Department of Psychology, University of Cologne, Germany.
Department of Psychology, University of Cologne, Germany; Melbourne School of Psychological Sciences, The University of Melbourne, Australia.
Neuroimage. 2019 Aug 15;197:544-556. doi: 10.1016/j.neuroimage.2019.05.006. Epub 2019 May 3.
Accurate force production is an essential motor function which, in most cases, requires continuous performance monitoring. Unlike choice-response tasks with two response alternatives, the accuracy in a force production paradigm is defined as an area between an upper and lower limit on the force continuum. In the present study, we investigated the neural mechanisms underlying force production. We used a force production task in which the participants (n = 48) were asked to exert a brief force pulse within a specific force range. This allowed: (1) investigation of action monitoring activity during force execution using response-locked and feedback-locked event-related potential (ERP) components known to be involved in error monitoring; (2) multivariate pattern analysis (MVPA) for ERPs. We found that the different force production ranges (characterised as too low, correct, and too high with respect to the target force range) showed no clear error-specific variations in the ERP components of interest. MVPA, on the other hand, allowed for successful classification, not only between the correct and the incorrect outcome conditions, but also between the two incorrect outcome conditions. This suggests that the classifier identified neural patterns reflecting the force magnitude rather than the correctness of a response. Moreover, additional support-vector regression (SVR) analyses showed that single-trial response parameters (i.e. peak force and time-to-peak) could be decoded from the brain activity pattern starting from 140 ms (for peak force) and 270 ms (for time-to-peak) before the response onset. These results indicate that the motor program defined the magnitude and timing of the force pulse before response execution, while the correctness of that response (in relation to the "default force" required) was not yet foreshadowed in neural signals. Finally, this study presents the first evidence of a post-error force adjustment mechanism, for which participants produced a higher force in trials after under-producing the required force, and a lower force in trials after over-producing the required force.
精确的力量产生是一种基本的运动功能，在大多数情况下，需要持续的性能监测。与仅有两个反应选择的选择反应任务不同，力量产生范式中的准确性被定义为力量连续体上限和下限之间的区域。在本研究中，我们研究了力量产生的神经机制。我们使用了一种力量产生任务，要求参与者（n=48）在特定的力量范围内短暂地施加力量脉冲。这允许：（1）使用与错误监测相关的已知的反应锁定和反馈锁定事件相关电位（ERP）成分来研究力量执行过程中的动作监测活动；（2）对 ERP 进行多元模式分析（MVPA）。我们发现，不同的力量产生范围（特征为相对于目标力量范围过低、正确和过高）在感兴趣的 ERP 成分中没有显示出明显的错误特异性变化。另一方面，MVPA 允许成功分类，不仅可以区分正确和不正确的结果条件，还可以区分两个不正确的结果条件。这表明分类器识别的神经模式反映了力量的大小，而不是响应的正确性。此外，额外的支持向量回归（SVR）分析表明，从反应开始前 140ms（用于峰值力）和 270ms（用于到达峰值时间）开始，就可以从大脑活动模式中解码单次试验的反应参数（即峰值力和到达峰值时间）。这些结果表明，在响应执行之前，运动程序定义了力量脉冲的大小和时间，而该响应的正确性（与所需的“默认力量”相关）尚未在神经信号中预示。最后，本研究首次提供了一种错误后力量调整机制的证据，参与者在需要的力量产生不足的试验后产生更高的力量，在需要的力量产生过高的试验后产生更低的力量。
