Multi-Modular Associative Memory
Abstract
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.
Cite
Text
Levy et al. "Multi-Modular Associative Memory." Neural Information Processing Systems, 1997.Markdown
[Levy et al. "Multi-Modular Associative Memory." Neural Information Processing Systems, 1997.](https://mlanthology.org/neurips/1997/levy1997neurips-multimodular/)BibTeX
@inproceedings{levy1997neurips-multimodular,
title = {{Multi-Modular Associative Memory}},
author = {Levy, Nir and Horn, David and Ruppin, Eytan},
booktitle = {Neural Information Processing Systems},
year = {1997},
pages = {52-58},
url = {https://mlanthology.org/neurips/1997/levy1997neurips-multimodular/}
}