Abstract: Successful decoding of vocal emotion is critical for social interaction. Specifically, it is adaptively important to detect vocal emotion transition in time, since changes in vocal emotion are important signals for detecting the speakers’ emotion change and are common in spoken interactions. Despite the fact that human beings are born with competence to process vocal emotion transition efficiently, the underlying neurophysiological mechanism remains largely unclear. To answer this question, the present study acquired electroencephalogram (EEG) during implicit processing of two types of vocal emotion transitions (neutral to angry and angry to neutral) and their control unchanged vocal emotion from 15 healthy volunteers. Fifty sentences of neutral content produced by a trained native male actor of Mandarin Chinese in neutral and angry prosodies served as original materials. Then we constructed sentences with vocal emotion transition through cross-splicing. The participants were required to perform sound intensity change judgment when the EEG was recorded. In addition to the ordinary ERP analysis in time domain, we also conducted the analysis in frequency domain including event related spectral power (ERSP) and inter-trail coherence (ITC) to specify the neurophysiological source of vocal emotion transition processing. The results indicated that vocal emotion transition elicited N2/P3 complex, as well as theta (4~6 HZ) band power (ERSP) and inter-trail coherence (ITC) increase, irrespective of transition types. In addition, vocal emotion transition induced beta band power decrease and ITC increase. Moreover, these effects were modulated by transition types, specifically, the more intense transition of emotion resulted in shorter latency of N2/P3 complex, and much stronger increase of theta band ERSP and ITC enhancement, and different features in beta band power change. These findings suggested that the processing of vocal emotion transition is a process consisting of change detection and reintegration, similar to the processing of other auditory materials, such as spoken language and music. Moreover, theta and beta band power change and ITC increase appear to be the main neurophysiological source of the processing of vocal emotion transition. In addition, the present study implies that the analysis in frequency domain can be a useful tool for verifying the neurophysiological mechanism of cognitive processing.

Key words: vocal emotion, neuro-oscillation, ERP, ERSP, ITC