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RESEARCH PRODUCT
Coupling of Action-Perception Brain Networks during Musical Pulse Processing: Evidence from Region-of-Interest-Based Independent Component Analysis
Iballa BurunatValeri TsatsishviliElvira BratticoPetri Toiviainensubject
Speech recognitionMusiciansRhythm perceptionBehavioral Neuroscience0302 clinical medicinemedia_commonOriginal ResearchmuusikotFunctional integration (neurobiology)medicine.diagnostic_test05 social sciencesmusicianscerebral structurePulse (music)Psychiatry and Mental healthNeuropsychology and Physiological PsychologyNeurologyforecaststa6131Psychologyaivotcerebellar structureärsykkeetmedia_common.quotation_subjectbrainAuditory areamusiikkinaturalisticta3112rhythmbehavioral disciplines and activities050105 experimental psychologylcsh:RC321-57103 medical and health sciencesRhythmRegion of interestPerceptionmedicine0501 psychology and cognitive sciencesmusicstimuli (role related to effect)lcsh:Neurosciences. Biological psychiatry. NeuropsychiatryBiological Psychiatryfunctional magnetic resonance imaging (fMRI)ennusteetIndependent Component Analysis (ICA)predictionIndependent component analysisrytmirhythm perceptionFunctional magnetic resonance imagingindependent component analysis (ICA)030217 neurology & neurosurgeryNeurosciencedescription
Our sense of rhythm relies on orchestrated activity of several cerebral and cerebellar structures. Although functional connectivity studies have advanced our understanding of rhythm perception, this phenomenon has not been sufficiently studied as a function of musical training and beyond the General Linear Model (GLM) approach. Here, we studied pulse clarity processing during naturalistic music listening using a data-driven approach (independent component analysis; ICA). Participants’ (18 musicians and 18 controls) functional magnetic resonance imaging (fMRI) responses were acquired while listening to music. A targeted region of interest (ROI) related to pulse clarity processing was defined, comprising auditory, somatomotor, basal ganglia, and cerebellar areas. The ICA decomposition was performed under different model orders, i.e., under a varying number of assumed independent sources, to avoid relying on prior model order assumptions. The components best predicted by a measure of the pulse clarity of the music, extracted computationally from the musical stimulus, were identified. Their corresponding spatial maps uncovered a network of auditory (perception) and motor (action) areas in an excitatory-inhibitory relationship at lower model orders, while mainly constrained to the auditory areas at higher model orders. Results revealed (a) a strengthened functional integration of action-perception networks associated with pulse clarity perception hidden from GLM analyses, and (b) group differences between musicians and non-musicians in pulse clarity processing, suggesting lifelong musical training as an important factor that may influence beat processing. peerReviewed
year | journal | country | edition | language |
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2017-05-01 | Frontiers in Human Neuroscience |