Chuang Chun-Hsiang, Ko Li-Wei, Jung Tzyy-Ping, Lin Chin-Teng
Brain Research Center, National Chiao Tung University, Hsinchu, Taiwan; Institute of Electrical Control Engineering, Department of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu, Taiwan; Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California, San Diego, CA, USA.
Brain Research Center, National Chiao Tung University, Hsinchu, Taiwan; Department of Biological Science and Technology, National Chiao Tung University, Hsinchu, Taiwan.
Neuroimage. 2014 May 1;91:187-202. doi: 10.1016/j.neuroimage.2014.01.015. Epub 2014 Jan 18.
This study investigated the effects of kinesthetic stimuli on brain activities during a sustained-attention task in an immersive driving simulator. Tonic and phasic brain responses on multiple timescales were analyzed using time-frequency analysis of electroencephalographic (EEG) sources identified by independent component analysis (ICA). Sorting EEG spectra with respect to reaction times (RT) to randomly introduced lane-departure events revealed distinct effects of kinesthetic stimuli on the brain under different performance levels. Experimental results indicated that EEG spectral dynamics highly correlated with performance lapses when driving involved kinesthetic feedback. Furthermore, in the realistic environment involving both visual and kinesthetic feedback, a transitive relationship of power spectra between optimal-, suboptimal-, and poor-performance groups was found predominately across most of the independent components. In contrast to the static environment with visual input only, kinesthetic feedback reduced theta-power augmentation in the central and frontal components when preparing for action and error monitoring, while strengthening alpha suppression in the central component while steering the wheel. In terms of behavior, subjects tended to have a short response time to process unexpected events with the assistance of kinesthesia, yet only when their performance was optimal. Decrease in attentional demand, facilitated by kinesthetic feedback, eventually significantly increased the reaction time in the suboptimal-performance state. Neurophysiological evidence of mutual relationships between behavioral performance and neurocognition in complex task paradigms and experimental environments, presented in this study, might elucidate our understanding of distributed brain dynamics, supporting natural human cognition and complex coordinated, multi-joint naturalistic behavior, and lead to improved understanding of brain-behavior relations in operating environments.
本研究调查了在沉浸式驾驶模拟器中,持续注意力任务期间动觉刺激对大脑活动的影响。使用独立成分分析(ICA)识别的脑电图(EEG)源的时频分析,分析了多个时间尺度上的强直和相位脑反应。根据对随机引入的车道偏离事件的反应时间(RT)对EEG频谱进行分类,揭示了动觉刺激在不同性能水平下对大脑的不同影响。实验结果表明,当驾驶涉及动觉反馈时,EEG频谱动态与性能失误高度相关。此外,在涉及视觉和动觉反馈的现实环境中,在大多数独立成分中,主要发现了最佳、次优和差性能组之间功率谱的传递关系。与仅具有视觉输入的静态环境相比,动觉反馈在准备行动和错误监测时减少了中央和额叶成分中的θ功率增强,同时在转动方向盘时增强了中央成分中的α抑制。在行为方面,受试者在动觉的帮助下倾向于对意外事件有较短的反应时间,但仅当他们的表现最佳时。动觉反馈促进了注意力需求的降低,最终在次优性能状态下显著增加了反应时间。本研究中呈现的复杂任务范式和实验环境中行为表现与神经认知之间相互关系的神经生理学证据,可能会阐明我们对分布式脑动态的理解,支持自然人类认知和复杂协调的多关节自然行为,并有助于更好地理解操作环境中的脑-行为关系。