Neural Net Simulation of the Corpus Callosum

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Abstract
The effects of simulated anatomical and physiological parameters were investigated in a “neural net” model, where two neural nets corresponding to two small patches of cerebral cortex were connected by a simulated “corpus callosum.” The isolated neural nets have previously been shown to exhibit oscillatory activity similar to the raw EEG. By connecting the nets with fibers which have a specified percentage of inhibition and a specified percentage of homotopicity, the effects of such parameters on the cyclic activity of the nets were studied. It was found that, regardless of the inhibitory-excitatory nature of the simulated corpus callosum, the cyclic activity established in one hemisphere is more readily transferred to the contralateral hemisphere, the greater the percentage of homotopic callosal fibers. Learning was more rapid when the effect of the corpus callosum was primarily excitatory, but learning also took place over inhibitory or mixed callosal tracts. The simulation does not therefore resolve the issue of the predominant physiological effect of the corpus callosum, but does indicate that, given the assumptions of the simulation, “learning” can occur regardless of the percentage of excitatory or inhibitory fibers. It is noteworthy that homotopicity was more important for learning across an inhibitory tract than across an excitatory tract.

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