Hippocampus as unitary coherent particle filter

Abstract

We present a mapping of the hippocampal formation onto a Temporal Restricted Boltzmann Machine [1] based architecture, running a deterministic version of Gibbs sampling, and extended with a lostness detection and recovery circuit modelled on subiculum and septal acetylcholine (ACh). The mapping approximates Bayesian filtering, which infers both auto-associative de-noised percepts and temporal sequences, the latter including sequences of places during navigation. Inference may be viewed as a neurally implemented particle filter with a single particle-as suggested previously [2] as a purely behavioural animal model

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