ArticleBMC biology2022
Deep learning-based behavioral profiling of rodent stroke recovery.
Article in BMC biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.
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Who cites it
37 citing papers in PubMed, 1 synthesis or guideline pooled it, 74 citations in OpenAlex.
- Does advancement in marker-less pose-estimation mean more quality research? A systematic review.Frontiers in behavioral neuroscience · 2025Pooled it
- Advancing Neurorehabilitation and Recovery Through Human Movement Quantification via Wearable Sensing.Neurorehabilitation and neural repair · 2026Article
- Engineered Brain-Targeted Exosomes Delivering FGF1 for Sustained Glycemic Regulation and Multitarget Neurovascular Protection in Diabetic Stroke.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Chronic Administration of Marinobufagenin in Mice Causes Hyperlocomotion and Decrease in Anxiety by Altering Monoamine Turnover Unaccompanied by Motor Deficits or Oxidative Stress.International journal of molecular sciences · 2026Article
- Temporal assessment of behavior in Parkinson's visual hallucinations via a multidimensional analysis strategy.Signal transduction and targeted therapy · 2026Article
- Decoding fetal motion in 4D ultrasound with DeepLabCut.Journal of medical ultrasonics (2001) · 2026Article
- Objective quantification of gait impairment in rats using automated video analysis.Biophysics and physicobiology · 2026Article
- Development of a deep learning-based grid walking test for assessing post-stroke motor function in mice.Frontiers in behavioral neuroscience · 2026Article
- Gait and posture analysis in rats with Parkinson's disease using DeepLabCut during beam test.Open veterinary journal · 2025Article
- FERAL: A Video-Understanding System for Direct Video-to-Behavior Mapping.bioRxiv : the preprint server for biology · 2025Article
- Role of the Medial Agranular Cortex in Sensory-Motor Integration During Walking: Insights From a Rodent Stroke Model.Cureus · 2025Article
- Neural xenografts contribute to long-term recovery in stroke via molecular graft-host crosstalk.Nature communications · 2025Article
- Delayed Transplantation of Neural Stem Cells Improves Initial Graft Survival after Stroke.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Manual assessment of cylinder rearing behavior is more sensitive than automated gait evaluations in young, male mice post-stroke of the forepaw somatosensory cortex.Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association · 2025Article
- A hybrid machine learning model with attention mechanism and multidimensional multivariate feature coding for essential gene prediction.BMC biology · 2025Article
- Forestwalk: A Machine Learning Workflow Brings New Insights Into Posture and Balance in Rodent Beam Walking.The European journal of neuroscience · 2025Article
- DeepLabCut custom-trained model and the refinement function for gait analysis.Scientific reports · 2025Article
- refineDLC: An advanced post-processing pipeline for DeepLabCut outputs.Biology methods & protocols · 2025Article
- OpenLabCluster: active learning based clustering and classification of animal behaviors based on kinematic body keypoints.Frontiers in systems neuroscience · 2025Article
- Effective identification of Alzheimer's disease in mouse models via deep learning and motion analysis.Heliyon · 2024Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundStroke research heavily relies on rodent behavior when assessing underlying disease mechanisms and treatment efficacy. Although functional motor recovery is considered the primary targeted outcome, tests in rodents are still poorly reproducible and often unsuitable for unraveling the complex behavior after injury.
resultsHere, we provide a comprehensive 3D gait analysis of mice after focal cerebral ischemia based on the new deep learning-based software (DeepLabCut, DLC) that only requires basic behavioral equipment. We demonstrate a high precision 3D tracking of 10 body parts (including all relevant joints and reference landmarks) in several mouse strains. Building on this rigor motion tracking, a comprehensive post-analysis (with >100 parameters) unveils biologically relevant differences in locomotor profiles after a stroke over a time course of 3 weeks. We further refine the widely used ladder rung test using deep learning and compare its performance to human annotators. The generated DLC-assisted tests were then benchmarked to five widely used conventional behavioral set-ups (neurological scoring, rotarod, ladder rung walk, cylinder test, and single-pellet grasping) regarding sensitivity, accuracy, time use, and costs.
conclusionsWe conclude that deep learning-based motion tracking with comprehensive post-analysis provides accurate and sensitive data to describe the complex recovery of rodents following a stroke. The experimental set-up and analysis can also benefit a range of other neurological injuries that affect locomotion.
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Registered trials
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.