1 h 32 min
Neural codes in early sensory areas maximize fitness
Computational Neuroscience, Neuroscience, Vision Science and seminar by Prof Todd Hare, University of Zürich
Hosted by Caltech SocDecNeuro
Wednesday 18:00–19:10 Los Angeles (GMT-7)
Recording available
Recording
Abstract
It has generally been presumed that sensory information encoded by a nervous system should be as accurate as its biological limitations allow. However, perhaps counter intuitively, accurate representations of sensory signals do not necessarily maximize the organism’s chances of survival. We show that neural codes that maximize reward expectation—and not accurate sensory representations—account for retinal responses in insects, and retinotopically-specific adaptive codes in humans. Thus, our results provide evidence that fitness-maximizing rules imposed by the environment are applied at the earliest stages of sensory processing.
Topics
Related seminars
Design principles of adaptable neural codes
Video · 1 h 11 min · Nov 19, 2021Ann Hermundstad, JaneliaUsing ML tools in neuroscience to define optimality in complex natural behavior
Video · 42 min · Jun 5, 2024Stephanie Palmer, University of ChicagoEfficient Random Codes in a Shallow Neural Network
Video · 56 min · Jun 15, 2022Rava Azeredo da Silveira, French National Centre for Scientific Research (CNRS), Paris
More from Caltech SocDecNeuro
All talksDeciding to stop deciding: A cortical-subcortical circuit for forming and terminating a decision
Video · 1 h 23 min · Jun 10, 2021Michael ShadlenFrontal circuit specialisations for decision making
Video · 1 h 30 min · May 27, 2021Laurence HuntRace and the brain: Insights from the neural systems of emotion and decisions
Apr 29, 2021Elizabeth PhelpsChoosing, fast and slow: Implications of prioritized-sampling models for understanding automaticity and control
Apr 15, 2021Cendri Hutcherson
Upcoming in Computational Neuroscience
All seminarsA prospective code for value in the serotonin system
Nov 10, 2026Emerson Harkin