Midfrontal mechanisms of performance monitoring continuously adapt to incoming information during outcome anticipation

Q4 Neuroscience
Leon Lange , Joanna Kisker , Roman Osinsky
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引用次数: 0

Abstract

Performance monitoring is essential for successful action execution and previous studies have suggested that frontomedial theta (FMT) activity in scalp-recorded EEG reflects need for control signaling in response to negative outcomes. However, these studies have overlooked the fact that anticipating the most probable outcome is often possible. To optimize action execution, it is necessary for the time-critical performance monitoring system to utilize continuously updated information to adjust actions in time. This study used a combination of mobile EEG and virtual reality to investigate how the performance monitoring system adapts to continuously updated information during brief phases of outcome evaluation that follow action execution. In two virtual shooting tasks, participants were either able to observe the projectile and hence anticipate the outcome or not. We found that FMT power increased in response to missing shots in both tasks, but this effect was suppressed when participants were able to anticipate the outcome. Specifically, the suppression was linearly related to the duration of the anticipatory phase. Our results suggest that the performance monitoring system dynamically integrates incoming information to evaluate the most likely outcome of an action as quickly as possible. This dynamic mode of performance monitoring provides significant advantages over idly waiting for an action outcome before getting engaged. Early and adaptive performance monitoring not only helps prevent negative outcomes but also improves overall performance. Our findings highlight the crucial role of dynamic integration of incoming information in the performance monitoring system, providing insights for real-time decision-making and action control.

在预期结果的过程中,中额叶性能监测机制不断适应传入的信息
绩效监测对于成功执行动作至关重要,先前的研究表明,头皮记录脑电图中的额内侧θ(FMT)活动反映了对负面结果的控制信号的需要。然而,这些研究忽略了一个事实,即预测最可能的结果往往是可能的。为了优化行动执行,时间关键型性能监控系统有必要利用不断更新的信息及时调整行动。本研究将移动脑电图和虚拟现实相结合,研究了绩效监测系统如何在行动执行后的结果评估的短暂阶段适应不断更新的信息。在两个虚拟射击任务中,参与者要么能够观察到炮弹,从而预测结果,要么不能。我们发现,在两项任务中,FMT的力量都会因投篮失误而增加,但当参与者能够预测结果时,这种影响就会被抑制。具体而言,抑制与预期阶段的持续时间呈线性相关。我们的结果表明,性能监控系统动态集成传入信息,以尽快评估行动的最可能结果。这种动态的性能监控模式提供了显著的优势,而不是在参与之前无所事事地等待行动结果。早期和适应性的绩效监控不仅有助于防止负面结果,还可以提高整体绩效。我们的研究结果强调了传入信息的动态集成在绩效监控系统中的关键作用,为实时决策和行动控制提供了见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Neuroimage. Reports
Neuroimage. Reports Neuroscience (General)
CiteScore
1.90
自引率
0.00%
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0
审稿时长
87 days
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