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, 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… 

Figures and Tables from this paper

Using Black Hole Algorithm to Improve EEG-Based Emotion Recognition
TLDR
A new method to adjust the classifier is proposed using metaheuristics based on the black hole algorithm aimed at obtaining results similar to those obtained with manual noise elimination methods.
Affect Recognition using Psychophysiological Correlates in High Intensity VR Exergaming
TLDR
Gaze fixations, eye blinks, pupil diameter and skin conductivity are identified as psychophysiological measures suitable for affect recognition in VR exergaming and their utility in determining affective valence and arousal is analyzed.

References

SHOWING 1-10 OF 13 REFERENCES
Decoding the Nature of Emotion in the Brain
Decoding magnetoencephalographic rhythmic activity using spectrospatial information
Anger and frontal brain activity: EEG asymmetry consistent with approach motivation despite negative affective valence.
TLDR
The hypothesis that dispositional anger, an approach-related motivational tendency with negative valence, would be associated with greater left- than right-anterior activity was tested, suggesting that the anterior asymmetry varies as a function of motivational direction rather than affective valence.
Real-Time EEG-Based Human Emotion Recognition and Visualization
TLDR
Fractal dimension based algorithm of quantification of basic emotions is proposed and its implementation as a feedback in 3D virtual environments adding one more so-called “emotion dimension” to human computer interfaces.
ADJUST: An automatic EEG artifact detector based on the joint use of spatial and temporal features.
TLDR
A completely automatic algorithm (ADJUST) that identifies artifacted independent components by combining stereotyped artifact-specific spatial and temporal features is proposed that provides a fast, efficient, and automatic way to use ICA for artifact removal.
EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis
Neuronal Oscillations in Cortical Networks
TLDR
Recent findings indicate that network oscillations bias input selection, temporally link neurons into assemblies, and facilitate synaptic plasticity, mechanisms that cooperatively support temporal representation and long-term consolidation of information.
On the interpretation of weight vectors of linear models in multivariate neuroimaging
...
...