@article {2023, title = {Intra- and inter-brain coupling and activity dynamics during improvisational music therapy with a person with dementia: an explorative EEG-hyperscanning single case study}, journal = {Frontiers in Psychology: Cognitive Science}, volume = {14:1155732}, year = {2023}, month = {09/2023}, abstract = {Objective: Real-life research into the underlying neural dynamics of improvisational music therapy, used with various clinical populations, is largely lacking. This single case study explored within-session differences in musical features and in within- and between-brain coupling between a Person with Dementia (PwD) and a music therapist during a music therapy session. Methods: Dual-EEG from a music therapist and a PwD (male, 31 years) was recorded. Note density, pulse clarity and synchronicity were extracted from audio-visual data. Three music therapists identified moments of interest and no interest (MOI/MONI) in two drum improvisations. The Integrative Coupling Index, reflecting time-lagged neural synchronization, and musical features were compared between the MOI and MONI. Results: Between-brain coupling of 2 Hz activity was increased during the MOI, showing anteriority of the therapist{\textquoteright}s neural activity. Within-brain coupling for the PwD was stronger from frontal and central areas during the MOI, but within-brain coupling for the therapist was stronger during MONI. Differences in musical features indicated that both acted musically more similar to one another during the MOI. Conclusion: Within-session differences in neural synchronization and musical features highlight the dynamic nature of music therapy. Significance: The findings contribute to a better understanding of social and affective processes in the brain and (interactive) musical behaviors during specific moments in a real-life music therapy session. This may provide insights into the role of such moments for relational-therapeutic processes.}, keywords = {brain coupling, dementia, EEG, improv, Music Therapy}, doi = {doi:10.3389/fpsyg.2023.1155732}, author = {Clemens Maidhof and Viktor M{\"u}ller and Olivier Lartillot and Kat Agres and Jodie Bloska and Rie Asano and Helen Odell-Miller and J{\"o}rg Fachner} } @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} }