During everyday tasks, salient distractors may capture our attention. Recently, it was shown that through implicit learning, capture by a salient distractor is reduced by suppressing the location where a distractor is likely to appear. In the current study, we presented distractors of different saliency levels at the same specific location, asking the question whether there is always one suppression level for a particular location or whether, for one location, suppression depends on the actual saliency of the distractor appearing at that location. In three experiments, we demonstrate a saliency-specific mechanism of distractor suppression, which can be flexibly modulated by the overall probability of encountering distractors of different saliency levels to optimize behavior in a specific environment. The results also suggest that this mechanism has dimension-independent aspects, given that the saliency-specific suppression pattern is unaffected when saliency signals of distractors are generated by different dimensions. It is argued that suppression is saliency-dependent, implying that suppression is modulated on a trial-by-trial basis contingent on the saliency of the actual distractor presented.

在日常工作中，明显的干扰因素可能会引起我们的注意。最近，显示出通过隐式学习，通过抑制可能出现干扰物的位置来减少突出干扰物的捕获。在当前的研究中，我们介绍了在同一特定位置具有不同显着性水平的干扰物，询问以下问题：特定位置是否始终存在一个抑制水平，或者对于一个位置，抑制是否取决于出现在干扰源处的干扰物的实际显着性？该位置。在三个实验中，我们证明了干扰力抑制的显着性特定机制，可以通过遇到不同显着性级别的干扰器的总概率来灵活地调节干扰器，以优化特定环境中的行为。结果还表明，这种机制具有与尺寸无关的方面，因为当不同尺寸的干扰物的显着性信号产生时，显着性特定的抑制模式不会受到影响。有人认为抑制是与显着性有关的，这意味着抑制是根据所呈现的实际干扰因素的显着性在逐个试验的基础上进行调制的。