Embodied meaning in musical gestureCross-disciplinary approaches

Porto International Conference on Musical Gesture17-19 March, 2016

Erik ChristensenAalborg University, Denmark

erc@timespace.dkhttps://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 person4. Neuroscience 3rd person

Piece for string quartet 30 secondsListen twiceWhat did you hear?Tell your neighbor One minute

1.1 Phenomenology - Open Listening1st & 2nd person

Emerson String Quartet

Webern: Bagatelle op. 9, no. 1 0’30

Thomas Clifton 1976, 1983

1.2

1.3 Intensive listening: Phenomenological variations

Open listeningsFocused listenings: descriptionsHermeneutical listenings: interpretationsDialogues

Christensen 2012: 42-63

1.4 Intensive listening1st & 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

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2.1 Expressive music therapy Improvisation, one minute. Therapist: drums. Autistic boy: cymbal

Fra: Erik Christensen erc@timespace.dkEmne:Dato: 18. nov. 2015 kl. 22.48

Til:

Wigram et al. 2002: 253-256

gesture expression interaction

2.2 Methods for description and interpretationof gesture, expression, and interaction1st, 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 therapyParent-child improvisation1st, 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 therapyMusic 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

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4.1 NeuroscienceMusic listening activates motor planning in Cortex PMA: Premotor Area SMA: Supplementary Motor Area

Zatorre et al. 2007

4.2 NeuroscienceMusic listening activates the Basal Ganglia and Cerebellum

Basal Ganglia Thalamus

Hippocampus Cerebellum

Cortex

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Zatorre et al. 2007

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

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4.4 Neuroscience method: EEG 3rd person

4.5 Two different kinds of music:

Beat-related musicMusic 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

tasks such as duration discrimination and “emergent timing” asbeing associated with the processing of a temporal regularity or abeat in the sequence to be timed. The authors suggested that tasksrequiring an explicit or discrete representation of time intervalssuch as the temporal control of a series of discrete movementsinvolve the cerebellum and that temporal control of rhythmicand continuous movements might be subserved by cortical net-works and not the cerebellum (Spencer et al., 2003). Comple-mentary to this dissociation in timing of movements, here wereport a functional dissociation in perceptual timing with noexplicit linked motor output such as tapping.

Role of the olivocerebellar systemThe inferior olive has remarkable cellular and network propertiesthat make it an ideal generator of temporal patterns (Yarom andCohen, 2002; Jacobson et al., 2008). The intrinsic voltage-gatedconductances present in olivary neurons sustain rhythmic sub-threshold membrane potential oscillations at !5–15 Hz and en-able them to generate a timing signal (Llinas and Yarom, 1981).These oscillations are synchronized by electrical coupling be-tween the olivary cells and organize them into temporally co-herent groups (Llinas et al., 1974). The electrical couplingcoefficient is controlled by GABAergic projections from thedeep cerebellar nuclei, which synapse directly on the gap junc-tions between olivary cells and organize them into dynamic,functional subgroups. The deep cerebellar nuclei receive in-hibitory input from the cerebellar Purkinje cells, which in turnreceive climbing fiber afferents from the olivary cells, thusforming a dynamic network capable of producing accuratetiming signals (Welsh et al., 1995).

Inferior olive activity has been reported previously in fMRIstudies of perceptual timing based on visual sequences (Xu et al.,2006; Liu et al., 2008). Here, we observed significant inferior oliveactivation for auditory timing of irregular sequences without anapparent beat in contrast to the timing of regular sequences withan isochronous beat. Xu et al. (2006) found similar inferior oliveactivity in a perceptual timing task when they contrasted timingof metrical rhythmic sequences to timing of isochronous se-quences. Moreover, the inferior olive has been suggested to me-diate adaptive timing of the classically conditioned, eye-blinkresponse and the vestibulo-ocular reflex (Ito et al., 1970). Thesole source of climbing fiber input to the Purkinje cells, the infe-rior olive has been shown to subserve error-based learning by

mediating long-term depression of the parallel fiber input to thePurkinje cells (Ito et al., 1982). Together, these results suggest apossible role for the olivocerebellar system in detecting errors inthe regular operation of a beat-based timer in the striatum.

In addition to the inferior olive, we found strong activa-tions in the cerebellum, which has been widely implicated ininterval timing (Ivry and Keele, 1989; Nichelli et al., 1996; Ivryet al., 2002; Grube et al., 2010a,b). Its specific role in absolute,duration-based timing was demonstrated in patients withspinocerebellar ataxia type 6 by Grube et al. (2010a), who useda battery of auditory timing tasks based on duration-based orbeat-based timing mechanisms and found a significant im-pairment only on the duration-based timing tasks (e.g., com-paring the absolute duration of single intervals) and not onrelative timing of rhythmic sequences based on a regular beat.

