ArticlePLoS biology2019
Data-driven analyses of motor impairments in animal models of neurological disorders.
Article in PLoS biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 19 papers.
What it found
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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.
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.
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Who cites it
19 citing papers in PubMed, 26 citations in OpenAlex.
- Correction: Correction: Data-driven analyses of motor impairments in animal models of neurological disorders.PLoS biology · 2026Article
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- Correction: Data-driven analyses of motor impairments in animal models of neurological disorders.PLoS biology · 2024Article
- Biologically-inspired neuronal adaptation improves learning in neural networks.Communicative & integrative biology · 2023Article
- Deep learning-based behavioral profiling of rodent stroke recovery.BMC biology · 2022Article
- Epileptic seizures and link to memory processes.AIMS neuroscience · 2022Article
- Combining backpropagation with Equilibrium Propagation to improve an Actor-Critic reinforcement learning framework.Frontiers in computational neuroscience · 2022Article
- DeepEthogram, a machine learning pipeline for supervised behavior classification from raw pixels.eLife · 2021Article
- Closed-loop automated reaching apparatus (CLARA) for interrogating complex motor behaviors.Journal of neural engineering · 2021Article
- New Mechanistic Insights, Novel Treatment Paradigms, and Clinical Progress in Cerebrovascular Diseases.Frontiers in aging neuroscience · 2021Article
- A Neural Network Reveals Motoric Effects of Maternal Preconception Exposure to Nicotine on Rat Pup Behavior: A New Approach for Movement Disorders Diagnosis.Frontiers in neuroscience · 2021Article
- Application of Spatio-Temporal Context and Convolution Neural Network (CNN) in Grooming Behavior ofInsects · 2020Article
- A Matlab-based toolbox for characterizing behavior of rodents engaged in string-pulling.eLife · 2020Article
- Neurostimulation and Reach-to-Grasp Function Recovery Following Acquired Brain Injury: Insight From Pre-clinical Rodent Models and Human Applications.Frontiers in neurology · 2020Review
- The Neuroscience of Spatial Navigation and the Relationship to Artificial Intelligence.Frontiers in computational neuroscience · 2020Review
- Article
Corrections and comments
- Erratum issued
- Erratum issued
Authors and funding
12 authors at 2 institutions in 3 countries.
Funding
Abstract
Behavior provides important insights into neuronal processes. For example, analysis of reaching movements can give a reliable indication of the degree of impairment in neurological disorders such as stroke, Parkinson disease, or Huntington disease. The analysis of such movement abnormalities is notoriously difficult and requires a trained evaluator. Here, we show that a deep neural network is able to score behavioral impairments with expert accuracy in rodent models of stroke. The same network was also trained to successfully score movements in a variety of other behavioral tasks. The neural network also uncovered novel movement alterations related to stroke, which had higher predictive power of stroke volume than the movement components defined by human experts. Moreover, when the regression network was trained only on categorical information (control = 0; stroke = 1), it generated predictions with intermediate values between 0 and 1 that matched the human expert scores of stroke severity. The network thus offers a new data-driven approach to automatically derive ratings of motor impairments. Altogether, this network can provide a reliable neurological assessment and can assist the design of behavioral indices to diagnose and monitor neurological disorders.
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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.