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Vigilance, arousal, and acetylcholine: Optimal control of attention in a simple detection task

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dc.contributor.author CHEBOLU, SAHITI en_US
dc.contributor.author Dayan, Peter en_US
dc.contributor.author Lloyd, Kevin en_US
dc.date.accessioned 2023-02-28T10:46:14Z
dc.date.available 2023-02-28T10:46:14Z
dc.date.issued 2022-10 en_US
dc.identifier.citation PLOS Computational Biology, 18(10), e1010642. en_US
dc.identifier.issn 1553-734X en_US
dc.identifier.issn 1553-7358 en_US
dc.identifier.uri https://doi.org/10.1371/journal.pcbi.1010642 en_US
dc.identifier.uri http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/7636
dc.description.abstract Paying attention to particular aspects of the world or being more vigilant in general can be interpreted as forms of ‘internal’ action. Such arousal-related choices come with the benefit of increasing the quality and situational appropriateness of information acquisition and processing, but incur potentially expensive energetic and opportunity costs. One implementational route for these choices is widespread ascending neuromodulation, including by acetylcholine (ACh). The key computational question that elective attention poses for sensory processing is when it is worthwhile paying these costs, and this includes consideration of whether sufficient information has yet been collected to justify the higher signal-to-noise ratio afforded by greater attention and, particularly if a change in attentional state is more expensive than its maintenance, when states of heightened attention ought to persist. We offer a partially observable Markov decision-process treatment of optional attention in a detection task, and use it to provide a qualitative model of the results of studies using modern techniques to measure and manipulate ACh in rodents performing a similar task. en_US
dc.language.iso en en_US
dc.publisher PUBLIC LIBRARY SCIENCE en_US
dc.subject Biology en_US
dc.subject 2022 en_US
dc.title Vigilance, arousal, and acetylcholine: Optimal control of attention in a simple detection task en_US
dc.type Article en_US
dc.contributor.department Dept. of Physics 
dc.identifier.sourcetitle PLOS Computational Biology en_US
dc.publication.originofpublisher Foreign en_US


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