Cluster analysis of activity-time series in motor learning

D Balslev*, FA Nielsen, SA Frutiger, JJ Sidtis, TB Christiansen, C Svarer, SC Strother, DA Rottenberg, LK Hansen, OB Paulson, I Law

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

29 Citations (Scopus)

Abstract

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. (C) 2002 Wiley-Liss, Inc.

Original languageEnglish
Pages (from-to)135-145
Number of pages11
JournalHuman Brain Mapping
Volume15
Issue number3
DOIs
Publication statusPublished - Mar 2002

Keywords

  • multivariate analysis
  • generalization error
  • cross-validation
  • positron emission tomography
  • functional neuroimaging
  • POSITRON EMISSION TOMOGRAPHY
  • CEREBRAL BLOOD-FLOW
  • HUMAN VISUAL-CORTEX
  • BASAL GANGLIA
  • PET
  • ACTIVATION
  • FMRI
  • PERFORMANCE
  • MODEL
  • LIKELIHOOD

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