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University of Washington, Seattle
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Schedule
Wednesday, April 19, 2023
1:00 AM America/New_York
Recording provided by the organiser.
Domain
NeuroscienceHost
van Vreeswijk TNS
Duration
70 minutes
Learning in neural networks requires assigning the right values to thousands to trillions or more of individual connections, so that the network as a whole produces the desired behavior. Neuroscientists have gained insights into this “credit assignment” problem through decades of experimental, modeling, and theoretical studies. This has suggested key roles for synaptic eligibility traces and top-down feedback signals, among other factors. Here we study the potential contribution of another type of signaling that is being revealed in greater and greater fidelity by ongoing molecular and genomics studies. This is the set of modulatory pathways local to a given circuit, which form an intriguing second type of connectome overlayed on top of synaptic connectivity. We will share ongoing modeling and theoretical work that explores the possible roles of this local modulatory connectome in network learning.
Eric Shea-Brown
University of Washington, Seattle
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