Toward an objective neurophysiological measure of musical engagement
Abstract/Contents
- Abstract
- Engaging listeners is an inherent goal of music. The concept of 'musical engagement', however, carries multiple connotations and remains difficult to quantify or even define. In particular, an objective measure of musical engagement is lacking. Over past decades, cortical responses have been used to investigate processing of music. While these responses are objective and can be recorded in real time, they suffer from a low signal-to-noise ratio and reflect, at best, an abstraction of the corresponding stimuli. As a result, approaches to this research have historically focused primarily on controlled stimuli with limited ecological validity, and event-related averaging of responses, which requires short stimulus epochs and numerous stimulus presentations. Responses to real-world stimuli have proven challenging to analyze and interpret. How can we move beyond these limitations to derive a measure of engagement with 'real' music (i.e., naturalistic and complete musical works) from the brain response? In this thesis, we address these limitations by introducing a novel analysis framework for interpreting listeners' responses to music, with the ultimate goal of developing a meaningful, quantitative, and dynamically changing index of musical engagement. We draw from recent approaches in neuroscience and physiology that use synchrony of audience responses to study engagement in other domains. Specifically, we examine time-resolved inter-subject correlations (ISCs) of cortical, physiological, and behavioral responses to musical pieces heard in their entirety. The current approach is facilitated by a recently developed method that efficiently extracts relevant, stimulus-related activity from a complex, noisy response. This method allows for full-length, ecologically valid stimuli to be presented in a single-listen experimental paradigm. The proposed methodologies are tested and evaluated in two experiments. First, we validate the approach by deriving cortical components from scalp-recorded electroencephalographic (EEG) responses to intact and scrambled songs and computing their ISCs. In a second experiment, we broaden the context of the approach by comparing EEG-ISCs to the activity and synchrony of physiological and continuous behavioral responses. This work makes several novel contributions to the field of music cognition. First, we show that the presence of temporally relevant musical features produces a consistent component topography in the brain response. Furthermore, the ISCs computed from this component are higher when such musical features are retained. We additionally employ a novel approach to experimental design, choosing highly engaging stimuli that were unknown to our participants, and introducing computational procedures for manipulating the stimuli. Finally, we demonstrate that brain responses to full-length musical works from various genres and styles can be successfully analyzed in a single-listen paradigm.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2016 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Kaneshiro, Blair Bohannan | |
|---|---|---|
| Associated with | Stanford University, Department of Music. | |
| Primary advisor | Berger, Jonathan | |
| Primary advisor | Norcia, Anthony Matthew | |
| Thesis advisor | Berger, Jonathan | |
| Thesis advisor | Norcia, Anthony Matthew | |
| Thesis advisor | Smith, Julius O. (Julius Orion) | |
| Advisor | Smith, Julius O. (Julius Orion) |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Blair Bohannan Kaneshiro. |
|---|---|
| Note | Submitted to the Department of Music. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2016. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2016 by Blair Bohannan Kaneshiro
- License
- This work is licensed under a Creative Commons Attribution 3.0 Unported license (CC BY).
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