Acetylcholine and Cortical Inference
Angela Yu & Peter Dayan
Submitted to Neural Networks
Abstract
Acetylcholine (ACh) plays an important role in a wide variety of
cognitive tasks, such as perception, selective attention,
associative learning, and memory. Extensive experimental and
theoretical work in tasks involving learning and memory has
suggested that ACh reports on unfamiliarity and controls plasticity
and effective network connectivity. Based on these computational
and mechanistic insights, we develop a theory of cholinergic
modulation in perceptual inference. We propose that ACh levels
reflect the uncertainty associated with top-down information,
and have the effect of modulating the interaction between top-down
and bottom-up processing in determining the appropriate neural
representations for inputs. We illustrate our proposal by means of an
hierarchical hidden Markov model, showing that cholinergic
modulation of contextual information leads to appropriate perceptual
inference.
compressed postscript
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