Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06519, USA.
Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06519, USA; Department of Neuroscience, Yale University School of Medicine, New Haven, CT, 06520, USA; Interdepartmental Neuroscience Program, Yale University, New Haven, CT, 06520, USA.
Neuroimage. 2018 Jun;173:240-248. doi: 10.1016/j.neuroimage.2018.02.029. Epub 2018 Feb 15.
Functional connectivity analysis is an essential tool for understanding brain function. Previous studies showed that brain regions are functionally connected through low-frequency signals both within the default mode network (DMN) and task networks. However, no studies have directly compared the time scale (frequency) properties of network connectivity during task versus rest, or examined how they relate to task performance. Here, using fMRI data collected from sixty-eight subjects at rest and during a stop signal task, we addressed this issue with a novel functional connectivity measure based on detrended partial cross-correlation analysis (DPCCA). DPCCA has the advantage of quantifying correlations between two variables in different time scales while controlling for the influence of other variables. The results showed that the time scales of within-network connectivity of the DMN and task networks are modulated in opposite directions across rest and task, with the time scale increased during rest vs. task in the DMN and vice versa in task networks. In regions of interest analysis, the within-network connectivity time scale of the pre-supplementary motor area - a medial prefrontal cortical structure of the task network and critical to proactive inhibitory control - correlated inversely with Barratt impulsivity and stop signal reaction time. Together, these findings demonstrate that time scale properties of brain networks may vary across mental states and provide evidence in support of a role of low frequency fluctuations of BOLD signals in behavioral control.
功能连接分析是理解大脑功能的重要工具。先前的研究表明,大脑区域通过默认模式网络(DMN)和任务网络内的低频信号在功能上相互连接。然而,尚无研究直接比较任务和休息期间网络连接的时间尺度(频率)特性,也没有研究它们与任务表现的关系。在这里,我们使用从 68 名被试在休息和停止信号任务期间采集的 fMRI 数据,使用基于去趋势部分互相关分析(DPCCA)的新功能连接测量方法解决了这个问题。DPCCA 的优点是在控制其他变量影响的同时,量化两个变量在不同时间尺度上的相关性。结果表明,DMN 和任务网络内的连接时间尺度在休息和任务期间以相反的方向进行调制,在 DMN 中休息时比任务时增加,而在任务网络中则相反。在感兴趣区域分析中,任务网络中补充运动前区(前扣带皮层的一个内侧前额皮质结构,对主动抑制控制至关重要)的内连时间尺度与巴瑞特冲动性和停止信号反应时间呈负相关。总之,这些发现表明,脑网络的时间尺度特性可能会因心理状态而异,并为支持 BOLD 信号低频波动在行为控制中的作用提供了证据。