Table 2. Stereotactic MNI coordinates for relative, beat-based timing

Brain area Hemisphere x y z t-value

Caudate nucleus Right 14 9 18 5.69Left "14 6 21 4.32

Putamen Right 23 21 0 4.28Left "24 15 "2 4.55

Internal capsule Right 15 3 6 6.99Left "15 3 12 3.16

Thalamus Right 9 "15 12 6.44Left "9 "21 12 6.06

Pre-SMA/SMA Right 15 6 64 12.61Left "2 "3 67 6.61

Premotor cortex Right 38 "6 60 8.04Left "41 5 51 5.53

Dorsolateral prefrontal cortex Right 35 9 31 4.62Left "38 18 25 5.30

Superior temporal gyrus Right 66 "39 3 5.82Left "41 "30 9 6.72

Local maxima for relative, beat-based timing are shown at p # 0.001 (uncorrected).

Figure 5. Dissociation between neural substrates underlying absolute and relative timing.A, Glass brain image in MNI space showing activations for absolute, duration-based timing(irregular vs regular) at a t-value threshold of 4.00 and an extent threshold of 10 voxels. B, Glassbrain image in MNI space showing activations for relative, beat-based timing (regular vs irreg-ular) at a t-value threshold of 4.00 and an extent threshold of 10 voxels. C, Activations forabsolute timing are depicted in yellow, and activations for relative timing are shown in green ona sagittal section of the average normalized structural image at x $%7 mm and a threshold ofp # 0.01 (uncorrected) to show the clear differences in the brain bases for absolute and relativetiming, respectively.

3810 • J. Neurosci., March 9, 2011 • 31(10):3805–3812 Teki et al. • Absolute and Relative Timing of Auditory Rhythmic Sequences

4.6 Two networks for auditory timing

Beat-based:Cortex

Basal ganglia

Thalamus

Duration-based: Brainstem nuclei Cerebellum

Teki et al. 2011, 2012

5. Suggestions for Cross-disciplinary approaches

5.1. Cross-disciplinary approach

Extending studiesof guqin music to neuroscience

Henbing & Leman 2007, Leman et al. 2009

5.2 Cross-disciplinary approachNeuroscience and music therapy Systematic comparisons in fMRI: Predominant gestural music in free flowversusPredominant beat-related music

including audio and video recordings of music therapy improvisations,music from different continents,contemporary art music

5.3 Cross-disciplinary approachPhenomenology, linguistics, sound analysis, neuroscience

Comparison of gestural timing in music and spoken language

Kotz & Schwartze 2010; Schwartze et al. 2013

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The comparison between synchronized and non synchronizedacts showed statistical differences in interbrain phase synchroniesfor all frequency bands analyzed (alpha-mu, beta, and gamma)except for the theta band. Designing specific interbrain statisticalanalyses, we were able to show that the alpha-mu rhythm was themost robust interbrain oscillatory activity discriminating behav-ioral synchrony vs. non synchrony in the centroparietal regions ofthe two interacting partners. The alpha-mu band is considered asa neural correlate of the mirror neuron system functioning [57].Specific frequencies of this band (9.2–11.5 Hz) over the rightcentroparietal region have been proposed as a neuromarker of

social coordination [19]. The symmetrical pattern found for themodel and the imitator possibly reflects a coordinated dynamics ofhand movements. The pattern however became asymmetrical inthe higher frequency bands and should be seen as a brain-to-braintop-down modulation reflecting the differential roles of model andimitator. This is consistent with motor transient activities involvedin the beta band [57] and the implication of gamma in attentionalprocesses, perceptual awareness and cognitive control [34,58].

The other contrasts performed complement these findings. Theabsence of a significant difference between imitative and non-imitative episodes during spontaneous imitation assesses that

Figure 3. Brain synchronization: online example. Samples of spontaneous imitation episodes in the dyad nu3 showing the correspondencebetween interactional synchrony and brain activities. The green areas indicate periods where subjects were behaviorally synchronized and the redones periods without behavioral synchrony. A. Time course of normalized EEG signal filtered in the alpha-mu frequency band for the channels P8 ofboth subjects. These channels are members of the cluster shown in figure 2A. B. Phase extracted from the signals. C. PLV calculated with slidingcentred 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 forthe 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. PLVcalculated with sliding centred time windows of 800ms length in the alpha-mu band (related to D and E) quantifying the neural synchronizationbetween 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

Interacting Brains Synchronize

PLoS ONE | www.plosone.org 7 August 2010 | Volume 5 | Issue 8 | e12166

5.4 Cross-disciplinary approachMusic therapy and neuroscience: Dual EEG

Dumas et al. 2010

Inter-brain research: Konvalinka & Roepstorff 2012; DeVos et al. 2014

Thank you for listening!

What are your questions and suggestions?

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References

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