A computationally efficient associative memory model of hippocampus CA3 by spiking neurons

The hippocampus is involved with the storage and retrieval of short-term associative memories. In this paper, we propose a computationally efficient associative memory model of the hippocampus CA3 region by spiking neurons, and explores the storage of auto-associative memory. The spiking neural network encodes different associative memories by different subsets of the principal neurons. These memory items are activated in different gamma subcycles, and auto-associative memory is maintained by the synaptic modifications of recurrent collaterals by N-methyl-D-aspartate (NMDA) channels. Accurate formation of auto-associative memory is achievable in single presentation of memory items when synaptic modifications depend on fast NMDA channels having a deactivation time within the duration of a gamma subcycle. Simulation results also show that spike response model (SRM) improves computational efficiency over the integrate-and-fire (I&F) neuron model.