Neuromusical Research
Donald A. Hodges, MRi
Jonathan Burdette, ANSIR, WFUSM*
David Hairston, ANSIR, WFUSM*
(*Advanced Neuroscience Imaging Research Lab, Wake Forest University School of Medicine)
The MRi and ANSIR are collaborating on a series of studies on multisensory processing in conductors. Projects that have been published and/or presented are as follows:
1One of the requirements for being a successful musical conductor is to be able to locate sounds instantaneously in time and space. Because this requires the integration of auditory and visual information, the purpose of this study was to examine multisensory processing in conductors and a matched set of control subjects. Subjects participated in a series of behavioral tasks, including pitch discrimination, temporal-order judgment (TOJ), and target localization. Additionally, fMRI scans were done on a subset of subjects who performed a multisensory TOJ task. Analyses of behavioral data indicate that, in the auditory realm, conductors were more accurate in both pitch discrimination and TOJs as well as in locating targets in space. Furthermore, these same subjects also demonstrated a benefit from the combination of auditory and visual information that was not observed in control subjects when locating visual targets. Finally, neural substrates in BA 37, 39/40 were identified as potential areas underlying the conductors’ superior multisensory TOJs. Data collection and analyses are ongoing and will lead to an improved understanding of multisensory integration in a complex, musical behavior.
Publications and Presentations
1Hodges, D., Burdette, J. & Hairston, D. (2006). Aspects of multisensory perception: The integration of visual and auditory information processing in musical experiences. In G. Avanzini, L. Lopez, S. Koelsch, & M. Majno (eds.), 175-185. The Neurosciences and Music II: From Perception to Performance, Annals of the New York Academy of Sciences, Vol. 1060.
Hairston, W., Burdette, J., and Hodges, D. (2006). Neural mechanisms underlying multisensory processing in conductors. 9th International Conference on Music Perception and Cognition. Bologna, Italy. August 24.
Hodges, D., Burdette, J. & Hairston, D. (2005). Aspects of multisensory perception: The integration of visual and auditory information processing in musical experiences. Neurosciences of Music II. Leipzig, Germany. May 6.
Hodges, D. Auditory and multisensory enhancement of localization ability in music conductors . Society for Neuroscience. Washington, D.C. November 15, 2006. Also displayed at Society for Music Teacher Education national conference. The University of North Carolina at Greensboro, September 16, 2005; North Carolina Music Educators Association state convention. Winston-Salem, NC, November 15, 2005; Music Educators National Conference national convention. Salt Lake City, April 20, 2006.
Cortical Deactivation in Multisensory Processing
1Although numerous studies have shown that response times can be speeded by the presentation of multisensory stimuli, here we show that such speeding can be seen even when the second sensory channel fails to provide any task-relevant (i.e. redundant) information, and where cueing appears an unlikely explanation. Study participants performed a visual temporal order judgment task in the presence of task uninformative auditory cues, with the latter sound delayed relative to the latter visual cue. Responses were maximally speeded when the auditory stimulus was delayed by a short time (i.e. 100 ms) relative to the second visual target. These results illustrate a unique form of temporal benefit underlying a multisensory interaction, and form the basis for a novel explanation of these perceptual enhancements.
2Blood oxygen-level-dependent signal decreases relative to baseline (deactivations) can occur with stimulation of an opposing sensory modality. Here, we show the importance of the difficulty of an auditory task on the deactivation of visual cortical areas. Participants performed an auditory temporal-order judgment task in conjunction with sparse-sampling functional MRI at both moderate and high levels of difficulty (adjusted for each individual's own threshold). With moderate difficulty, small deactivations were observed not only in parietal and cingulate cortex, but occipital cortex as well. When the same task was more difficult, deactivations increased significantly to include a greater extent of functionally defined visual cortex. Together, these results suggest that cross modal deactivations occur in compensation for task difficulty, perhaps acting as an intrinsic filter for nonrelevant information.
