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Many experimental results have generated renewed appreciation that precise temporal synchronization, and synchronized oscillatory activity in distributed groups of neurons, may play a fundamental role in perception, memory and sensory computation, especially to encode relationship and increase saliency. Here we investigate how precise temporal synchronization of groups of neurons can be memorized as attractors of the network dynamics. Multiple patterns, each corresponding to different groups of synchronized oscillatory activity, are encoded using a temporally asymmetric learning rule inspired to the spike-timing-dependent plasticity recently observed in cortical area. In this paper we compare the results previously obtained for phase-locked oscillation in the random phases hypothesis, to the case of patterns with synchronous subgroups of neurons, each pattern having neurons with only Q = 4 possible values of the phase.
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