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Solving the problem of negative synaptic weights in cortical models

Summary: Solving the problem of negative synaptic weights in
cortical models
Christopher Parisien,1
Charles H. Anderson,2
Chris Eliasmith3
Dept. of Computer Science, University of Toronto,
Toronto, ON M5S 3G4, Canada
Dept. of Anatomy and Neurobiology, Washington University School of Medicine,
St. Louis, MO 63110, U.S.A.
Centre for Theoretical Neuroscience, University of Waterloo,
Waterloo, ON N2L 3G1, Canada

To whom correspondence should be addressed; E-mail: celiasmith@uwaterloo.ca
In cortical neural networks, connections from a given neuron are either in-
hibitory or excitatory, but not both. This constraint is often ignored by the-
oreticians who build models of these systems. There is currently no general
solution to the problem of converting such unrealistic network models into


Source: Anderson, Charles H. - Departments of Anatomy and Neurobiology & Physics, Washington University in St. Louis


Collections: Computer Technologies and Information Sciences; Biology and Medicine