Department of Psychiatry, Yale University, New Haven, Connecticut, USA.
Hum Brain Mapp. 2012 Jan;33(1):89-104. doi: 10.1002/hbm.21197. Epub 2011 Mar 1.
Cognitive control is a critical executive function of the human brain. 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 the neural processes underlying stop signal inhibition (SS > SE) and error processing (SE > SS). To complement this parameterized approach, here, we employed a data-driven method--independent component analysis (ICA)--to elucidate neural networks and the relationship between neural networks subserving cognitive control. In 59 adults performing the SST during fMRI, we characterized six independent components with ICA. These functional networks, temporally sorted for go success, SS, and SE trials as the events of interest, included a motor cortical network for motor preparation and execution; a right fronto-parietal network for attentional monitoring; a left fronto-parietal network for response inhibition; a midline cortico-subcortical network for error processing; a cuneus-precuneus network for behavioral engagement; and a "default" network for self-referential processing. Across subjects the event-associated weights of these functional networks showed a distinct pattern of correlation. These results provide new insight into the component processes of cognitive control.
认知控制是人类大脑的一项关键执行功能。许多研究结合了一般线性模型和停止信号任务 (SST) 来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，研究人员研究了停止信号抑制 (SS > SE) 和错误处理 (SE > SS) 的神经过程。为了补充这种参数化方法，我们在这里采用了一种数据驱动的方法——独立成分分析 (ICA)——来阐明认知控制的神经网络及其关系。在 59 名成年人进行 fMRI 期间的 SST 中，我们使用 ICA 对六个独立成分进行了特征描述。这些功能网络，根据 Go 成功、SS 和 SE 试验的时间顺序进行排序，作为感兴趣的事件，包括用于运动准备和执行的运动皮质网络；用于注意力监测的右额顶网络；用于反应抑制的左额顶网络；用于错误处理的中脑皮质下网络；用于行为参与的楔前叶网络；以及用于自我参照处理的“默认”网络。在受试者之间，这些功能网络的事件相关权重表现出一种独特的相关性模式。这些结果为认知控制的组成过程提供了新的见解。
