Zhang Sheng, Tsai Shang-Jui, Hu Sien, Xu Jiansong, Chao Herta H, Calhoun Vince D, Li Chiang-Shan R
Department of Psychiatry, Yale University, New Haven, Connecticut.
Department of Medicine, National Yang-Ming University, Taipei, Taiwan.
Hum Brain Mapp. 2015 Sep;36(9):3289-302. doi: 10.1002/hbm.22819. Epub 2015 Jun 18.
Cognitive control is a critical executive function. Many studies have combined general linear modeling and the stop signal task (SST) to delineate the component processes of cognitive control. For instance, by contrasting stop success (SS) and stop error (SE) trials in the SST, investigators examined regional responses to stop signal inhibition. In contrast to this parameterized approach, independent component analysis (ICA) elucidates brain networks subserving cognitive control. In our earlier work of 59 adults performing the SST during fMRI, we characterized six independent components (ICs). However, none of these ICs correlated with stop signal performance, raising questions about their behavioral validity. Here, in a larger sample (n = 100), we identified and explored 23 ICs for correlation with the stop signal reaction time (SSRT), a measure of the efficiency of response inhibition. At a corrected threshold (P < 0.0005), a paracentral lobule-midcingulate network and a left inferior parietal-supplementary motor-somatomotor network showed a positive correlation between SE beta weight and SSRT. In contrast, a midline cerebellum-thalamus-pallidum network showed a negative correlation between SE beta weight and SSRT. These findings suggest that motor preparation and execution prolongs the SSRT, likely via an interaction between the go and stop processes as suggested by the race model. Behaviorally, consistent with this hypothesis, the difference in G and SE reaction times is positively correlated with SSRT across subjects. These new results highlight the importance of cognitive motor regions in response inhibition and support the utility of ICA in uncovering functional networks for cognitive control in the SST.
认知控制是一项关键的执行功能。许多研究将一般线性模型与停止信号任务(SST)相结合,以描绘认知控制的组成过程。例如,通过对比SST中的停止成功(SS)和停止错误(SE)试验,研究人员检查了对停止信号抑制的区域反应。与这种参数化方法不同,独立成分分析(ICA)阐明了支持认知控制的脑网络。在我们早期对59名成年人在功能磁共振成像(fMRI)期间执行SST的研究中,我们确定了六个独立成分(IC)。然而,这些IC中没有一个与停止信号表现相关,这引发了对其行为有效性的质疑。在此,在一个更大的样本(n = 100)中,我们识别并探索了23个IC与停止信号反应时间(SSRT)的相关性,SSRT是反应抑制效率的一种度量。在校正阈值(P < 0.0005)下,中央旁小叶 - 扣带回中部网络和左侧顶下小叶 - 辅助运动 - 躯体运动网络在SE贝塔权重与SSRT之间呈现正相关。相比之下,中线小脑 - 丘脑 - 苍白球网络在SE贝塔权重与SSRT之间呈现负相关。这些发现表明,运动准备和执行可能通过竞争模型所暗示的启动和停止过程之间的相互作用延长了SSRT。在行为上,与这一假设一致,启动(G)和停止错误(SE)反应时间的差异在不同受试者中与SSRT呈正相关。这些新结果突出了认知运动区域在反应抑制中的重要性,并支持了ICA在揭示SST中认知控制功能网络方面的实用性。