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在明显的和想象的执行中,不可预测的停止和不停顿线索的神经关联。

Neural correlates of unpredictable Stop and non-Stop cues in overt and imagined execution.

机构信息

Psychological Neuroscience Lab, CIPsi, School of Psychology, University of Minho, Braga, Portugal.

Department of Clinical Psychology and Psychobiology, University of Santiago de Compostela, Santiago de Compostela, Spain.

出版信息

Psychophysiology. 2022 Jul;59(7):e14019. doi: 10.1111/psyp.14019. Epub 2022 Feb 27.

Abstract

The ability to inhibit incorrect behaviors is crucial for survival. In real contexts, cues that require stopping usually appear intermixed with indications to continue the ongoing action. However, in the classical Stop-signal task (SST), the unpredictable stimuli are always signals that require inhibition. To understand the neural mechanisms activated by low-probability nonstop cues, we recorded the electroencephalography from 23 young volunteers while they performed a modified SST where the unpredictable stimuli could be either Stop or confirmatory Go signals (CGo). To isolate the influence of motor output, the SST was performed during overt and covert execution. We found that, paradoxically, CGo stimuli activated motor inhibition processes, and evoked patterns of brain activity similar to those obtained after Stop signals (N2/P3 event-related potentials and midfrontal theta power increase), though in lesser magnitude. These patterns were also observed during the imagined performance. Finally, applying machine learning procedures, we found that the brain activity evoked after CGo versus Stop signals can be classified above chance during both, overt and imagined execution. Our results provide evidence that unpredictable signals cause motor inhibition even when they require to continue an ongoing action.

摘要

抑制错误行为的能力对生存至关重要。在实际环境中,需要停止的线索通常与继续进行当前动作的指示混合出现。然而,在经典的停止信号任务(SST)中,不可预测的刺激总是需要抑制的信号。为了了解由低概率非停止线索激活的神经机制,我们在 23 名年轻志愿者执行修改后的 SST 时记录了他们的脑电图,其中不可预测的刺激可以是停止或确认的 Go 信号(CGo)。为了隔离运动输出的影响,SST 在明显和隐蔽执行时进行。我们发现,矛盾的是,CGo 刺激激活了运动抑制过程,并引起了类似于停止信号后获得的脑活动模式(N2/P3 事件相关电位和额中theta 功率增加),尽管幅度较小。这些模式在想象的表现中也观察到。最后,通过应用机器学习程序,我们发现,在明显和想象的执行过程中,CGo 与停止信号后诱发的脑活动可以超过机会水平进行分类。我们的结果提供了证据,表明不可预测的信号即使需要继续进行当前动作,也会引起运动抑制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a66/9286458/9bff8862391a/PSYP-59-0-g003.jpg

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