Balslev Daniela, Nielsen Finn A, Frutiger Sally A, Sidtis John J, Christiansen Torben B, Svarer Claus, Strother Stephen C, Rottenberg David A, Hansen Lars K, Paulson Olaf B, Law I
Neurobiology Research Unit, N 9201, Copenhagen University Hospital, Rigshospitalet, 9 Blegdamsvej, 2100 Copenhagen, Denmark.
Hum Brain Mapp. 2002 Mar;15(3):135-45. doi: 10.1002/hbm.10015.
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.
关于学习的神经影像学研究聚焦于那些活动随时间变化的脑区。为了规避模型选择这一难题，我们使用了一种数据驱动的分析工具——聚类分析，它从体素时间序列中提取具有代表性的时空模式。使用交叉验证似然法选择最优聚类数，该方法突出了在受试者中泛化性最佳的聚类模式。在一项视觉运动任务的练习过程中的不同时间点，通过正电子发射断层扫描（PET）采集数据。聚类分析结果显示，在额顶小脑网络中存在与练习相关的活动，这与先前关于运动学习的研究结果一致。这些体素与一组显示非特异性时间效应的体素以及另一组激活是平滑处理伪影的体素区分开来。
