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Neurocomputational mechanisms of prior-informed perceptual decision-making in humans
Date Issued
2021-04-01
Date Available
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.
Sponsorship
European Commission Horizon 2020
Irish Research Council
Science Foundation Ireland
Other Sponsorship
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
Language
English
Status of Item
Peer reviewed
ISSN
2397-3374
This item is made available under a Creative Commons License
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