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老路重访:纹状体和海马系统对熟悉路线导航的贡献。

The well-worn route revisited: Striatal and hippocampal system contributions to familiar route navigation.

机构信息

Department of Psychology, Durham University, Durham, UK.

School of Information and Physical Sciences, University of Newcastle Australia, Callaghan, New South Wales, Australia.

出版信息

Hippocampus. 2024 Jul;34(7):310-326. doi: 10.1002/hipo.23607. Epub 2024 May 9.

Abstract

Classic research has shown a division in the neuroanatomical structures that support flexible (e.g., short-cutting) and habitual (e.g., familiar route following) navigational behavior, with hippocampal-caudate systems associated with the former and putamen systems with the latter. There is, however, disagreement about whether the neural structures involved in navigation process particular forms of spatial information, such as associations between constellations of cues forming a cognitive map, versus single landmark-action associations, or alternatively, perform particular reinforcement learning algorithms that allow the use of different spatial strategies, so-called model-based (flexible) or model-free (habitual) forms of learning. We sought to test these theories by asking participants (N = 24) to navigate within a virtual environment through a previously learned, 9-junction route with distinctive landmarks at each junction while undergoing functional magnetic resonance imaging (fMRI). In a series of probe trials, we distinguished knowledge of individual landmark-action associations along the route versus knowledge of the correct sequence of landmark-action associations, either by having absent landmarks, or "out-of-sequence" landmarks. Under a map-based perspective, sequence knowledge would not require hippocampal systems, because there are no constellations of cues available for cognitive map formation. Within a learning-based model, however, responding based on knowledge of sequence would require hippocampal systems because prior context has to be utilized. We found that hippocampal-caudate systems were more active in probes requiring sequence knowledge, supporting the learning-based model. However, we also found greater putamen activation in probes where navigation based purely on sequence memory could be planned, supporting models of putamen function that emphasize its role in action sequencing.

摘要

经典研究表明,在支持灵活(例如,走捷径)和习惯(例如,遵循熟悉的路线)导航行为的神经解剖结构中存在分歧,海马-尾状核系统与前者有关,而壳核系统与后者有关。然而,对于参与导航过程的神经结构是否处理特定形式的空间信息存在分歧,例如形成认知地图的线索组合与单个地标-动作关联之间的关联,或者相反,执行特定的强化学习算法,允许使用不同的空间策略,即所谓的基于模型(灵活)或无模型(习惯)的学习形式。我们通过让参与者(N=24)在功能磁共振成像(fMRI)期间在虚拟环境中通过先前学习的 9 个路口的路线进行导航,每个路口都有独特的地标,以此来测试这些理论。在一系列探测试验中,我们通过去除地标或“不在序列中的”地标,区分了沿路线的单个地标-动作关联的知识与地标-动作关联的正确序列的知识。从基于地图的角度来看,序列知识不需要海马系统,因为没有可供认知地图形成的线索组合。然而,在基于学习的模型中,基于序列知识的反应需要海马系统,因为必须利用先前的上下文。我们发现,在需要序列知识的探测中,海马-尾状核系统的活性更高,支持基于学习的模型。然而,我们也发现,在纯粹基于序列记忆的导航可以计划的探测中,壳核的激活程度更高,这支持了强调其在动作序列中的作用的壳核功能模型。

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