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脑区的交互网络构成人类空间导航的基础:文献综述与新综合

Interacting networks of brain regions underlie human spatial navigation: a review and novel synthesis of the literature.

作者信息

Ekstrom Arne D, Huffman Derek J, Starrett Michael

机构信息

Center for Neuroscience, University of California , Davis, California.

Department of Psychology, University of California , Davis, California.

出版信息

J Neurophysiol. 2017 Dec 1;118(6):3328-3344. doi: 10.1152/jn.00531.2017. Epub 2017 Sep 20.

Abstract

Navigation is an inherently dynamic and multimodal process, making isolation of the unique cognitive components underlying it challenging. The assumptions of much of the literature on human spatial navigation are that 1) spatial navigation involves modality independent, discrete metric representations (i.e., egocentric vs. allocentric), 2) such representations can be further distilled to elemental cognitive processes, and 3) these cognitive processes can be ascribed to unique brain regions. We argue that modality-independent spatial representations, instead of providing exact metrics about our surrounding environment, more often involve heuristics for estimating spatial topology useful to the current task at hand. We also argue that egocentric (body centered) and allocentric (world centered) representations are better conceptualized as involving a continuum rather than as discrete. We propose a neural model to accommodate these ideas, arguing that such representations also involve a continuum of network interactions centered on retrosplenial and posterior parietal cortex, respectively. Our model thus helps explain both behavioral and neural findings otherwise difficult to account for with classic models of spatial navigation and memory, providing a testable framework for novel experiments.

摘要

导航本质上是一个动态的多模态过程,因此要分离其背后独特的认知成分具有挑战性。许多关于人类空间导航的文献假设如下:1)空间导航涉及模态独立的离散度量表征(即自我中心与他我中心);2)此类表征可进一步提炼为基本认知过程;3)这些认知过程可归因于独特的脑区。我们认为,模态独立的空间表征并非提供关于我们周围环境的确切度量,而更常涉及用于估计对当前手头任务有用的空间拓扑的启发法。我们还认为,自我中心(以身体为中心)和他我中心(以世界为中心)表征更好地被概念化为涉及一个连续体而非离散的。我们提出一个神经模型来容纳这些观点,认为此类表征还分别涉及以压后皮质和顶叶后皮质为中心的连续网络交互。因此,我们的模型有助于解释行为和神经学发现,否则这些发现很难用经典的空间导航和记忆模型来解释,为新实验提供了一个可测试的框架。

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