Multi-layer network learning in an electric fish
Computational Neuroscience, Ichthyology, Machine Learning and seminar by Prof Larry Abbott, Columbia University
Hosted by U Oregon Neuro
Wednesday 23:59–01:09 Los Angeles (GMT-7)
Ended
Abstract
The electrosensory lobe (ELL) in mormyrid electric fish is a cerebellar-like structure that cancels the sensory effects of self-generated electric fields, allowing prey to be detected. Like the cerebellum, the ELL involves two stages of processing, analogous to the Purkinje cells and cells of the deep cerebellar nuclei. Through the work of Curtis Bell and others, a model was previously developed to describe the output stage of the ELL, but the role of the Purkinje-cell analogs, the medium ganglion (MG) cells, in the circuit had remained mysterious. I will present a complete, multi-layer circuit description of the ELL, developed in collaboration with Nate Sawtell and Salomon Muller, that reveals a novel role for the MG cells. The resulting model provides an example of how a biological system solves well-known problems associated with learning in multi-layer networks, and it reveals that ELL circuitry is organization on the basis of learning rather than by the response properties of neurons.
Topics
Related seminars
- Video page · Nov 16, 2020Angel Caputi, MD, PhD, Profesor Titular de Investigación, Departamento de Neurociencias Integrativas y Computacionales
A Changing View of Vision: From Molecules to Behavior in Zebrafish
Video · 1 h 16 min · May 3, 2021Herwig Baier, Max PLanck InstituteYoung IBRO NextInNeuro Webinar - The retinal basis of colour vision: from fish to humans
Video · 1 h 16 min · Mar 19, 2021Tom Baden, University of Sussex
More from U Oregon Neuro
All talksTheory of gating in recurrent neural networks
Sep 16, 2020Kamesh KrishnamurthyFlexible motor sequencing through thalamic control of cortical dynamics
May 19, 2020Laureline LogiacoCortical circuits for olfactory navigation
May 14, 2020Cindy Poo
More with Larry Abbott
All their workThe Brain Prize winners' webinar
Seminar · Nov 30, 2024Brain Prize Webinar Series 2024Using Dynamical Systems Theory to Improve Temporal Credit Assignment in Spiking Neural Networks
ePoster · Sep 29, 2024Bernstein Conference 2024Modeling the Navigational Circuitry of the Fly
Seminar · Dec 1, 2023NYU SwartzThe desire to know: representations of information value in mouse orbitofrontal cortex during information seeking
ePoster · Mar 11, 2023COSYNE 2023
Upcoming in Computational Neuroscience
All seminarsCircuit mechanisms of sensorimotor learning in the cortico-basal ganglia-thalamocortical network
Oct 28, 2026Arthur Leblois