Cognitive Neuroscience of Perception and Action, Department of Psychology, Philipps-University Marburg, Marburg, Germany.
Sci Rep. 2023 Jan 30;13(1):1672. doi: 10.1038/s41598-022-25816-9.
When searching for a shape target, colour distractors typically capture our attention. Capture is smaller when observers search for a fixed target that allows for a feature-specific target template compared to a varying shape singleton target. Capture is also reduced when observers learn to predict the likely distractor location. We investigated how the precision of the target template modulates distractor location learning in an additional singleton search task. As observers are less prone to capture with a feature-specific target, we assumed that distractor location learning is less beneficial and therefore less pronounced than with a mixed-feature target. Hierarchical Bayesian parameter estimation was used to fit fine-grained distractor location learning curves. A model-based analysis of the time course of distractor location learning revealed an effect on the asymptotic performance level: when searching for a fixed-feature target, the asymptotic distractor cost indicated smaller distractor interference than with a mixed-feature target. Although interference was reduced for distractors at the high-probability location in both tasks, asymptotic distractor suppression was less pronounced with fixed-feature compared to mixed-feature targets. We conclude that with a more precise target template less distractor location learning is required, likely because the distractor dimension is down-weighted and its salience signal reduced.
当搜索形状目标时，颜色干扰项通常会吸引我们的注意力。与搜索允许特定特征目标模板的固定目标相比，观察者搜索变化形状的单一目标时，捕获会更小。当观察者学会预测可能的干扰位置时，捕获也会减少。我们研究了目标模板的精度如何在额外的单一搜索任务中调节干扰位置学习。由于观察者使用特定特征的目标不太容易被捕获，我们假设干扰位置学习的益处较小，因此不如混合特征目标明显。使用分层贝叶斯参数估计来拟合细粒度的干扰位置学习曲线。对干扰位置学习的时程进行基于模型的分析揭示了对渐近性能水平的影响：当搜索固定特征目标时，渐近干扰成本表明干扰干扰小于混合特征目标。尽管在两种任务中，高概率位置的干扰者的干扰都减少了，但与混合特征目标相比，固定特征目标的渐近干扰抑制效果不那么明显。我们得出的结论是，由于目标维度的权重降低，目标模板越精确，需要的干扰位置学习就越少，其显著性信号也会降低。
