Forskning ved Københavns Universitet - Københavns Universitet


Cluster analysis of activity-time series in motor learning.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

  • Daniela Balslev
  • Finn Å Nielsen
  • Sally A Futiger
  • John J Sidtis
  • Torben B Christiansen
  • Claus Svarer
  • Stephen C. Strother
  • David A Rottenberg
  • Lars K Hansen
  • Paulson, Olaf B.
  • I Law
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
TidsskriftHuman Brain Mapping
Udgave nummer2
Sider (fra-til)351-361
StatusUdgivet - 2002

ID: 34058390