Dunbar, K. N. (2008). Arts education, the brain, and language. In C. Asbury & C. Rich (Eds.) Learning, Arts, and the Brain. New York, NY: Dana Foundation.

Abstract:

This study uses neuroscientific methods to examine whether there are cognitive differences between performing arts and non-performing arts students and among students studying different performing arts, in particular between music students and theater students. The researchers conducted the study with college students over a three-year period. In years one and three, they collected and analyzed research data, and in year two they developed tools for measuring cognitive function and for examining possible interactions between environmental and genetic factors affecting cognition. The researchers found that performing arts students exhibit more divergent thinking than non-performing arts students and that music students exhibit differences in working memory when compared with non-music students. Additionally, they find some evidence that there may be a genetic component to cognitive differences between performing arts and non-performing arts students.

Key Findings:

In year one, cognitive differences were found between performing arts and non-performing arts students on the Uses of Objects task, which measures how many different uses a person can identify for a particular object. Performing arts students evidenced more divergent thinking (generated more unusual or atypical uses for objects), than non-performing arts students who generated more standard uses for objects.

During the Uses of Objects task, performing arts students activated regions of the brain associated with language processing while non-performing arts students activated regions of the brain associated with perception.

In year three, the researchers investigated the differences between performing arts students studying theater and music and non-performing arts students. They found significant working memory differences between music students and the other two groups (theater students and non-performing arts students). DNA genotyping indicated that there are genetic differences (in MAOS and COMT genetic markers) between performing arts students and controls. However, no differences were found between groups on brain activity for the Uses of Objects task; the researchers modified the task between years one and three which they believe accounted for the lack of difference in year three.

Significance of the Findings:

The findings indicate that performing arts students and non-performing arts students activate different regions of the brain when completing a cognitive task. This result is important because research on scientific thinking and expertise indicates that expertise can lead to increased activation in linguistic areas associated with conceptual thinking. Additionally, findings from the third-year research suggest that the differences between performing arts and non-performing arts students may be due to a genetic predisposition toward the arts.

Methodology:

The researchers conducted this study over three years. In year one, they aimed to (1) determine whether there are cognitive differences between performing arts and non-performing arts students; and (2) to understand brain-based differences that might underlie any cognitive differences and to postulate the specific neural mechanisms that might be involved. In this phase of the study, the researches employed the Uses of Objects task to assess cognitive functioning and functional magnetic resonance imaging (fMRI) to compare the brain activity of performing arts students and non-performing arts students as they worked on a creative thinking task. The number of students and data analytic methods was not specified.

In the second year of the study, the researchers developed tools to help them assess differences in cognitive functioning including: (1) a battery of tasks to measure performance on attention, working memory, and reasoning; (2) a DNA-microarray technology to address the possible interaction of environmental and genetic mechanisms; and (3) tasks to assess differences, through imaging in brain activities, of performing arts and non-performing arts students.

The third year of the study further explored previous findings and compared differences between music majors, theater majors, and non-performing arts majors. Researchers relied on three types of data collection and analysis: (1) a cognitive test battery consisting of standardized behavioral tasks including the Uses of Objects task, Shipley Vocabulary, WAIS-III Digit Span Forward and Backward sub-tests, an analogy completion task, the Group Embedded Figures Task, as well as a general background questionnaire; (2) buccal swabs for DNA genotyping; and (3) fMRI data. Sixty students were tested; three groups of 20 theater, music, and non-performing arts majors (controls). Two planned t-tests were conducted for each test score: a comparison of performing arts and non-performing arts students; and a comparison of music versus theater performing arts students.

Limitations of the Research:

Sample size for the year one research was not specified, while the sample size for the third-year research was small, particularly for subgroups. Further, demographic descriptions of the samples are not provided, although it is assumed participants were college students. The author’s note the need for a more diverse sample regarding demographics and academic indicators. Also testing does not account for prior informal experience in the arts.

Questions to Guide New Research:

Is there a “sensitive period” occurring at a younger age for the acquisition of cognitive processes involved in the performing arts? How would those with dance or visual arts training compare to those with music, theatre, or no arts training?