NEURAL COMPUTATIONS IN VISUAL CORTEX

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The proposed research consists of two complementary approaches to further the understanding of how visual information is represented and processed in visual cortex, particularly primary visual cortex. Aims I will focus on the temporal structure of the neural discharge. These aims will determine (a) the extent to which the temporal pattern of a neural discharge contributes to the representation of particular kinds of visual information, including elementary spatial features and color; (b) whether the temporal representation of visual information can facilitate subsequent visual processing; and (c) the relationship of temporal coding (representation of visual information within the spike train of a single neuron) to spatial coding (representation of visual information across two or more neurons). Standard visual stimuli (bars, gratings, and compound gratings) will be used. The usual analytical approaches of histogram, Fourier, and cross-correlation analysis will be augmented by a family of new methods recently developed in this laboratory, based on the embedding of neural responses into a metric space. Aim II will focus on the generation of response dynamics by subregions of the receptive field. The main strategy will be an adaptation of the m-sequence technique to allow analysis of the temporal structure of the response. Through comparison of receptive field maps generated by all spikes, by bursts, and by "reliable" spikes, we will determine to what extent these temporal structures participate in the signaling and extraction of features. The m-sequence analysis will show the extent to which these temporal structures arise from an overall modulation of response properties, specific receptive field subregions, or specific interactions over an extended region of space. The goals of these quantitative experiments are new qualitative insights into how the visual cortex represents and processes information, on phenomenological (Aims I) and mechanistic (Aim II) levels. This will serve as a basis for a better understanding of brain function in health and disease.