Practice-related changes in neural activation patterns investigated via wavelet-based clustering analysis

Objectives: To evaluate brain activation using functional magnetic resonance imaging (fMRI) and specifically, activation changes across time associated with practice‐related cognitive control during eye movement tasks. Experimental design: Participants were engaged in antisaccade performance (generating a glance away from a cue) while fMR images were acquired during two separate test sessions: (1) at pre‐test before any exposure to the task and (2) at post‐test, after 1 week of daily practice on antisaccades, prosaccades (glancing toward a target), or fixation (maintaining gaze on a target). Principal observations: The three practice groups were compared across the two test sessions, and analyses were conducted via the application of a model‐free clustering technique based on wavelet analysis. This series of procedures was developed to avoid analysis problems inherent in fMRI data and was composed of several steps: detrending, data aggregation, wavelet transform and thresholding, no trend test, principal component analysis (PCA), and K‐means clustering. The main clustering algorithm was built in the wavelet domain to account for temporal correlation. We applied a no trend test based on wavelets to significantly reduce the high dimension of the data. We clustered the thresholded wavelet coefficients of the remaining voxels using PCA K‐means clustering. Conclusion: Over the series of analyses, we found that the antisaccade practice group was the only group to show decreased activation from pre‐test to post‐test in saccadic circuitry, particularly evident in supplementary eye field, frontal eye fields, superior parietal lobe, and cuneus. Hum Brain Mapp 34:2276–2291, 2012. © 2012 Wiley Periodicals, Inc.