Applied Cognitive Neuroscience Laboratory, Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong; Laboratory of Neuropsychology and Human Neuroscience, Department of Psychology, The University of Hong Kong, Hong Kong; The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China.
College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, 1 Huatuo Road, Minhou Shangjie, Fuzhou, Fujian 350122, China; National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, China; Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, United States; Key Laboratory of Orthopedics & Traumatology of Traditional Chinese Medicine and Rehabilitation (Fujian University of Traditional Chinese Medicine), Ministry of Education.
Neuroimage. 2021 Feb 1;226:117556. doi: 10.1016/j.neuroimage.2020.117556. Epub 2020 Nov 13.
Processing speed is an important construct in understanding cognition. This study was aimed to control task specificity for understanding the neural mechanisms underlying cognitive processing speed. Forty young adult subjects performed attention tasks of two modalities (auditory and visual) and two levels of task rules (compatible and incompatible). Block-design fMRI captured BOLD signals during the tasks. Thirteen regions of interest were defined with reference to publicly available activation maps for processing speed tasks. Cognitive speed was derived from task reaction times, which yielded six sets of connectivity measures. Mixed-effect LASSO regression revealed six significant paths suggestive of a cerebello-frontal network predicting the cognitive speed. Among them, three are long range (two fronto-cerebellar, one cerebello-frontal), and three are short range (fronto-frontal, cerebello-cerebellar, and cerebello-thalamic). The long-range connections are likely to relate to cognitive control, and the short-range connections relate to rule-based stimulus-response processes. The revealed neural network suggests that automaticity, acting on the task rules and interplaying with effortful top-down attentional control, accounts for cognitive speed.
加工速度是理解认知的一个重要结构。本研究旨在控制任务特异性,以了解认知加工速度的神经机制。四十名年轻成年受试者执行了两种模态(听觉和视觉)和两种任务规则水平(相容和不相容)的注意任务。块设计 fMRI 在任务期间捕获了 BOLD 信号。参考处理速度任务的公开激活图,定义了 13 个感兴趣区。认知速度源自任务反应时间,得出了六组连接度量。混合效应 LASSO 回归揭示了六个具有预测认知速度的显著路径,提示存在一个小脑-前额叶网络。其中,有三个是长程的(两个额-小脑,一个小脑-前额叶),三个是短程的(额-额、小脑-小脑和小脑-丘脑)。长程连接可能与认知控制有关,而短程连接与基于规则的刺激-反应过程有关。所揭示的神经网络表明,自动性作用于任务规则,并与费力的自上而下的注意力控制相互作用,解释了认知速度。