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.
Balslev
Daniela
D
Neurobiology Research Unit, N 9201, Copenhagen University Hospital, Rigshospitalet, 9 Blegdamsvej, 2100 Copenhagen, Denmark. daniela@nru.dk
Nielsen
Finn A
FA
Frutiger
Sally A
SA
Sidtis
John J
JJ
Christiansen
Torben B
TB
Svarer
Claus
C
Strother
Stephen C
SC
Rottenberg
David A
DA
Hansen
Lars K
LK
Paulson
Olaf B
OB
Law
I
I
D000328:Adult; D001921:Brain / Q000502:physiology; D001931:Brain Mapping / Q000379:methods; D016000:Cluster Analysis; D005260:Female; D006801:Humans; D007858:Learning / Q000502:physiology*; D008297:Male; D016011:Normal Distribution; D011597:Psychomotor Performance / Q000502:physiology*; D018709:Statistics, Nonparametric; D013997:Time Factors; D014055:Tomography, Emission-Computed / Q000379:methods / Q000706:statistics & numerical data