Ala-Ruona, Esa

Bonde, Lars Ole

Fachner, Jörg

    Aalborg UniversitetGuided Imagery and MusicFachner, Jörg ; Ala-Ruona, Esa; Bonde, Lars OlePublished in:Proceedings of the Ninth Triennial Conference of the European Society for the Cognitive Sciences of Music, 17-22 August 2015, Manchester, UK Ginsborg, J., Lamont, A., Phillips, M., Bramley, S. (Editors)Publication date:2015Document VersionOgså kaldet Forlagets PDFLink to publication from Aalborg UniversityCitation for published version (APA):Fachner, J., Ala-Ruona, E., & Bonde, L. O. (2015). Guided Imagery and Music: A neurometric EEG/Loreta CaseStudy. I Proceedings of the Ninth Triennial Conference of the European Society for the Cognitive Sciences ofMusic, 17-22 August 2015, Manchester, UK Ginsborg, J., Lamont, A., Phillips, M., Bramley, S. 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You may freely distribute the URL identifying the publication in the public portal ?Take down policyIf you believe that this document breaches copyright please contact us at vbn@aub.aau.dk providing details, and we will remove access tothe work immediately and investigate your claim.Downloaded from vbn.aau.dk on: April 30, 2017Proceedings of the Ninth Triennial Conference of the European Society for the Cognitive Sciences of Music, 17-22 August 2015, Manchester, UK Ginsborg, J., Lamont, A., Phillips, M., Bramley, S. (Editors)   Guided imagery in music - A neurometric EEG/LORETA case study Jörg Fachner,*1 Esa Ala-Ruona #2 Lars Ole Bonde +3 *Department of Music and Performing Arts., Anglia Ruskin University, Cambridge, UK #Finish Centre of Interdisciplinary Music Research., University of Jyvaskyla, Finland +Department of Communication and Psychology, Aalborg University, Denmark 1jorg.fachner@anglia.ac.uk, 2esa.ala-ruona@jyu.fi, 3lobo@hum.aau.dk  ABSTRACT Background Musical imagery research investigates imagination of intervals, melodies and other musical elements in order to compare them to the listening process (Hubbard, 2010). This may include any imagery of sound and music where there is no physical source, e.g. when conductors study scores or composers compose without piano. Visual imagery plays an important role in music-induced emotions, especially when music is combined with narrative descriptions (Eerola & Vuoskoski, 2013). In search of invariants of altered state of consciousness (ASC) Dittrich (1998) described visual restructuring and auditory alterations as core ingredients of an ASC. Listening to music can completely absorb people, cutting off other sensory input, but absorption skills seem to be linked to music preference, imagery, hypnotisability and intensity of emotions evoked (Kreutz, Ott, Teichmann, Osawa, & Vaitl, 2008; Schäfer, Fachner, & Smukalla, 2013 ; Snodgrass & Lynn, 1989). In the Bonny Method of Guided Imagery and Music (GIM) a client describes images, feelings, or thoughts that occur spontaneously while eyes-closed listening to special music programs in an induced ASC (Bonny & Savary, 1973). Commonly, certain passages during the imagery process will have pivotal meaning for the traveller and become a focus in the therapy process (Grocke, 1999). Imagery is diverse including visual, auditory, somatic, direct memories, involuntary and unbidden imagery, images of significant people, places and events from the person’s history 5. Aims Here we are interested how spontaneously evoked and guided imagery in connection to music and ASC is processed. What happens in the brain during ASC and imagery processes of pivotal moments in GIM? Method A typical GIM session comprises an initial discussion of the client’s concerns, and a focus for the music and imagery experience. The therapist provides a relaxation induction for the client who reclines with eyes closed. The therapist chooses a pre-determined music program, or spontaneously chooses music to match the client’s imagery. As the music plays the client describes any imagery, feeling, or thoughts.  