Departmental Papers (BE)

Document Type

Conference Paper

Date of this Version

December 2002


We describe a self-configuring neuromorphic chip that uses a model of activity-dependent axon remodeling to automatically wire topographic maps based solely on input correlations. Axons are guided by growth cones, which are modeled in analog VLSI for the first time. Growth cones migrate up neurotropin gradients, which are represented by charge diffusing in transistor channels. Virtual axons move by rerouting address-events. We refined an initially gross topographic projection by simulating retinal wave input.


Advances in Neural Information Processing Systems 15 (NIPS 2002), pages 1163-1170.
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Date Posted: 11 November 2004

This document has been peer reviewed.