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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
1
Dept. of Computer Science, University of Toronto,
Toronto, ON M5S 3G4, Canada
2
Dept. of Anatomy and Neurobiology, Washington University School of Medicine,
St. Louis, MO 63110, U.S.A.
3
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