Journal article
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.
Language: | English |
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Publisher: | John Wiley & Sons, Inc. |
Year: | 2002 |
Pages: | 135-145 |
ISSN: | 10970193 and 10659471 |
Types: | Journal article |
DOI: | 10.1002/hbm.10015 |
ORCIDs: | Nielsen, Finn Årup , Hansen, Lars Kai and 0000-0001-7712-8596 |