3Background: Cortical deactivation can occur when opposing modalities compete (e.g., visual cortex activity can decrease during an auditory task) [1]. Although these deactivations may be related to attention [2], it is also possible that they are related to the difficulty of the task at hand. Also, extensive training may alter cross-modal deactivations. Aims: To investigate BOLD signal decreases related to auditory task difficulty in experienced conductors and musically untrained individuals.
Method: Subjects included musical conductors (n = 17; mean10 years of podium experience) and control subjects (n = 18; variety of occupations and no formal musical training). Groups were matched on all other demographics such as age, gender, and education. Each participant’s individual threshold for auditory temporal-order judgment (TOJ) was determined prior to fMRI scanning. During sparse-sampling MRI, subjects performed the auditory task at threshold level (“hard-task”) or well above that level (“moderate-task”) as well as a visual TOJ. Having each subject perform at threshold ensured consistent relative task difficulty. Task conditions alternated with baseline (no-task) conditions involving no stimulation (eyes remained open).
Results: Control subjects showed significant decreases (BOLD signal < baseline) in parietal and cingulate cortex and significant activation in auditory cortex during the hard-task auditory condition. Also, significant (FWE corrected p<.05) deactivations were observed in visual cortex. These deactivations were reduced during the moderate-task version. In contrast, conductors showed only small visual cortical deactivations during both task conditions, despite behavioral confirmation of task difficulty. Group differences related to other factors such as gray matter volume (VBM) are being explored using Biological Parametric Mapping [3], a toolbox designed for combining multiple imaging modality datasets.
Conclusions: These results indicate that cross-modal deactivations may be related to task difficulty, acting perhaps as an intrinsic filter for irrelevant information. However, that conductors experienced minimal changes in visual cortex during even hard-task auditory conditions suggests that their extensive training and daily experiences in multisensory integration allow them to perform at higher levels without necessitating the same degree of intrinsic inhibition.
Publications and Presentations
1Hairston, W., Hodges, D., Burdette, J. & Wallace, M. (2006) Auditory enhancement of visual temporal order judgment. NeuroReport. May 29;17:8, 791-5. Available online at: http://www.ncbi.nlm.nih.gov/pubmed/16708016?ordinalpos=1&itool=EntrezSystem2.
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2Hairston, D., Hodges, D., Casanova, R., Hayasaka, S., Kraft, R., Maldjian, J., & Burdette, J. (2007). Closing the mind’s eye: Deactivation of visual cortex related to auditory task difficulty. NeuroReport, 19:2, 151-154. Available online at: http://www.ncbi.nlm.nih.gov/pubmed/18185099?ordinalpos=1&itool=EntrezSystem2.
PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_RVDocSum
Hairston, W.D., Hodges, D.A., Hussain, H.H., and Burdette, J.H. (2007). Closing the mind’s eye to listen: exploring visual cortical deactivation related to auditory task difficulty. Annual Meeting of the Society for Neuroscience, November, San Diego, CA.
Hairston, D., Burdette, J., Maldjian, J., Mace, S., & Hodges, D. (2007). Cross-modal deactivation related to auditory task difficulty: non-musicians verses conductors. Organization for Human Brain Mapping. Chicago, June 10-14.
3Hodges, D., Hairston, D., Maldjian, J., & Burdette, J. (2008). “Cross-modal Deactivations are Minimized in Conductors.” International Conference on Music Perception and Cognition. August, Sapporo, Japan.
Tierney, J. (2008). Figaro! Figaro! Training the Multitasking Brain. The New York Times, Science Blog (http://tierneylab.blogs.nytimes.com/2008/01/18/figaro-figaro-training-the-multitasking-brain/?hp).
