016.

Pouget A, Drugowitsch J, Kepecs A. Confidence and certainty: distinct probabilistic quantities for different goals. Nature Neuroscience 2016;19(3):366-374.

Kohn A, Coen-Cagli R, Kanitscheider I, Pouget A. Correlations and Neuronal Population Information. Annual Review of Neuroscience 2016;39:237-256.

Tajima S, Drugowitsch J, Pouget A. Optimal policy for value-based decision-making. Nature Communications 2016;7:12400



Pitkow X, Liu S, Angelaki DE, DeAngelis GC, Pouget A. How Can Single Sensory Neurons Predict Behavior? Neuron 2015;87(2):411-423.

Kanitscheider I, Coen Cagli R, Kohn A, Pouget A. Measuring Fisher Information Accurately in Correlated Neural Populations. PLOS Computational Biology 2015;11(6):e1004218.

Kanitscheider I, Brown A, Pouget A, Churchland AK. Multisensory decisions provide support for probabilistic number representations. Journal of Neurophysiology 2015;113(10):3490-3498.

Kanitscheider I, Coen-Cagli R, Pouget A. Origin of information-limiting noise correlations. Proceedings of the National Academy of Sciences 2015;112(50):E6973-6982.

Drugowitsch J, DeAngelis GC, Angelaki DE, Pouget A. Tuning the speed-accuracy trade-off to maximize reward rate in multisensory decision-making. eLife 2015;4:e06678.



Bejjanki VR, Zhang R, Li R, Pouget A, Green CS, Lu Z-L, Bavelier D. Action video game play facilitates the development of better perceptual templates. Proceedings of the National Academy of Sciences 2014;111(47):16961-6.

Mainen ZF, Pouget A. European Commission: Put brain project back on course. Nature 2014;511(7511):534.
Moreno-Bote R, Beck J, Kanitscheider I, Pitkow X, Latham P, Pouget A. Information-limiting correlations. Nature Neuroscience 2014;17(10):1410-7.

Drugowitsch J, DeAngelis GC, Klier EM, Angelaki DE, Pouget A. Optimal multisensory decision-making in a reaction-time task. eLife 2014;n/a:e03005.

Drugowitsch J, Moreno-Bote R, Pouget A. Relation between Belief and Performance in Perceptual Decision Making. PLOS ONE 2014;9(5):e96511.

Vo VA, Li R, Kornell N, Pouget A, Cantlon JF. Young Children Bet on Their Numerical Skills: Metacognition in the Numerical Domain. Psychological Science 2014;n/a.



Pouget A, Beck JM, Ma WJ, Latham PE. Probabilistic brains: knowns and unknowns. Nature Neuroscience 2013;16(9):1170-8.

Grabska-Barwinska A, Beck JM, Pouget A, Latham PE. Demixing odors — fast inference in olfaction. In: Advances in Neural Information Processing Systems 26 (NIPS 2013). Red Hook, New York: Curran; 2013



Bavelier D, Green CS, Pouget A, Schrater P. Brain plasticity through the life span: learning to learn and action video games. Annual Review of Neuroscience 2012;35:391-416.

Griffiths TL, Chater N, Norris D, Pouget A. How the Bayesians got their beliefs (and what those beliefs actually are): comment on Bowers and Davis (2012). Psychological Bulletin 2012;138(3):415-22.

Fetsch CR, Pouget A, DeAngelis GC, Angelaki DE. Neural correlates of reliability-based cue weighting during multisensory integration. Nature Neuroscience 2012;15(1):146-54.

Beck J, Ma WJ, Pitkow X, Latham PE, Pouget A. Not noisy, just wrong: the role of suboptimal inference in behavioral variability. Neuron 2012;74(1):30-9.

Drugowitsch J, Pouget A. Probabilistic vs. non-probabilistic approaches to the neurobiology of perceptual decision-making. Current Opinion in Neurobiology 2012;22(6):963-9.

Drugowitsch J, Moreno-Bote R, Churchland AK, Shadlen MN, Pouget A. The cost of accumulating evidence in perceptual decision making. Journal of Neuroscience 2012;32(11):3612-28.



Moreno-Bote R, Knill DC, Pouget A. Bayesian sampling in visual perception. Proceedings of the National Academy of Sciences 2011;108(30):12491-6.

Beck J, Bejjanki VR, Pouget A. Insights from a simple expression for linear fisher information in a recurrently connected population of spiking neurons. Neural Computation 2011;23(6):1484-502.

Beck JM, Latham PE, Pouget A. Marginalization in neural circuits with divisive normalization. Journal of Neuroscience 2011;31(43):15310-9.

Bejjanki VR, Beck JM, Lu Z-L, Pouget A. Perceptual learning as improved probabilistic inference in early sensory areas. Nature Neuroscience 2011;14(5):642-8.

