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Associative Memory in a Multimodular Network
1999
Neural Computation
Recent imaging studies suggest that object knowledge is stored in the brain as a distributed network of many cortical areas. Motivated by these observations, we study a multi-modular associative memory network, whose functional goal is to store patterns with di erent coding levels, i.e., patterns that vary in the number of modules in which they are encoded. We show that in order to accomplish this task, synaptic inputs should be segregated into intra-modular projections and inter-modular
doi:10.1162/089976699300016205
pmid:10490944
fatcat:icbsfqg7cve4nbzewk2wl3fwiq