Stimulus-dependent correlations in stochastic networks

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Abstract
It has been observed that cortical neurons display synchronous firing for some stimuli and not for others. The resulting synchronous cell assemblies are thought to form the basis of object perception. In this paper this ``dynamic linking'' phenomenon is demonstrated in networks of binary neurons with stochastic dynamics. Analytical treatment within the mean field theory and linear response theory is possible and is compared with simulations. We establish that correlations are a sensitive function of the spatial coherence in the stimulus. We discuss the possibility to use these correlations as a mechanism for scene segmentation.

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