Memories as bifurcations: Realization by collective dynamics of spiking neurons under stochastic inputs

How the neural system proceeds from sensory stimuli to generate appropriate behaviors is a basic question that has not yet been fully answered. In contrast to the conventional viewpoint, in which the external stimulus dominantly drives the response behavior, recent studies have revealed that not only external stimuli, but also intrinsic neural dynamics, contribute to the generation of response behavior. In particular, spontaneous activity, which is neural activity without extensive external stimuli, has been found to exhibit similar patterns to those evoked by external inputs, from time to time. In order to further understand the role of this spontaneous activity on the response, we propose a viewpoint, memories-as-bifurcations, that differs from the traditional memories-as-attractors viewpoint. According to this viewpoint, memory is recalled when spontaneous neural activity is changed to an appropriate output activity upon the application of an input. After reviewing the previous rate-coding model embodying this viewpoint, we employ a model of a spiking neuron network that can embed input/output associations, and study the dynamics of collective neural activity. The organized neural activity, which matched the target pattern, is shown to be generated even under application of stochastic input, while the spontaneous activity, which apparently shows noisy dynamics, is found to exhibit selectively higher similarity with evoked activities corresponding to embedded target patterns. These results suggest that such an intrinsic structure in the spontaneous activity might play a role in generating the higher response. The relevance of these results to biological neural processing is also discussed.