Coen-Cagli laboratory for Computational Neuroscience
Laboratory for Computational Neuroscience - Albert Einstein College of Medicine - Bronx NY
Investigating neural computation in natural sensory processing
WHAT? The Coen-Cagli lab studies neural computation with the broader goal of explaining our perceptual experience. A central function of the visual system is to produce correct interpretations of sensory signals, to guide appropriate behavioral responses. However, the surrounding environment is in general 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 solve these problems, the brain must estimate the probability of different interpretations of the sensory input. Understanding such probabilistic inference in natural sensory processing will be central to understanding perception, and much of the computation realized by cortical neurons.
HOW? The 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. Our 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.
We also coordinate the Machine Learning Reading Group at Einstein, and the graduate course on AI for biomedical research.
The lab strives to be an open, inclusive, harassment-free environment.
Ruben is an ally of Black In AI and a member of Einstein's Diversity, Equity and Inclusion council.
Undergraduate and High school students interested in computational neuroscience, check out Einstein's programs PREP, SURP, and HSSRP
NEWS
2024.02 - Our review paper linking response variability and sub-additivity is out on Nature Reviews Neuroscience
2023.12 - Interested in modeling neural variability with CNNs? Check out Xu Pan's new paper with Odelia Schwartz inNeural Computation
2023.11 - Please join us on 11/11 at the SFN minisymposium on Suppression and Variability in Visual Cortex
2023.11 - Oren's paper relating noise correlations and divisive gain control with Adesnik lab now accepted in PLoS Comput Biol!
2023.10 - Our paper on perceptual segmentation is now in PLoS Comput Biol
2023.08 - Welcome to the lab Concetta and Tridib!
2023.05 - We have completed the first graduate course in AI for biomedical research at Einstein.
2023.02 - WE ARE HIRING! Please get in touch if you're interested in doing a postdoc with us!
2023.01 - We propose the first method to measure perceptual segmentation maps and their uncertainties: outstanding work by Jonathan with Claire and P. Mamassian.
2023.01 - Substantial update of Oren's manuscript relating noise correlations and divisive gain control with Adesnik lab
2022.11 - New preprint on spatial information encoding in the hippocampus, nice collab with Augustina Frechou and the Goncalves lab
2022.10 - Check out our mega-review Calibrating the Visual System - monumental effort led by Michael Webster
2022.09 - We received a BRAIN R01 grant to develop Computational Tools for assessing mechanisms and functional relevance of divisive normalization!
2022.09 - We received a pilot grant from Einstein's RFK IDDRC to study perceptual segmentation in ASD
2022.08 - Check out Amir's new work on normative models of noise correlations at the CCN conference
2022.06 - We're excited that Claire's paper on dynamic segmentation is accepted at IEEE-ICIP 2022! Our first at a pure CV conference.
2022.06 - Oren's manuscript relating noise correlations and divisive gain control is online on biorXiv!
2022.04 - We're hiring! Postdoc opening on sensory processing in autism, collaboration with CNL (Molholm lab) at Einstein.
2022.03 - For a preview of our current work, check out Ruben's talk at World Wide Theoretical Neuroscience Seminar
2022.02 - Congrats to Jonathan and Claire, whose paper on Flexible Mixture Models is published at Neural Networks!
2022.01 - Welcome to the lab Linghao Xu!
2021.12 - Check out our work on segmentation and many other exciting talks at the NeurIPS workshop SVRHM
2021.10 - Ruben is promoted to Associate Professor. Thanks to all past and current lab members who have made this possible!
2021.09 - Sacha's model of correlated, context-dependent neural activity is now accepted at eLife, congrats!
2021.08 - Congrats to Daniel Herrera for a successful PhD thesis defense!
2021.08 - We have a new preprint on modeling neural variability in deep nets, nice work by Xu Pan with Odelia Schwartz.
2021.07 - We are hiring! If you're looking for a postdoc job contact Ruben
2021.07 - Congrats Daniel on publishing the second paper from his PhD work on segmentation and texture perception!
2021.06 - Congrats Dylan! Paper is out on contextual modulation of V1 response variability, with Amir Aschner, Aida Davila, and Adam Kohn.
2021.04 - Daniel's new preprint is out, on the redundancy of summary statistics and what it implies for texture-based segmentation.
2021.03 - We are delighted to welcome Amirhossein Farzmahdi as a postdoc in the lab!
2021.03 - Dylan leaves the lab to join the Gjorgjieva lab in Frankfurt. Good luck Dylan!
