Evidence map›Paper›PMID 42349755›Full record

ArticleJournal of neuroscience methods2026

Methods for measuring neural activity during voluntary wheel running.

Ayland C Letsinger, Bryan N Ochoa, Jessica J Wu, Kayen U Tang, Diane Youngstrom, Shaohua Wang, Matt Bridge, Guohong Cui, Jerrel L Yakel

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of neuroscience methods, 2026. 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
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0citing papers in PubMed
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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

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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

9 authors.

Ayland C LetsingerNeurobiology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA; The Department of Kinesiology and Health Education, University of Texas at Austin, Austin, TX, USA. Electronic address: Ayland.Letsinger@Austin.UTexas.edu.
Bryan N OchoaNeurobiology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA.
Jessica J WuNeurobiology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA.
Kayen U TangNeurobiology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA.
Diane YoungstromNeurobiology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA.
Shaohua WangNeurobiology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA.
Matt BridgeDLH, LLC, Bethesda, MD, USA.
Guohong CuiNeurobiology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA.
Jerrel L YakelNeurobiology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA.

Funding

MODULATION OF NEURONAL LIGAND-GATED CHANNELS BY CALCIUM DEPENDENT MECHANISMSZ01ES090089 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI YAKEL, JERREL L · 1997 to 2008
$3.6M
Intramural NIH HHS Z01 ES090089NIDA NIH HHS K99 DA058974
6 · The paper itself

Abstract

backgroundRodent wheel running provides a translational model to study the neurobiology of physical activity, including motivation, affect, and plasticity. However, the voluntary and unconstrained nature of wheel running makes precise behavior-to-signal alignment technically challenging. NEW

methodWe present a workflow that aligns fiber photometry signals with pose-derived behavior during voluntary wheel running. As a use case, we record acetylcholine activity in the ventral dentate gyrus of mature male C57BL/6 J mice and integrate pose estimation (DeepLabCut), supervised behavior classification (SimBA), spectral/event processing (FiPhA), and custom within-event trend estimations (R).

resultsIn this proof-of-concept application, acetylcholine in the ventral dentate gyrus appeared to increase 0-5 s before and throughout wheel running events during both acquisition and maintenance phases. Acetylcholine levels also showed a positive correlation with off-wheel body length. COMPARISON WITH EXISTING

methodsPrior studies measuring neural activity during physical activity have relied on head-fixation or forced treadmill running, which introduce stress confounds and reduce ecological validity, or wheel rotational velocity signals, which cannot distinguish active running from passive wheel rotation without manual annotation of video frames. The present workflow addresses these limitations by using voluntary home-cage wheel running to minimize stress and supervised machine learning classification that reduces behavioral annotation time by an estimated 90% while achieving greater than 96% precision and recall.

conclusionsThis workflow provides a template for efficiently and accurately aligning wheel running behavior with neural in vivo signals. Our proof-of-concept demonstrates the feasibility of generalizing the approach to other neuromodulators, brain regions, and recording modalities.

Indexed as

AcetylcholineDentate GyrusMotor ActivityPhotometryRunningAnimalsMaleMiceMice, Inbred C57BLNeuronsAcetylcholineCholinergicDeepLabCutFiber photometryPhysical activity neurobiologySimBAVentral dentate gyrusVoluntary wheel running

Identifiers

PMID42349755
PMCPMC13404277

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LicenceCC BY
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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.