@article {2019,
	title = {A closed-loop, music-based brain-computer interface for emotion mediation},
	journal = {PLoS ONE},
	volume = {14},
	year = {2019},
	month = {03/2019},
	pages = {e0213516},
	type = {Research Article},
	abstract = {Emotions play a critical role in rational and intelligent behavior; a better fundamental knowledge of them is indispensable for understanding higher order brain function. We propose a non-invasive brain-computer interface (BCI) system to feedback a person{\textquoteright}s affective state such that a closed-loop interaction between the participant{\textquoteright}s brain responses and the musical stimuli is established. We realized this concept technically in a functional prototype of an algorithm that generates continuous and controllable patterns of synthesized affective music in real-time, which is embedded within a BCI architecture. We evaluated our concept in two separate studies. In the first study, we tested the efficacy of our music algorithm by measuring subjective affective responses from 11 participants. In a second pilot study, the algorithm was embedded in a real-time BCI architecture to investigate affective closed-loop interactions in 5 participants. Preliminary results suggested that participants were able to intentionally modulate the musical feedback by self-inducing emotions (e.g., by recalling memories), suggesting that the system was able not only to capture the listener{\textquoteright}s current affective state in real-time, but also potentially provide a tool for listeners to mediate their own emotions by interacting with music. The proposed concept offers a tool to study emotions in the loop, promising to cast a complementary light on emotion-related brain research, particularly in terms of clarifying the interactive, spatio-temporal dynamics underlying affective processing in the brain.},
	keywords = {brain-computer interface, EEG, emotion mediation, music BCI, neurofeedback},
	doi = {https://doi.org/10.1371/journal.pone.0213516},
	author = {Stefan Ehrlich and Kat Agres and Cuntai Guan and Gordon Cheng}
}
@proceedings {2019,
	title = {A Comparative Study of Mental States in 2D and 3D Virtual Environments Using EEG},
	year = {2019},
	month = {10/2019},
	publisher = {IEEE},
	address = {Bari, Italy},
	abstract = {There is growing evidence that virtual reality (VR) can be used as an optional therapy method for stress relief and treatment of mental disorders such as a variety of anxiety disorders, depression and psychosis. However, more systematic studies to quantify the effects of VR for emotion elicitation and compare the effects of 3D and 2D environment for the same is necessary to design feasible and effective treatments. In this study, we design a cross-over experiment protocol comprising of two emotion eliciting environments relaxation and arousal - that is presented to the participant either in a 2D monitor or a 3D head-mounted (HMD) VR display. The EEG data is collected during the experiment and analyzed offline to classify emotion elicited by low and high arousal environments using SVM classification of band power features. A 10-fold cross validation is performed and classification accuracy for each subject is computed for 3D-VR and 2D-screen display. The average classification accuracies over subjects are obtained as 66.88\% and 59.27\% in 3D-VR and 2D-screen group respectively. The performance difference between 3D-VR and 2D screen is statistically significant (p < 0.05), indicating that 3D-VR generates more distinct EEG patterns associated with emotion elicitation. Further, significant differences in band powers from alpha, theta and beta bands are also observed between both groups. The results presented in this paper support the use of VR as an effective tool to study emotion elicitation and regulation, compared to a 2D screen.},
	author = {Pinar Bilgin and Kat Agres and Neethu Robinson and Aung Aung Phyo Wai and Cuntai Guan}
}
