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Ongoing brain activity can be recorded as electroen-cephalograph (EEG) to discover the links between emotional states and brain activity. This study applied machine-learning algorithms to categorize EEG dynamics according to subject self-reported emotional states during music listening. A framework was proposed to optimize EEG-based emotion recognition by systematically 1) seeking emotion-specific...
The brain structure mismatch between western and eastern people may lead to an inappropriate interpretation of neurocognitive studies. To minimize this interracial misinterpretation, we developed the National Taiwan University Chinese Brain Template (NTU-CBT). 102 (M/F=55/47) healthy Chinese subjects were recruited and received 3T MR brain scans. The template development processes were based on the...
This study explores the electroencephalographic (EEG) correlates of emotions during music listening. Principal component analysis (PCA) is used to correlate EEG features with complex music appreciation. This study also applies machine-learning algorithms to demonstrate the feasibility of classifying EEG dynamics in four subjectively-reported emotional states. The high classification accuracy (81.58plusmn3...
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