Year: 2002
Type: conference-paper
Abstract: Inference and adaptation in noisy and changing, rich sensory environments are rife with a variety of specific sorts of variability.Experimental and theoretical studies suggest that these different forms of variability play different behavioral, neural and computational roles, and may be reported by different (notably neuromodulatory) systems.Here, we refine our previous theory of acetylcholine's role in cortical inference in the (oxymoronic) terms of expected uncertainty, and advocate a theory for norepinephrine in terms of unexpected uncertainty.We suggest that norepinephrine reports the radical divergence of bottom-up inputs from prevailing top-down interpretations, to influence inference and plasticity.We illustrate this proposal using an adaptive factor analysis model.
Authors: Peter Dayan, Angela J. Yu
Institution: Gatsby Computational Neuroscience Unit
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
Funder: National Science Foundation
OpenAlex ID: W2108393070