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Synchronous Oscillations Based on Lateral Connections
DeLiang Wang
Laboratory for AI Research
Department of Computer and Information Science
and Center for Cognitive Science
The Ohio State University
Columbus, OH 43210-1277, USA
dwang@cis.ohio-state.edu
Abstract
The discovery of long range synchronous oscillations in the visual cortex has
triggered much interest in understanding the underlying neural mechanisms
and in exploring possible applications of neural oscillations. Many neural
models thus proposed end up relying on global connections, leading to the
question of whether lateral connections alone can produce remote
synchronization. With a formulation different from frequently used phase
models, we find that locally coupled neural oscillators can 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. Furthermore, we illustrates
the potential of locally connected oscillator networks in perceptual
grouping and scene segmentation, which is missing in globally connected
ones. Finally, we review most recent advances in understanding oscillatory
dynamics and in applying oscillator networks to real image segmentation, and
discuss issues of biological plausibility and origin of cortical synchronous
oscillations.
Next: Introduction
Up: Lateral Interactions in the Cortex: Structure and Function
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