The t-test results were FDR corrected using a threshold of P < 0.01. In the second analysis, the goal was to examine whether significant ISS

during the Natural Music condition was associated with constant synchronization of subjects’ fMRI AZD0530 concentration time-series measured across the entire musical sequence, or alternatively whether ISS was associated with isolated and concentrated periods of synchronization measured in the musical sequence. To this end, we performed an inter-subject time-frequency analysis using a continuous wavelet transform in order to examine changes in synchronization over time and frequency (Torrence & Compo, 1998; Grinsted et al., 2004). In this analysis, we computed

the wavelet cross spectra between ROI time series extracted from all pairs of subjects at 64 different frequency scales using the Matlab function ‘wcoher.m’ (www.mathworks.com/products/matlab) with ‘cgau2’ as a mother wavelet. The wavelet cross spectrum Cxy of two time series x and y is defined as: In the third analysis, the selleck inhibitor goal was to examine whether correlations in subjects’ movement patterns within the scanner may have driven ISS results. To address this question, we performed an inter-subject correlation analysis using the time series for each of the six movement parameters. Similar to the main ISS analysis described previously, we calculated Pearson’s correlations for all pair-wise subject comparisons (i.e. 136 subject-to-subject comparisons) for each of the six time-varying movement parameters specified by SPM8 during fMRI data pre-processing (i.e. x, y, z, pitch, roll, yaw) for both the FAD Natural Music and the Phase-Scrambled conditions. Data were linearly detrended prior to performing the correlation analysis. The resulting Pearson’s correlation values for all subject-to-subject comparisons were Fisher transformed, and then these values were entered into a paired t-test (i.e. Natural

Music vs. Phase-Scrambled) to examine whether movement correlations measured during the Natural Music condition were significantly different from those measured during the Phase-Scrambled condition. We measured fMRI activity in 17 adult non-musicians while they listened to 9.5 min of symphonic music from the late-Baroque period and the Spectrally-Rotated and Phase-Scrambled versions of those same compositions (control stimuli). Musical stimuli were similar to those used in a previous study investigating neural dynamics of event segmentation in music across the boundaries of musical movements (Sridharan et al., 2007), except that here we removed ‘silent’ movement boundaries from the musical stimuli. This stimulus manipulation enabled us to isolate brain synchronization during audible musical segments.