Presenter Name:Joshua Hoddinott

School/Affiliation:Western University

Co-Authors:Jessica A. Grahn

Abstract:

Humans spontaneously perceive an underlying pulse, or “beat,” arising from the rhythmic structure in music. Functional magnetic resonance imaging studies show that motor regions of the brain, such as the basal ganglia, supplementary motor area, and premotor cortices, have increased activity when people listen to rhythms with a strong beat (Grahn & Brett, 2007). However, previous fMRI studies have generally used univariate analyses, which investigate activity averaged over voxels in a region, whereas multivariate techniques identify patterns of covariance across voxels that allow greater sensitivity and better identification of neural features that predict brain–behavior relationships. Thus, here we use multivariate pattern analysis to compare neural activity patterns elicited by rhythms with strong, weak, or no beat. The results enable us to determine which neural regions are sensitive to beat strength, as they will have high dissimilarity between activity patterns elicited by individual strong-beat rhythms, and low dissimilarity between patterns elicited by individual weak- and non-beat rhythms. Data collection is ongoing, but preliminary results reveal that multivariate patterns do indeed appear sensitive to individual rhythm types, building on previous univariate work.