A Brown University Research Group

Understanding the neural computations supporting visual perception

There is little doubt that even a partial solution to the question of which computations are carried out by the visual cortex would be a major breakthrough: It would begin to explain one of our most amazing abilities, vision; and it would open doors to other aspects of intelligence such as language, planning or reasoning. It would also help connect neurobiology and mathematics, making it possible to develop computer algorithms that follow the information processing principles used by biological organisms and honed by natural evolution.

We are proud members of the Carney Institute for Brain Science and the Center for Computational Brain Science at Brown! We also work in close collaboration with and leverage resources from the Center for Computation and Visualization.

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Computational Neuroscience at Brown

Brown has strong expertise in computational approaches to higher-order brain function, from perception to cognition, spanning the departments of Neuroscience, Cognitive, Linguistic & Psychological Sciences, Applied Mathematics, Computer Science, Neurosurgery, Biostatistics, and Engineering. More information related to the Carney Center for Computational Brain Science can be found here.

Prospective students

The lab is actively recruiting! Brown students interested in conducting research in the lab are encouraged to email Prof. Serre with a copy of their course transcripts and CV. Expectations are that students would have taken an intro to CS sequence, at least one course in machine learning, computer vision and/or deep learning. Prospective Ph.D. students can apply to the graduate programs in cognitive science, computer science and neuroscience. Prospective postdoc applicants should email Prof. Serre directly.


Our work is currently supported by ONR (N00014-24-1-2026), NSF (EAR-1925481), DARPA (D19AC00015), and the ANR-3IA Artificial and Natural Intelligence Toulouse Institute (ANR-19-PI3A-0004).

Additional support was provided by the Carney Institute for Brain Science, the Center for Vision Research (CVR), and the Center for Computation and Visualization (CCV). We acknowledge the Cloud TPU hardware resources that Google made available via the TensorFlow Research Cloud (TFRC) program as well as computing hardware supported by NIH Office of the Director grant S10OD025181.