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Modeling Globabl Synchrony in the Visual Cortex by Locally Coupled Neural Oscillators
Abstract
A fundamental aspect of perception is to bind spatially separate sensory features, essential for object identification, segmentation of different objects, and figure/ground segregation. Theoretical considerations and neurophysiological findingspoint to the temporal correlation of feature detectors as a binding mechanism. In particular, it has been demonstrated that the cat visual cortex exhibits 40-60 H z stimulus-dependent oscillations, and synchronization exists in spatially remote columns (up to 7 m m ) which reflects global stimulus properties (Gray et al., 1989; Eckhom et al., 1988). What neural mechanisms underlie this global synchrony? Many neural models thus proposed end up relying on global connections, leading to the question of whether lateral connections alone can jwoduce remote synchronization. With a formulation diffwent from the frequently used phase model, w e find that locally coupled neural oscillators can indeed yield global synchrony. The model employs a previously suggested mechanism that the efficacy of the connections is allowed to change on a fast time scale. Based on the known connectivity of the visual cortex, the model outputs closely resemble the experimental findings. This model lays a computational foundation for Gestalt perceptual grouping.
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