Individual differences and modulation of conflict monitoring intensity as a determinant of avoidance learning: Evidence for an integrative ACC theory?

作为先前研究结果的延伸，我们的目标是在最近的前扣带皮层（ACC）活动理论的背景下研究冲突监测和被动回避学习，说明通过所需努力和厌恶强化调节冲突监测强度。这两位研究人员从2012年开始在波恩大学（University of Bonn）以双职工夫妇的身份成功合作了几年。迄今为止，作为强化学习的一种形式，冲突监测和被动回避学习的神经过程已经得到了相当独立的研究。然而，只要还没有研究Botvinick假设的强化冲突监测是否会导致任务执行过程中被动回避学习的强化，我们就不能得出强化冲突监测在决策过程和被动回避学习过程中起到厌恶教学信号作用的结论。然而，这些发现将进一步推动最近关于行政协调会职能相关性的广泛理论辩论。提高冲突监测强度和后续被动回避学习的一种可能是动机因素的准实验操纵。在这方面，在研究1中，我们的目标是通过在执行歧视任务期间使用最大和平均认知努力试验来改变个体动机。我们认为，个体努力动机导致的冲突监测强度的增加会强化被动回避学习。如果强化的冲突监测和随后强化的被动回避学习在日常情境中是重要的，那么强化的冲突监测对回避学习的影响应该推广到嵌入到日常情境中的歧视任务中。在研究2中，参与者执行基于描述更自然背景的小插图的辨别任务。初步研究表明，基于面孔的歧视任务和基于小插曲的歧视任务诱导冲突监测和被动回避学习的可能性。此外，同伴的存在被操纵，以调节冲突监测，从而被动回避学习。为了验证我们的假设，我们在大样本（每项研究超过120名参与者）中，通过多通道脑电图和行为参数来评估众所周知的事件相关电位。为了研究冲突监测与被动回避学习的个体差异之间的直接关系，我们创新性地采用了成长模型作为统计分析工具。

As an extension of prior findings illustrating the modulation of the conflict monitoring intensity by means of required effort and aversive reinforcement we aim at investigating conflict monitoring and passive avoidance learning in the context of recent theories on anterior cingulate cortex (ACC) activity. For several years, both researchers have successfully collaborated as a dual-career couple as they officially do since 2012 at the University of Bonn. Till date, the neural processes of conflict monitoring and passive avoidance learning as one form of reinforcement learning have been investigated rather independently. However, as long as it has not yet been investigated whether, as postulated by Botvinick, an intensified conflict monitoring results in an intensified passive avoidance learning during task performance, we cannot conclude that an intensified conflict monitoring serves as an aversive teaching signal in decision-making processes and during passive avoidance learning. Those findings would, however, further the most recent and extensive theoretical debate on the functional relevance of the ACC. One possibility to enhance the conflict monitoring intensity and subsequent passive avoidance learning is the quasi-experimental manipulation of motivational factors. In this respect, in Study 1 we aim at varying an individuals motivation by using a maximal vs. average cognitive effort trial-by-trial treatment during performance of a discrimination task. We expect that an increased conflict monitoring intensity induced by means of an individuals effort motivation should intensify passive avoidance learning. If an intensified conflict monitoring and subsequently an intensified passive avoidance learning are of importance for every-day contexts the effect of intensified conflict monitoring on avoidance learning should generalize to discrimination tasks that are embedded into every-day contexts. In Study 2, participants perform discrimination tasks that are based on a vignette describing a more natural context. The possibility to induce conflict monitoring and passive avoidance learning by means of a discrimination task based on faces and a discrimination task based on a vignette has been shown in preliminary studies. Moreover, the presence of peers is manipulated in order to modulate conflict monitoring and thereby passive avoidance learning. To test our hypotheses, well-known event-related potentials are assessed by means of a multi-channel electroencephalogram along with behavioral parameters in large samples (more than 120 participants per study). To investigate the direct relations of individual differences in conflict monitoring and passive avoidance learning growth-modeling is applied as an innovative statistical analysis tool.