Effect of Synaptic Loss on Memory in a Neural Network Model

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.