Connolly Joanna, McNulty Jonathan P, Boran Lorraine, Roche Richard A P, Delany David, Bokde Arun L W
1 Cognitive Systems Group, Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience , Trinity College Dublin, Dublin, Ireland .
2 School of Medicine, University College Dublin , Dublin, Ireland .
Brain Connect. 2016 Jun;6(5):365-74. doi: 10.1089/brain.2015.0399. Epub 2016 Mar 31.
The structural networks in the human brain are consistent across subjects, and this is reflected also in that functional networks across subjects are relatively consistent. These findings are not only present during performance of a goal oriented task but there are also consistent functional networks during resting state. It suggests that goal oriented activation patterns may be a function of component networks identified using resting state. The current study examines the relationship between resting state networks measured and patterns of neural activation elicited during a Stroop task. The association between the Stroop-activated networks and the resting state networks was quantified using spatial linear regression. In addition, we investigated if the degree of spatial association of resting state networks with the Stroop task may predict performance on the Stroop task. The results of this investigation demonstrated that the Stroop activated network can be decomposed into a number of resting state networks, which were primarily associated with attention, executive function, visual perception, and the default mode network. The close spatial correspondence between the functional organization of the resting brain and task-evoked patterns supports the relevance of resting state networks in cognitive function.
人类大脑中的结构网络在不同个体间是一致的，这也反映在不同个体间的功能网络相对一致。这些发现不仅在执行目标导向任务时存在，在静息状态下也存在一致的功能网络。这表明目标导向的激活模式可能是使用静息状态识别出的组成网络的一种功能。当前研究考察了静息状态网络测量值与在Stroop任务中引发的神经激活模式之间的关系。使用空间线性回归对Stroop激活网络与静息状态网络之间的关联进行了量化。此外，我们研究了静息状态网络与Stroop任务的空间关联程度是否可以预测Stroop任务的表现。这项研究的结果表明，Stroop激活网络可以分解为多个静息状态网络，这些网络主要与注意力、执行功能、视觉感知和默认模式网络相关。静息大脑的功能组织与任务诱发模式之间紧密的空间对应关系支持了静息状态网络在认知功能中的相关性。
