Zang Zhenxiang, Geiger Lena S, Braun Urs, Cao Hengyi, Zangl Maria, Schäfer Axel, Moessnang Carolin, Ruf Matthias, Reis Janine, Schweiger Janina I, Dixson Luanna, Moscicki Alexander, Schwarz Emanuel, Meyer-Lindenberg Andreas, Tost Heike
Department of Psychiatry and Psychotherapy, Research Group System Neuroscience in Psychiatry, Central Institute of Mental Health, University of Heidelberg, Medical Faculty Mannheim, Mannheim, Germany.
Department of Neuroimaging, Central Institute of Mental Health, University of Heidelberg, Medical Faculty Mannheim, Mannheim, Germany.
Netw Neurosci. 2018 Oct 1;2(4):464-480. doi: 10.1162/netn_a_00045. eCollection 2018.
Graph theoretical functional magnetic resonance imaging (fMRI) studies have demonstrated that brain networks reorganize significantly during motor skill acquisition, yet the associations between motor learning ability, brain network features, and the underlying biological mechanisms remain unclear. In the current study, we applied a visually guided sequential pinch force learning task and graph theoretical analyses to investigate the associations between short-term motor learning ability and resting-state brain network metrics in 60 healthy subjects. We further probed the test-retest reliability ( = 26) and potential effects of the -methyl-d-aspartate (NMDA) antagonist ketamine ( = 19) in independent healthy volunteers. Our results show that the improvement of motor performance after short-term training was positively correlated with small-worldness ( = 0.032) and global efficiency ( = 0.025), whereas negatively correlated with characteristic path length ( = 0.014) and transitivity ( = 0.025). In addition, using network-based statistics (NBS), we identified a learning ability-associated ( = 0.037) and ketamine-susceptible ( = 0.027) cerebellar-cortical network with fair to good reliability (intraclass correlation coefficient [ICC] > 0.7) and higher functional connectivity in better learners. Our results provide new evidence for the association of intrinsic brain network features with motor learning and suggest a role of NMDA-related glutamatergic processes in learning-associated subnetworks.
基于图论的功能磁共振成像(fMRI)研究表明,在运动技能习得过程中脑网络会发生显著重组,但运动学习能力、脑网络特征与潜在生物学机制之间的关联仍不清楚。在本研究中,我们应用视觉引导的顺序捏力学习任务和图论分析,来研究60名健康受试者的短期运动学习能力与静息态脑网络指标之间的关联。我们还在独立的健康志愿者中进一步探究了重测信度(n = 26)以及N-甲基-D-天冬氨酸(NMDA)拮抗剂氯胺酮(n = 19)的潜在影响。我们的结果表明,短期训练后运动表现的改善与小世界特性(p = 0.032)和全局效率(p = 0.025)呈正相关,而与特征路径长度(p = 0.014)和传递性(p = 0.025)呈负相关。此外,使用基于网络的统计方法(NBS),我们识别出一个与学习能力相关(p = 0.037)且对氯胺酮敏感(p = 0.027)的小脑-皮质网络,其具有较好到良好的可靠性(组内相关系数[ICC] > 0.7),并且在学习能力较好者中具有更高的功能连接性。我们的结果为内在脑网络特征与运动学习之间的关联提供了新证据,并提示NMDA相关的谷氨酸能过程在学习相关子网络中的作用。