Models of Correlation Based Neural Development

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DESCRIPTION (adapted from applicant's abstract): The long-term goal of this work is to understand the circuitry of the cerebral cortex and the rules underlying its activity-dependent development. Primary visual cortex (V1) of the cat is studied as a model system for understanding cortex more generally. Computational modeling is used to determine what patterns of circuitry can account for the functional response properties of V1 neurons and what rules of activity-instructed synaptic modification can yield the self-organization of these patterns of circuitry. Cerebral cortical circuitry underlies most sensory perception, much of motor planning, and most of the higher cognitive functions associated with human intelligence, so an understanding of cortical circuitry and its development will strongly impact our understanding of both normal and diseased brain function. In particular, understanding of V1 circuitry and development will impact our understanding of normal vision and of central diseases of vision such as amblyopia and strabismus. The specific aims of this work are to develop biologically identifiable and testable models of the circuitry of layer 4, the input-recipient layer, of cat V1 and of the development of that circuitry. Studies of development will test the hypothesis that spike-timing-dependent plasticity (STDP), based on spontaneous patterns of activity that exist before visual experience impacts development, can account for the organization of V1 receptive fields and functional circuits. A particular focus will be to understand the development of direction selectivity and of the associated cortical circuitry. Studies of the mature circuit will build on previous work showing that a "correlation-based" circuit, in which excitatory cells tend to project to cells with similar or well correlated receptive fields (overlapping ON- and OFF-subregions) and inhibitory cells tend to project to cells with roughly opposite or anticorrelated or antiphase receptive fields, can account for many of the functional response properties of V1 layer 4 cells. This work will be extended to incorporate new experimental findings on the roles of voltage noise in V1 responses, of orientation-untuned complex inhibitory neurons, and of synaptic depression in V1 responses. It will also be extended to address direction selectivity by incorporating diversity of temporal response properties of input neurons and by extending the spatial correlation-based circuitry to circuitry based on spatiotemporal correlations.