前额纹状体回路中认知程序学习的纵向标记以及 BDNF 可塑性相关变体的推定效应。

IF 3.6 1区 心理学 Q1 EDUCATION & EDUCATIONAL RESEARCH npj Science of Learning Pub Date : 2024-11-28 DOI:10.1038/s41539-024-00282-2
Lena S Geiger, Torsten Wüstenberg, Zhenxiang Zang, Mirjam Melzer, Stephanie H Witt, Marcella Rietschel, Markus M Nöthen, Stefan Herms, Franziska Degenhardt, Andreas Meyer-Lindenberg, Carolin Moessnang
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引用次数: 0

摘要

行为心理学对程序学习和自动化进行了广泛的研究,其典型特征是在反复训练中,学习成绩会迅速提高,然后趋于稳定。最近,脑成像研究发现额叶-纹状体脑回路与技能学习有关。然而,在技能学习和行为变化过程中,额叶-纹状体的激活是否遵循类似的学习曲线模式,这在很大程度上还是个未知数。为了填补这一知识空白,我们使用程序性工作记忆(pWM)任务进行了一项纵向脑成像研究,在两周内重复测量,以绘制技能学习的时间动态图。此外,我们还探讨了BDNF Val66Met多态性(一种影响神经可塑性的常见基因多态性)的影响,以进一步了解已识别神经标记的相关性。我们使用线性和指数模型,通过行为和大脑功能层面的学习曲线来描述程序学习的特征。我们的研究表明,重复训练会导致包括前额纹状体回路在内的一系列分布式脑区出现指数衰减,这与任务表现的指数级提高相一致。此外,我们还发现行为和神经功能读数对 BDNF Val66Met 多态性很敏感,这表明 66Met 等位基因携带者的学习效率较低,同时额叶和纹状体脑区的信号衰减时间较长。我们的研究结果扩展了现有的文献,显示了程序性学习与额叶-纹状体大脑功能之间的时间关系,并提示了BDNF在介导神经可塑性以建立自动化行为中的作用。
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Longitudinal markers of cognitive procedural learning in fronto-striatal circuits and putative effects of a BDNF plasticity-related variant.

Procedural learning and automatization have widely been studied in behavioral psychology and typically involves a rapid improvement, followed by a plateau in performance throughout repeated training. More recently, brain imaging studies have implicated frontal-striatal brain circuits in skill learning. However, it is largely unknown whether frontal-striatal activation during skill learning and behavioral changes follow a similar learning curve pattern. To address this gap in knowledge, we performed a longitudinal brain imaging study using a procedural working memory (pWM) task with repeated measurements across two weeks to map the temporal dynamics of skill learning. We additionally explored the effect of the BDNF Val66Met polymorphism, a common genetic polymorphism impacting neural plasticity, to further inform the relevance of the identified neural markers. We used linear and exponential modeling to characterize procedural learning by means of learning curves on the behavioral and brain functional level. We show that repeated training led to an exponential decay in a distributed set of brain regions including fronto-striatal circuits, which paralleled the exponential improvement in task performance. In addition, we show that both behavioral and neurofunctional readouts were sensitive to the BDNF Val66Met polymorphism, suggesting less efficient learning in 66Met-allele carriers along with protracted signal decay in frontal and striatal brain regions. Our results extend existing literature by showing the temporal relationship between procedural learning and frontal-striatal brain function and suggest a role of BDNF in mediating neural plasticity for establishing automatized behavior.

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来源期刊
CiteScore
5.40
自引率
7.10%
发文量
29
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