Irons Jessica L, Leber Andrew B
Department of Psychology, The Ohio State University, 225 Psychology Building, 1835 Neil Avenue, Columbus, OH, 43210, USA.
Atten Percept Psychophys. 2016 Oct;78(7):2031-48. doi: 10.3758/s13414-016-1125-4.
Goal-directed attentional control supports efficient visual search by prioritizing relevant stimuli in the environment. Previous research has shown that goal-directed control can be configured in many ways, and often multiple control settings can be used to achieve the same goal. However, little is known about how control settings are selected. We explored the extent to which the configuration of goal-directed control is driven by performance maximization (optimally configuring settings to maximize speed and accuracy) and effort minimization (selecting the least effortful settings). We used a new paradigm, adaptive choice visual search, which allows participants to choose one of two available targets (a red or a blue square) on each trial. Distractor colors vary predictively across trials, such that the optimal target switches back and forth throughout the experiment. Results (N = 43) show that participants chose the optimal target most often, updating to the new target when the environment changed, supporting performance maximization. However, individuals were sluggish to update to the optimal color, consistent with effort minimization. Additionally, we found a surprisingly high rate of nonoptimal choices and switching between targets, which could not be explained by either factor. Analysis of participants' self-reported search strategy revealed substantial individual differences in the control strategies used. In sum, the adaptive choice visual search enables a fresh approach to studying goal-directed control. The results contribute new evidence that control is partly determined by both performance maximization and effort minimization, as well as at least one additional factor, which we speculate to include novelty seeking.
目标导向的注意力控制通过对环境中的相关刺激进行优先级排序来支持高效的视觉搜索。先前的研究表明，目标导向控制可以通过多种方式进行配置，并且通常可以使用多种控制设置来实现相同的目标。然而，对于如何选择控制设置却知之甚少。我们探讨了目标导向控制的配置在多大程度上是由性能最大化（以最优方式配置设置以最大化速度和准确性）和努力最小化（选择最省力的设置）驱动的。我们使用了一种新的范式，即自适应选择视觉搜索，它允许参与者在每次试验中从两个可用目标（一个红色或一个蓝色正方形）中选择一个。干扰物颜色在各次试验中具有预测性变化，使得最优目标在整个实验过程中来回切换。结果（N = 43）表明，参与者最常选择最优目标，并在环境变化时更新到新目标，这支持了性能最大化。然而，个体向最优颜色更新的速度较慢，这与努力最小化一致。此外，我们发现非最优选择和目标之间切换的比例高得出奇，这两个因素都无法解释这种情况。对参与者自我报告的搜索策略的分析揭示了所使用的控制策略存在很大的个体差异。总之，自适应选择视觉搜索为研究目标导向控制提供了一种新方法。这些结果提供了新的证据，表明控制部分由性能最大化和努力最小化以及至少一个额外因素决定，我们推测这个额外因素包括寻求新奇。
