A Model for Real-Time Computation in Generic Neural Microcircuits

A key challenge for neural modeling is to explain how a continuous stream of multi-modal input from a rapidly changing environment can be processed by stereotypical recurrent circuits of integrate-and-fire neurons in real-time. We propose a new computational model that is based on principles of high dimensional dynamical systems in combination with statistical learning theory. It can be implemented on generic evolved or found recurrent circuitry


Presented at:
NIPS 2002, Vancouver, British Columbia, December 12-14, 2002
Year:
2003
Publisher:
MIT Press
Laboratories:




 Record created 2008-02-27, last modified 2018-01-28


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