Title :
Emergent synchrony in locally coupled neural oscillators
Author_Institution :
Dept. of Comput. & Inf. Sci., Ohio State Univ., Columbus, OH, USA
fDate :
7/1/1995 12:00:00 AM
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 illustrate the potential of locally connected oscillator networks in perceptual grouping and pattern segmentation, which seems missing in globally connected ones
Keywords :
image segmentation; neural nets; neurophysiology; physiological models; synchronisation; visual perception; global synchrony; locally coupled neural oscillators; neurophysiology; pattern segmentation; synchronous oscillations; visual cortex; visual perception; Artificial intelligence; Brain modeling; Computer vision; Delay; Detectors; Frequency synchronization; Information science; Local oscillators; Mathematical model; Neurodynamics;
Journal_Title :
Neural Networks, IEEE Transactions on