Learning from quantified episodic prediction errors: Individual biases in gist revision

从量化的情景预测错误中学习：要点修订中的个体偏差

• 批准号: 419037023
• 负责人: Professorin Dr. Ricarda Ines Schubotz
• 金额: --
• 依托单位: Arbeitseinheit Biologische Psychologie
• 依托单位国家: 德国
• 项目类别: Research Units
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/419037023?language=en
• 关键词: Learning; quantified; episodic; prediction; errors

To what extent and in which ways can episodic prediction errors (PEs) during retrieval alter episodic memories, and what properties do episodic PEs have that initiate such changes? Complementary to the first funding period, where we manipulated PE qualitatively, we will quantitatively manipulate episodic PEs in personally meaningful episodes of social interaction. We use a multi-step reconsolidation protocol that includes fMRI during both encoding and retrieval of episodes. In Exp. 1, we examine the modifiability of reactivated episodes by introducing PEs of variable strength. This will be achieved by independently manipulating the level of episodic predictedness and episodic predictability as quantified on the basis of an online rating study. We investigate whether the (dis)similarity between encoded and retrieved episodes is quantified by the PE strength at retrieval in two ways: at the behavioral level by multidimensional scaling of memory performance and at the neural level by analyzing the representative dissimilarity of BOLD responses. To identify potentially distinct contributions of hippocampus and neocortex, PEs refer either to episodic gist, i.e., the specific sequence of events that essentially constitute the episode, or to the episodic surface, i.e., the exact perceptual configuration of the episode. Exp. 2 extends the approach by accounting for idiosyncratic differences in episodic expectancy that may influence individual propensity to revise episodes after PE. The subjects' individual experiences and beliefs are captured by four moderator variables that quantify, for each episode, their subjective (a) association with an own autobiographical encounter, (b) emotionality, (c) social rule consistency, and (d) everyday typicality. Using these variables, we examine individual preconditions for the modifying effect of episodic PEs during scenario construction, with variables (a) and (b) modeling aspects of autobiographical and affective prior experience, and variables (c) and (d) rather experiential knowledge about (semantic) social rules. Exp. 3 employs episodic continuations as a specific type of PE, some of which additionally plausibly bridge previously unrelated episodes. Such continuing and bridging PEs should be easier to integrate as they leave the coherence of existing memories untouched or even increase it, and thus more readily lead to revision of encoded episodes. We examine the rating-quantified strength of PEs and their systematic effects on episode similarity (pre- vs. post-PE) in BOLD response and behavior.

在提取过程中，情景预测错误（PE）能在多大程度上以何种方式改变情景记忆，情景PE有什么性质引发了这种变化？作为对第一个资助期的补充，我们定性地操纵了PE，我们将定量地操纵个人有意义的社交互动事件中的情景PE。我们使用一个多步骤的重新整合协议，包括fMRI在编码和检索的情节。在Exp. 1，我们通过引入可变强度的PE来检查重新激活的事件的可修改性。这将通过独立操纵情景可预测性和情景可预测性的水平来实现，这些水平是在在线评级研究的基础上量化的。我们调查是否编码和检索的情节之间的（不）相似性量化的PE强度在检索两种方式：在行为水平上的多维尺度的记忆性能和在神经水平上通过分析BOLD反应的代表性相异。为了识别海马和新皮层的潜在不同贡献，PE指的是情节要点，即，基本上构成情节的事件的特定序列，或情节表面，即，这一集的确切感知结构。Exp. 2通过解释可能影响PE后个体修改发作倾向的发作预期的特异质差异来扩展方法。受试者的个人经验和信念被捕获的四个调节变量，量化，为每一集，他们的主观（a）与自己的自传体遭遇，（B）情感，（c）社会规则的一致性，（d）日常典型性。使用这些变量，我们研究个人的先决条件，在情景构建过程中的情景PE的修改效果，变量（a）和（B）建模方面的自传体和情感的经验，和变量（c）和（d），而经验知识（语义）的社会规则。Exp. 3采用情节延续作为一种特定类型的PE，其中一些额外的桥梁先前不相关的事件。这种连续的和桥接的PE应该更容易整合，因为它们保持了现有记忆的连贯性，甚至增加了它，因此更容易导致对编码情节的修改。我们研究了PE的评级量化强度及其对BOLD反应和行为中事件相似性（PE前与PE后）的系统影响。