Inferring how internal brain state shapes neural responses with state-dependent diffusion models | OpenReview
Neural responses to the same stimulus can vary dramatically with fluctuations in the brain's internal state and the organism's behavioral state. Yet studying how brain state shapes neural responses is difficult: limited experimental recordings sparsely sample this joint space, leaving many biologically valid state-stimulus pairings unobserved. Existing methods either capture state-dependent modulation with restricted model assumptions or synthesize neural activity without explicitly controlling internal brain state. We introduce BrainStateDiff, a conditional diffusion framework that models the spatiotemporal distribution of future neural activity and behavior given external stimuli and recent brain states. Motivated by two gaps in finite recordings, missing state-stimulus combinations and limited repeats of observed conditions, BrainStateDiff introduces two state-aware sampling strategies: cross-state sampling, which recombines observed states and stimuli to synthesize plausible neural