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Working Memory in the Network of Neuron-like Units with Noise

A model of working memory system in the form of a network of neuron-like units is considered. The units are stimulated by a periodic subthreshold stimulus and interact via inhibitory feedback. The information storage in the system occurs in the form of periodic clusters of neural activity. Several sequentially firing clusters can coexist in the network simultaneously corresponding to several stored images. The influence of noise on cluster dynamics and noise resistance of the system are studied. Optimal parameters corresponding to maximal noise resistance of the system were found.