東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Rapid Modulation of Dynamics and Com...

Pang, Rich.

FindBook

Google Book

Amazon

博客來

Rapid Modulation of Dynamics and Computation in Neural Systems.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Rapid Modulation of Dynamics and Computation in Neural Systems./
作者:	Pang, Rich.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:	188 p.
附註:	Source: Dissertations Abstracts International, Volume: 80-10, Section: B.
Contained By:	Dissertations Abstracts International80-10B.
標題:	Neurosciences. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13808067
ISBN:	9781392070352

Rapid Modulation of Dynamics and Computation in Neural Systems.
Pang, Rich.

Rapid Modulation of Dynamics and Computation in Neural Systems. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 188 p.

Source: Dissertations Abstracts International, Volume: 80-10, Section: B.

Thesis (Ph.D.)--University of Washington, 2019.

This item must not be added to any third party search indexes.

A central goal in theoretical neuroscience is to understand how neural systems perform computations over the continuum of timescales that underlie behavior. In particular, what are the algorithms and mechanisms enabling single-neuron membrane voltage fluctuations, which occur over milliseconds, to produce the dynamics and information processing in behavior that unfold over hours to years? Notably, while the core ionic processes of membrane voltage fluctuations have been largely elucidated and while extensive theories and evidence exist to explain how slow modulation of neural network structures might underlie learning, almost nothing is known about the liminal regime of seconds to minutes that bridges these two timescales. In the work that follows I address three questions in three different systems, each of which centers around neural computations occurring over the timescales of seconds to minutes. I first investigate the navigational decisions made by flying insects during odor tracking, where I show that fruit flies and mosquitoes exhibit a history dependence in their odor-triggered turning responses that is qualitatively similar to an information-maximizing tracking strategy, but not to others. Next, in collaboration with Ari Zolin, Raphael Cohn, and Vanessa Ruta, I analyze the dynamics of dopaminergic neuromodulation of a short-term memory circuit in the fruit fly mushroom body, where we suggest that the fly dopamine system encodes multiplexed representations of a wide diversity of sensory, motor, and valence signals, some of which predict behavior several seconds in the future. Third, I develop a spiking neural network model capable of storing and replaying sequential activity patterns using a heterosynaptic and fast-acting biological plasticity rule, and which reconstructs sequences through the existing recurrent network structure. Collectively, these results elucidate the computational capacities of three distinct systems and shed new light on short-term information processing in neural computations from three novel angles. Finally, in collaboration with Sid Henriksen and Mark Wronkiewicz, I describe a simple network-growth model reproducing several statistical features of mouse brain network connectivity at the mesoscale; while this work does not explicitly address short-term computations, simplified statistical network models will be crucial to eventually understanding how such computations occur within large scale distributed brain networks.

ISBN: 9781392070352Subjects--Topical Terms:

588700
Neurosciences.

Rapid Modulation of Dynamics and Computation in Neural Systems.
LDR:03642nmm a2200337 4500 001 2210727
005 20191121124303.5
008 201008s2019 ||||||||||||||||| ||eng d
020 $a 9781392070352
035 $a (MiAaPQ)AAI13808067
035 $a (MiAaPQ)washington:19673
035 $a AAI13808067
040 $a MiAaPQ $c MiAaPQ
100 1 $a Pang, Rich. $3 3437863
245 1 0 $a Rapid Modulation of Dynamics and Computation in Neural Systems.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2019
300 $a 188 p.
500 $a Source: Dissertations Abstracts International, Volume: 80-10, Section: B.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Fairhall, Adrienne L.
502 $a Thesis (Ph.D.)--University of Washington, 2019.
506 $a This item must not be added to any third party search indexes.
506 $a This item must not be sold to any third party vendors.
520 $a A central goal in theoretical neuroscience is to understand how neural systems perform computations over the continuum of timescales that underlie behavior. In particular, what are the algorithms and mechanisms enabling single-neuron membrane voltage fluctuations, which occur over milliseconds, to produce the dynamics and information processing in behavior that unfold over hours to years? Notably, while the core ionic processes of membrane voltage fluctuations have been largely elucidated and while extensive theories and evidence exist to explain how slow modulation of neural network structures might underlie learning, almost nothing is known about the liminal regime of seconds to minutes that bridges these two timescales. In the work that follows I address three questions in three different systems, each of which centers around neural computations occurring over the timescales of seconds to minutes. I first investigate the navigational decisions made by flying insects during odor tracking, where I show that fruit flies and mosquitoes exhibit a history dependence in their odor-triggered turning responses that is qualitatively similar to an information-maximizing tracking strategy, but not to others. Next, in collaboration with Ari Zolin, Raphael Cohn, and Vanessa Ruta, I analyze the dynamics of dopaminergic neuromodulation of a short-term memory circuit in the fruit fly mushroom body, where we suggest that the fly dopamine system encodes multiplexed representations of a wide diversity of sensory, motor, and valence signals, some of which predict behavior several seconds in the future. Third, I develop a spiking neural network model capable of storing and replaying sequential activity patterns using a heterosynaptic and fast-acting biological plasticity rule, and which reconstructs sequences through the existing recurrent network structure. Collectively, these results elucidate the computational capacities of three distinct systems and shed new light on short-term information processing in neural computations from three novel angles. Finally, in collaboration with Sid Henriksen and Mark Wronkiewicz, I describe a simple network-growth model reproducing several statistical features of mouse brain network connectivity at the mesoscale; while this work does not explicitly address short-term computations, simplified statistical network models will be crucial to eventually understanding how such computations occur within large scale distributed brain networks.
590 $a School code: 0250.
650 4 $a Neurosciences. $3 588700
650 4 $a Applied Mathematics. $3 1669109
690 $a 0317
690 $a 0364
710 2 $a University of Washington. $b Physiology and Biophysics. $3 3437864
773 0 $t Dissertations Abstracts International $g 80-10B.
790 $a 0250
791 $a Ph.D.
792 $a 2019
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13808067