The EEG of an experienced GIM traveler was recorded during rest, ASC induction and listening (Imagery – music progam). EEG data (Power, Asymmetry) was compared (z-scores) against a normative EEG/LORETA database (John, 1989; Thatcher, Biver, & North, 2009) investigating artifact free rest, ASC and pivotal parts of the music listening preceding verbal response. Verbal responses were analysed separately and GIM EEG data was chosen based on the ratings of an independent GIM therapist.  Results A difference between rest and ASC induction indicated a state change on lower alpha (8-10 Hz). Z-scored LORETA Alpha1 power 8+9Hz bins exhibited highest z-score values in cuneus (8Hz) and precuneus (9Hz). Z-Scored LORETA power differences (inter-individual rest – ASC) were most prominent in Brodmann Area (BA) 23 (8Hz) and BA 31 (9Hz) indicating involvement of cuneus and posterior cingulate in state changes. Verbal GIM responses elicited two nodes of interest. During pivotal music listening one node exhibited a high beta anterior left temporal (T5) asymmetry decrease (resembling the ASC induction topography), while z-LORETA current density values increased in BA 37 (Left inferior / Middle temporal lobe on 21-30Hz). On lower Alpha right parietal z-score power values and z-LORETA current density increased in pre-cuneus (resembling the ASC pattern). Conclusions ASC seem to be of importance for GIM and seems to influence the music listening process. ASC related change indicates connection to visual imagery processing during GIM Music listening. Keywords Guided imagery, musical imagery, music listening, altered states of consciousness, Neurometrics, EEG, alpha1, beta, topography, asymmetry, cuneus, pre-cuneus REFERENCES Bonny, H. L., & Savary, L. M. (1973). Music and your mind. Listening with a new consciousness. New York: Harper & Row. Dittrich, A. (1998). The standardized psychometric assessment of altered states of consciousness (ASCs) in humans. Pharmacopsychiatry, 31 Suppl 2, 80-84.  Eerola, T., & Vuoskoski, J. K. (2013). A Review of Music and Emotion Studies: Approaches, Emotion Models, and Stimuli. Music Perception: An Interdisciplinary Journal, 30(3), 307-340.  Grocke, D. E. (1999). Pivotal Moments in Guided Imagery and Music. In J. Hibben (Ed.), Inside Music Therapy: Client Experiences (pp. 295-305). Gilsum, NH: Barcelona. Hubbard, T. L. (2010). Auditory imagery: Empirical findings. Psychological Bulletin, 136(2), 302.  John, E. R. (1989). The role of quantitative EEG topographic mapping or 'neurometrics' in the diagnosis of psychiatric and neurological Proceedings of the Ninth Triennial Conference of the European Society for the Cognitive Sciences of Music, 17-22 August 2015, Manchester, UK Ginsborg, J., Lamont, A., Phillips, M., Bramley, S. (Editors)   disorders: the pros. Electroenceph. Clin. Neurophysiol., 73(1), 2-4.  Kreutz, G., Ott, U., Teichmann, D., Osawa, P., & Vaitl, D. (2008). Using music to induce emotions: Influences of musical preference and absorption. [Psychology of Music]. Psychology of music, 36(1), 101-126. doi: 10.1177/0305735607082623 Schäfer, T., Fachner, J., & Smukalla, M. (2013 ). Changes in the representation of space and time while listening to music. Front Psychol, 4(508). doi: 10.3389/fpsyg.2013.00508 Snodgrass, M., & Lynn, S. J. (1989). Music absorption and hypnotizability. Int J Clin Exp Hypn, 37(1), 41-54.  Thatcher, R. W., Biver, C., & North, D. (2009). Neuroguide (Version 2.5.6). St Petersburg: http://www.appliedneuroscience.com. Retrieved from http://www.appliedneuroscience.com    

Guided Imagery and Music:A neurometric EEG/Loreta Case Study

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Guided Imagery and Music:A neurometric EEG/Loreta Case Study

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