1 Department of Psychology, Georgetown University , Washington, District of Columbia.
Brain Connect. 2013;3(6):601-10. doi: 10.1089/brain.2013.0169. Epub 2013 Nov 14.
Abstract Implicit probabilistic sequence learning (IPSL) involves extracting statistical regularities from sequences of events without awareness, and is thought to underlie learning of language and behavioral repertoires of everyday life. We examined whether resting-state functional connectivity networks of the caudate predicted individual differences in IPSL performance measured on a separate day. Whole-brain connectivity maps of a bilateral dorsal caudate (DC) seed were created for each subject and examined for voxelwise correlations with sequence learning performance, as well as with overall response speed. Higher learning scores (but not overall response speed) were associated with stronger resting-state connectivity between the DC and right medial temporal lobe, as well as with lower resting-state connectivity between the DC and premotor regions involved in motor planning. Thus, how well one learns probabilistic regularities without awareness is predicted by the strength of a striato-cortical network in the resting brain.
摘要 内隐概率序列学习（IPSL）涉及在无意识的情况下从事件序列中提取统计规律，被认为是语言学习和日常生活行为模式的基础。我们研究了在另一天测量的 IPSL 表现的个体差异是否可以用尾状核的静息态功能连接网络来预测。为每个被试创建了双侧尾状核（DC）种子的全脑连接图，并检查了与序列学习表现以及整体反应速度的体素相关性。更高的学习分数（而非整体反应速度）与 DC 与右侧内侧颞叶之间的静息状态连接较强，以及 DC 与参与运动规划的运动前区域之间的静息状态连接较弱有关。因此，在静息状态下，大脑中纹状体-皮质网络的强度可以预测一个人无意识地学习概率规律的能力。
