Evidence map›Paper›PMID 40766723›Full record

ArticlebioRxiv : the preprint server for biology2025

Slow synaptic plasticity from the hippocampus underlies gradual mapping and fragmentation of novel spaces by grid cells.

Lujia Chen, Ling Liang Dong, Hoon Shin, Farid Shahid, Taylor Joseph Malone, Yan Ma, Sreerag Othayoth Vasu, Nai-Wen Tien, Kyle Cekada, Kevin Jiang Zhang and 5 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Lujia ChenSpatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA.ORCID 0000-0002-9853-2413
Ling Liang DongDepartment of Brain and Cognitive Sciences and McGovern Institute, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Hoon ShinLaboratory on Neurobiology of Compulsive Behaviors, National Institutes of Mental Health, NIH, Bethesda, MD 20892, USA.
Farid ShahidSpatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA.
Taylor Joseph MaloneSpatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA.
Yan MaSpatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA.
Sreerag Othayoth VasuLaboratory on Neurobiology of Compulsive Behaviors, National Institutes of Mental Health, NIH, Bethesda, MD 20892, USA.
Nai-Wen TienSpatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA.
Kyle CekadaSpatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA.
Kevin Jiang ZhangSpatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA.
Lucy AndersonLaboratory on Neurobiology of Compulsive Behaviors, National Institutes of Mental Health, NIH, Bethesda, MD 20892, USA.
Sarthak ChandraDepartment of Brain and Cognitive Sciences and McGovern Institute, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Ila FieteDepartment of Brain and Cognitive Sciences and McGovern Institute, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.ORCID 0000-0003-4738-2539
Veronica A AlvarezLaboratory on Neurobiology of Compulsive Behaviors, National Institutes of Mental Health, NIH, Bethesda, MD 20892, USA.
Yi GuSpatial Navigation and Memory Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA.

Funding

Synaptic mechanisms underlying reward seeking and compulsive drug useZIAAA000421 · NIAAA · NATIONAL INSTITUTE ON ALCOHOL ABUSE AND ALCOHOLISM · PI ALVAREZ, VERONICA A · 2009 to 2025
$23.1M
Neural mechanism of spatial navigation and memoryZIANS009415 · NINDS · NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE · PI GU, YI · 2020 to 2025
$13.4M
Section on Neurobiology of Compulsive BehaviorsZIAMH002987 · NIMH · NATIONAL INSTITUTE OF MENTAL HEALTH · PI ALVAREZ, VERONICA · 2023 to 2025
$5.2M
Intramural NIH HHS ZIA AA000421Intramural NIH HHS ZIA MH002987Intramural NIH HHS ZIA NS009415
6 · The paper itself

Abstract

Animals construct internal "cognitive maps" of the world during navigation in spatial and non-spatial domains, with grid cells in the medial entorhinal cortex (MEC) playing a key role. This requires associating internal position estimates with external cues to reduce spatial uncertainty over time. However, how grid cell representations evolve in novel spaces to support map formation is unclear. To address this question, we longitudinally imaged calcium dynamics of grid cells over 10 days as mice learn operant tasks in novel virtual linear tracks. We observe that spatial tuning of grid cells is present immediately in novel tracks but evolves as a significant fraction of spatial fields shift backward on a run-by-run basis, within and across days. Backward shifts are more prevalent and persistent in successful learners. The fields gradually stabilize across days, anchored by landmarks, suggesting slow plasticity. The backward shifts partially reset daily, reflecting a slower consolidation timescale. While individual fields of a cell shift differentially, co-active fields of co-modular grid cells shift together, indicating their coupled dynamics on the same two-dimensional torus. Spatial learning leads to systematic changes and stabilization of their population phase trajectory, including lateral shift, rotation, and phase resets at landmarks, forming a landmark-fragmented representation for the environment. Next, we build an entorhinal-hippocampal model that provides a mechanistic explanation of the diverse phenomena - grid field shifts, increasing fidelity, and fragmentation of the spatial map - and predicts slow Hebbian plasticity in the hippocampus-to-entorhinal pathway. Supporting this, electrophysiology demonstrates that learning-performance-correlated weakening of local inhibition facilitates potentiation of indirect hippocampal inputs to superficial MEC. Together, our study provides multifaceted evidence of slow hippocampus-to-MEC plasticity, elucidating the formation of stable and fragmented cognitive maps that combine internal and cue-driven positional estimates in rich environments during learning. This mechanism may extend to broader memory processes involving this circuit.

Identifiers

PMID40766723
PMCPMC12324395

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.