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Ruben Coen Cagli, Ph.D.

Ruben Coen Cagli, Ph.D.

Assistant Professor, Department of Systems & Computational Biology

Assistant Professor, Dominick P. Purpura Department of Neuroscience

Area of Research: We study neural computation to understand how the brain produces perceptual experiences. Topics: neural coding and perception of natural images; perceptual variability and uncertainty; neural variability and sensory information; image segmentation; AI.

Contact Information

718.678.1150

Albert Einstein College of Medicine
Michael F. Price Center
1301 Morris Park Avenue, Room 353B
Bronx, NY 10461

Research Profiles PubMed Portal

More Resources: Coen-Cagli Laboratory for Computational NeuroscienceGoogle scholar profile

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Professional Interests

WHAT? My lab studies neural computation with the broader goal of explaining our perceptual experience. When we interpret the surrounding environment, our visual system faces two major challenges: The natural environment is ambiguous (e.g. different objects can produce similar retinal images) and computationally intractable (e.g. the same object can produce countless different retinal images). To face these problems, the brain must evaluate how probable different interpretations of the sensory input are. Understanding such probabilistic inference in natural sensory processing will be central to understanding perception, and much of the computation realized by cortical neurons.

HOW? Our lab follows a hypothesis-driven approach to understanding cortical processing of natural images and linking it to visual perception. Computer vision and machine learning provide insights into the complex structure of natural signals and how they could be processed efficiently. Probabilistic neural coding provides the theoretical framework to understand how veridical perception is achieved in face of abundant sensory noise and image ambiguities. We combine advances in both fields to generate novel hypotheses about cortical computation in natural vision, and test them experimentally with psychophysics in the lab and electrophysiology through collaborations.

WHY? Explaining how the human visual system achieves its impressive feats — from fast and accurate recognition of people and their actions, to the appreciation of Picasso’s Guernica — is a major goal of neuroscience, and more generally biology and medicine. My lab’s research aims to contribute a substantial step forward to this endeavor, by taking a principled approach to studying the visual system in its natural operation mode. In the longer run, we hope this research will contribute to elucidating how the brain produces the vivid, coherent, stable percepts we experience in everyday life; to advancing technologies that could restore impaired vision and enhance normal vision; and to deciphering the neural basis of human visual creativity.

Selected Publications

(2021) G. Dehaene,R. Coen-Cagli, A. Pouget. Investigating the representation of uncertainty in neuronal circuits. PLoS Computational Biology 17(1):e1008138.

(2021) D. Herrera, R. Coen-Cagli*, L. Gomez-Sena*. Flexible contextual modulation of naturalistic texture perception in peripheral vision. Journal of Vision 21(1):1(preprint: https://doi.org/10.1101/2020.01.24.918813)

(2020) J. Vacher, A. Davila, A. Kohn, R. Coen-Cagli. Texture interpolation for probing visual perception. NeurIPS 2020 (preprint: ArXiv:2006.03698).

(2020) D. Festa, A. Aschner, A. Davila, A. Kohn, R. Coen-Cagli. Neuronal variability reflects probabilstic inference tuned to natural image statistics. (preprint: https://doi.org/10.1101/2020.06.17.142182)

(2019) S. Sokoloski, A. Aschner, R. Coen-Cagli. Modeling the neural code in large populations of correlated neurons. (preprint: https://www.biorxiv.org/content/10.1101/2020.11.05.369827v1).

(2019) R. Coen-Cagli, S.S.. Solomon. Relating divisive normalization to neuronal response variability. Journal of Neuroscience 39(37):7344

(2019) J. Vacher, R. Coen-Cagli. Combining Mixture Models with Linear Mixing Updates: Multilayer Image Segmentation and Synthesis. ArXiv:1905.10629.

(2017) M. Snow, R. Coen-Cagli, O. Schwartz, Adaptation in visual cortex: a case for probing neural populations with natural stimuli. F1000Research, 6:1246.

(2016) A. Kohn, R. Coen-Cagli, I. Kanitscheider, A. Pouget, Correlations and neuronal population information. Annual Reviews of Neuroscience. 39:237-256.

(2016) M. Snow, R. Coen-Cagli, O. Schwartz, Specificity and timescales of cortical adaptation as inferences about natural movie statistics. Journal of Vision 16(13):1.

(2015) I. Kanitscheider*, R. Coen-Cagli*, A. Pouget, The origin of information-limiting noise correlations. PNAS, 112(50): E6973-E6982

(2015) R. Coen-Cagli, A. Kohn*, O. Schwartz*, Flexible Gating of Contextual Modulation During Natural Vision. Nature Neuroscience, 18: 1648–1655

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

(2013) R. Coen-Cagli, O. Schwartz, The Impact on Mid-Level Vision of Statistically Optimal Divisive Normalization in V1. Journal of Vision, 13(8):13

(2012) R. Coen-Cagli, P. Dayan, O. Schwartz, Cortical Surround Interactions and Perceptual Salience Via Natural Scene Statistics. PLoS Computational Biology, 8(3): e1002405

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Faculty Profile

Ruben Coen Cagli, Ph.D.

Contact Information

Professional Interests

Selected Publications