Suppr超能文献

任务相似性作为一个梯度,会出现顺行干扰:一项行为学研究。

Anterograde interference emerges along a gradient as a function of task similarity: A behavioural study.

机构信息

Département de kinanthropologie, Faculté des sciences de l'activité physique, Université de Sherbrooke, Sherbrooke, Québec, Canada.

Département de pédiatrie, Faculté de médecine et des sciences de la santé, Université de Sherbrooke; Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, Québec, Canada.

出版信息

Eur J Neurosci. 2022 Jan;55(1):49-66. doi: 10.1111/ejn.15561. Epub 2021 Dec 20.

Abstract

Anterograde interference emerges when two opposite (B → A) or identical tasks (A → A) are learned in close temporal succession, suggesting that interference cannot be fully accounted for by competing memories. Informed by neurobiological evidence, this work tested the hypothesis that interference depends upon the degree of overlap between the neural networks involved in the learning of two tasks. In a fully within-subject and counterbalanced design, participants (n = 24) took part in two learning sessions where the putative overlap between learning-specific neural networks was behaviourally manipulated across four conditions by modifying reach direction and the effector used during gradual visuomotor adaptation. The results showed that anterograde interference emerged regardless of memory competition-that is, to a similar extent in the B → A and A → A conditions-and along a gradient as a function of the tasks' similarity. Specifically, learning under similar reaching conditions generated more anterograde interference than learning under dissimilar reaching conditions, suggesting that putatively overlapping neural networks are required to generate interference. Overall, these results indicate that competing memories are not the sole contributor to anterograde interference and suggest that overlapping neural networks between two learning sessions are required to trigger interference. One discussed possibility is that initial learning modifies the properties of its neural networks to constrain further plasticity induction and learning capabilities, therefore causing anterograde interference in a network-dependent manner. One implication is that learning-specific neural networks must be maximally dissociated to minimize the interfering influences of previous learning on subsequent learning.

摘要

当两个相反的任务(B→A)或相同的任务(A→A)在时间上紧密连续学习时,就会出现顺行干扰,这表明干扰不能完全用竞争记忆来解释。本研究根据神经生物学证据,检验了这样一种假设,即干扰取决于参与两个任务学习的神经网络之间的重叠程度。在完全的被试内和平衡设计中,参与者(n=24)参加了两个学习阶段,通过在逐渐的视觉运动适应过程中修改到达方向和使用的效应器,在四个条件下从行为上操纵学习特定神经网络之间的假定重叠,从而改变了学习特定神经网络之间的假定重叠。结果表明,顺行干扰的出现与记忆竞争无关,即在 B→A 和 A→A 条件下的程度相似,并随着任务相似性的增加呈梯度增加。具体来说,在相似的到达条件下学习比在不相似的到达条件下学习产生更多的顺行干扰,这表明需要假定重叠的神经网络来产生干扰。总的来说,这些结果表明竞争记忆并不是顺行干扰的唯一贡献者,并表明两个学习阶段之间的重叠神经网络是触发干扰所必需的。一种被讨论的可能性是,初始学习改变了其神经网络的特性,以限制进一步的可塑性诱导和学习能力,因此以网络依赖的方式引起顺行干扰。一个含义是,必须最大限度地分离学习特定的神经网络,以最大限度地减少先前学习对后续学习的干扰影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a820/9299670/7dec7f7b871e/EJN-55-49-g005.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验