Megumi Fukuda, Yamashita Ayumu, Kawato Mitsuo, Imamizu Hiroshi
Advanced Telecommunications Research Institutes International Kyoto, Japan ; Graduate School of Information Science, Nara Institute of Science and Technology Ikoma, Japan ; Institute of Cognitive Neuroscience, University College London London, UK.
Advanced Telecommunications Research Institutes International Kyoto, Japan ; Department of Systems Science, Graduate School of Informatics, Kyoto University Sakyo-ku, Japan.
Front Hum Neurosci. 2015 Mar 30;9:160. doi: 10.3389/fnhum.2015.00160. eCollection 2015.
Motor or perceptual learning is known to influence functional connectivity between brain regions and induce short-term changes in the intrinsic functional networks revealed as correlations in slow blood-oxygen-level dependent (BOLD) signal fluctuations. However, no cause-and-effect relationship has been elucidated between a specific change in connectivity and a long-term change in global networks. Here, we examine the hypothesis that functional connectivity (i.e., temporal correlation between two regions) is increased and preserved for a long time when two regions are simultaneously activated or deactivated. Using the connectivity-neurofeedback training paradigm, subjects successfully learned to increase the correlation of activity between the lateral parietal and primary motor areas, regions that belong to different intrinsic networks and negatively correlated before training under the resting conditions. Furthermore, whole-brain hypothesis-free analysis as well as functional network analyses demonstrated that the correlation in the resting state between these areas as well as the correlation between the intrinsic networks that include the areas increased for at least 2 months. These findings indicate that the connectivity-neurofeedback training can cause long-term changes in intrinsic connectivity and that intrinsic networks can be shaped by experience-driven modulation of regional correlation.
运动或感知学习已知会影响脑区之间的功能连接,并在内在功能网络中引发短期变化,这种变化表现为慢血流灌注水平依赖(BOLD)信号波动的相关性。然而,连接性的特定变化与全局网络的长期变化之间尚未阐明因果关系。在此,我们检验这样一个假设:当两个区域同时被激活或失活时,功能连接(即两个区域之间的时间相关性)会增加并长期保持。使用连接性神经反馈训练范式,受试者成功学会增加外侧顶叶和初级运动区之间的活动相关性,这两个区域属于不同的内在网络,在静息状态下训练前呈负相关。此外,全脑无假设分析以及功能网络分析表明,这些区域在静息状态下的相关性以及包含这些区域的内在网络之间的相关性至少增加了2个月。这些发现表明,连接性神经反馈训练可导致内在连接的长期变化,并且内在网络可由区域相关性的经验驱动调制来塑造。