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Updated: Jun 27, 2026

Tracking Individual Running Metrics in Mice Using a Voluntary Wheel Running Protocol that Minimizes Social Isolation
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Tracking Individual Running Metrics in Mice Using a Voluntary Wheel Running Protocol that Minimizes Social Isolation

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Methods for Measuring Neural Activity During Voluntary Wheel Running.

Ayland C Letsinger1, Bryan N Ochoa2, Jessica J Wu2

  • 1Neurobiology 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.

Journal of Neuroscience Methods
|June 25, 2026
PubMed
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This summary is machine-generated.

Researchers developed a new workflow to precisely align neural signals with voluntary wheel running behavior in mice. This method enhances the study of physical activity

Area of Science:

  • Neuroscience
  • Behavioral Science
  • Computational Biology

Background:

  • Rodent wheel running is a valuable model for studying the neurobiology of physical activity.
  • Aligning neural signals with unconstrained wheel running behavior is technically challenging.

Purpose of the Study:

  • To present a novel workflow for aligning fiber photometry signals with pose-derived behavior during voluntary wheel running.
  • To demonstrate a proof-of-concept application of this workflow.

Main Methods:

  • Integrating pose estimation (DeepLabCut), supervised behavior classification (SimBA), and spectral/event processing (FiPhA).
  • Utilizing voluntary home-cage wheel running to minimize stress and improve ecological validity.
  • Employing supervised machine learning to reduce behavioral annotation time by ~90% with >96% precision and recall.
Keywords:
DeepLabCutFiber photometrySimBAcholinergicphysical activity neurobiologyventral dentate gyrusvoluntary wheel running

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Main Results:

  • Acetylcholine in the ventral dentate gyrus increased before and during wheel running events.
  • Acetylcholine levels positively correlated with off-wheel body length.
  • The workflow accurately aligns neural activity with specific behaviors.

Conclusions:

  • The workflow provides an efficient and accurate method for aligning in vivo neural signals with wheel running behavior.
  • The approach is generalizable to other neuromodulators, brain regions, and recording modalities.