Cluster analysis of activity-time series in motor learning
Research output: Contribution to journal › Journal article › Research › peer-review
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.
Original language | English |
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Journal | Human Brain Mapping |
Volume | 15 |
Issue number | 3 |
Pages (from-to) | 135-45 |
Number of pages | 11 |
ISSN | 1065-9471 |
DOIs | |
Publication status | Published - 2002 |
Links
- https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6871873/
Final published version
ID: 33620721