Top Highlights

• At best, they can compute the estimate of the true block prior given full knowledge of the task structure and the sequence of previous stimulus sides since the start of a session, which we refer thereafter as the Bayes-optimal prior
• This finding brings further support to the hypothesis that information flows across the brain in a way that could support the sort of multidirectional inference apparent in Bayesian networks
• Furthermore, we report that this subjective prior is encoded in at least 20% to 30% of brain regions which, remarkably, span all levels of processing, from early sensory areas (LGd, VISp) to motor regions (MOs, MOp, GRN) and high level cortical regions (ACCd, ORBvl).
• a neural model of Bayesian inference involving loops between areas, as opposed to a model in which the prior is incorporated only in decision making areas.
• it remains unclear where and how prior knowledge is represented in the brain.

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