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SUMMARY:Identifying Communication Between Brain Regions - Matthew Golub (U
 niversity of Washington)
DTSTART;VALUE=DATE-TIME:20250918T150000
DTEND;VALUE=DATE-TIME:20250918T163000
UID:https://talks.ox.ac.uk/talks/id/771d9668-7e50-426b-8d81-17566497708b/
DESCRIPTION:Neural recording technologies now enable simultaneous recordin
 g of population activity across many brain regions\, motivating the develo
 pment of data-driven models of communication between brain regions. Howeve
 r\, existing models can struggle to disentangle the sources that influence
  recorded neural populations\, leading to inaccurate portraits of inter-re
 gional communication. In this talk\, I will introduce Multi-Region Latent 
 Factor Analysis via Dynamical Systems (MR-LFADS)\, a sequential variationa
 l autoencoder designed to disentangle inter-regional communication\, input
 s from unobserved regions\, and local neural population dynamics. We show 
 that MR-LFADS outperforms existing approaches at identifying communication
  across dozens of simulations of task-trained multi-region networks. When 
 applied to large-scale electrophysiology\, MR-LFADS predicts brain-wide ef
 fects of circuit perturbations that were held out during model fitting. Th
 ese validations on synthetic and real neural data position MR-LFADS as a p
 romising tool for discovering principles of brain-wide information process
 ing.\nSpeakers:\nMatthew Golub (University of Washington)
LOCATION:Sherrington Library\, off Parks Road OX1 3PT
TZID:Europe/London
URL:https://talks.ox.ac.uk/talks/id/771d9668-7e50-426b-8d81-17566497708b/
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DESCRIPTION:Talk:Identifying Communication Between Brain Regions - Matthew
  Golub (University of Washington)
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