Dialogues in Music Therapy and Social Neuroscience: An Interdisciplinary Approach to Clinical Progress

In his book “Musicophilia: Tales of Music and the Brain”, the neurologist Oliver Sacks stated that music can “calm us, animate us, comfort us, thrill us, or serve to organize and synchronize us at work or play– it may be especially powerful and have great therapeutic potential for patients with a variety of neurological conditions.”

Our relationship with music starts in the womb: In the last trimester of fetal life, babies are able to hear external sounds, including musical stimuli. Once born, they will respond differently to those familiar sounds compared to novel ones. For instance, in investigations of prenatal auditory learning using electroencephalography (EEG), extensive prenatal exposure to a melody induced changes in newborn neural signal that lasted several months and correlated with the amount of prenatal exposure. This implies a memory of distinctive, low-level elements constituting speech and music that may form the basis of language learning in the first years of life. Indeed, prenatal music exposure has been show to induce long-term physiological and neural effects (Partanen et al., 2013).

Music has been a relevant stimulus for our species for a very long time (Cross, 2001) and there’s plenty of evidence about the beneficial effect of music on well-being (for an overview, see: Chanda & Levitin, 2013). For instance, Menon & Levitin (2005) investigated the neural correlates of musical pleasure showing enhanced activation in a network of areas, including the nucleus accumbens, the ventral tegmental area, the hypothalamus, and orbitofrontal cortex, when participants listened to classical music compared to scrambled music. The authors suggested that musical reward is dependent on similar neural networks as other reinforcing stimuli because these brain structures are known to be part of a brain reward system which is involved in processing pleasure and positively valenced emotions (Berridge & Kringelbach, 2015).

“The emotional power of music and its profound effect on the brain suggests that it can be wielded as a therapeutic tool to probe the neural basis of psychiatric disorders. “

The emotional power of music and its profound effect on the brain suggests that it can be wielded as a therapeutic tool to probe the neural basis of psychiatric disorders. In the last two decades, music therapy has been gradually recognized as a useful option for the treatment of several complex neuropsychiatric diseases, such as schizophrenia, dementia, autism spectrum disorder, anxiety, depression and Parkinson’s disease (Mossler et al., 2011; Vink et al., 2003; Gold et al., 2006; Bradt & Dileo, 2009; Maratos et al., 2008; de Dreu et al., 2012).

Music therapy describes the clinical use of music interventions to accomplish individualized goals within a therapeutic setting. It has also been defined as a psychological therapy that aims to create an interpersonal relationship between the client and the therapist to relieve symptoms and determine positive changes (for an overview, see Witusik et al., 2019). Major depressive disorder is the most studied medical condition in the context of music therapy (Maratos, 2011), the effectiveness of which was demonstrated, through a randomised controlled trial, by Erkkilä and colleagues (2011).

“The possibility of analyzing coupled activities of two or more brain regions from different brains represents a remarkable opportunity for the advancement of knowledge on social and therapeutic interactions involving musical stimuli.”

Neuroscience methods, such as fMRI and EEG, offer exciting and noninvasive ways to examine the physiological effects of music therapy interventions. One EEG study revealed how a music therapy rehabilitation program improved fine and gross motor skills in stroke patients (Altenmüller et al., 2009). The authors found that motor improvement has been accompanied by greater inter-regional brain communication and increased brain activity of motor regions (Altenmüller et al., 2009). Recently, the brain activity of an interacting couple during a music therapeutic intervention was measured via EEG hyperscanning (Fachner et al., 2019), which is a relatively new methodology to study the neural substrates of social interactions. The hyperscanning technique allows us to measure brain activity (either through EEG or fMRI) from two or more individuals simultaneously (Ayrolles et al., 2020).  The possibility of analyzing coupled activities of two or more brain regions from different brains represents a remarkable opportunity for the advancement of knowledge on social and therapeutic interactions involving musical stimuli. Fachner and colleagues (2019) had a client, therapist, and two external individuals rate moments in a therapy session by importance and emotional-relevance. By pairing this detailed audio-visual data with coupled EEG hyperscanning, they showed that the EEG time-course of both the therapist’s and client’s brain activity was aligned in the frontal part of the brain during emotionally-relevant moments compared to moments of non-interest. The implementation of this methodology provides a great opportunity to study authentic therapeutic relationships and explore the neural mechanisms underlying therapeutic interactions.

Altogether, the evidence illustrates how music therapy and neuroscience can inform each other. Decades of research have shown that neuroscience methods can provide insight into individuals’ interactions and social events, including precise and time-relevant measurements of ongoing cognitive processes. Pairing such with behavioural, physiological, or questionnaire measures provides a more powerful means to investigate the neural mechanisms underlying therapeutic processes.

A critical, ongoing experimental challenge for the field of music therapy research is to create dynamic conditions for the study of the music therapeutical impact on clinical settings without sacrificing well-controlled laboratory conditions. In other words, research in the field of music therapy needs to account for a social and real-time neuroscientific approach (Schilbach et al., 2013) allowing the study of authentic therapeutic relationships.

Written by Filippo Pasqualitto. Illustrated by Sumana Shrestha.
Edited by Zoe Guttman, Sean Noah, and Desislava Nesheva.

 

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References

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Altenmüller E, Marco-Pallares J, Münte TF, Schneider S. (2009). Neural reorganization underlies improvement in stroke-induced motor dysfunction by music-supported therapy. Ann N Y Acad Sci. 2009 Jul;1169:395-405. doi: 10.1111/j.1749-6632.2009.04580.x. PMID: 19673814.

Ayrolles, A., Brun, F., Chen, P., Djalovski, A., Beauxis, Y., Delorme, R., Bourgeron, T., Dikker, S., & Dumas, G. (2021). HyPyP: a Hyperscanning Python Pipeline for inter-brain connectivity analysis. Social cognitive and affective neuroscience, 16(1-2), 72–83. https://doi.org/10.1093/scan/nsaa141

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Author(s)

  • Filippo is a PhD student at the Cambridge Institute for Music Therapy Research (CIMTR) and his PhD project aims to investigate the neural dynamics underlying the individual therapeutic relationship by monitoring client-therapist brain activity through EEG Hyperscanning. He is also investigating whether a music-based intervention within a Community Substance Misuse Treatment Service (CSMTS) has positive effects on depressive and anxiety symptoms, cravings and perceived therapeutic alliance as assessed by subjective psychometric measures and objective resting-state EEG biomarkers.

Filippo Pasqualitto

Filippo is a PhD student at the Cambridge Institute for Music Therapy Research (CIMTR) and his PhD project aims to investigate the neural dynamics underlying the individual therapeutic relationship by monitoring client-therapist brain activity through EEG Hyperscanning. He is also investigating whether a music-based intervention within a Community Substance Misuse Treatment Service (CSMTS) has positive effects on depressive and anxiety symptoms, cravings and perceived therapeutic alliance as assessed by subjective psychometric measures and objective resting-state EEG biomarkers.

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