Embodied Meaning in Musical Gesture Cross-Disciplinary Approaches

Embodied meaning in musical gesture Cross-disciplinary approaches

Porto International Conference on Musical Gesture 17-19 March, 2016

Erik Christensen Aalborg University, Denmark [email protected] https://aalborg.academia.edu/ErikChristensen Listening for embodied meaning

1. Phenomenology 1st, 2nd person 2. Expressive music therapy 1st, 2nd, 3rd person 3. Receptive music therapy 1st, 2nd, 3rd person 4. Neuroscience 3rd person

1.1 Phenomenology - Open Listening 1st & 2nd person

Piece for string quartet 30 seconds Listen twice What did you hear? Tell your neighbor One minute

1.2

Emerson String Quartet

Webern: Bagatelle op. 9, no. 1 0’30

Thomas Clifton 1976, 1983 1.3 Intensive listening: Phenomenological variations

Open listenings Focused listenings: descriptions Hermeneutical listenings: interpretations Dialogues

Christensen 2012: 42-63 1.4 Intensive listening 1st & 2nd person

Multiple repeated listenings: First person descriptions and interpretations

Dialogues: Intersubjective evaluations of the multivariable musical experience

Don Ihde 2007: 29-32, 2012:18-22; Ian Cross 2005:30; Aksnes & Ruud 2008:55 2.1 Expressive music therapy Fra: Erik Christensen [email protected] Emne: Dato: 18. nov. 2015 kl. 22.48 Improvisation, one Tilminute.: Therapist: drums. Autistic boy: cymbal

gesture expression interaction Wigram et al. 2002: 253-256

7 2.2 Methods for description and interpretation of gesture, expression, and interaction 1st, 2nd, 3rd person

Lawrence Ferrara 1984; Even Ruud 1987 Colin Lee 2000; Gro Trondalen 2003, 2007 Overview in Christensen 2012: 26-42 2.3 Expressive music therapy Parent-child improvisation 1st, 2nd, 3rd person

Goal: Assessment and development of parental competences

Jacobsen 2012 Jacobsen, McKinney & Holck 2014 2.4 Method: Interaction analysis Jacobsen 2012:162 3.1 Receptive music therapy Music listening in a relaxed state

GIM: Guided Imagery and Music The client describes music-induced images, memories, body sensations, emotions, narratives

The therapist guides with sparse comments

3.2 Method: Correlations between

Musical gestures and structures

and

Experienced imagery and narrative

Grocke 2007; Bonde 2004: 257-268 4.1 Neuroscience Music listening activates motor planning in Cortex PMA: Premotor Area SMA: Supplementary Motor Area

Zatorre et al. 2007

13 4.2 Neuroscience Music listening activates the Basal Ganglia and Cerebellum

Basal Ganglia Thalamus

Cortex

Hippocampus Cerebellum

Zatorre et al. 2007

14 4.3 Neuroscience method: fMRI scanning during music listening 3rd person

15 4.4 Neuroscience method: EEG 3rd person

16 4.5 Two different kinds of music:

Beat-related music Music in free ﬂow

“The mind is capable of organizing temporal patterns without reference to a beat” (Patel 2008:98)

Beat-related entrainment: Grahn & Rowe 2009 Free ﬂow: Huron 2006:187; Leman et al. 2009 3810 • J. Neurosci., March 9, 2011 • 31(10):3805–3812 Teki et al. • Absolute and Relative Timing of Auditory Rhythmic Sequences

Table 2. Stereotactic MNI coordinates for relative, beat-based timing Brain area Hemisphere x y zt-value Caudate nucleus Right 14 9 18 5.69 Left Ϫ14 6 21 4.32 Putamen Right 23 21 0 4.28 Left Ϫ24 15 Ϫ2 4.55 Internal capsule Right 15 3 6 6.99 Left Ϫ15 3 12 3.16 Thalamus Right 9 Ϫ15 12 6.44 Left Ϫ9 Ϫ21 12 6.06 Pre-SMA/SMA Right 15 6 64 12.61 Left Ϫ2 Ϫ3 67 6.61 Premotor cortex Right 38 Ϫ6 60 8.04 Left Ϫ41 5 51 5.53 Dorsolateral prefrontal cortex Right 35 9 31 4.62 Left Ϫ38 18 25 5.30 Superior temporal gyrus Right 66 Ϫ39 3 5.82 Left Ϫ41 Ϫ30 9 6.72 Local maxima for relative, beat-based timing are shown at p Ͻ 0.001 (uncorrected).4.6 Two networks for auditory timing tasks such as duration discrimination and “emergent timing” as being associated with the processing of a temporal regularity or a beat in the sequence to be timed. The authors suggested that tasks requiring an explicit or discrete representation of time intervals such as the temporal control of a series of discrete movements involve the cerebellum and that temporal control of rhythmic and continuous movements mightBeat-based: be subserved by cortical networks and not the cerebellum (Spencer et al., 2003). Comple- mentary to this dissociationCortex in timing of movements, here we report a functional dissociation in perceptual timing with no explicit linked motor output such as tapping.