Ma WJ, Navalpakkam V, Beck JM, Berg R van den, Pouget A. Behavior and neural basis of near-optimal visual search. Nature Neuroscience 2011;14(6):783-90.


Pouget A, Ringach DL, Landy M. Data rules; but theory understands: an introduction to a special issue on "Mathematical models of visual coding". Vision Research 2010;50(22):2189.

Green CS, Pouget A, Bavelier D. Improved probabilistic inference as a general learning mechanism with action video games. Current Biology 2010;20(17):1573-1579.

Drugowitsch J, Pouget A. Quick thinking: perceiving in a tenth of a blink of an eye. Nature Neuroscience 2010;13(3):279-280.



Klam, F., Zemel, R.S. and Pouget, A. Population coding with motion energy filters: the impact of correlations. Neural Computation. 20(1):146-75. 2008.

Banerjee, A., Series, P., and Pouget, A. Dynamical constraints on using precise spike timing to compute in recurrent cortical networks. Neural Computation. 20(4):974-93. 2008.

Ma, W..J., Beck, J. and Pouget, A. Spiking networks for Bayesian inference and choice. Current opinion in biology. 18:217-222. 2008.

Ma, W.J. and  Pouget, A. Linking neurons to behavior in multisensory perception: a computational review. Brain Research. 1242:4-12. 2008.

Beck, J., Ma, W..J., Kiani, R., Hanks, T., Churchland, A.K., Roitman, J., Shadlen, M.N, Latham, P.E. and Pouget, A. Probabilistic population codes for Bayesian decision making. Neuron. 60(6):1142-52. 2008.



Beck, J., Pouget, A. Exact inferences in a neural implementation of a hidden Markov model. Neural Computation. 19(5):1344-61. 2007

Deneve, S., Duhamel., J.R. and Pouget, A. Optimal sensorimotor integration in recurrent cortical networks.  Journal of Neuroscience. 27(21):5744-56. 2007.

 Ben Hamed, S., Schieber, M.H. and Pouget, A. Decoding M1 neurons during multiple finger movements. Journal of Neurophysiology. 98(1):327-33. 2007.

Beck, J., Ma, W.J., Latham, P.E. and  Pouget, A. Probabilistic Population Codes and the Exponential Family of Distributions. Progress in Brain Research. 165:509-19. 2007.



Averbeck, B., Latham, P.E., Pouget, A. Neural correlations, population coding and computation. Nature Review Neuroscience. 7, 358-366. 2006.

Ma, W.J., Beck, J., Latham, P.E. and Pouget, A. Bayesian inference with probabilistic population codes. Nature Neuroscience. 9(11), 1432-1438. 2006. Supplementary Information.



Avillac, M., Denève, S., Olivier, E., Pouget, A. and Duhamel, J.R. Reference frames for representing the location of visual and tactile locations in the parietal cortex. Nature Neuroscience. 8(7). 941-949. 2005.



Series, P., Latham, P.E. and Pouget, A. Tuning curve sharpening for orientation selectivity: coding efficiency and the impact of correlations. Nature Neuroscience. 7(10):1129-1135. 2004. Supplementary information.

Deneve, S., Pouget, A. Bayesian multisensory integration and cross-modal spatial links. Journal of Physiology (Paris).  98:249-258. 2004.

Knill, D., and Pouget, A. The Bayesian brain: the role of uncertainty in neural coding and computation. Trends in Neuroscience. 27(12):712-9. 2004.



Deneve, S. and Pouget, A. Basis functions for object-centered representations. Neuron. 37:347-359. 2003.

Pouget, A., Dayan, P. and Zemel, R.S. Computation and inference with population codes. Annual Review Neuroscience. 26:381-410. 2003.

Ben Hamed, S., Page, G., Duffy, C. and Pouget, A.. MSTd Neuronal Basis Functions for the Population Encoding of Heading Direction. Journal of Neurophysiology. 90(2):549-58. 2003.

Latham, P.E., Deneve, S., Pouget, A. Optimal computation with attractor networks. Journal of Physiology (Paris). 97(4-6): 683-694. 2003.



Deneve, S., Latham, P.E. and Pouget, A. Efficient computation and cue integration with noisy population codes. Nature Neuroscience. 4(8):826-831. 2001.

Pouget, A., and Sejnowski, T.J. Simulating a lesion in a basis function model of spatial representations: comparison with hemineglect. Psychological Review. 108: 653-673. 2001.



Pouget, A., and Snyder, L. Computational approaches to sensorimotor transformations. Nature Neuroscience. 3:1192-1198. 2000.



Deneve, S., Latham, P.E. and Pouget, A. Reading population codes: a neural implementation of ideal observers. Nature Neuroscience. 2(8):740-745. 1999.






Pouget 2016-2.jpg

group leader

Prof. Alexandre POUGET
Tel: +41 22 379 46 99
Offiche nb. C08.1538.A