Characterizing the Effects of Different Music Genres in Brain Circuit Dynamics of Patients with Depression using Neural Manifold Learning
Mental health disorders, or neuropsychiatric disorders, encompass disturbances in cognition, emotion, behavior, and physical well-being, with depression being one of the most prevalent. The subcortical limbic brain regions, particularly the amygdala, hippocampus, and dorsomedial thalamus, are profoundly impacted in depressed individuals. Music therapy has emerged as a promising intervention for various health issues, including depression, demonstrating substantial improvements in mental health, emotional well-being, and overall quality of life. Despite its global recognition, music therapy remains underutilized in the Philippines. This study aims to quantitatively assess the neu-rophysiological effects of music on patients diagnosed with depression using EEG-based neural manifold learning. This paper implements neural manifold learning and analysis on two datasets to quantitatively assess the effects of music on brain states and to characterize the effects of depression on neural manifolds. Our analysis revealed that distinct features of music provide a compelling effect on the neural manifold structures, suggesting a relationship between musical properties and brain dynamics. This research seeks to advance the understanding of music therapy's potential as a viable treatment for depression, particularly within the Philippine context.
Authors
- Seigfred V. Prado (ORCID: https://orcid.org/0000-0002-0111-7193)
- Wally Enrico M. Ingco (ORCID: https://orcid.org/0000-0003-0313-3290)
- L. Peralta (ORCID: https://orcid.org/0000-0002-3834-1762)
- Samuel John A. Ocenar
- Lianna Mae A. Fabay
- Nissa Anne Carmellisen M. Cañete
- Jiana F. Fabul
- Paul William B. Rombaoa
- Mark Melvin Inar L. Taguilaso
Institutions
- University of Santo Tomas (PH)
Publication Details
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1109/tencon61640.2024.10902978
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 0.00