2021.02 - We have updated Dylan's preprint on contextual modulation of V1 response variability, with Amir Aschner, Aida Davila, and Adam Kohn.
2021.02 - Come visit our posters at virtual Cosyne 2021: 1-003, 1-034, 2-047, 2-063, 3-059.
2021.02 - After years in the making, our paper on neural representations of uncertainty is out on PLoS CB, with Guillaume Dehaene and Alex Pouget.
2020.12 - Our paper on naturalistic texture processing and segmentation is the Journal of Vision cover article for January 2021, congrats Daniel Herrera!
2020.11 - Check out our new preprint, a remarkable tour de force by Sacha on exponential family mixture models of correlated neural
populations.
2020.10 - Welcome Claire Launay who joins the lab as a postdoc!
2020.09 - Congrats to Jonathan whose work on naturalistic texture synthesis and interpolation is a NeurIPS spotlight!
2020.09 - Jonathan leaves the lab to join the Mamassian lab in Paris. Good luck Jonathan!
2020.07 - Check out our new preprint on contextual modulation of V1 response variability by Dylan with Amir Aschner, Aida Davila, and Adam Kohn.
2020.06 - Jonathan will present at V-VSS our new experiments on perceptual segmentation, with Pascal Mamassian.
2020.06 - Check out our new preprint on naturalistic texture synthesis and interpolation by Jonathan with Aida Davila and Adam Kohn.
2020.06 - Congrats to Dylan who will be TA-ing at the Neuromatch summer school.
2020.04 - We're hiring! See the postdoc ad, starting date Fall 2020.
2020.03.18 - Congrats to Oren who passed his qualifying exam today!
2020.02 - The entire lab will be presenting at Cosyne 2020! come check out our new work at poster boards I-54, I-81 and II-116. 2020.02 - Congrats to Sacha whose abstract was accepted at CSHL From Neuroscience to Artificially Intelligent Systems!
2020.02 - Congrats to Sacha who is the recipient of Cosyne Childcare Grant Program (and shoutout to Cosyne for making this possible)!
2020.02 - Ruben is giving a talk at the Redwood Center for Theoretical Neuroscience in Berkeley on 02-12.
2020.01 - Check out our new preprint on naturalistic texture processing and segmentation, excellent work by Daniel Herrera!
2020.01 - We're hiring! See the postdoc ad, starting date Spring/Summer 2020.
2019.10 - Ruben is co-editor of Vision Research special issue Calibrating the Visual System, submissions are open until July 31st, 2020.
2019.09 - We received two R01s by NIH/NEI! Collaborations with Kohn lab on visual-cortical processing of natural images and Mamassian lab on perceptual grouping.
2019.09 - Dylan will present at CCNeuro and Bernstein our computational and experimental work on contextual modulation of response variability.
2019.08 - Check out Sacha's pre-print on a new model of correlated, context-dependent neural activity!
2019.08 - Jonathan will give a talk at ECVP on contour integration and grouping in natural images.
2019.07 - Welcome to Oren Weiss, the first full time student of the lab!
2019.07 - Our paper relating divisive normalization to V1 response variability is out at Journal of Neuroscience.
2019.06 - Check out Jonathan's new pre-print on hierarchical segmentation via interacting mixture models!
2019.05 - Check out Jonathan's new pre-print on segmentation of natural images with closed-form uncertainty-based updates!
2018.12 - Check out our preprint on cortical variability and divisive normalization!
2018.11 - Ruben will be at SFN presenting new work on cortical variability and divisive normalization.
2018.09 - We're excited to restart our Machine Learning Reading Group @Einstein!
2018.06 - Check out Jonathan's pre-print on segmentation of natural images!
2018.03 - The lab will be at Cosyne. Check out Dylan's poster III-61 on March 3rd!
2018.02 - Welcome to Daniel Herrera who will spend part of his PhD program in the lab!
2017.11 - Welcome to Sacha Sokoloski who joins the lab as a postdoc!
2017.09 - Welcome to Jonathan Vacher who joins the lab as a postdoc!
2017.09 - I will give the tutorial talk on Computational Neuroscience at the Cognitive Computational Neuroscience Conference on Sept 7.
2017.09 - We will be at the Cognitive Computational Neuroscience Conference on Sept 6-8 to present new work on neuronal population variability and image statistics.
2017.09 - I will be at the Bernstein Conference workshops on Sept 12-13 to talk about neuronal population variability in natural vision.
2017.05 - Congrats to Dylan Festa for being accepted at the Woods Hole summer school on Brains, Minds and Machines!