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Identifying Communication Between Brain Regions
Neural recording technologies now enable simultaneous recording of population activity across many brain regions, motivating the development of data-driven models of communication between brain regions. However, existing models can struggle to disentangle the sources that influence recorded neural populations, leading to inaccurate portraits of inter-regional communication. In this talk, I will introduce Multi-Region Latent Factor Analysis via Dynamical Systems (MR-LFADS), a sequential variational autoencoder designed to disentangle inter-regional communication, inputs 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 effects of circuit perturbations that were held out during model fitting. These validations on synthetic and real neural data position MR-LFADS as a promising tool for discovering principles of brain-wide information processing.
Date:
18 September 2025, 15:00
Venue:
Sherrington Library, off Parks Road OX1 3PT
Speaker:
Matthew Golub (University of Washington)
Organising department:
Medical Sciences Division
Organisers:
Dr Jascha Achterberg (University of Oxford),
Dr Rui Ponte Costa (University of Oxford)
Hosts:
Dr Jascha Achterberg (University of Oxford),
Dr Rui Ponte Costa (University of Oxford)
Part of:
Oxford NeuroAI Forum
Booking required?:
Not required
Audience:
Members of the University only
Editors:
Ian Cone,
Jascha Achterberg
