Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology, Universidad Politécnica de Madrid, Madrid, Spain.
Laboratory of Electrical Engineering and Bioengineering, Department of Industrial Engineering, Universidad de La Laguna, Tenerife, Spain.
Brain Topogr. 2018 May;31(3):407-418. doi: 10.1007/s10548-017-0607-6. Epub 2017 Nov 9.
One common assumption has been that prefrontal executive control is mostly required for target detection (Posner and Petersen in Ann Rev Neurosci 13:25-42, 1990). Alternatively, cognitive control has also been related to anticipatory updating of task-set (contextual) information, a view that highlights proactive control processes. Frontoparietal cortical networks contribute to both proactive control and reactive target detection, although their fast dynamics are still largely unexplored. To examine this, we analyzed rapid magnetoencephalographic (MEG) source activations elicited by task cues and target cards in a task-cueing analogue of the Wisconsin Card Sorting Test. A single-task (color sorting) condition with equivalent perceptual and motor demands was used as a control. Our results revealed fast, transient and largely switch-specific MEG activations across frontoparietal and cingulo-opercular regions in anticipation of target cards, including (1) early (100-200 ms) cue-locked MEG signals at visual, temporo-parietal and prefrontal cortices of the right hemisphere (i.e., calcarine sulcus, precuneus, inferior frontal gyrus, anterior insula and supramarginal gyrus); and (2) later cue-locked MEG signals at the right anterior and posterior insula (200-300 ms) and the left temporo-parietal junction (300-500 ms). In all cases larger MEG signal intensity was observed in switch relative to repeat cueing conditions. Finally, behavioral restart costs and test scores of working memory capacity (forward digit span) correlated with cue-locked MEG activations at key nodes of the frontoparietal network. Together, our findings suggest that proactive cognitive control of task rule updating can be fast and transiently implemented within less than a second and in anticipation of target detection.
一种常见的假设是,前额叶执行控制主要用于目标检测(波斯纳和彼得森,《神经科学年度评论》13:25 - 42,1990年)。另一种观点认为,认知控制也与任务集(情境)信息的预期更新有关,这种观点强调了主动控制过程。额顶叶皮层网络对主动控制和反应性目标检测都有贡献,尽管其快速动态变化在很大程度上仍未被探索。为了研究这一点,我们在威斯康星卡片分类测试的任务提示模拟实验中,分析了任务提示和目标卡片引发的快速脑磁图(MEG)源激活。使用了一个具有同等感知和运动需求的单任务(颜色分类)条件作为对照。我们的结果显示,在预期目标卡片出现时,额顶叶和扣带回 - 岛叶区域出现了快速、短暂且主要是与切换相关的MEG激活,包括:(1)右半球视觉、颞顶叶和前额叶皮层(即距状沟、楔前叶、额下回、前岛叶和缘上回)早期(100 - 200毫秒)与提示相关的MEG信号;以及(2)右前岛叶和后岛叶(200 - 300毫秒)以及左颞顶叶交界处(300 - 500毫秒)后期与提示相关的MEG信号。在所有情况下,与重复提示条件相比,切换提示条件下观察到的MEG信号强度更大。最后,行为重启成本和工作记忆容量(顺背数字广度)测试分数与额顶叶网络关键节点处与提示相关的MEG激活相关。总之,我们的研究结果表明,对任务规则更新的主动认知控制可以在不到一秒的时间内快速且短暂地实现,并先于目标检测。