Altered Dynamic Functional Connectivity of the Frontoparietal Network in Major Depressive Disorder: Evidence From a Large-Scale Resting-State fMRI Study

重度抑郁症患者额顶叶网络动态功能连接的改变:一项大规模静息态功能磁共振成像研究的证据

阅读:1

Abstract

Major depressive disorder (MDD) is a prevalent psychiatric condition characterized by affective disturbances and cognitive deficits. Among these, cognitive inflexibility and executive dysfunction are particularly prominent, yet the temporal dynamics of the frontoparietal control network (FPN), a core substrate of cognitive control, remain poorly understood. Using harmonized resting-state fMRI data from the REST-meta-MDD consortium (n = 887; 442 MDD, 445 healthy controls), we investigated dynamic functional connectivity (dFC) within the FPN. Time-varying correlations among 21 FPN nodes were estimated using a sliding-window approach and clustered via k-means to identify recurring connectivity states. Temporal metrics included fractional occupancy, mean dwell time, and transition counts. Three unique FPN states were recognized. In comparison to healthy individuals, those with MDD exhibited prolonged durations in a hypoconnected state, extended dwell times in this configuration, and fewer total transitions, indicating diminished neural flexibility. Direct transitions between low-connectivity (hypoconnected) and high-connectivity (hyperconnected) states were selectively diminished, indicating a disruption in the direct transition between two functionally distinct states of the FPN. Overall, these findings reveal a fundamental disruption in the temporal organization of frontoparietal connectivity in MDD, marked by predominant hypoconnectivity, reduced flexibility, and constrained state transitions. By delineating the dynamic properties of network function, this study advances a mechanistic framework for interpreting prior inconsistencies in static connectivity research and underscores the necessity of time-resolved approaches in characterizing large-scale network dysfunction in psychiatric disorders.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。