How learned expectations shape brain-wide responses

Expectations stemming from prior knowledge have long been known to influence stimulus processing and decision-making. Empowered by brain-wide recordings during a two-choice sensory decision-making task from the International Brain Laboratory1, we sought to identify the form of expectation-based modulations and how they influence ongoing computations. To discern where, when, and how prior knowledge about the stimulus - known to be stored in the brain over the inter-trial period2 - influences brain activity over the arc from stimulus processing to choice selection and action generation, we disentangled the encoding of the highly correlated stimulus, choice, and prior variables as sensory processors, choice/integration processors, and movement generators. We examined which brain regions were modulated by prior expectations and at which point in the task, and characterized whether those modulations take the form of biasing initial activations or response gains. We found that the activities of choice/integrators and movement generators were influenced by prior expectation, while purely stimulus processors were not significantly modulated by prior expectation. In addition, we found that expectation-based modulation takes the form of both initial activity bias and gain modulation in integration/choice computations and in movement generators. We further find that the brain-wide recordings reveal an emergent simplicity: A few-parameter mechanistic neural circuit model captures the population dynamics of stimulus response, integration/choice processing, and action initiation, as well as their modulations by the prior. After fitting to physiology, the models behavior predicts the psychometric and chronometric behavior of mice with no additional parameters. It reveals that the larger bias and gain modulations of movement initiators relative to integration/choice in the data and model is inherited by amplifying integrator/choice inputs rather than being an additional expectation-based effect. Collectively, our results characterize in fine spatiotemporal detail and brain-wide breadth the mechanisms and loci where prior expectations influence cognition, while the novel synthesis between large-scale electrophysiology and mechanistic modeling reveals an organizing simplicity behind perceptual decision making across the brain.