Synchronous neural activities associated with the segmentation of sound sequences

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Segmentation of sound sequences is an important ability for language acquisition. However, its neural mechanism has not been revealed yet. In this study, we hypothesize that synchronized activities among neurons leads typical state transition dynamics for segmentation. Here, we verify this hypothesis by recording multi-neuronal activities simultaneously from HVC, which is a responsible brain area for sequential processing in Bengalese finches. Through cross-correlation analysis between multiple spike train data, we revealed that population activity in HVC makes transition among synchronous and de-synchronous states according to song sequences. This result indicated that synchronous neural activities are involved in segmentation of complex sequences.