Journal Article

DKFZ-2025-01884

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Grid cells accurately track movement during path integration-based navigation despite switching reference frames.

Peng, J. (First author)DKFZ* ; Throm, B. (First author)DKFZ* ; Najafian Jazi, M.DKFZ* ; Yen, T.-Y.DKFZ* ; Pizzarelli, R. ; Monyer, H. (Last author)DKFZ* ; Allen, K. (Last author)DKFZ*

2025
Nature America New York, NY

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Please use a persistent id in citations: doi:10.1038/s41593-025-02054-6

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.

Note: #EA:A230#LA:A230#LA:C140# / 2025 Oct;28(10):2092-2105

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Contributing Institute(s):

1. A230 Klinische Neurobiologie (A230)
2. Digitale Prävention, Diagnostik und Therapiesteuerung (C140)

Research Program(s):

1. 311 - Zellbiologie und Tumorbiologie (POF4-311) (POF4-311)

Appears in the scientific report 2025

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Database coverage:
; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; Current Contents - Life Sciences ; DEAL Nature ; Ebsco Academic Search ; Essential Science Indicators ; IF >= 25 ; JCR ; Nationallizenz ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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