Theoretical Considerations of Bio-guided Music Therapy

By Eric B. Miller

Abstract

Music therapists rarely have the opportunity to consider a new model of music therapy and need to review prior models and theoretical approaches to make an informed determination regarding Bio-guided Music Therapy. While initially appearing to fall within the confines of Behavioral Music Therapy, technical advances in sound reproduction, physiological data acquisition methods, as well as innovative application techniques are argued to bring the bio-guided approach into the realm of in-the-moment improvisation. Bio-guided Music Therapy distinguishes itself from other music therapy models by virtue of the client's physiological data being presented in real-time either musically or visually back to the client or the therapist during the therapy session. This real-time data may be presented in key, scale and tempo for flexibility in musical interaction with the music therapist or group. General treatment areas include ADHD, Stress/anxiety, dementia, depression and addictions. The resulting charts and graphs document the impact of the music therapy session in the language of mainstream medicine, readily accessible to other medical professionals.

Considering Bio-guided Music Therapy

It's not often that we music therapists have the opportunity to consider a new model of music therapy, but then again, the basic fundamentals of bio-guided music therapy (Miller, 2011) were described by Scartelli back in the late '80s in his MMB Music publications booklet entitled Music & Self-Management Methods (Scartelli, 1989). There are numerous reasons why this approach was not readily adopted at the time. Some of these factors continue to exist today, while others have diminished in scope. In effect, bio-guided music therapy could either be viewed as a new model due to the technological developments now making it more viable as a music therapy model or as an older approach that has been recently innovated.

A few of the more salient reasons why the incorporation of real-time physiological data had not been widely adopted by music therapists in the past, include the consistency, economics and portability of quality sound reproduction, ease of physiological data acquisition methods and the fluidity of digital assignment of midi and real audio to physiological parameters. In the early personal computers, manipulating recorded audio was impractical due to machine memory constraints and limitations of central unit processing speed. Early audio amplifiers were heavy and cumbersome. Early physiological monitors were bulky and primitive in terms of audio output options. Wireless transmission was still yet to be developed. These encumbrances combined would seem discouraging enough for music therapists, let alone the prospect of a steep learning curve to master the technology.

One of the most striking advances since Scartelli wrote about biofeedback and music therapy in 1989 is the improved quality of electronic audio sounds. We now have crystal clear digital tones and synthesized instruments that have amazing power and depth with adjustable timbres and tonal qualities. This is in sharp contrast to the old computerized tones that were perceived by some, including this author, as more annoying than musical! Current systems also provide multiple channels of real and synthesized audio for high quality layering and texturing of sound. The audio units of today are extremely portable with simple audio players often being pocket-size or smaller. These technological advances contribute both to the flexibility and aesthetics of translating physiological information into musical output.

The methods used for physiological data acquisition in bio-guided music therapy are standard in biofeedback practice and research. These may include finger sensors that measure Galvanic Skin Response or take an infra-red measure of peripheral blood flow and heart-rate. EEG sensors may be placed on the head to collect brainwave data and an infra-red emitting headband may be placed on the forehead to measure cerebral blood flow and blood oxygenation (hemoencephalograhy). The innovation in the application of these methods to music therapy lies in the art and science of assigning musical parameters to the live physiological data in real-time and in choice of live improvisational or recorded musical background if any. In essence, the music therapist is creating a musical environment that is responsive to the dynamics of physiological measures and aimed at clinical goals.

While acknowledging the impressive amount of quantitative and qualitative research published in the Journal of Music Therapy and Music Therapy Perspectives over the years, one pattern that has persisted for at least two decades, is a perceived tendency for music therapists to avoid conducting formal research and acquiring associated skills such as advanced statistics and quantitative research methods. While some may initially take offense at this opinion, I would point out that in the large plenary sessions of music therapy conferences such as the Joint Music Therapy conference in Toronto in 1993 to the 2011 World Music Therapy Congress in Seoul South Korea, the same message regarding research is reiterated time and time again; that music therapists do not need to be afraid of research. In fact the speakers implore music therapists to conduct research and they remind us that even documentation of clinical work can contribute to the body of music therapy knowledge. I was surprised when teaching a recent graduate music therapy course in physiological research, how few of the students were comfortable with basic spreadsheet functions and statistical analysis. There was an accompanying underlying apprehension about conducting research. I find it striking that this same fear of research was present as when I instructed graduate music therapy courses a decade ago! Why am I surprised? This is fairly understandable given that the creative skills needed to become an accomplished musician and to master improvisation are in some ways antithetical to the linear thinking required for math and research. Music improvisation is often thought of as a "right brain" activity related to feeling, creative expression, and artistic talent, while research is associated with typical "left brain" activities such as cognitive analysis, linear and sequential tasking, and numeric calculation (Décosterd, M. L., 2008; Szirony, G. M, et al. 2007).

What Distinguishes Bio-guided Music Therapy From other Music Therapy Models and What Does it Offer That Does Not Exist in Other Models?

