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Neural Computation, Vol 7, 182-205, Copyright © 1995 by The MIT Press

ARTICLES

Compensatory mechanisms in an attractor neural network model of schizophrenia

D Horn and E Ruppin
School of Physics and Astronomy, Tel Aviv University, Israel.

We investigate the effect of synaptic compensation on the dynamic behavior of an attractor neural network receiving its input stimuli as external fields projecting on the network. It is shown how, in the face of weakened inputs, memory performance may be preserved by strengthening internal synaptic connections and increasing the noise level. Yet, these compensatory changes necessarily have adverse side effects, leading to spontaneous, stimulus-independent retrieval of stored patterns. These results can support Stevens' recent hypothesis that the onset of schizophrenia is associated with frontal synaptic regeneration, occurring subsequent to the degeneration of temporal neurons projecting on these areas.


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Neural Comput., May 1, 2001; 13(5): 1045 - 1064.
[Abstract] [Full Text]


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Copyright © 1995 by The MIT Press.