Human Effectiveness Section, Defence Research and Development Canada, Toronto Research Centre, Toronto, ON, Canada.
Human Effectiveness Section, Defence Research and Development Canada, Toronto Research Centre, Toronto, ON, Canada; Department of Psychology, University of Toronto, Toronto, ON, Canada.
Neuropsychologia. 2022 Sep 9;174:108350. doi: 10.1016/j.neuropsychologia.2022.108350. Epub 2022 Aug 19.
Multitasking is a common requirement in many occupations. Considerable research has demonstrated that performance declines as a result of multitasking, and that it engages multiple brain regions. Despite growing evidence suggesting that brain regions operate as networks, minimal research has investigated the cognitive brain networks implicated in multitasking. The Multi-Attribute Task Battery II (MATB) is a common method for assessing multitasking ability that simulates a pilot's operational environment inside an aircraft cockpit. The aim of the present study was to examine multitasking performance on the MATB, and the associated neural patterns underlying performance with functional magnetic resonance imaging (fMRI). Twenty-four participants completed the MATB in the fMRI scanner. Participants completed four runs of the MATB in a 2 (Task: multitasking vs. single tasking) × 2 (Difficulty: hard vs. easy) design. MATB performance was measured as a function of accuracy. We analyzed the fMRI brain scans using both static and dynamic functional connectivity to determine whether there were differences in the connectivity patterns associated with each of the four conditions. A significant interaction between Task and Difficulty was observed such that multitasking performance accuracy, which was derived from the average across tasks, was lower than single tasking in the hard, but not easy, condition. The fMRI data revealed that static and dynamic functional connectivity between the default mode and dorsal attention networks was stronger during multitasking relative to single tasking. The static functional connectivity between the default mode and left frontoparietal networks, along with the dynamic functional connectivity between the dorsal attention and left frontoparietal networks, were both more anti-correlated during multitasking relative to single tasking. Taken together, the static and dynamic functional connectivity analyses provide complementary information to reveal the interactions among cognitive networks that support multitasking performance. Targeting these networks may offer a path to enhance multitasking ability through the application of neurostimulation and neuroenhancement techniques.
多任务处理是许多职业的常见要求。大量研究表明，多任务处理会导致性能下降，并且涉及多个大脑区域。尽管越来越多的证据表明大脑区域作为网络运作，但很少有研究调查涉及多任务处理的认知大脑网络。多属性任务电池 II（MATB）是评估多任务处理能力的常用方法，它模拟了飞行员在飞机驾驶舱内的操作环境。本研究的目的是检查 MATB 上的多任务处理性能，以及与功能磁共振成像（fMRI）相关的性能的相关神经模式。二十四名参与者在 fMRI 扫描仪中完成了 MATB。参与者在 2（任务：多任务处理与单任务处理）×2（难度：难与易）设计中完成了四个 MATB 运行。MATB 性能以准确性为衡量标准。我们使用静态和动态功能连接来分析 fMRI 脑扫描，以确定与四个条件中的每一个相关的连接模式是否存在差异。任务和难度之间观察到显著的交互作用，即多任务处理的准确性（通过任务的平均值得出）在困难条件下低于单任务处理，而在容易条件下则不然。fMRI 数据显示，在多任务处理相对于单任务处理时，默认模式和背侧注意网络之间的静态和动态功能连接更强。在多任务处理相对于单任务处理时，默认模式和左额顶叶网络之间的静态功能连接以及背侧注意和左额顶叶网络之间的动态功能连接都更加反相关。总之，静态和动态功能连接分析提供了互补的信息，揭示了支持多任务处理性能的认知网络之间的相互作用。通过应用神经刺激和神经增强技术，针对这些网络可能为提高多任务处理能力提供一条途径。