MusicBIRD
Richard Edwards
Ithaca College
Click here to access MusicBIRD: http://mri.uncg.edu:80/fmi/iwp/cgi?-db=MusicBIRD473.9&-loadframes
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Introduction
The Musical Brain Imaging Research Database (MusicBIRD) was originally created by Richard Edwards as a component of his UNC Greensboro Ph.D. dissertation titled, “The Neurosciences and Music Education: An Online Database of Musical Brain Imaging Research” (2008). The MusicBIRD is intended to serve as a resource for anyone interested in the field of neuromusical research (i.e., the study of brain processes associated with musical experiences) and its primary objective is to organize neuromusical research by presenting summative information from all peer-reviewed musical brain imaging studies.
Dissertation Abstract
EDWARDS, RICHARD D., The Neurosciences and Music Education: An Online Database of Brain Imaging Neuromusical Research (2008).
Directed by Dr. Donald A. Hodges. 162 pp.
The purpose of this study was to create an online database to organize and summarize the field of neuromusical research (i.e., the study of brain processes involved with musical experiences). The guiding principles of this dissertation were to (1) assess and clarify the current state of neuromusical research, and (2) explore how this research relates to the pedagogical, psychological and philosophical foundations of music education. Given the rise of brain-imaging neuromusical research in the last two decades, in conjunction with a lack of holistic efforts to evaluate these studies, there is a clear need to compile and summarize neuromusical research into a summative database. Until this time, no such resource has existed.
The resulting database of this project has been titled the Musical Brain Imaging Research Database (MusicBIRD) and currently holds 473 studies of neuromusical research available online. Qualifying neuromusical studies were identified with a keyword search for “music” and “brain” in leading electronic research databases (e.g., PubMed and RILM). After reviewing each study, summative information was entered into an electronic storage format within the following data fields: Title, Author(s), Date, Keywords, Source, Volume, Issue, Online Source, and Abstract.
A content analysis of the studies in the final database was conducted to reveal trends in neuromusical research and insights for music educators about the role of neuroscience in music teaching. Among the leading trends in neuromusical research identified in the content analysis were the most frequently used brain imaging device (EEG in 28.8% of all MusicBIRD studies), the most common research methodologies - evaluating changes in brain activity due to music processing (35.57% of all MusicBIRD studies), and comparisons between musically and non-musically trained subjects (25.57% of all MusicBIRD studies).
The implications of neuromusical research for music educators include a strengthening of the belief that the potential for music processing is ubiquitous to all humans, and that until more longitudinal studies can be conducted, a clear understanding of whether musical training does or does not have an effect on non-musical brain processes (e.g., language skills) is not possible at this time. Based on a review of neuromusical research through 2006, several recommendations for future research include brain imaging scans associated with effective pedagogical music learning practices, longitudinal studies of brain development during periods of musical training (e.g., preschool to adulthood), and investigating the potential for shared, proximal, or distinct neural networks dedicated to music and non-music systems.
Sources and Qualifying Parameters for MusicBIRD Article Selection
473 articles are currently included in the MusicBIRD and were selected from a possible 2,112 neuromusical studies published by December 31, 2006 as identified in keyword searches for “music” and “brain” across four prominent research databases covering biological sciences (PubMed), social sciences (PsycInfo), music research (RILM), and educational research (ERIC).
All articles entered into the MusicBIRD employed the use of some form of imaging technology to investigate a neuromusical event or condition. The keyword searches to identify music related brain-imaging studies yielded hundreds of articles, many of which did not fulfill a consistent definition of neuromusical research. For the purposes of this dissertation, neuromusical research fulfilled at least one of the following conditions:
- Auditory perception (i.e., sub-conscious awareness) or cognition (i.e., conscious awareness) of complex tone musical processes (e.g., pitch, timbre, melody, harmony, rhythm, timbre, phrasing, formal music structure, performance, reading or writing notation, or composition).
- Mental imagery of music processing (i.e., audiation, or imagining musical processes).
- Subjects performing multiple tasks (e.g., reading, talking, and singing) to compare neuromusical correlates (i.e. the relationship between neural networks dedicated to musical and nonmusical tasks).
- Comparisons of musically and nonmusically trained subjects.
