Department of Experimental Psychology, University College London, 26 Bedford Way, London, WC1H 0AP, UK.
The Alan Turing Institute, London, UK.
Nat Commun. 2019 Dec 12;10(1):5685. doi: 10.1038/s41467-019-13760-8.
One view is that conceptual knowledge is organized using the circuitry in the medial temporal lobe (MTL) that supports spatial processing and navigation. In contrast, we find that a domain-general learning algorithm explains key findings in both spatial and conceptual domains. When the clustering model is applied to spatial navigation tasks, so-called place and grid cell-like representations emerge because of the relatively uniform distribution of possible inputs in these tasks. The same mechanism applied to conceptual tasks, where the overall space can be higher-dimensional and sampling sparser, leading to representations more aligned with human conceptual knowledge. Although the types of memory supported by the MTL are superficially dissimilar, the information processing steps appear shared. Our account suggests that the MTL uses a general-purpose algorithm to learn and organize context-relevant information in a useful format, rather than relying on navigation-specific neural circuitry.
有一种观点认为，概念知识是通过支持空间处理和导航的内侧颞叶（MTL）中的电路来组织的。相比之下，我们发现一种通用的学习算法可以解释空间和概念领域的关键发现。当聚类模型应用于空间导航任务时，由于这些任务中可能输入的相对均匀分布，会出现所谓的位置和网格细胞样表示。同样的机制应用于概念任务，其中整体空间可以是高维的，采样稀疏，导致与人类概念知识更一致的表示。虽然 MTL 支持的记忆类型表面上不同，但信息处理步骤似乎是共享的。我们的解释表明，MTL 使用通用算法以有用的格式学习和组织与上下文相关的信息，而不是依赖于特定于导航的神经电路。
