Brain emotional oscillatory activity during the different affective picture and sound experience

Good mood state is an important indicator of good healthy life, while the bad emotional state could give rise to some social or mental state health issues. To properly manage the psychological and emotional health caused by negative emotions in our daily life, we need to recognize the various emotional states firstly. In order to find out the special cognitive emotional characteristics to reach high emotional identification accuracy, the aim of this paper is to explore the brain emotional oscillatory activity induced by visual and audio stimuli from IAPS and IADS databases in the amplitude measurement. Event related potential (ERP) analysis is used to find out the pronounced emotional characteristics in the emotion recognition. Thirty subjects are employed in the visual and audio experiments. A significance level of p < 0.01 is combined with ERP to analyze the brain signal data in order to discover significant effects. The results show that, two narrow time ranges (650–750ms and 800–900ms) in the late positive potential (LPP) are come up with five emotional states in the several brain regions for the visual induced emotion state changes. Six narrow time ranges from 0 to 1s of ERP are proposed to study potential various with three emotional states in the several brain regions for the audio induced emotion state changes. The results provide preliminary evidence for narrowing the time range of ERP in the emotion recognition research.

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