title: ECoG high gamma activity reveals distinct cortical representations of lyrics passages, harmonic and timbre-related changes in a rock song.
abstract: Listening to music moves our minds and moods, stirring interest in its neural underpinnings. A multitude of compositional features drives the appeal of natural music. How such original music, where a composer's opus is not manipulated for experimental purposes, engages a listener's brain has not been studied until recently. Here, we report an in-depth analysis of two electrocorticographic (ECoG) data sets obtained over the left hemisphere in ten patients during presentation of either a rock song or a read-out narrative. First, the time courses of five acoustic features (intensity, presence/absence of vocals with lyrics, spectral centroid, harmonic change, and pulse clarity) were extracted from the audio tracks and found to be correlated with each other to varying degrees. In a second step, we uncovered the specific impact of each musical feature on ECoG high-gamma power (70-170 Hz) by calculating partial correlations to remove the influence of the other four features. In the music condition, the onset and offset of vocal lyrics in ongoing instrumental music was consistently identified within the group as the dominant driver for ECoG high-gamma power changes over temporal auditory areas, while concurrently subject-individual activation spots were identified for sound intensity, timbral, and harmonic features. The distinct cortical activations to vocal speech-related content embedded in instrumental music directly demonstrate that song integrated in instrumental music represents a distinct dimension in complex music. In contrast, in the speech condition, the full sound envelope was reflected in the high gamma response rather than the onset or offset of the vocal lyrics. This demonstrates how the contributions of stimulus features that modulate the brain response differ across the two examples of a full-length natural stimulus, which suggests a context-dependent feature selection in the processing of complex auditory stimuli.
authors.affiliation: Berlin School of Mind and Brain, Humboldt Universität zu Berlin Berlin, Germany ; Neurotechnology Group, Department of Electrical Engineering and Computer Science, Berlin Institute of Technology Berlin, Germany ; Neurophysics Group, Department of Neurology and Clinical Neurophysiology, Charité - University Medicine Berlin Berlin, Germany.
authors.forename: Irene
authors.initials: I
authors.lastname: Sturm
authors.affiliation: Neurotechnology Group, Department of Electrical Engineering and Computer Science, Berlin Institute of Technology Berlin, Germany ; Bernstein Focus: Neurotechnology Berlin, Germany.
authors.forename: Benjamin
authors.initials: B
authors.lastname: Blankertz
authors.affiliation: National Resource Center for Adaptive Neurotechnologies, Wadsworth Center, New York State Department of Health Albany, NY, USA ; Department of Electrical and Computer Engineering, University of Texas at El Paso El Paso, TX, USA.
authors.forename: Cristhian
authors.initials: C
authors.lastname: Potes
authors.affiliation: National Resource Center for Adaptive Neurotechnologies, Wadsworth Center, New York State Department of Health Albany, NY, USA ; Department of Electrical and Computer Engineering, University of Texas at El Paso El Paso, TX, USA ; Department of Neurosurgery, Washington University in St. Louis St. Louis, MO, USA ; Department of Biomedical Engineering, Rensselaer Polytechnic Institute Troy, NY, USA ; Department of Neurology, Albany Medical College Albany, NY, USA ; Department of Neurosurgery, Washington University in St. Louis St. Louis, MO, USA.
authors.forename: Gerwin
authors.initials: G
authors.lastname: Schalk
authors.affiliation: Berlin School of Mind and Brain, Humboldt Universität zu Berlin Berlin, Germany ; Neurophysics Group, Department of Neurology and Clinical Neurophysiology, Charité - University Medicine Berlin Berlin, Germany ; Bernstein Focus: Neurotechnology Berlin, Germany.
authors.forename: Gabriel
authors.initials: G
authors.lastname: Curio
keywords: acoustic features; electrocorticography (ECoG); high gamma; music processing; natural music