Neurocomputational mechanisms of prior-informed perceptual decision-making in humans

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Title: Neurocomputational mechanisms of prior-informed perceptual decision-making in humans
Authors: Kelly, Simon P.Corbett, Elaine A.O'Connell, Redmond G.
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Date: 1-Apr-2021
Online since: 2022-02-28T11:53:43Z
Abstract: To interact successfully with diverse sensory environments, we must adapt our decision processes to account for time constraints and prior probabilities. The full set of decision-process parameters that undergo such flexible adaptation has proven to be difficult to establish using simplified models that are based on behaviour alone. Here, we utilize well-characterized human neurophysiological signatures of decision formation to construct and constrain a build-to-threshold decision model with multiple build-up (evidence accumulation and urgency) and delay components (pre- and post-decisional). The model indicates that all of these components were adapted in distinct ways and, in several instances, fundamentally differ from the conclusions of conventional diffusion modelling. The neurally informed model outcomes were corroborated by independent neural decision signal observations that were not used in the model’s construction. These findings highlight the breadth of decision-process parameters that are amenable to strategic adjustment and the value in leveraging neurophysiological measurements to quantify these adjustments.
Funding Details: European Commission Horizon 2020
Irish Research Council
Science Foundation Ireland
Funding Details: U.S. National Science Foundation
Type of material: Journal Article
Publisher: Nature Research
Journal: Nature Human Behaviour
Volume: 5
Issue: 4
Start page: 467
End page: 481
Keywords: HumansAffectDecision makingChoice behaviorPsychomotor performanceReaction timeNeurological models
DOI: 10.1038/s41562-020-00967-9
Language: en
Status of Item: Peer reviewed
ISSN: 2397-3374
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