Multi-modular Associative Memory

Part of Advances in Neural Information Processing Systems 10 (NIPS 1997)

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Nir Levy, David Horn, Eytan Ruppin


Motivated by the findings of modular structure in the association cortex, we study a multi-modular model of associative memory that can successfully store memory patterns with different levels of ac(cid:173) tivity. We show that the segregation of synaptic conductances into intra-modular linear and inter-modular nonlinear ones considerably enhances the network's memory retrieval performance. Compared with the conventional, single-module associative memory network, the multi-modular network has two main advantages: It is less sus(cid:173) ceptible to damage to columnar input, and its response is consistent with the cognitive data pertaining to category specific impairment.