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The Graphical Brain: Belief Propagation and Active Inference

Overview
Journal Netw Neurosci
Publisher MIT Press
Specialty Neurology
Date 2018 Feb 9
PMID 29417960
Citations 146
Authors
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Abstract

Author Summary: This paper considers functional integration in the brain from a computational perspective. We ask what sort of neuronal message passing is mandated by active inference-and what implications this has for context-sensitive connectivity at microscopic and macroscopic levels. In particular, we formulate neuronal processing as belief propagation under deep generative models that can entertain both discrete and continuous states. This leads to distinct schemes for belief updating that play out on the same (neuronal) architecture. Technically, we use Forney (normal) factor graphs to characterize the requisite message passing, and link this formal characterization to canonical microcircuits and extrinsic connectivity in the brain.

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