Continuous action with a neurobiologically inspired computational approach reveals the dynamics of selection history.
Continuous action with a neurobiologically inspired computational approach reveals the dynamics of selection history.
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DOI：
10.1371/journal.pcbi.1011283
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发表时间：
2023-07
影响因子：
4.3
通讯作者：
中科院分区：
文献类型：
--
作者：
日常的感知-行动交互通常需要从多种可能性中选择一个目标。根据最近的注意力控制框架，对象选择不仅受到知觉显著性和当前目标等既定因素的指导，而且还受到选择历史的影响。然而，连接选择历史和视觉引导的行动的潜在机制知之甚少。为了研究这种相互作用，并解开目标和干扰物历史对动作选择的影响，我们采用了启动弹出（PoP）范式，结合连续跟踪达到运动和计算建模。参与者达到了一个奇怪的颜色目标之间的同质干扰，而我们系统地操纵的序列的目标和干扰颜色从一个试验到下一个。我们观察到，当前的达到运动显着影响的相互作用的吸引力由先前的目标功能和排斥的先前的干扰功能。通过主成分回归分析，我们发现先前干扰物导致的抑制作用对到达目标选择的影响早于先前目标物导致的易化作用。与此同时，我们新开发的计算模型验证，目前达到目标的选择，可以解释最好的机制假设之前的干扰，其次是以前的目标的影响。这种融合的经验和计算证据表明，先前的选择历史触发了目标促进和干扰抑制之间的动态相互作用，以成功地引导目标导向的行动。这反过来又强调了明确整合方法的必要性，以确定在复杂环境中视觉注意力选择与适应性行为的联系。大多数真实世界的视觉场景是复杂和拥挤的，其中多个对象竞争注意力和目标导向的动作。注意选择机制和行为选择机制之间的相互作用是许多复杂行为的根源。然而，它们之间的联系却没有得到充分的研究。为了研究这种相互作用，并解开目标和干扰物的历史对动作选择的影响，我们采用了启动弹出（PoP）范式结合连续跟踪达到运动和计算建模。这种综合办法与通常分别调查注意力和行动选择机制的现行做法有很大不同。我们的收敛证据支持的概念，事先选择的历史触发目标促进和干扰抑制之间的动态相互作用，以指导目标导向的行动成功。这一发现强调了明确的集成方法来确定视觉注意力选择如何在复杂环境中与适应性行动联系起来的必要性。总之，我们的研究提供了有价值的见解注意选择和行动选择的机制，并在这一领域的未来研究具有重要意义。
Everyday perception-action interaction often requires selection of a single goal from multiple possibilities. According to a recent framework of attentional control, object selection is guided not only by the well-established factors of perceptual salience and current goals but also by selection history. Yet, underlying mechanisms linking selection history and visually-guided actions are poorly understood. To examine such interplay and disentangle the impact of target and distractor history on action selection, we employed a priming-of-popout (PoP) paradigm combined with continuous tracking of reaching movements and computational modeling. Participants reached an odd-colored target among homogeneous distractors while we systematically manipulated the sequence of target and distractor colors from one trial to the next. We observed that current reach movements were significantly influenced by the interaction between attraction by the prior target feature and repulsion by the prior distractor feature. With principal component regression, we found that inhibition led by prior distractors influenced reach target selection earlier than facilitation led by the prior target. In parallel, our newly developed computational model validated that current reach target selection can be explained best by the mechanism postulating the preceded impact of previous distractors followed by a previous target. Such converging empirical and computational evidence suggests that the prior selection history triggers a dynamic interplay between target facilitation and distractor inhibition to guide goal-directed action successfully. This, in turn, highlights the necessity of an explicitly integrated approach to determine how visual attentional selection links with adaptive actions in a complex environment. Most real-world visual scenes are complex and crowded, where multiple objects compete for attention and goal-directed action. The interactions between mechanisms of attentional selection and action selection are at the root of many complex behaviors. However, their link has been understudied. To examine this interplay and disentangle the impact of target and distractor history on action selection, we employed a priming-of-popout (PoP) paradigm combined with continuous tracking of reaching movements and computational modeling. This integrated approach constitutes a significant departure from existing practice, where attention and action selection mechanisms are typically investigated separately. Our converging evidence supports the notion that prior selection history triggers a dynamic interplay between target facilitation and distractor inhibition to guide goal-directed action successfully. This finding highlights the necessity of an explicitly integrated approach to determine how visual attentional selection links with adaptive actions in complex environments. Taken together, our study provides valuable insights into the mechanisms underlying attentional selection and action selection, and has important implications for future research in this field.
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影响因子：
19.9
作者：
Awh, Edward;Belopolsky, Artem V.;Theeuwes, Jan
通讯作者：
Theeuwes, Jan
影响因子：
1.8
作者：
Lamy, Dominique;Antebi, Charlie;Carmel, Tomer
通讯作者：
Carmel, Tomer
影响因子：
5.4
作者：
Erlhagen, W;Schöner, G
通讯作者：
Schöner, G
DOI：
10.1073/pnas.1104047108
发表时间：
2011-06-21
影响因子：
11.1
作者：
Anderson, Brian A.;Laurent, Patryk A.;Yantis, Steven
通讯作者：
Yantis, Steven
影响因子：
1.8
作者：
Eimer, Martin;Kiss, Monika;Cheung, Theodore
通讯作者：
Cheung, Theodore