Dynamic analysis of synaptic loss and synaptic compensation in the process of associative memory ability decline in Alzheimer’s disease

Weiping Wang, Chang He, Zhen Wang, Alexander Hramov, Denggui Fan, Manman Yuan, Xiong Luo and Jürgen Kurths

Applied Mathematics and Computation, 2021, vol. 408, issue C

Abstract: The cognitive decline caused by Alzheimer’s disease (AD) has a great impact on the life of patients and their families. Modern medicine has shown that loss of synaptic function is one of the causes of AD, and synaptic compensation compensates for cognitive abilities of the human brain. However, there are no studies on the internal mechanism of synaptic loss and synaptic compensation affecting human cognitive ability. In order to solve this problem, we propose here a three-layer neural network with multiple associative memory abilities, which is one of the main cognitive abilities. Based on synaptic plasticity, models of synaptic loss and synaptic compensation are established to study the pathogenesis of the degeneration of associative memory and explore feasible treatment approaches by setting different degrees of loss and compensation. Our simulation results show that the model can describe the associative memory ability at different stages of AD, which is of great significance for paramedics to determine the stage of disease and develop effective treatment strategies.

Keywords: Associative memory neural network; Synaptic plasticity; Synapse loss; Synapse compensation (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:408:y:2021:i:c:s0096300321004616

DOI: 10.1016/j.amc.2021.126372

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