Effect of Synaptic Loss on Memory in a Neural Network Model.
- Author:
In Song KOH
1
;
Jeong Wook PARK
;
Byung Keol CHOI
;
Chang Keun KIM
;
Sun Hee YOON
Author Information
1. Department of Biomedical Science, Division of Degenerative Diseases, National Institute of Health, Korea.
- Publication Type:Original Article
- Keywords:
Alzheimer's disease;
Computer model;
Neural network;
Synapse;
Memory impairment
- MeSH:
Alzheimer Disease;
Computer Simulation;
Memory*;
Neural Networks (Computer)*;
Synapses
- From:Journal of the Korean Neurological Association
2000;18(1):44-49
- CountryRepublic of Korea
- Language:Korean
-
Abstract:
BACKGROUND: In order to understand the pathogenesis and symptom development in Alzheimer's disease (AD), we attempted to develop a computer model for memory impairment in this study. METHODS: We made a simple autoassocia-tive memory network, first developed by Hopfield, which remembers numbers or patterns, transformed it into an AD model by pruning synapses, and measured its memory performance as a function of synaptic deletion. RESULTS: Decline in memory performance was measured as amount of synaptic loss increased and its mode of decline varied with different synaptic pruning methods. CONCLUSIONS: The developed computer model demonstrated how synaptic loss could cause memory impairment through a series of computer simulations, and suggested a new way of research in AD.
