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Neural Computation, Vol 10, 451-465, Copyright © 1998 by The MIT Press


LETTERS

Synaptic Runaway In Associative Networks And The Pathogenesis Of Schizophrenia

Asnat Greenstein-Messica and Eytan Ruppin

Synaptic runaway denotes the formation of erroneous synapses and premature functional decline accompanying activity-dependent learning in neural networks. This work studies synaptic runaway both analytically and numerically in binary-firing associative memory networks. It turns out that synaptic runaway is of fairly moderate magnitude in these networks under normal, baseline conditions. However, it may become extensive if the threshold for Hebbian learning is reduced. These findings are combined with recent evidence for arrested N-methyl-D-aspartate (NMDA) maturation in schizophrenics, to formulate a new hypothesis concerning the pathogenesis of schizophrenic psychotic symptoms in neural terms.


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G. Chechik, I. Meilijson, and E. Ruppin
Effective Neuronal Learning with Ineffective Hebbian Learning Rules
Neural Comput., April 1, 2001; 13(4): 817 - 840.
[Abstract] [Full Text]




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Copyright © 1998 by The MIT Press.