Evidence map›Paper›PMID 41231927›Full record

ArticlePLoS biology2025

A framework to determine active neurons and networks within the mouse brain reveals how brain activity changes over the course of the day.

Guanhua Sun, Tomoyuki Mano, Shoi Shi, Alvin Li, Koji L Ode, Alex Rosi-Andersen, Erica Pedron, Steven A Brown, Hiroki R Ueda, Konstantinos Kompotis and 1 more

Abstract read
In one paragraph

Article in PLoS biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

11 authors.

Guanhua SunDepartment of Mathematics, University of Michigan, Ann Arbor, Michigan, United States.ORCID 0000-0002-3710-2807
Tomoyuki ManoDepartment of Mathematics, University of Michigan, Ann Arbor, Michigan, United States.
Shoi ShiDepartment of Systems Pharmacology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Alvin LiDepartment of Mathematics, University of Michigan, Ann Arbor, Michigan, United States.
Koji L OdeDepartment of Systems Pharmacology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Alex Rosi-AndersenChronobiology and Sleep Research Group, Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland.
Erica PedronChronobiology and Sleep Research Group, Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland.
Steven A BrownChronobiology and Sleep Research Group, Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland.
Hiroki R UedaDepartment of Systems Pharmacology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Konstantinos KompotisDepartment of Mathematics, University of Michigan, Ann Arbor, Michigan, United States.
Daniel B ForgerDepartment of Mathematics, University of Michigan, Ann Arbor, Michigan, United States.ORCID 0000-0001-7581-4031

Funding

National Science Foundation 2052499
6 · The paper itself

Abstract

The mouse brain's activity changes drastically over a day despite being generated from the same neurons and physical connectivity. To better understand this, we develop an experimental-computational pipeline to determine which neurons and networks are most active at different times of the day. We genetically mark active neurons of freely behaving mice at four times of the day with a c-Fos activity-dependent TRAP2 system. Neurons are imaged and digitized in 3D, and their molecular properties are inferred from the latest brain spatial transcriptomic dataset. We then develop a new computational method to analyze the network formed by the identified active neurons. Applying this pipeline, we observe region and layer-specific activation of neurons in the cortex, especially activation of layer five neurons at the end of the dark (wake) period. We also observe a shift in the balance of excitatory (glutamatergic) neurons versus inhibitory (GABAergic) neurons across the whole brain, especially in the thalamus. Moreover, as the dark (wake) period progresses, the network formed by the active neurons becomes less modular, and the hubs switch from subcortical regions, such as the posterior hypothalamic nucleus, to cortical regions in the default mode network. Taken together, we present a pipeline to understand which neurons and networks may be most activated in the mouse brain during an experimental protocol, and use this pipeline to understand how brain activity changes over the course of a day.

Indexed as

BrainCircadian RhythmNerve NetNeuronsAnimalsGABAergic NeuronsMaleMiceMice, Inbred C57BLProto-Oncogene Proteins c-fosProto-Oncogene Proteins c-fos

Identifiers

PMID41231927
PMCPMC12633928

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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.