Effect of Synaptic Loss on Memory in a Neural Network Model

J Korean Neurol Assoc > Volume 18(1); 2000 > Article

Journal of the Korean Neurological Association 2000;18(1): 44-49.

신경망 모델에서 시냅스 소실이 기억력에 미치는 효과

고인송, 박정욱 ·최병걸 ·김창근 ·윤선희

국립보건원 특수질환부 퇴행성질환과 국립보건원 뇌의약학연구센터 수리신경과학 연구팀

Effect of Synaptic Loss on Memory in a Neural Network Model

InSong Koh, M.D., JeongWook Park, M.D., ByungKeol Choi, M.S., ChangKeun Kim, M.S., SunHee Yoon, M.S.

Department of Biomedical Science, Division of Degenerative Diseases, National Institute of Health, Korea Biomedical Brain Research Center, Lab. Of Computational Neuroscience, National Institute of Health, Korea

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. J Korean Neurol Assoc 18(1):44~49, 2000 Key Words : Alzheimer’s disease, Computer model, Neural network, Synapse, Memory impairment