Toward automatic detection of brain responses to emotional music through analysis of EEG effective connectivity
作者：
Highlights：
• We used both classical and Iranian musical excerpts.
• We recorded EEG signals while participants listened to musical selections.
• We defined features based on the theory effective connectivity.
• We examined the correlation of the extracted features with valence and arousal.
• We classified signals into different categories using connectivity-based features.
摘要
•We used both classical and Iranian musical excerpts.•We recorded EEG signals while participants listened to musical selections.•We defined features based on the theory effective connectivity.•We examined the correlation of the extracted features with valence and arousal.•We classified signals into different categories using connectivity-based features.
论文关键词：Brain connectivity,Electroencephalography (EEG),Directed transfer function,Machine learning,Multivariate autoregressive modeling,Musical emotions
论文评审过程：Received 8 January 2015, Revised 3 January 2016, Accepted 5 January 2016, Available online 14 January 2016, Version of Record 14 January 2016.
论文官网地址：https://doi.org/10.1016/j.chb.2016.01.005
