Nonlinear Dynamics of the Primary Visual Cortex

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McLaughlin0211655 The investigator and colleagues have been developing abiologically constrained large-scale computational model of the"front-end" of the cortical visual system -- the primary visualcortex (V1). To date, their work has focused upon localproperties of individual cells within the large-scale network --properties such as orientation selectivity and simple vs complexcellular dynamics. In this project, they scale up to a moreglobal model of V1, reaching scales large enough to study someelementary optical illusions of psychology and psychophysics.This involves several square millimeters of lateral corticalarea, together with a multi-layered architecture -- with emphasisgiven to cortical dynamics. First, a "coarse-grained mixedrepresentation" is derived mathematically and tested numerically-- a representation that combines spatially coarse-grained(local) mean firing rates, representing local background corticaloperating points, with an idealized representation of asub-network of individual point neurons embedded within thisbackground and retaining the detailed firing patterns ofindividual neurons. These two components interact with eachother -- with the coarse-grained local operating pointsinfluencing the responses of the individual neurons, and viceversa. Second, the global mixed representation is used to studyspecific dynamical phenomena in visual cortical processing: (i)the layer-specific "dynamics of orientation selectivity" (asmeasured by reverse time correlation methods); and later (ii)"bistability in figure-ground assignments" (as detected inpsychology and psychophysics experiments). In both cases, thephenomena involve extensive lateral regions of V1, its layeredstructure, and (likely in the case of figure-ground assignment)other cortical regions. And in both cases the work involvesclose interaction with the experimental work of neural scientistRobert Shapley. Today, through new biological experiments combined with thepower of modern scientific computation, scientists and appliedmathematicians are making significant strides towardunderstanding the human brain. Visual perception and the corticalprocessing of visual information provide important startingpoints. By focusing upon the "front end" of the cortical visualsystem, McLaughlin and his colleagues develop computationalmodels of the visual cortex that are strongly constrained bybiological experiments. In this project the investigatorsdevelop computationally efficient numerical methods that permitscale-up of the models to global representations of the primaryvisual cortex -- reaching cortical scales large enough to studysome elementary optical illusions of psychology. This workrequires the direct interaction of applied mathematicians,computational scientists, and neural scientists -- and involvestheoretical, computational, and experimental components.