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Exploring the Many Scales of Neural ...
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Benson, Brandon,
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Exploring the Many Scales of Neural Activity Underlying Perception and Decision Making /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Exploring the Many Scales of Neural Activity Underlying Perception and Decision Making // Brandon Benson.
作者:
Benson, Brandon,
面頁冊數:
1 electronic resource (170 pages)
附註:
Source: Dissertations Abstracts International, Volume: 85-07, Section: B.
Contained By:
Dissertations Abstracts International85-07B.
標題:
Neurons. -
電子資源:
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30726767
ISBN:
9798381018318
Exploring the Many Scales of Neural Activity Underlying Perception and Decision Making /
Benson, Brandon,
Exploring the Many Scales of Neural Activity Underlying Perception and Decision Making /
Brandon Benson. - 1 electronic resource (170 pages)
Source: Dissertations Abstracts International, Volume: 85-07, Section: B.
Experimental technologies that probe neural circuits from single neuron to brain-wide scales have allowed us to deepen our understanding of neural phenomena ranging from perception to decision making. For example in visual perception, orientation tuning in primary visual cortex (V1) has long been thought to play an important functional role in perception, but tests of this role have only recently been made possible through direct optogenetic stimulation of mouse cortex. Indeed, optogenetic stimulation reveals that a surprisingly small number of excited neurons (~20) can drive both large-scale neural ensembles (~1000) and perception. We develop a mean field neural circuit theory for how such small stimulation can create large responses. Our theory also explains constraints on avalanche like behavior widely observed in the spontaneous activity of many species. We further study decision-making at a global-brain scale leveraging multi-region neuropixel recordings collected across a collaboration of 11 experimental labs (part of "the International Brain Lab" (IBL)). We analyzed a massive dataset consisting of the neural activity of 300,000 neurons in mice performing a decision making task and developed techniques to elucidate the contribution of many different brain regions to decision making. Through decoding analyses, we discovered that task and behavioral variables can be decoded from regions which are both classically known as well as other regions which are functionally surprising. Overall, through theoretical analysis of unprecedented datasets, we propose a mechanism for perception in V1 and uncover region-specific details of brain-wide activity underlying decision making.
English
ISBN: 9798381018318Subjects--Topical Terms:
588699
Neurons.
Exploring the Many Scales of Neural Activity Underlying Perception and Decision Making /
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Experimental technologies that probe neural circuits from single neuron to brain-wide scales have allowed us to deepen our understanding of neural phenomena ranging from perception to decision making. For example in visual perception, orientation tuning in primary visual cortex (V1) has long been thought to play an important functional role in perception, but tests of this role have only recently been made possible through direct optogenetic stimulation of mouse cortex. Indeed, optogenetic stimulation reveals that a surprisingly small number of excited neurons (~20) can drive both large-scale neural ensembles (~1000) and perception. We develop a mean field neural circuit theory for how such small stimulation can create large responses. Our theory also explains constraints on avalanche like behavior widely observed in the spontaneous activity of many species. We further study decision-making at a global-brain scale leveraging multi-region neuropixel recordings collected across a collaboration of 11 experimental labs (part of "the International Brain Lab" (IBL)). We analyzed a massive dataset consisting of the neural activity of 300,000 neurons in mice performing a decision making task and developed techniques to elucidate the contribution of many different brain regions to decision making. Through decoding analyses, we discovered that task and behavioral variables can be decoded from regions which are both classically known as well as other regions which are functionally surprising. Overall, through theoretical analysis of unprecedented datasets, we propose a mechanism for perception in V1 and uncover region-specific details of brain-wide activity underlying decision making.
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