Departmental Papers (BE)

Document Type

Conference Paper

Date of this Version

July 2004


We describe a neuromorphic chip designed to model active dendrites, recurrent connectivity, and plastic synapses to support one-shot learning. Specifically, it is designed to capture neural firing patterns (short-term memory), memorize individual patterns (long-term memory), and retrive them when primed (associative recall). It consists of a recurrently connected population of excitatory pyramidal cells and a recurrently connected population of inhibitory basket cells. In addition to their recurrent connections, the excitatory and inhibitory populations are reciprocally connected. The model is novel in that it utilizes recurrent connections and active dendrites to maintain short-term memories as well as to store long-term memories.


Copyright 2004 IEEE. Reprinted from Proceedings of the 2004 IEEE International Joint Conference on Neural Networks, Volume 3, pages 1699-1704.

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Date Posted: 22 November 2005