Department of Neuroscience, University of Padova, Padova, Italy.
Department of Neuroscience & Padova Neuroscience Center, University of Padova, Padova, Italy.
Psychophysiology. 2020 Nov;57(11):e13642. doi: 10.1111/psyp.13642. Epub 2020 Jul 28.
Task-switching paradigms, which involve task repetitions and between-task switches, have long been used as a benchmark of cognitive control processes. When mixed and single-task blocks are presented, two types of costs usually occur: the switch cost, measured by contrasting performance on switch and repeat trials during the mixed-task blocks, and the mixing cost, calculated as the performance difference between the all-repeat trials from the single-task blocks and the repeat trials from the mixed-task blocks. Both costs can be mitigated by informational cues that signal the upcoming task switch beforehand. Recent electroencephalographic studies have started unveiling the brain oscillatory activity underlying the switch cost during the preparatory cue-target interval, thus, targeting proactive control processes. Less attention has instead been paid to the mixing cost and, importantly, to the oscillatory dynamics involved in switch and mixing costs during reactive control. To fill this gap, here, we analyzed the time-frequency data obtained during a task-switching paradigm wherein the simultaneous presentation of task cues and targets increased the need for reactive control. Results showed that while alpha and beta bands were modulated by switch and mixing costs in a similar gradual fashion, with greater suppression going from switch to repeat and all-repeat trials, theta power was sensitive to the switch cost with increased power for switch than repeat trials. Together, our findings join previous studies underlining the importance of theta, alpha and beta oscillations in task-switching and extend them by depicting the oscillations involved in switch and mixing costs during reactive control processes.
任务转换范式，涉及任务重复和任务间转换，长期以来一直被用作认知控制过程的基准。当混合和单任务块呈现时，通常会出现两种类型的成本：切换成本，通过对比混合任务块中切换和重复试验的表现来衡量；混合成本，通过计算单任务块中的所有重复试验与混合任务块中的重复试验之间的表现差异来计算。这两种成本都可以通过提前发出信号告知即将到来的任务切换的信息线索来减轻。最近的脑电图研究已经开始揭示在预备线索-目标间隔期间，切换成本背后的大脑振荡活动，从而针对主动控制过程。然而，对混合成本的关注较少，而且，对反应性控制期间涉及切换和混合成本的振荡动力学的关注也较少。为了填补这一空白，在这里，我们分析了在任务转换范式中获得的时频数据，其中任务线索和目标的同时呈现增加了对反应性控制的需求。结果表明，虽然 alpha 和 beta 波段以相似的渐变方式被切换和混合成本调制，随着从切换到重复和所有重复试验的抑制增加，但 theta 功率对切换成本敏感，切换试验的功率大于重复试验的功率。总的来说，我们的研究结果加入了先前的研究，强调了 theta、alpha 和 beta 振荡在任务转换中的重要性，并通过描绘反应性控制过程中涉及切换和混合成本的振荡，扩展了这些研究。
