Dynamic divisive normalization circuits explain and predict change detection in monkey area MT.

Sudden changes in visual scenes often indicate important events for behavior. For their quick and reliable detection, the brain must be capable to process these changes as independently as possible from its current activation state. In motion-selective area MT, neurons respond to instantaneous speed...

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Autores principales:	Udo A Ernst, Xiao Chen, Lisa Bohnenkamp, Fingal Orlando Galashan, Detlef Wegener
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/b56025e1fcbd484dab66918ca0d31a5b
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spelling	oai:doaj.org-article:b56025e1fcbd484dab66918ca0d31a5b2021-12-02T19:58:11ZDynamic divisive normalization circuits explain and predict change detection in monkey area MT.1553-734X1553-735810.1371/journal.pcbi.1009595https://doaj.org/article/b56025e1fcbd484dab66918ca0d31a5b2021-11-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009595https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Sudden changes in visual scenes often indicate important events for behavior. For their quick and reliable detection, the brain must be capable to process these changes as independently as possible from its current activation state. In motion-selective area MT, neurons respond to instantaneous speed changes with pronounced transients, often far exceeding the expected response as derived from their speed tuning profile. We here show that this complex, non-linear behavior emerges from the combined temporal dynamics of excitation and divisive inhibition, and provide a comprehensive mathematical analysis. A central prediction derived from this investigation is that attention increases the steepness of the transient response irrespective of the activation state prior to a stimulus change, and irrespective of the sign of the change (i.e. irrespective of whether the stimulus is accelerating or decelerating). Extracellular recordings of attention-dependent representation of both speed increments and decrements confirmed this prediction and suggest that improved change detection derives from basic computations in a canonical cortical circuitry.Udo A ErnstXiao ChenLisa BohnenkampFingal Orlando GalashanDetlef WegenerPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 11, p e1009595 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Udo A Ernst Xiao Chen Lisa Bohnenkamp Fingal Orlando Galashan Detlef Wegener Dynamic divisive normalization circuits explain and predict change detection in monkey area MT.
description	Sudden changes in visual scenes often indicate important events for behavior. For their quick and reliable detection, the brain must be capable to process these changes as independently as possible from its current activation state. In motion-selective area MT, neurons respond to instantaneous speed changes with pronounced transients, often far exceeding the expected response as derived from their speed tuning profile. We here show that this complex, non-linear behavior emerges from the combined temporal dynamics of excitation and divisive inhibition, and provide a comprehensive mathematical analysis. A central prediction derived from this investigation is that attention increases the steepness of the transient response irrespective of the activation state prior to a stimulus change, and irrespective of the sign of the change (i.e. irrespective of whether the stimulus is accelerating or decelerating). Extracellular recordings of attention-dependent representation of both speed increments and decrements confirmed this prediction and suggest that improved change detection derives from basic computations in a canonical cortical circuitry.
format	article
author	Udo A Ernst Xiao Chen Lisa Bohnenkamp Fingal Orlando Galashan Detlef Wegener
author_facet	Udo A Ernst Xiao Chen Lisa Bohnenkamp Fingal Orlando Galashan Detlef Wegener
author_sort	Udo A Ernst
title	Dynamic divisive normalization circuits explain and predict change detection in monkey area MT.
title_short	Dynamic divisive normalization circuits explain and predict change detection in monkey area MT.
title_full	Dynamic divisive normalization circuits explain and predict change detection in monkey area MT.
title_fullStr	Dynamic divisive normalization circuits explain and predict change detection in monkey area MT.
title_full_unstemmed	Dynamic divisive normalization circuits explain and predict change detection in monkey area MT.
title_sort	dynamic divisive normalization circuits explain and predict change detection in monkey area mt.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/b56025e1fcbd484dab66918ca0d31a5b
work_keys_str_mv	AT udoaernst dynamicdivisivenormalizationcircuitsexplainandpredictchangedetectioninmonkeyareamt AT xiaochen dynamicdivisivenormalizationcircuitsexplainandpredictchangedetectioninmonkeyareamt AT lisabohnenkamp dynamicdivisivenormalizationcircuitsexplainandpredictchangedetectioninmonkeyareamt AT fingalorlandogalashan dynamicdivisivenormalizationcircuitsexplainandpredictchangedetectioninmonkeyareamt AT detlefwegener dynamicdivisivenormalizationcircuitsexplainandpredictchangedetectioninmonkeyareamt
_version_	1718375797419409408

Dynamic divisive normalization circuits explain and predict change detection in monkey area MT.

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