بررسی الکتروانسفالوگرام شبکه موثر مغز انسان در حین گوش دادن به موسیقی به منظور تشخیص احساسات

In the current research brain effective networks related to happy and sad emotions are studied during listening to music. Connectivity patterns among different EEG channels were extracted using multivariate autoregressive modeling and partial directed coherence while participants listened to musical excerpts. Both classical and Iranian musical selections were used as stimulus. Participants’ self-reported emotional values were used for classification of excerpts. The connectivity matrices varied from happy to sad musical selections. Moreover, the parameters extracted from different regions correlated with subjective assessments of the emotional content. Self-reported valance had a positive correlation with the inflow of frontal channels while listening to happy excerpts. This correlation was negative for sad pieces. The obtained results demonstrate that the connectivity indices among different regions can be used for differentiating happy and sad emotions.