There are various approaches to the task of describing music therapy models. Kenneth Bruscia (1987) describes twenty-five Improvisational Models of Music Therapy, each with their unique contribution to clinical treatment. In another approach, Wigram, Pedersen & Bonde (2002) describe five internationally utilized models of music therapy along with 3 traditional methods that appear to approach, but not quite attain "model" status. These models include Helen Bonny's Guided imagery and Music (GIM), Mary Priestly's Analytic Music Therapy, Nordoff and Robbins' Creative Music Therapy, Benezon Music Therapy and Behavioral Music Therapy. It is the this last model, that comes the closest to bio-guided music therapy with the concept of music as a component of operant conditioning as described by Madsen, Cotter & Madsen (1968) in their article detailing a "Behavioral Approach to Music Therapy." Also relevant to the bio-guided approach are two of the three methods presented by Wigram, Pedersen & Bonde, physiological responses to music, including vibro-acoustic therapy, and music in medicine. The theoretical basis for the bio-guided approach could be construed as within the scope of bio-medical music therapy (Taylor, 1997) and related conceptually in some ways to Michael Thaut's Neurologic Music Therapy, (Thaut, 2008).

Where bio-guided music therapy departs from other approaches is that the client's physiological data is presented in real-time either musically or visually back to the client or the therapist as part of the therapy session. One might argue that this approach falls squarely within a behaviorist paradigm and as such would be included as part of Behavioral Music Therapy. Conversely, this author suggests the bio-guided approach expands beyond the use of music as cue or as a reward, to the point where physiologically driven tones in real-time contribute to the creation of improvisational music! When utilized at this level, the bio-guided process may be used not only in behavioral approaches, but also in analytic music therapy, and even in guided imagery models similar to Helen Bonny's GIM method (Miller, 2011). In this model, music has the potential to simultaneously be a stimulus, cue, response, reward and creative improvisational product. Some of the target disorders this may be applied to include ADHD, stress and anxiety, depression and addictions.

One significant feature of bio-guided music therapy in this day and age of outcome driven treatment authorizations and pay schedules, is the tangible session graphs it produces. These graphs clearly display physiological variation within a music therapy session in the language of mainstream medicine.

Consider the following graph (Fig. 1). In this assessment example we can see some reversible effects of vocal toning over three 2 minute periods. There is an increase in electrodermal response indicating slightly elevated arousal, accompanied by a decrease in heart rate and increase in healthy heart rate variability during the vocal toning. Note that HRV, while decreasing after the vocal toning, still remains higher at the end than during the initial baseline. Based on this analysis we might continue to utilize toning for the HRV benefits and assign a real-time musical tone to eletrodermal response in order to train for prevention of over-arousal and accompanying anxiety. The musical tone assigned to the electrodermal response may be set to a key, note length and scale if the toning is tonally based, for example D harmonic minor.

This kind of data gives the client and music therapist physiological information in the moment, that may assist in guiding the therapeutic process. This information may be instructive whether the clinical objective is the physical relief from anxiety, or the psychoanalytic insight from the process of hearing and seeing our physiology in action. In the case of the former, the client uses the real-time data to train his/her nervous system to reduce the physical markers associated with anxiety. An example of the latter is discovery of what archetypal images contribute to the activation of physical anxiety and how that impacts the client's relationships in the here and now. In the practical realm of insurance coverage, charts such as these may help verify the impact of music therapy sessions even when tones are not provided as feedback and the device is simply used as a monitor.

In summary, bio-guided music therapy offers a physiology-based treatment within the bio-medical theoretical model. Physiological data is utilized in real-time by either the client, the therapist or both, to help facilitate clinical goals. This real-time data may be presented in key, scale and tempo for flexibility in musical interaction with the music therapist or group. Resulting charts and graphs document the session in a quantitative manner and may help communicate the impact of music therapy to other medical professionals.

References

Bruscia, K. (1987) Improvisational models of music therapy. Springfield, IL: Charles C. Thomas Publications.

Décosterd, M. L. (2008). Right brain/left brain leadership: Shifting style for maximum impact. Westport, CT, US: Praeger Publishers/Greenwood Publishing Group.

Madsen, C.K., Cotter, V., & Madsen, C.H. (1968). A behavioral approach to music therapy. Journal of Music Therapy, 5, 69–71.

Miller, Eric (2011). Bio-Guided Music Therapy: A practitioner's guide to the clinical integration of music and biofeedback. London: Jessica Kingsley Publishers.

Scartelli, J.P. (1989). Music and self-management methods: A physiological Model. St. Louis: MMB Music Inc.

Szirony, G. M., Pearson, L. C., Burgin, J. S., Murray, G. C., & Elrod, L. M. (2007). Brain hemisphere dominance and vocational preference: A preliminary analysis. Work: Journal of Prevention, Assessment & Rehabilitation, 29(4), 323-329.

Taylor, Dale (1997). Biomedical Foundations of Music as Therapy. St. Louis: MMB.

Thaut, M.H. (2008). Rhythm, Music, and the Brain: Scientific Foundations and Clinical Applications. New York, NY: Taylor and Francis.

Wigram, T., Pedersen, I. N., Ole Bonde, L. (2002). A Comprehensive Guide to Music Therapy. Jessica Kingsly: London.