Cluster analysis of activity-time series in motor learning

Research output: Research - peer-reviewJournal article – Annual report year: 2002

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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.
Original languageEnglish
JournalHuman Brain Mapping
Issue number3
Pages (from-to)135-145
StatePublished - 2002
CitationsWeb of Science® Times Cited: 29

    Research areas

  • motor learning, positron emission tomography, cluster analysis
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ID: 3938643