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内隐学习过程中的思维游荡与脑电图周期性活动增加及隐藏概率模式提取改善有关。

Mind Wandering during Implicit Learning Is Associated with Increased Periodic EEG Activity and Improved Extraction of Hidden Probabilistic Patterns.

作者信息

Simor Péter, Vékony Teodóra, Farkas Bence C, Szalárdy Orsolya, Bogdány Tamás, Brezóczki Bianka, Csifcsák Gábor, Németh Dezső

机构信息

Institute of Psychology, Eötvös Loránd University, Budapest 1075, Hungary

Institute of Behavioral Sciences, Semmelweis University, Budapest 1085, Hungary.

出版信息

J Neurosci. 2025 May 7;45(19):e1421242025. doi: 10.1523/JNEUROSCI.1421-24.2025.

DOI:10.1523/JNEUROSCI.1421-24.2025
PMID:40194844
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12060634/
Abstract

Mind wandering, occupying 30-50% of our waking time, remains an enigmatic phenomenon in cognitive neuroscience. A large number of studies showed a negative association between mind wandering and attention-demanding (model-based) tasks in both natural settings and laboratory conditions. Mind wandering, however, does not seem to be detrimental for all cognitive domains and was observed to benefit creativity and problem-solving. We examined if mind wandering may facilitate model-free processes, such as probabilistic learning, which relies on the automatic acquisition of statistical regularities with minimal attentional demands. We administered a well-established implicit probabilistic learning task combined with thought probes in healthy adults ( = 37, 30 females). To explore the neural correlates of mind wandering and probabilistic learning, participants were fitted with high-density electroencephalography. Our findings indicate that probabilistic learning was not only immune to periods of mind wandering but was positively associated with it. Spontaneous, as opposed to deliberate mind wandering, was particularly beneficial for extracting the probabilistic patterns hidden in the visual stream. Cortical oscillatory activity in the low-frequency (slow and delta) range, indicative of covert sleep-like states, was associated with both mind wandering and improved probabilistic learning, particularly in the early stages of the task. Given the importance of probabilistic implicit learning in predictive processing, our findings provide novel insights into the potential cognitive benefits of task-unrelated thoughts in addition to shedding light on its neural mechanisms.

摘要

走神占据了我们清醒时间的30%至50%,在认知神经科学领域仍是一个谜一般的现象。大量研究表明,在自然环境和实验室条件下,走神与需要注意力的(基于模型的)任务之间存在负相关。然而,走神似乎并非对所有认知领域都有损害,而且人们观察到它对创造力和解决问题有好处。我们研究了走神是否可能促进无模型过程,比如概率学习,这种学习依赖于以最少的注意力需求自动获取统计规律。我们对37名健康成年人(30名女性)进行了一项成熟的内隐概率学习任务,并结合思维探测。为了探究走神和概率学习的神经关联,我们让参与者佩戴高密度脑电图仪。我们的研究结果表明,概率学习不仅不受走神时期的影响,而且与之呈正相关。与刻意走神相反,自发走神对于提取视觉流中隐藏的概率模式特别有益。低频(慢波和δ波)范围内的皮层振荡活动,表明存在类似睡眠的隐蔽状态,它与走神和概率学习的改善都有关联,尤其是在任务的早期阶段。鉴于概率内隐学习在预测处理中的重要性,我们的研究结果除了揭示其神经机制外,还为与任务无关的思维潜在的认知益处提供了新的见解。