Theories of associative learning often propose that learning is proportional to prediction error, or the difference between expected events and those that occur. Spicer et al. (2020) suggested an alternative, that humans might instead selectively attribute surprising outcomes to cues that they are not confident about, to maintain cue-outcome associations about which they are more confident. Spicer et al. reported three predictive learning experiments, the results of which were consistent with their proposal ("theory protection") rather than a prediction error account (Rescorla, 2001). The four experiments reported here further test theory protection against a prediction error account. Experiments 3 and 4 also test the proposals of Holmes et al. (2019), who suggested a function mapping learning to performance that can explain Spicer et al.'s results using a prediction-error framework. In contrast to the previous study, these experiments were based on inhibition rather than excitation. Participants were trained with a set of cues (represented by letters), each of which was followed by the presence or absence of an outcome (represented by + or -). Following this, a cue that previously caused the outcome (A+) was placed in compound with another cue (B) with an ambiguous causal status (e.g., a novel cue in Experiment 1). This compound (AB-) did not cause the outcome. Participants always learned more about B in the second training phase, despite A always having the greater prediction error. In Experiments 3 and 4, a cue with no apparent prediction error was learned about more than a cue with a large prediction error. Experiment 4 tested participants' relative confidence about the causal status of cues A and B prior to the AB- stage, producing findings that are consistent with theory protection and inconsistent with the predictions of Rescorla, and Holmes et al. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

中文翻译：

---

理论保护：人类是否保护现有的关联链接？

联想学习理论经常提出，学习与预测误差或预期事件与发生事件之间的差异成正比。斯派塞等人。(2020) 提出了另一种选择，即人类可能会选择性地将令人惊讶的结果归因于他们不自信的线索，以保持他们更有信心的线索-结果关联。斯派塞等人。报告了三个预测学习实验，其结果与他们的提议（“理论保护”）一致，而不是预测错误帐户（Rescorla，2001）。这里报告的四个实验进一步测试了针对预测错误帐户的理论保护。实验 3 和 4 也测试了 Holmes 等人的提议。（2019），他提出了一个函数映射学习到性能，可以解释斯派塞等人。的结果使用预测误差框架。与之前的研究相比，这些实验是基于抑制而不是激发。参与者接受了一组提示（用字母表示）的训练，每个提示后面都有结果的存在或不存在（用+或-表示）。在此之后，将先前导致结果 (A+) 的提示与另一个具有模糊因果状态的提示 (B) 组合在一起（例如，实验 1 中的新提示）。这种化合物 (AB-) 不会导致结果。尽管 A 总是有更大的预测误差，但参与者总是在第二个训练阶段更多地了解 B。在实验 3 和 4 中，一个没有明显预测误差的提示被学习到的不仅仅是一个具有大预测误差的提示。实验 4 测试参与者的 在 AB 阶段之前对线索 A 和 B 的因果状态的相对置信度，产生的结果与理论保护一致，与 Rescorla 和 Holmes 等人的预测不一致。（PsycInfo 数据库记录 (c) 2022 APA，保留所有权利）。