Please use this identifier to cite or link to this item: http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/7636
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dc.contributor.authorCHEBOLU, SAHITIen_US
dc.contributor.authorDayan, Peteren_US
dc.contributor.authorLloyd, Kevinen_US
dc.date.accessioned2023-02-28T10:46:14Z
dc.date.available2023-02-28T10:46:14Z
dc.date.issued2022-10en_US
dc.identifier.citationPLOS Computational Biology, 18(10), e1010642.en_US
dc.identifier.issn1553-734Xen_US
dc.identifier.issn1553-7358en_US
dc.identifier.urihttps://doi.org/10.1371/journal.pcbi.1010642en_US
dc.identifier.urihttp://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/7636
dc.description.abstractPaying 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.isoenen_US
dc.publisherPUBLIC LIBRARY SCIENCEen_US
dc.subjectBiologyen_US
dc.subject2022en_US
dc.titleVigilance, arousal, and acetylcholine: Optimal control of attention in a simple detection tasken_US
dc.typeArticleen_US
dc.contributor.departmentDept. of Physics 
dc.identifier.sourcetitlePLOS Computational Biologyen_US
dc.publication.originofpublisherForeignen_US
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