<p>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.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

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

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

摘要

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.