Inference of functional interactions from sparse sampling of large neural ensembles

Abstract

A long-standing goal of neuroscience research is to provide practical solutions for altering cognitive behavior through manipulations of neural circuits as a way to ameliorate cognitive dysfunction. The development of targeted manipulation of neural circuits is currently hampered by our insufficient understanding of how cognitive functions arise from the interactions of large neural ensembles. This project aims at developing a novel foundational framework to infer functional interactions from sparse sampling of large neural ensembles and test our framework on the prefrontal cortex of the monkey brain. The goal is to deliver an innovative technique for targeted manipulation of the prefrontal circuit and alter the monkey’s cognitive behavior in real-time, a key step toward advanced brain-machine interfaces and novel therapeutic interventions in the human brain.

  • In collaboration with prof. Luca Mazzucato, University of Oregon, Eugene
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LIPh
Laboratory of Interdisciplinary Physics

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