Role of the olivocerebellar systemBasal ganglia The inferior olive has remarkable cellular and network properties that make it an ideal generator of temporal patterns (Yarom and Cohen, 2002; Jacobson et al., 2008). The intrinsic voltage-gated conductances present in olivary neurons sustainThalamus rhythmic sub- threshold membrane potential oscillations at ϳ5–15 Hz and en- able them to generate a timing signal (Llina´s and Yarom, 1981). Figure 5. Dissociation between neural substrates underlying absolute and relative timing. These oscillations are synchronized by electrical coupling be- A,Duration-based: Glass brain image in MNI space showing activations for absolute, duration-based timing tween the olivary cells and organize them into temporally co- (irregularvsregular)atat-valuethresholdof4.00andanextentthresholdof10voxels.B,Glass brain image in MNI space showing activations for relative, beat-based timing (regular vs irreg- herent groups (Llinas et al., 1974). The electrical coupling ular) at a t-value Brainstem threshold of 4.00 and an extent nuclei threshold of 10 voxels. C, Activations for coefficient is controlled by GABAergic projections from the absolutetimingaredepictedinyellow,andactivationsforrelativetimingareshowningreenon deep cerebellar nuclei, which synapse directly on the gap junc- asagittalsectionoftheaveragenormalizedstructuralimageat Cerebellumxϭϩ7mmandathresholdof tions between olivary cells andTeki organize et them al. into2011, dynamic, 2012pϽ0.01(uncorrected)toshowthecleardifferencesinthebrainbasesforabsoluteandrelative functional subgroups. The deep cerebellar nuclei receive in- timing, respectively. hibitory input from the cerebellar Purkinje cells, which in turn receive climbing fiber afferents from the olivary cells, thus forming a dynamic network capable of producing accurate mediating long-term depression of the parallel fiber input to the timing signals (Welsh et al., 1995). Purkinje cells (Ito et al., 1982). Together, these results suggest a Inferior olive activity has been reported previously in fMRI possible role for the olivocerebellar system in detecting errors in studies of perceptual timing based on visual sequences (Xu et al., the regular operation of a beat-based timer in the striatum. 2006; Liu et al., 2008). Here, we observed significant inferior olive In addition to the inferior olive, we found strong activa- activation for auditory timing of irregular sequences without an tions in the cerebellum, which has been widely implicated in apparent beat in contrast to the timing of regular sequences with interval timing (Ivry and Keele, 1989; Nichelli et al., 1996; Ivry an isochronous beat. Xu et al. (2006) found similar inferior olive et al., 2002; Grube et al., 2010a,b). Its specific role in absolute, activity in a perceptual timing task when they contrasted timing duration-based timing was demonstrated in patients with of metrical rhythmic sequences to timing of isochronous se- spinocerebellar ataxia type 6 by Grube et al. (2010a), who used quences. Moreover, the inferior olive has been suggested to me- a battery of auditory timing tasks based on duration-based or diate adaptive timing of the classically conditioned, eye-blink beat-based timing mechanisms and found a significant im- response and the vestibulo-ocular reflex (Ito et al., 1970). The pairment only on the duration-based timing tasks (e.g., com- sole source of climbing fiber input to the Purkinje cells, the infe- paring the absolute duration of single intervals) and not on rior olive has been shown to subserve error-based learning by relative timing of rhythmic sequences based on a regular beat. 5. Suggestions for Cross-disciplinary approaches 5.1. Cross-disciplinary approach

Extending studies of guqin music to neuroscience

Henbing & Leman 2007, Leman et al. 2009 5.2 Cross-disciplinary approach Neuroscience and music therapy

Systematic comparisons in fMRI: Predominant gestural music in free ﬂow versus Predominant beat-related music including audio and video recordings of music therapy improvisations, music from different continents, contemporary art music 5.3 Cross-disciplinary approach Phenomenology, linguistics, sound analysis, neuroscience

