We present a system of differential equations which abstractly models neural dynamics and synaptic plasticity of a cortical macrocolumn. The equations assume inhibitory coupling between minicolumn activities and Hebbian type synaptic plasticity of afferents to the minicolumns. If input in the form of activity patterns is presented, self-organization of receptive fields (RFs) of the minicolumns is induced. Self-organization is shown to appropriately classify input patterns or to extract basic constituents form input patterns consisting of superpositions of subpatterns. The latter is demonstrated using the bars benchmark test. The dynamics was motivated by the more explicit model suggested in [1] but represents a much compacter, continuous, and easier to analyze dynamic description.
机构:
UCL, Gatsby Computat Neurosci Unit, London WC1N 3AR, England
Goethe Univ Frankfurt, Frankfurt Inst Adv Studies, D-60438 Frankfurt, GermanyUCL, Gatsby Computat Neurosci Unit, London WC1N 3AR, England