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Neural populations encode the sensory world imperfectly: their capacity is limited by the number of neurons, availability of metabolic and other biophysical resources, and intrinsic noise. The brain is presumably shaped by these limitations, improving efficiency by discarding some aspects of incoming sensory streams, while preferentially preserving commonly occurring, behaviorally-relevant information. Here we construct a stochastic recurrent neural circuit model that can learn efficient, task-specific sensory codes using a novel form of reward-modulated Hebbian synaptic plasticity. We illustrate the flexibility of the model by training an initially unstructured neural network to solve two different tasks: stimulus estimation, and stimulus discrimination. The network achieves high performance in both tasks by appropriately allocating resources and using its recurrent circuitry to best compensate for different levels of noise. We also show how the interaction between stimulus priors and task structure dictates the emergent network representations.
Author Information
Colin Bredenberg (New York University)
Eero Simoncelli (FlatIron Institute / New York University)
Eero P. Simoncelli received the B.S. degree in Physics in 1984 from Harvard University, studied applied mathematics at Cambridge University for a year and a half, and then received the M.S. degree in 1988 and the Ph.D. degree in 1993, both in Electrical Engineering from the Massachusetts Institute of Technology. He was an Assistant Professor in the Computer and Information Science department at the University of Pennsylvania from 1993 until 1996. He moved to New York University in September of 1996, where he is currently a Professor in Neural Science, Mathematics, and Psychology. In August 2000, he became an Associate Investigator of the Howard Hughes Medical Institute, under their new program in Computational Biology. In Fall 2020, he resigned his HHMI appointment to become the scientific director of the Center for Computational Neuroscience at the Flatiron Institute, of the Simons Foundation. His research interests span a wide range of topics in the representation and analysis of visual images, in both machine and biological systems.
Cristina Savin (NYU)
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Jonathan Scarlett · Piotr Indyk · Ali Vakilian · Adrian Weller · Partha P Mitra · Benjamin Aubin · Bruno Loureiro · Florent Krzakala · Lenka Zdeborová · Kristina Monakhova · Joshua Yurtsever · Laura Waller · Hendrik Sommerhoff · Michael Moeller · Rushil Anirudh · Shuang Qiu · Xiaohan Wei · Zhuoran Yang · Jayaraman Thiagarajan · Salman Asif · Michael Gillhofer · Johannes Brandstetter · Sepp Hochreiter · Felix Petersen · Dhruv Patel · Assad Oberai · Akshay Kamath · Sushrut Karmalkar · Eric Price · Ali Ahmed · Zahra Kadkhodaie · Sreyas Mohan · Eero Simoncelli · Carlos Fernandez-Granda · Oscar Leong · Wesam Sakla · Rebecca Willett · Stephan Hoyer · Jascha Sohl-Dickstein · Sam Greydanus · Gauri Jagatap · Chinmay Hegde · Michael Kellman · Jonathan Tamir · Nouamane Laanait · Ousmane Dia · Mirco Ravanelli · Jonathan Binas · Negar Rostamzadeh · Shirin Jalali · Tiantian Fang · Alex Schwing · Sébastien Lachapelle · Philippe Brouillard · Tristan Deleu · Simon Lacoste-Julien · Stella Yu · Arya Mazumdar · Ankit Singh Rawat · Yue Zhao · Jianshu Chen · Xiaoyang Li · Hubert Ramsauer · Gabrio Rizzuti · Nikolaos Mitsakos · Dingzhou Cao · Thomas Strohmer · Yang Li · Pei Peng · Gregory Ongie -
2019 : Coffee Break & Poster Session »
Samia Mohinta · Andrea Agostinelli · Alexandra Moringen · Jee Hang Lee · Yat Long Lo · Wolfgang Maass · Blue Sheffer · Colin Bredenberg · Benjamin Eysenbach · Liyu Xia · Efstratios Markou · Jan Lichtenberg · Pierre Richemond · Tony Zhang · JB Lanier · Baihan Lin · William Fedus · Glen Berseth · Marta Sarrico · Matthew Crosby · Stephen McAleer · Sina Ghiassian · Franz Scherr · Guillaume Bellec · Darjan Salaj · Arinbjörn Kolbeinsson · Matthew Rosenberg · Jaehoon Shin · Sang Wan Lee · Guillermo Cecchi · Irina Rish · Elias Hajek -
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2017 Poster: Eigen-Distortions of Hierarchical Representations »
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2012 Poster: Efficient and direct estimation of a neural subunit model for sensory coding »
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2009 Poster: Hierarchical Modeling of Local Image Features through $L_p$-Nested Symmetric Distributions »
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2008 Oral: Reducing statistical dependencies in natural signals using radial Gaussianization »
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2007 Poster: A Bayesian Model of Conditioned Perception »
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2006 Poster: Statistical Modeling of Images with Fields of Gaussian Scale Mixtures »
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