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  Controlling Alzheimer’s Disease Through the Deep Brain Stimulation to Thalamic Relay Cells

Yang, X., Zhang, R., Sun, Z., Kurths, J. (2021): Controlling Alzheimer’s Disease Through the Deep Brain Stimulation to Thalamic Relay Cells. - Frontiers in Computational Neuroscience, 15, 636770.
https://doi.org/10.3389/fncom.2021.636770

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 Creators:
Yang, XiaoLi1, Author
Zhang, RuiXi1, Author
Sun, ZhongKui1, Author
Kurths, Jürgen2, Author              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: Experimental and clinical studies have shown that the technique of deep brain stimulation (DBS) plays a potential role in the regulation of Alzheimer’s disease (AD), yet it still desires for ongoing studies including clinical trials, theoretical approach and action mechanism. In this work, we develop a modified thalamo-cortico-thalamic (TCT) model associated with AD to explore the therapeutic effects of DBS on AD from the perspective of neurocomputation. First, the neuropathological state of AD resulting from synapse loss is mimicked by decreasing the synaptic connectivity strength from the Inter-Neurons (IN) neuron population to the Thalamic Relay Cells (TRC) neuron population. Under such AD condition, a specific deep brain stimulation voltage is then implanted into the neural nucleus of TRC in this TCT model. The symptom of AD is found significantly relieved by means of power spectrum analysis and nonlinear dynamical analysis. Furthermore, the therapeutic effects of DBS on AD are systematically examined in different parameter space of DBS. The results demonstrate that the controlling effect of DBS on AD can be efficient by appropriately tuning the key parameters of DBS including amplitude A, period P and duration D. This work highlights the critical role of thalamus stimulation for brain disease, and provides a theoretical basis for future experimental and clinical studies in treating AD.

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Language(s): eng - English
 Dates: 2021-11-082021-11
 Publication Status: Finally published
 Pages: 16
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.3389/fncom.2021.636770
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Complex Networks
Research topic keyword: Health
Model / method: Nonlinear Data Analysis
OATYPE: Gold Open Access
 Degree: -

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Title: Frontiers in Computational Neuroscience
Source Genre: Journal, SCI, Scopus, oa
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Pages: - Volume / Issue: 15 Sequence Number: 636770 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/frontiers-computational-neuroscience
Publisher: Frontiers