Dynamic reconfiguration of functional brain networks during working memory training
Dynamic reconfiguration of functional brain networks during working memory training
复制标题
DOI：
10.1038/s41467-020-15631-z
复制
发表时间：
2020-05-15
影响因子：
16.6
通讯作者：
Bassett, Danielle S.
中科院分区：
文献类型：
--
作者：
Finc, Karolina;Bonna, Kamil;Bassett, Danielle S.
大脑的功能网络不断适应不断变化的环境需求。行为自动化对任务相关功能网络架构的影响还远未被理解。我们研究了当参与者掌握双n-back任务时，行为自动化的神经反射。在四次功能性磁共振成像扫描中，我们评估了大脑网络的模块化，这是生物系统中适应的基础。我们发现，在双n-back任务的训练过程中，全脑模块性稳步增加。在动态分析中，我们发现默认模式系统的自主性和任务积极系统之间的整合受到训练的调节。通过训练实现n-back任务的自动化导致额顶叶和默认模式系统之间以及与皮层下系统的整合发生非线性变化。我们的研究结果表明，对认知要求较高的任务的自动化可能会导致更隔离的网络组织。工作记忆训练重塑大脑功能网络重组。在这里，作者证明了在n-back任务期间全脑网络分离的增加，伴随着默认模式系统和任务积极系统之间动态通信的改变。
The functional network of the brain continually adapts to changing environmental demands. The consequence of behavioral automation for task-related functional network architecture remains far from understood. We investigated the neural reflections of behavioral automation as participants mastered a dual n-back task. In four fMRI scans equally spanning a 6-week training period, we assessed brain network modularity, a substrate for adaptation in biological systems. We found that whole-brain modularity steadily increased during training for both conditions of the dual n-back task. In a dynamic analysis,we found that the autonomy of the default mode system and integration among task-positive systems were modulated by training. The automation of the n-back task through training resulted in non-linear changes in integration between the fronto-parietal and default mode systems, and integration with the subcortical system. Our findings suggest that the automation of a cognitively demanding task may result in more segregated network organization. Working memory training reshapes the brain functional network reorganization. Here, the authors demonstrate an increase of the whole-brain network segregation during the n-back task, accompanied by alterations in dynamic communication between the default mode system and task-positive systems.