Topic: higher-order autoregressive dynamics

Understanding how multiple brain regions interact to produce behavior is a major challenge in systems neuroscience. Sensory-driven decision making, in particular, has been shown to involve context-dependent processing in multiple brain regions, but a precise description of the interactions between regions remains an open problem. Addressing this problem requires new methods for inferring multi-region activity that account for sensory inputs and communication between brain regions. Here we develop multi-region switching state space models with higher-order autoregressive dynamics, allowing for