Image segmentation based on oscillatory correlation
Neural Computation
Synchronization in Time-delayed Binary Oscillatory Network
Neural Processing Letters
Synchrony and desynchrony in integrate-and-fire oscillators
Neural Computation
A biologically inspired autonomous robot that learns approach-avoidance behaviors
AGENTS '00 Proceedings of the fourth international conference on Autonomous agents
Synchronization in Relaxation Oscillator Networks with Conduction Delays
Neural Computation
An oscillatory hebbian network model of short-term memory
Neural Computation
The Periodic Solution of a Class of Two Neurons Hopfield Network with Distributed Delay
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Novel weighting-delay-based stability criteria for recurrent neural networks with time-varying delay
IEEE Transactions on Neural Networks
Optical Memory and Neural Networks
Periodic oscillation and exponential stability of a class of competitive neural networks
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
Computational Intelligence and Neuroscience - Special issue on Selected Papers from the 4th International Conference on Bioinspired Systems and Cognitive Signal Processing
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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