Wang Yu-Kai, Jung Tzyy-Ping, Lin Chin-Teng
Centre for Artificial Intelligence, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW, Australia.
Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California, San Diego, San Diego, CA, United States.
Front Behav Neurosci. 2018 Feb 9;12:3. doi: 10.3389/fnbeh.2018.00003. eCollection 2018.
Performing multiple tasks simultaneously usually affects the behavioral performance as compared with executing the single task. Moreover, processing multiple tasks simultaneously often involve more cognitive demands. Two visual tasks, lane-keeping task and mental calculation, were utilized to assess the brain dynamics through 32-channel electroencephalogram (EEG) recorded from 14 participants. A 400-ms stimulus onset asynchrony (SOA) factor was used to induce distinct levels of attentional requirements. In the dual-task conditions, the deteriorated behavior reflected the divided attention and the overlapping brain resources used. The frontal, parietal and occipital components were decomposed by independent component analysis (ICA) algorithm. The event- and response-related theta and alpha oscillations in selected brain regions were investigated first. The increased theta oscillation in frontal component and decreased alpha oscillations in parietal and occipital components reflect the cognitive demands and attentional requirements as executing the designed tasks. Furthermore, time-varying interactive over-additive (O-Add), additive (Add) and under-additive (U-Add) activations were explored and summarized through the comparison between the summation of the elicited spectral perturbations in two single-task conditions and the spectral perturbations in the dual task. Add and U-Add activations were observed while executing the dual tasks. U-Add theta and alpha activations dominated the posterior region in dual-task situations. Our results show that both deteriorated behaviors and interactive brain activations should be comprehensively considered for evaluating workload or attentional interaction precisely.
与执行单一任务相比,同时执行多项任务通常会影响行为表现。此外,同时处理多项任务往往涉及更多的认知需求。我们利用两项视觉任务,即车道保持任务和心算任务,通过记录14名参与者的32通道脑电图(EEG)来评估大脑动态。使用400毫秒的刺激起始异步(SOA)因素来诱导不同水平的注意力需求。在双任务条件下,行为恶化反映了注意力分散和大脑资源的重叠使用。通过独立成分分析(ICA)算法对额叶、顶叶和枕叶成分进行分解。首先研究了选定脑区中与事件和反应相关的θ波和α波振荡。额叶成分中θ波振荡增加,顶叶和枕叶成分中α波振荡减少,反映了执行设计任务时的认知需求和注意力需求。此外,通过比较两种单任务条件下诱发的频谱扰动总和与双任务中的频谱扰动,探索并总结了随时间变化的交互超加性(O-Add)、加性(Add)和次加性(U-Add)激活。在执行双任务时观察到了Add和U-Add激活。在双任务情况下,U-Add的θ波和α波激活在后部区域占主导地位。我们的结果表明,为了精确评估工作量或注意力交互,应综合考虑行为恶化和大脑交互激活。