Music serves a variety of functions in daily life and plays an important role in mental well-being by impacting moods, emotions and other affective states. Also, music can be considered a "mirror of the self" and our music listening strategies and habits speak volumes about our mental states and individual traits. The focus of this research is to identify risk of depression via music listening habits and uncover patterns that might be indicative of individual traits. This will then allow us to understand how individual variations modulate responses to music, especially if music therapy has to be tailored for an individual.
This research is a collaborative effort with Dr. Suvi Saarikallio from University of Jyväskylä, Department of Music as part of the 'My Music (OmaMusa in Finnish): Personalised music listening strategies to support emotional health in adolescents' 3-year research project (2018-2020), funded by the Academy of Finland https://www.jyu.fi/hytk/fi/laitokset/mutku/en/research/projects2/personalisedmusic
The primary goal is to unearth music processing in the brain via functional magnetic resonance imaging (fMRI) and how individual differences (personality, musical expertise, musical aptitude, empathy) modulate functional connectivity thereof. This is part of the Tunteet Project lead by Prof. Elvira Brattico (Aarhus University, Denmark) in collaboration with Prof. Petri Toiviainen (University of Jyvaskyla) which aims at investigating music processing and musicality in the naturalistic listening paradigm and involves several neuroimaging and neurophysiological measures in addition to behavioral and cognitive tests.
Specifically we are looking at dynamic functional connectivity differences in musicians and non-musicians and evolution of emotional states. In addition, we are currently attempting at incorporating genetics and understanding how that might modulate musical processing.
This line of research is part of the Addimex CONN project in Collaboration with Dr. Eduardo A. Garza-Villarreal (National Autonomous University of Mexico) and Associate Prof. Madhura Ingalhalikar (Symbiosis Institute of Technology, Pune), which aims at investigating Connectome of substance addiction in Mexican population. The aim is to investigate differences in functional connectivity in cocaine users and predicting whole-brain functional connectivity from strucutral conenctivity in the same.
This project comes under the VAJRA (Visiting Advanced Joint Research) Faculty Scheme in Collaboration with Prof. Petri Toiviainen of University of Jyvaskyla. The proposed project aims at determining how the brain processes musical features of varying levels of abstraction and how this depends on musical exposure, implicit learning, and enculturation. To this end, it uses a highly interdisciplinary approach combining state-of-the-art methods of brain imaging, computational music analysis, and artificial intelligence. In particular, it employs Deep Neural Networks (DNN) to learn abstract features from musical recordings, which are subsequently compared with brain imaging data recorded with functional magnetic resonance imaging during music listening.