Comparison of gestural timing in music and spoken language

Kotz & Schwartze 2010; Schwartze et al. 2013 Interacting Brains Synchronize

5.4 Cross-disciplinary approach Music therapy and neuroscience: Dual EEG

Dumas et al. 2010

Figure 3. Brain synchronization: online example. Samples of spontaneous imitation episodes in the dyad nu3 showing the correspondence between interactional synchrony and brain activities. The green areas indicate periods where subjects were behaviorally synchronized and the red ones periods without behavioral synchrony. A. Time course of normalized EEG signal filtered in the alpha-mu frequency band for the channels P8 of both subjects. These channels are members of the cluster shown in figure 2A. B. Phase extracted from the signals. C. PLV calculated with sliding centred time windows of 800ms length in the alpha-mu band (related to A and B) quantifying the neural synchronization between the two subjects. Beta band PLV for the same electrodes is also shown in dashed line. D. Time course of normalized EEG signal filtered in alpha-mu frequency band for the channels PO2 in Subject 1 and Cz in Subject 2. Those channels are not members of any clusters. E. Phase extracted from the signals. F. PLV calculated with sliding centred time windows of 800ms length in the alpha-mu band (related to D and E) quantifying the neural synchronization between the two subjects. Beta band PLV for the same electrodes is also shown in dashed line. G Representation of the pairs of electrodes P8-P8 (A,B,C) and PO2-Cz (D,E,F). doi:10.1371/journal.pone.0012166.g003

The comparison between synchronized and non synchronized social coordination [19]. The symmetrical pattern found for the acts showed statistical differences in interbrain phase synchronies model and the imitator possibly reflects a coordinated dynamics of for all frequency bands analyzed (alpha-mu, beta, and gamma) hand movements. The pattern however became asymmetrical in except for the theta band. Designing specific interbrain statistical the higher frequency bands and should be seen as a brain-to-brain analyses, we were able to show that the alpha-mu rhythm was the top-down modulation reflecting the differential roles of model and most robust interbrain oscillatory activity discriminating behav- imitator. This is consistent with motor transient activities involved ioral synchrony vs. non synchrony in the centroparietal regions of in the beta band [57] and the implication of gamma in attentional the two interacting partners. The alpha-mu band is considered as processes, perceptual awareness and cognitive control [34,58]. a neural correlate of the mirror neuron system functioning [57]. The other contrasts performed complement these findings. The Specific frequencies of this band (9.2–11.5 Hz) over the right absence of a significant difference between imitative and non- Inter-brain research:centroparietal Konvalinka region have been & proposed Roepstorff as a neuromarker of2012;imitative DeVos episodes during et spontaneous al. 2014 imitation assesses that

PLoS ONE | www.plosone.org 7 August 2010 | Volume 5 | Issue 8 | e12166 23 Thank you for listening!

What are your questions and suggestions? References

Aksnes, H. & Ruud, E. (2008). Body-based schemata in receptive music therapy. Musicae Scientiae 12 (1), 49-74. Bonde, L.O. (2004). The Bonny Method of Guided Imagery and Music (BMGIM) with Cancer Survivors. PhD Dissertation, Aalborg University. Available at http://www.mt-phd.aau.dk/phd-theses/ Christensen, E. (2012). Music Listening, Music Therapy, Phenomenology and Neuroscience. PhD Thesis, Aalborg University. Available at http://www.mt-phd.aau.dk/phd-theses/ Clifton, T. (1976). Music as constituted object. Music and Man 2, 73-98. Clifton, T. (1983). Music as Heard. A Study in Applied Phenomenology. New Haven: Yale University Press. Cross, I. (2005). Music and meaning, ambiguity and evolution. In Miell, D., MacDonald, R. and Hargreaves, D.J. (eds.) Musical Communication. Oxford: Oxford University Press, 27-43. DeVos, M., Gandras, K., and Debener, S. (2014). Towards a truly mobile auditory brain – computer interface: Exploring the P300 to take away. International Journal of Psychophysiology 91, 46–53. Dumas, G., Nadel, J., Soussignan, R., Martinerie, J. & Garnero, L. (2010). Inter-Brain Synchronization during Social Interaction. PLoS ONE 5(8): e12166. doi:10.1371/journal.pone.0012166 Ferrara, L. (1984). Phenomenology as a Tool for Musical Analysis. Musical Quarterly 70 (3), 355-373.

