Material Type  

 학위논문

 

0016932562

Date and Time of Latest Transaction  

20240214100514

ISBN  

9798379678128

DDC  

591

Author  

Zirkle, Joel.

Title/Author  

Modeling Temporal Patterns of Neural Synchronization: Synaptic Plasticity and Stochastic Mechanisms - [electronic resource]

Publish Info  

[S.l.] : Purdue University., 2020

Publish Info  

Ann Arbor : ProQuest Dissertations & Theses, 2020

Material Info  

1 online resource(89 p.)

General Note  

Source: Dissertations Abstracts International, Volume: 84-12, Section: B.

General Note  

Advisor: Rubchinsky, Leonid.

학위논문주기  

Thesis (Ph.D.)--Purdue University, 2020.

Restrictions on Access Note  

This item must not be sold to any third party vendors.

Abstracts/Etc  

요약Neural synchrony in the brain at rest is usually variable and intermittent, thus intervals of predominantly synchronized activity are interrupted by intervals of desynchronized activity. Prior studies suggested that this temporal structure of the weakly synchronous activity might be functionally significant: many short desynchronizations may be functionally different from few long desynchronizations, even if the average synchrony level is the same. In this thesis, we use computational neuroscience methods to investigate the effects of (i) spike-timing dependent plasticity (STDP) and (ii) noise on the temporal patterns of synchronization in a simple model. The model is composed of two conductance-based neurons connected via excitatory unidirectional synapses. In (i) these excitatory synapses are made plastic, in (ii) two different types of noise implementation to model the stochasticity of membrane ion channels is considered. The plasticity results are taken from our recently published article [47], while the noise results are currently being compiled into a manuscript.The dynamics of this network is subjected to the time-series analysis methods used in prior experimental studies. We provide numerical evidence that both STDP and channel noise can alter the synchronized dynamics in the network in several ways. This depends on the time scale that plasticity acts on and the intensity of the noise. However, in general, the action of STDP and noise in the simple network considered here is to promote dynamics with short desynchronizations (i.e. dynamics reminiscent of that observed in experimental studies) over dynamics with longer desynchronizations.

Subject Added Entry-Topical Term  

Neurons.

Subject Added Entry-Topical Term  

Potassium.

Subject Added Entry-Topical Term  

Mathematical models.

Subject Added Entry-Topical Term  

Sodium.

Subject Added Entry-Topical Term  

Ions.

Subject Added Entry-Topical Term  

Ordinary differential equations.

Subject Added Entry-Topical Term  

Mathematics.

Added Entry-Corporate Name  

Purdue University.

Host Item Entry  

Dissertations Abstracts International. 84-12B.

Host Item Entry  

Dissertation Abstract International

Electronic Location and Access  

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소장사항  

202402 2024

Control Number  

joongbu:641392