Introduction to the theory of neural computation
Introduction to the theory of neural computation
Gamma oscillations and stimulus selection
Neural Computation
Computation with spikes in a winner-take-all network
Neural Computation
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
A biologically plausible winner-takes-all architecture
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
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Synaptic interactions in cortical circuits involve strong recurrent excitation between nearby neurons and lateral inhibition that is more widely spread. This architecture is commonly thought to promote a winner-take-all competition, in which asmall fraction of neuronal responsesis selected for further processing. Here I report that such a competition is remarkably sensitive to the timing of neuronal action potentials. This is shown using simulations of model neurons and synaptic connections representing a patch of cortical tissue. In the simulations, uncorrelated discharge among neuronal units results in patterns of response dominance and suppression, that is, in a winner-take-all competition. Synchronization of firing, however, prevents such competition. These results demonstrate a novel property of recurrent cortical-like circuits, suggesting that the temporal patterning of cortical activity may play an important part in selection among stimuli competing for the control of attention and motor action.