Pedraza Felipe, Vékony Teodóra, Farkas Bence C, Haesebaert Frederic, Phelipon Romane, Mihalecz Imola, Janacsek Karolina, Tillmann Barbara, Anders Royce, Plancher Gaën, Nemeth Dezso
Laboratoire d'Étude des Mécanismes Cognitifs, Université Lumière Lyon 2, Bron, France.
Centre de Recherche en Neurosciences de Lyon, INSERM, CNRS, Université Claude Bernard Lyon 1, CRNL U1028 UMR5292, Bron, France.
Sci Rep. 2025 Aug 20;15(1):30555. doi: 10.1038/s41598-025-14876-2.
Modifying habits, particularly unwanted behaviors, is often challenging. Cognitive research has focused on understanding the mechanisms underlying habit formation and how habits can be rewired. A key mechanism is statistical learning, the continuous, implicit extraction of probabilistic patterns from the environment, which forms the basis of predictive processing. However, the interplay between executive functions (EF) and the rewiring - or updating - of these probabilistic representations remains largely unexplored. To address this gap, we conducted an experiment consisting of four sessions: (1) Learning Phase - acquisition of probabilistic representations, (2) Rewiring Phase - updating these probabilistic representations, (3) Retrieval Phase - accessing learned representations, and (4) EF assessment, targeting five key aspects: attentional control, inhibition, working memory, flexibility, and verbal fluency. We focused on the relationship between these EF measures and the updating of previously acquired knowledge using an interindividual differences approach. Our results revealed a positive relationship between rewiring and inhibition, suggesting that better inhibitory control may facilitate the adaptive restructuring of probabilistic predictive representations. Conversely, a negative relationship was identified between rewiring and semantic fluency, implying that certain underlying aspects of verbal fluency tasks, such as access to long-term memory representations, may hinder the updating process. We interpret this relationship through the lens of competitive memory network models. Our findings indicate that the rewiring of implicit probabilistic representations is a multifaceted cognitive process requiring both the suppression of proactive interference from prior knowledge through cognitive inhibition and a strong reliance on model-free functioning.
改变习惯，尤其是不良行为，往往具有挑战性。认知研究一直专注于理解习惯形成的潜在机制以及如何重塑习惯。一个关键机制是统计学习，即从环境中持续、隐性地提取概率模式，这构成了预测性处理的基础。然而，执行功能（EF）与这些概率表征的重塑（即更新）之间的相互作用在很大程度上仍未得到探索。为了填补这一空白，我们进行了一项由四个阶段组成的实验：（1）学习阶段——获取概率表征；（2）重塑阶段——更新这些概率表征；（3）检索阶段——访问所学表征；（4）EF评估，针对五个关键方面：注意力控制、抑制、工作记忆、灵活性和语言流畅性。我们使用个体差异方法，重点研究了这些EF测量指标与先前获取知识的更新之间的关系。我们的结果显示，重塑与抑制之间存在正相关关系，这表明更好的抑制控制可能有助于概率预测表征的适应性重构。相反，在重塑与语义流畅性之间发现了负相关关系，这意味着语言流畅性任务的某些潜在方面，如对长期记忆表征的访问，可能会阻碍更新过程。我们通过竞争性记忆网络模型来解释这种关系。我们的研究结果表明，隐性概率表征的重塑是一个多方面的认知过程，既需要通过认知抑制来抑制先前知识的主动干扰，又强烈依赖于无模型功能。
