Abstract
Neural connectivity of the prefrontal cortex is essential to working memory. Reduction
of prefrontal connectivity and abnormal prefrontal dopamine modulation are common
characteristics associated with schizophrenia.
Two experiments separately modeled the effects of exaggerated pruning and of synaptic
depression to imitate schizophrenic performance in a prefrontal neural network. In
the first model, effects of cortical pruning were simulated with a set of scale-free
networks of neurons and compared with empirical results from the Sternberg working
memory task. The second set of simulations were based on the synaptic theory of working
memory. Simulations of this model measured memory duration in relation to synaptic
facilitation and depression constants and in relation to the level of neural connectivity.
In the first set of simulations, modulating levels of cortical pruning resulted in
a gain or loss in accuracy and speed of memory recollection. In the second set of
simulations, increased facilitation time constants and decreased inhibitory time constants
resulting in longer memory durations, and overly connected networks resulted in very
low memory durations.
In the first model, the decline in memory performance can be attributed to the emergence
of pathological memory behavior brought about by the warping of the basins of attraction.
Collectively, the simulations demonstrate that a reduction of prefrontal cortical
hubs can lead to schizophrenia like performance in neural networks, and may account
for pathological working memory in the disorder.
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Correspondence
C. D. Gore
Center for Complex Systems Studies
Kalamazoo College
1200 Academy Street
Kalamazoo, Michigan
USA
Phone: +1/734/272 3099
Fax: +1/269/337 7101
Email: christopher.d.gore@wmich.edu
