海德堡大学医学院Kevin Allen研究组取得一项新突破。他们揭示了网格单元在基于路径整合的导航过程中准确地跟踪运动，尽管切换参考帧。2025年9月10日出版的《自然—神经科学》杂志发表了这项成果。

在这项研究中，通过记录小鼠执行基于自我运动的导航任务时网格细胞的活动，研究团队发现网格细胞在任务期间没有稳定的网格模式。相反，网格细胞在单个试验中在多个参考帧中跟踪动物的运动。具体来说，网格单元通过网格模式的转换重新锚定到与任务相关的对象上。此外，在自运动导航过程中，网格细胞内部的运动方向表示出现了漂移，这种漂移预测了母主题的归巢方向。他们的发现表明，网格单元并不像全球定位系统那样运作，而是在多个局部参考框架内估计位置。

据介绍，网格细胞具有周期性的放电场，是神经网络中进行路径整合的基本单元。人们普遍认为网格单元在一个单一的全局参考框架中编码运动。

附：英文原文

Title: Grid cells accurately track movement during path integration-based navigation despite switching reference frames

Author: Peng, Jing-Jie, Throm, Beate, Najafian Jazi, Maryam, Yen, Ting-Yun, Pizzarelli, Rocco, Monyer, Hannah, Allen, Kevin

Issue&Volume: 2025-09-10

Abstract: Grid cells, with their periodic firing fields, are fundamental units in neural networks that perform path integration. It is widely assumed that grid cells encode movement in a single, global reference frame. In this study, by recording grid cell activity in mice performing a self-motion-based navigation task, we discovered that grid cells did not have a stable grid pattern during the task. Instead, grid cells track the animal movement in multiple reference frames within single trials. Specifically, grid cells reanchor to a task-relevant object through a translation of the grid pattern. Additionally, the internal representation of movement direction in grid cells drifted during self-motion navigation, and this drift predicted the mouse’s homing direction. Our findings reveal that grid cells do not operate as a global positioning system but rather estimate position within multiple local reference frames.

DOI: 10.1038/s41593-025-02054-6

Source: https://www.nature.com/articles/s41593-025-02054-6