• DOI:10.1109/EMBC.2017.8037768
• Corpus ID: 6489049

Decoding emotional valence from electroencephalographic rhythmic activity

@article{elikkanat2017DecodingEV,
  title={Decoding emotional valence from electroencephalographic rhythmic activity},
  author={Hande Çelikkanat and Hiroki Moriya and Takeshi Ogawa and Jukka-Pekka Kauppi and Motoaki Kawanabe and Aapo Hyv{\"a}rinen},
  journal={2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)},
  year={2017},
  pages={4143-4146}
}

• H. Çelikkanat, H. Moriya, +3 authors A. Hyvärinen
• Published 1 July 2017
• Psychology
• 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

We attempt to decode emotional valence from electroencephalographic rhythmic activity in a naturalistic setting. We employ a data-driven method developed in a previous study, Spectral Linear Discriminant Analysis, to discover the relationships between the classification task and independent neuronal sources, optimally utilizing multiple frequency bands. A detailed investigation of the classifier provides insight into the neuronal sources related with emotional valence, and the individual differences of the subjects in processing emotions. Our findings show: (1) sources whose locations are similar across subjects are consistently involved in emotional responses, with the involvement of parietal sources being especially significant, and (2) even though the locations of the involved neuronal sources are consistent, subjects can display highly varying degrees of valence-related EEG activity in the sources.