25 Grahn, J.A. & Rowe, J.B. (2009). Feeling the Beat: Premotor and Striatal Interactions in Musicians and Nonmusicians during Beat Perception. The Journal of Neuroscience 29 (23), 7540 –7548. Grocke, D.E. (2007). A Structural Model of Music Analysis. In Wosch, T. & Wigram, T. (eds.) Microanalysis in Music Therapy. London: Jessica Kingsley, 149-161. Henbing, L. & Leman, M. (2007) A Gesture-based Typology of Sliding-tones in Guqin Music. Journal of New Music Research 36 (2), 61-82. DOI: 10.1080/09298210701755073 Huron, D. (2006). Sweet Anticipation. Music and the Psychology of Expectation. Cambridge, Massachusetts: The MIT Press. Ihde, D. (2007). Listening and Voice. Phenomenologies of Sound. 2nd edition. Albany, NY: State University of New York Press. Ihde, D. (2012). Experimental Phenomenology: multistabilities. 2nd edition. Albany, NY: State University of New York Press. Jacobsen, S.L. (2012). Music Therapy Assessment and Development of Parental Competences in Families Where Children Have Experienced Emotional Neglect. PhD Thesis, Aalborg University. Available at http://www.mt-phd.aau.dk/phd-theses/ Leman, M., Desmet, F., Styns, F., van Noorden, L. & Moelants, D. (2009). Sharing musical expression through embodied listening: A case study based on Chinese Guqin music. Music Perception 26 (3), 263-278.

26 Jacobsen, S.L., McKinney, C.H. & Holck, U. (2014). Effects of a Dyadic Music Therapy Intervention on Parent-Child Interaction, Parent Stress, and Parent-Child Relationship in Families with Emotionally Neglected Children: A Randomized Controlled Trial. Journal of Music Therapy 51 (4), 310–332. doi:10.1093/jmt/thu028 Konvalinka, I., and Roepstorff, A. (2012). The two-brain approach: how can mutually interacting brains teach us something about social interaction? Frontiers in human neuroscience, Vol. 6, Article 215. http://dx.doi.org/10.3389/fnhum.2012.00215 Kotz, S.A. & Schwartze, M. (2010). Cortical speech processing unplugged: a timely subcortico- cortical framework. Trends in Cognitive Sciences 14 (2010) 392–399. doi:10.1016/j.tics.2010.06.005 Lee, C. (2000). A Method of Analyzing Improvisations in Music Therapy. Journal of Music Therapy 37(2),147-167. Lindenberger, U., Li, S-C., Gruber, W., and Müller, V. (2009). Brains swinging in concert: cortical phase synchronization while playing guitar. BMC Neuroscience 10(22). doi:10.1186/1471-2202-10-22 Magee, W.L. & Stewart, L. (2015). The challenges and beneﬁts of a genuine partnership between Music Therapy and Neuroscience: a dialog between scientist and therapist. Frontiers in Human Neuroscience Volume 9, Article 223, 1-4. doi: 10.3389/fnhum.2015.00223 Moens, B. & Leman, M. (2015). Alignment strategies for the entrainment of music and movement rhythms. Annals of the New York Academy of Sciences 1337, 86–93. Ruud, E. (1987). Musikk som kommunikasjon og samhandling.Teoretiske perspektiv på musikkterapien. [Music as communication and interaction. Theoretical perspectives of music therapy]. Doctoral Dissertation. Oslo: Universitetet i Oslo, Institut for musikkvitenskap.

27 Schwartze, M., Farrugia, N. & Kotz, S.A. (2013). Dissociation of formal and temporal predictability in early auditory evoked potentials. Neuropsychologia 51, 320–325. Teki, S., Grube, M., Kumar, S. & Griffiths, T.D. (2011). Distinct Neural Substrates of Duration-Based and Beat-Based Auditory Timing. The Journal of Neuroscience 31(10), 3805–3812. Teki, S., Grube, M. & Griffiths, T.D. (2012). A unified model of time perception accounts for duration-based and beat-based timing mechanisms. Frontiers in Integrative Neuroscience 5, Article 90, 1-7. Trondalen, G. (2003). ’Self-Listening’ in Music Therapy with a Young Woman Suffering from Anorexia Nervosa. Nordic Journal of Music Therapy 12 (1), 3-17. Trondalen, G. (2007). A Phenomenologically Inspired Approach to Microanalyses of Improvisation in Music Therapy. In Wosch, T. & Wigram, T. (eds.). Microanalysis in Music Therapy. London: Jessica Kingsley, 198-210 Wigram, T., Pedersen, I.N., & Bonde, L.O. (2002). A Comprehensive Guide to Music Therapy. London: Jessica Kingsley. Zatorre, R.J. et al. (2007). When the brain plays music: auditory-motor interactions in music perception and production. Nature Reviews Neuroscience 8 (4), 494-521.