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  Dynamic analysis of disease progression in Alzheimer’s disease under the influence of hybrid synapse and spatially correlated noise

Wang, W., He, C., Wang, Z., Cheng, J., Mo, X., Tian, K., Fan, D., Luo, X., Yuan, M., Kurths, J. (2021): Dynamic analysis of disease progression in Alzheimer’s disease under the influence of hybrid synapse and spatially correlated noise. - Neurocomputing, 456, 23-35.
https://doi.org/10.1016/j.neucom.2021.05.067

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Wang, Weiping1, Autor
He, Chang1, Autor
Wang, Zhen1, Autor
Cheng, Jun1, Autor
Mo, Xishuo1, Autor
Tian, Kuo1, Autor
Fan, Denggui1, Autor
Luo, Xiong1, Autor
Yuan, Manman1, Autor
Kurths, Jürgen2, Autor              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Zusammenfassung: Alzheimer’s disease (AD), characterized by cognitive impairment, mainly affects middle-aged and elderly people. As the aging process of the world continues to intensify, AD harms people’s life, economy and society more and more seriously. Therefore, it has become an urgent problem to study the pathogenesis of AD and seek treatment on this basis. Hybrid synapse, autapse and spatial correlated noise in diverse neural activities have been investigated separately, however, theoretically understanding combination of them still has not been fully studied. Here in this paper, a neural network with multiple associative memory abilities is established from the perspective of the degeneration of associative memory ability in AD patients under the conditions of hybrid synapse, autapse and spatial correlated noise. In order to explore the pathogenesis, a synaptic loss and synaptic compensation model are established to analyze the associative memory ability of AD in different degrees of disease. The simulation results demonstrate the effectiveness of the proposed models and pave a way in the study of dynamic mechanism with higher bio-interpretability in neural networks.

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 Datum: 2021-10
 Publikationsstatus: Final veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1016/j.neucom.2021.05.067
MDB-ID: No data to archive
Research topic keyword: Complex Networks
Research topic keyword: Health
Research topic keyword: Nonlinear Dynamics
Model / method: Nonlinear Data Analysis
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
 Art des Abschluß: -

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Titel: Neurocomputing
Genre der Quelle: Zeitschrift, SCI, Scopus
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Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 456 Artikelnummer: - Start- / Endseite: 23 - 35 Identifikator: Publisher: Elsevier
CoNE: https://publications.pik-potsdam.de/cone/journals/resource/neurocomputing