Moran Rani, Teodorescu Andrei R, Usher Marius
School of Psychological Sciences, Tel Aviv University, Ramat Aviv, 69978, Israel; Sagol School of Neuroscience, Tel Aviv University, Ramat Aviv, 69978, Israel.
Department of Psychological and Brain Science, Indiana University, 1101 E. 10th St., Bloomington, IN, USA.
Cogn Psychol. 2015 May;78:99-147. doi: 10.1016/j.cogpsych.2015.01.002. Epub 2015 Apr 8.
Confidence judgments are pivotal in the performance of daily tasks and in many domains of scientific research including the behavioral sciences, psychology and neuroscience. Positive resolution i.e., the positive correlation between choice-correctness and choice-confidence is a critical property of confidence judgments, which justifies their ubiquity. In the current paper, we study the mechanism underlying confidence judgments and their resolution by investigating the source of the inputs for the confidence-calculation. We focus on the intriguing debate between two families of confidence theories. According to single stage theories, confidence is based on the same information that underlies the decision (or on some other aspect of the decision process), whereas according to dual stage theories, confidence is affected by novel information that is collected after the decision was made. In three experiments, we support the case for dual stage theories by showing that post-choice perceptual availability manipulations exert a causal effect on confidence-resolution in the decision followed by confidence paradigm. These finding establish the role of RT2, the duration of the post-choice information-integration stage, as a prime dependent variable that theories of confidence should account for. We then present a novel list of robust empirical patterns ('hurdles') involving RT2 to guide further theorizing about confidence judgments. Finally, we present a unified computational dual stage model for choice, confidence and their latencies namely, the collapsing confidence boundary model (CCB). According to CCB, a diffusion-process choice is followed by a second evidence-integration stage towards a stochastic collapsing confidence boundary. Despite its simplicity, CCB clears the entire list of hurdles.
信心判断在日常任务的执行以及包括行为科学、心理学和神经科学在内的许多科学研究领域中都至关重要。积极分辨率，即选择正确性与选择信心之间的正相关，是信心判断的一个关键属性，这证明了它们的普遍性。在本文中，我们通过研究信心计算输入的来源，来探讨信心判断及其分辨率背后的机制。我们关注信心理论的两个阵营之间有趣的争论。根据单阶段理论，信心基于与决策相同的信息（或决策过程的其他方面），而根据双阶段理论，信心受到决策做出后收集的新信息的影响。在三个实验中，我们通过表明选择后感知可用性操作对决策后信心范式中的信心分辨率产生因果效应，来支持双阶段理论。这些发现确立了RT2（选择后信息整合阶段的持续时间）作为信心理论应考虑的主要因变量的作用。然后，我们提出了一份涉及RT2的稳健实证模式（“障碍”）的新颖清单，以指导关于信心判断的进一步理论化。最后，我们提出了一个关于选择、信心及其潜伏期的统一计算双阶段模型，即崩溃信心边界模型（CCB）。根据CCB，一个扩散过程选择之后是一个朝向随机崩溃信心边界的第二个证据整合阶段。尽管CCB很简单，但它清除了所有障碍清单。
