Topic: communication channels

Cognition arises from the coordinated interaction of multiple circuits with individual computational roles. While our ability to extract the dynamics underlying circuit computation from population activity recorded in individual areas, understanding how multiple areas jointly support distributed computation remains a challenge. Here we propose a novel multi-region statistical model which reflects a process level description of distributed neural computation. Specifically, the model includes local within-region nonlinear dynamics, potentially driven by task-specific inputs, and communication c

Advancements in large-scale neural recordings are now enabling opportunities to probe cognitive computations across simultaneously recorded brain regions, necessitating modeling tools for deciphering multi-region interactions. In an emerging class of dynamical models, brain-wide neural activity is reconstructed by region-specific modules that interact through communication channels and may receive additional information as inputs. These models aim to recover the effective connectome, which includes the inter-region connection diagram and the messages communicated between regions. However, with