那么,如果任务中同时涉及了空间位置变化和抽象认知变量,海马1区中的神经元会如何表征呢?神经元对这两个变量的编码会是独立的么?空间变量和认知变量都能在神经元活动空间中形成有集合属性的认知地图么?来自美国普林斯顿大学的Carlos D. Brody和David W. Tank等学者,于2021年6月在Nature发表文章,介绍了他们关于神经元抽象知识表征的研究。
1. Nieh, E. H., Schottdorf, M., Freeman, N. W., Low, R. J., Lewallen, S., Koay, S. A., Pinto, L., Gauthier, J. L., Brody, C. D., & Tank, D. W. (2021). Geometry of abstract learned knowledge in the hippocampus. _Nature_, _595_(7865), 80–84. https://doi.org/10.1038/s41586-021-03652-72. Park, S. A., Miller, D. S., Nili, H., Ranganath, C., & Boorman, E. D. (2020). Map Making: Constructing, Combining, and Inferring on Abstract Cognitive Maps. _Neuron_, _107_(6), 1226-1238.e8. https://doi.org/10.1016/j.neuron.2020.06.0303. Recanatesi, S., Farrell, M., Lajoie, G., Deneve, S., Rigotti, M., & Shea-Brown, E. (2021). Predictive learning as a network mechanism for extracting low-dimensional latent space representations. _Nature Communications_, _12_(1), 1417. https://doi.org/10.1038/s41467-021-21696-1