Entorhinal cortex represents task-relevant remote locations independently of CA1

Neurons can collectively represent the current sensory experience during exploration or remote experiences during immobility. Remote representations can reflect learned associations and support learning. Neurons in medial entorhinal cortex (MEC) represent the animal's current location during movement, but little is known about MEC representations during immobility. We recorded hundreds of neurons simultaneously in MEC and CA1 as mice learned to associate pairs of rewarded locations. During immobility, the MEC neural population frequently represented positions far from the animal's location ('nonlocal coding'). Cells with spatial firing fields at remote locations drove nonlocal coding, even as cells representing the current position remained active. While MEC nonlocal coding has been reported during sharp-wave ripples in CA1, we observed nonlocal coding more often outside of ripples and saw less CA1-MEC coordination during nonlocal coding. Further, nonlocal coding preferentially represented remote task-relevant locations at appropriate times. Together, this work suggests that MEC nonlocal coding could strengthen associations between locations independently from CA1.

Authors

Institutions

Publication Details

Journal
Nature Neuroscience
Published
2026-04-01
DOI
https://doi.org/10.1038/s41593-026-02232-0
Primary Topic
Neural dynamics and brain function
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Entorhinal cortex represents task-relevant remote locations independently of CA1

Frances S. Cho, Isabel I. C. Low, Emily A. Aery Jones, Lisa M. Giocomo
Nature Neuroscience
Neural dynamics and brain function
article

Entorhinal cortex represents task-relevant remote locations independently of CA1

Frances S. Cho, Isabel I. C. Low, Emily A. Aery Jones, Lisa M. Giocomo
article en

Abstract

Neurons can collectively represent the current sensory experience during exploration or remote experiences during immobility. Remote representations can reflect learned associations and support learning. Neurons in medial entorhinal cortex (MEC) represent the animal's current location during movement, but little is known about MEC representations during immobility. We recorded hundreds of neurons simultaneously in MEC and CA1 as mice learned to associate pairs of rewarded locations. During immobility, the MEC neural population frequently represented positions far from the animal's location ('nonlocal coding'). Cells with spatial firing fields at remote locations drove nonlocal coding, even as cells representing the current position remained active. While MEC nonlocal coding has been reported during sharp-wave ripples in CA1, we observed nonlocal coding more often outside of ripples and saw less CA1-MEC coordination during nonlocal coding. Further, nonlocal coding preferentially represented remote task-relevant locations at appropriate times. Together, this work suggests that MEC nonlocal coding could strengthen associations between locations independently from CA1.

Nature NeuroscienceVol. 29(5)
University of Maryland, Baltimore (US), Stanford Medicine (US), Columbia University (US), Stanford University (US)
James S. McDonnell Foundation, A.P. Giannini Foundation, Giannini Foundation of Agricultural Economics, National Institute of Mental Health
Openalex Percentile: Top 40%
Neural dynamics and brain function
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Entorhinal cortex represents task-relevant remote locations independently of CA1 — Frances S. Cho, Isabel I. C. Low, et al. · Nature Neuroscience (2026) | TGRS Research Map | TGRS