1 School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, P. R. China.
2 School of Biomedical Engineering, Science & Health Systems, Drexel University, Philadelphia, Pennsylvania, USA.
Int J Neural Syst. 2018 Sep;28(7):1850002. doi: 10.1142/S0129065718500028. Epub 2018 Jan 25.
Task-related reorganization of functional connectivity (FC) has been widely investigated. Under classic static FC analysis, brain networks under task and rest have been demonstrated a general similarity. However, brain activity and cognitive process are believed to be dynamic and adaptive. Since static FC inherently ignores the distinct temporal patterns between rest and task, dynamic FC may be more a suitable technique to characterize the brain's dynamic and adaptive activities. In this study, we adopted [Formula: see text]-means clustering to investigate task-related spatiotemporal reorganization of dynamic brain networks and hypothesized that dynamic FC would be able to reveal the link between resting-state and task-state brain organization, including broadly similar spatial patterns but distinct temporal patterns. In order to test this hypothesis, this study examined the dynamic FC in default-mode network (DMN) and motor-related network (MN) using Blood-Oxygenation-Level-Dependent (BOLD)-fMRI data from 26 healthy subjects during rest (REST) and a hand closing-and-opening (HCO) task. Two principal FC states in REST and one principal FC state in HCO were identified. The first principal FC state in REST was found similar to that in HCO, which appeared to represent intrinsic network architecture and validated the broadly similar spatial patterns between REST and HCO. However, the second FC principal state in REST with much shorter "dwell time" implied the transient functional relationship between DMN and MN during REST. In addition, a more frequent shifting between two principal FC states indicated that brain network dynamically maintained a "default mode" in the motor system during REST, whereas the presence of a single principal FC state and reduced FC variability implied a more temporally stable connectivity during HCO, validating the distinct temporal patterns between REST and HCO. Our results further demonstrated that dynamic FC analysis could offer unique insights in understanding how the brain reorganizes itself during rest and task states, and the ways in which the brain adaptively responds to the cognitive requirements of tasks.
任务相关的功能连接(FC)重组已经得到了广泛的研究。在经典的静态 FC 分析中,已经证明任务和休息状态下的大脑网络具有一般相似性。然而,大脑活动和认知过程被认为是动态和自适应的。由于静态 FC 本质上忽略了休息和任务之间的明显时间模式,动态 FC 可能是一种更适合描述大脑动态和自适应活动的技术。在这项研究中,我们采用了[公式:见文本]-均值聚类来研究动态脑网络的任务相关时空重组,并假设动态 FC 能够揭示静息态和任务态大脑组织之间的联系,包括广泛相似的空间模式但不同的时间模式。为了验证这一假设,本研究使用 26 名健康受试者在静息(REST)和手部闭合-张开(HCO)任务期间的血氧水平依赖(BOLD)-fMRI 数据,检查了默认模式网络(DMN)和运动相关网络(MN)的动态 FC。在 REST 和 HCO 中分别确定了两个主要的 FC 状态和一个主要的 FC 状态。在 REST 中发现第一个主要 FC 状态与 HCO 中的状态相似,这似乎代表了内在网络结构,并验证了 REST 和 HCO 之间广泛相似的空间模式。然而,REST 中第二个 FC 主要状态的“停留时间”要短得多,这意味着在 REST 期间 DMN 和 MN 之间存在短暂的功能关系。此外,两个主要 FC 状态之间更频繁的转换表明,在 REST 期间,大脑网络在运动系统中动态地保持了一种“默认模式”,而单一主要 FC 状态的存在和 FC 可变性的降低则表明在 HCO 期间连接更加稳定,验证了 REST 和 HCO 之间不同的时间模式。我们的研究结果进一步表明,动态 FC 分析可以为理解大脑在静息和任务状态下如何自我重组以及大脑如何自适应地应对任务的认知要求提供独特的见解。