MusicBIRD Presentation Format
All studies that met any of the qualifying parameters for MusicBIRD article selection were evaluated and after reviewing each article, an abstract was written by the dissertation author to serve as a musician’s perspective of that particular area of neuromusical research. Summative information from each article was entered into the following data fields using electronic storage software (File Maker ProÓ 7.0v3 for Mac OS X, 2004):
- Title
- Author(s)
- Year
- Keywords (original article keywords provided when available)
- Source
- Volume
- Issue
- Online Source (web links provided for PubMed articles only)
- Abstract
Word Search Protocols
Anyone may access the MusicBIRD by entering “guest” into the username field and leaving the password field blank. The search engine of File Maker ProÓ allows for basic word searches throughout the database in one field, or across all fields.
For example, to obtain all of the studies that include the term “pitch discrimination” in the abstract field, left-click on the search icon (a magnifying glass symbol) in the top of the left side toolbar and then enter the words “pitch discrimination” in the blank abstract field (Figure 1). Left-click on the “Perform Find” tab in the left side toolbar to complete the search and yield all of the “pitch discrimination” studies in the MusicBIRD.
Figure 1. Basic MusicBIRD word search procedure
Other search options include an advanced word search using multiple levels of search requests that may omit certain words while yielding other combinations of words across the MusicBIRD database. For example, a search for both “rhythm” and “temporal grouping” in the Abstract field could be refined by omitting the word “temporal lobe” to filter out all of the studies that only include the phrase “temporal lobe” while yielding all the studies that include the words “rhythm” and “temporal grouping”.
To conduct an advanced word search that omits certain words yielding other multiple requests for other words and phrases, left-click on the search icon (a magnifying glass symbol) in the top of the left side toolbar to begin a new search and then type the first search word (e.g., “rhythm”) in the abstract field (Figure 2a). Next, left-click on the “add new request” icon in the left side toolbar located below the word “Find” to further refine the search for the word “rhythm” by typing another search word or phrase (e.g., “temporal grouping”) in the Abstract field (Figure 2b). Notice in the left hand column of Figure 2b that the second level of an advanced search will be labeled as “Request 2” in the Request field. More words and phrases can be added and each successive “add new request” will increase the number in the Request field. Finally, left-click “add new request” once more and select “omit” in the left hand column checkbox followed by typing the word or phrase that needs to be omitted from the overall search in the abstract (e.g., “temporal lobe” in Figure 2c). When all desired and omitted words have been entered, left-click the “Perform Find” tab to yield the resulting studies (Figure 2d). Scrolling through the yielded studies is accomplished by left-clicking the “right” and “left” arrows above the Record number index.
Figure 2a. Advanced MusicBIRD word search: Request 1
Figure 2b. Advanced MusicBIRD word search: Request 2
Figure 2c. Advanced MusicBIRD word search: Request 3
Figure 2d. Advanced MusicBIRD word search results
About the Author
Originally from Willoughby, Ohio, Richard Edwards currently serves as an assistant professor at Ithaca College. He completed the Ph.D. in Music Education at UNC Greensboro (2008), the Master of Music in Music Education at UNC Greensboro (2002) and received the Bachelor of Music degree from Ohio University (1996). His research interests include neuroscience, psychology, philosophy and the pedagogy of music education. Dr. Edwards has taught for six years in the public schools of Ohio and North Carolina as both a high school band director and an elementary music teacher, and as an undergraduate, he served as the field commander for “The Ohio University Marching 110". He is a member of MENC, Phi Mu Alpha Sinfonia, Pi Kappa Lambda, The College Band Director’s National Association, and the Society for Music Perception and Cognition.
Contact Information
Richard D. Edwards, Asst. Professor
Music Education Department
Conductor, Ithaca College Campus Band
School of Music
Ithaca College
Ithaca, NY 14850-7240
(607) 274-3857
(607) 274-1727 (Fax)
redwards@ithaca.edu
