Clinical and Cognitive Neurosciences, Department of Neurology, RWTH Aachen University Hospital, Pauwelsstr. 30, 52074, Aachen, Germany.
Institute of Occupational, Social and Environmental Medicine, Center for Health and Society, Medical Faculty, Heinrich Heine University Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany.
Brain Struct Funct. 2019 Jun;224(5):1845-1869. doi: 10.1007/s00429-019-01870-4. Epub 2019 Apr 29.
Although there are well-known limitations of the human cognitive system in performing two tasks simultaneously (dual-tasking) or alternatingly (task-switching), the question for a common vs. distinct neural basis of these multitasking limitations is still open. We performed two Activation Likelihood Estimation meta-analyses of neuroimaging studies on dual-tasking or task-switching and tested for commonalities and differences in the brain regions associated with either domain. We found a common core network related to multitasking comprising bilateral intraparietal sulcus (IPS), left dorsal premotor cortex (dPMC), and right anterior insula. Meta-analytic contrasts revealed eight fronto-parietal clusters more consistently activated in dual-tasking (bilateral frontal operculum, dPMC, and anterior IPS, left inferior frontal sulcus and left inferior frontal gyrus) and, conversely, four clusters (left inferior frontal junction, posterior IPS, and precuneus as well as frontomedial cortex) more consistently activated in task-switching. Together with sub-analyses of preparation effects in task-switching, our results argue against purely passive structural processing limitations in multitasking. Based on these findings and drawing on current theorizing, we present a neuro-cognitive processing model of multitasking.
尽管人类认知系统在同时执行两项任务(双重任务)或交替执行任务(任务转换)方面存在众所周知的局限性,但对于这些多任务限制的共同或独特的神经基础的问题仍然存在争议。我们对双重任务或任务转换的神经影像学研究进行了两次激活似然估计荟萃分析,并测试了与这两个领域相关的大脑区域的相似性和差异性。我们发现了一个与多任务相关的共同核心网络,包括双侧顶内沟(IPS)、左背侧运动前皮质(dPMC)和右前岛叶。荟萃分析对比显示,有八个额顶叶集群在双重任务中更一致地激活(双侧额下外侧回、dPMC 和前 IPS,左额下回和左额下回),相反,四个集群(左额下回连接部、后 IPS 和楔前叶以及额前皮质)在任务转换中更一致地激活。结合任务转换中准备效应的子分析,我们的结果反对多任务中纯粹的被动结构处理限制。基于这些发现,并借鉴当前的理论,我们提出了一个多任务的神经认知处理模型。