國立高雄大學圖資館 |

Language: English

Back

Neural oscillators and integrators in the dynamics of decision tasks

Record Type:	Electronic resources : Monograph/item
Title/Author:	Neural oscillators and integrators in the dynamics of decision tasks
Author:	Brown, Eric T.
Description:	183 p.
Notes:	Adviser: Philip Holmes.
Notes:	Source: Dissertation Abstracts International, Volume: 65-02, Section: B, page: 0775.
Contained By:	Dissertation Abstracts International65-02B.
Subject:	Mathematics.
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3123416
ISBN:	0496707272

Neural oscillators and integrators in the dynamics of decision tasks
Brown, Eric T.

Neural oscillators and integrators in the dynamics of decision tasks [electronic resource] - 183 p.

Adviser: Philip Holmes.

Thesis (Ph.D.)--Princeton University, 2004.

First, I study and apply nonlinear oscillator dynamics. I develop and extend phase reductions for single compartment ordinary differential equation neuron models that show how both type of, and distance from, the four codimension-one bifurcations to periodic firing affect responses of neural populations to stimuli. I also extend results from equivariant dynamics which describe how coupling functions determine the existence and stability of phase-locked states in which subgroups of oscillators are synchronized. These results are then applied to the firing rate dynamics of the locus coeruleus (LC) brainstem nucleus, thereby characterizing the inputs that drive the LC and suggesting a new biophysical mechanism for transitions among LC-mediated states of cognitive performance.

ISBN: 0496707272Subjects--Topical Terms:

184409
Mathematics.

Neural oscillators and integrators in the dynamics of decision tasks
LDR:03497nmm _2200301 _450 001 162464
005 20051017073449.5
008 230606s2004 eng d
020 $a 0496707272
035 $a 00148965
035 $a 162464
040 $a UnM $c UnM
100 0 $a Brown, Eric T. $3 227603
245 1 0 $a Neural oscillators and integrators in the dynamics of decision tasks $h [electronic resource]
300 $a 183 p.
500 $a Adviser: Philip Holmes.
500 $a Source: Dissertation Abstracts International, Volume: 65-02, Section: B, page: 0775.
502 $a Thesis (Ph.D.)--Princeton University, 2004.
520 # $a First, I study and apply nonlinear oscillator dynamics. I develop and extend phase reductions for single compartment ordinary differential equation neuron models that show how both type of, and distance from, the four codimension-one bifurcations to periodic firing affect responses of neural populations to stimuli. I also extend results from equivariant dynamics which describe how coupling functions determine the existence and stability of phase-locked states in which subgroups of oscillators are synchronized. These results are then applied to the firing rate dynamics of the locus coeruleus (LC) brainstem nucleus, thereby characterizing the inputs that drive the LC and suggesting a new biophysical mechanism for transitions among LC-mediated states of cognitive performance.
520 # $a In this dissertation I develop both general results on the dynamics of neural oscillators and integrators and specific applications of these results to brain areas involved in simple cognitive tasks. The scientific motivation is broad: neural networks inside our brains are able to adapt to changing information processing demands by exercising cognitive control, for example focussing on salient components of noisy sensory inputs when making specific decisions based on these inputs, but relaxing this focus when other needs become prominent. But what free variables or parameters can account for the observed adaptability? And does this adaptation occur optimally, with respect to simple economic metrics and physiological limitations? Here I address these questions via reduced models of neurons and populations near bifurcations, which characterize the dynamics of a brainstem nucleus involved in adaptive cognitive control, and via variational problems arising from neural signal processing, which clarify the role of this nucleus, and other dynamical mechanisms in decision tasks.
520 # $a LC-driven neuromodulation transiently adjusts the sensitivity ("gain") of integrator units believed to determine simple cognitive decisions in response to sensory stimuli, and these gain effects are the focus of the second part of this dissertation. I study how transient parameter adjustments can optimize decision tasks for speed and accuracy in the presence of noise. The results indicate a surprising match between empirical data on the time course of LC firing rates and optimal gain trajectories found via variational methods, providing an explicit hypothesis for the role of the LC in decision tasks.
590 $a School code: 0181.
650 # 0 $a Mathematics. $3 184409
650 # 0 $a Biology, Neuroscience. $3 226972
690 $a 0317
690 $a 0405
710 0 # $a Princeton University. $3 212488
773 0 # $g 65-02B. $t Dissertation Abstracts International
790 $a 0181
790 1 0 $a Holmes, Philip, $e advisor
791 $a Ph.D.
792 $a 2004
856 4 0 $u http://libsw.nuk.edu.tw/login?url=http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3123416 $z http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3123416