Song & Speech Perception & Covert Production: New Findings using Multi-Voxel Pattern Analysis

Dirk Goldhahn¹, Daniel E. Callan², Gabriele Lohmann¹, Robert Turner¹

Multi-Voxel Pattern Analysis (MVPA) is a powerful technique for the analysis of fMRI data. It uses the information present in multiple voxels to distinguish between experimental conditions. In this abstract we apply MVPA to examine brain regions differentially involved with listening to and covert production of song relative to speech. We present new findings that univariate analysis failed to discover, and investigate what underlies this discrepancy. As a particular example the superior temporal gyri are discussed, which show highly differential activity for the contrast of covert production of song versus covert production of speech only when using MVPA.