Cluster analysis of activity‐time series in motor learning

Neuroimaging studies of learning focus on brain areas where the activity changes as a function of time. To circumvent the difficult problem of model selection, we used a data‐driven analytic tool, cluster analysis, which extracts representative temporal and spatial patterns from the voxel‐time series. The optimal number of clusters was chosen using a cross‐validated likelihood method, which highlights the clustering pattern that generalizes best over the subjects. Data were acquired with PET at different time points during practice of a visuomotor task. The results from cluster analysis show practice‐related activity in a fronto‐parieto‐cerebellar network, in agreement with previous studies of motor learning. These voxels were separated from a group of voxels showing an unspecific time‐effect and another group of voxels, whose activation was an artifact from smoothing. Hum. Brain Mapping 15:135–145, 2002. © 2002 Wiley‐Liss, Inc.