ArticleFrontiers in systems neuroscience2019
DeepBehavior: A Deep Learning Toolbox for Automated Analysis of Animal and Human Behavior Imaging Data.
Article in Frontiers in systems neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
41 citing papers in PubMed, 1 synthesis or guideline pooled it, 114 citations in OpenAlex.
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- Arm dominance is an emergent effect of practice executing complex trajectory shapes required by tools and objects.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Semi-automated detection of cleaning interactions using supervised machine learning.Scientific reports · 2026Article
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- The MacqD deep-learning-based model for automatic detection of socially housed laboratory macaques.Scientific reports · 2025Article
- The effect of depth data and upper limb impairment on lightweight monocular RGB human pose estimation models.Biomedical engineering online · 2025Article
- ABNet: AI-Empowered Abnormal Action Recognition Method for Laboratory Mouse Behavior.Bioengineering (Basel, Switzerland) · 2024Article
- The Kinematics of 3D Arm Movements in Sub-Acute Stroke: Impaired Inter-Joint Coordination is Attributable to Both Weakness and Flexor Synergy Intrusion.Neurorehabilitation and neural repair · 2024Article
- Harmony in the Molecular Orchestra of Hearing: Developmental Mechanisms from the Ear to the Brain.Annual review of neuroscience · 2024Review
- Reconfiguration of Behavioral Signals in the Anterior Cingulate Cortex Based on Emotional State.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- How is Big Data reshaping preclinical aging research?Lab animal · 2023Review
- From beasts to bytes: Revolutionizing zoological research with artificial intelligence.Zoological research · 2023Review
- 3D Analysis of Human Movement, Sport, and Health Promotion.Journal of functional morphology and kinesiology · 2023Article
- ICT Framework for Supporting Applied Behavior Analysis in the Social Inclusion of Children with Neurodevelopmental Disorders.Sensors (Basel, Switzerland) · 2023Article
- Data-Driven Quantitation of Movement Abnormality after Stroke.Bioengineering (Basel, Switzerland) · 2023Article
- PolarBearVidID: A Video-Based Re-Identification Benchmark Dataset for Polar Bears.Animals : an open access journal from MDPI · 2023Article
- An integrated workflow for 2D and 3D posture analysis during vestibular system testing in mice.Frontiers in neurology · 2023Article
- Bringing machine learning to research on intellectual and developmental disabilities: taking inspiration from neurological diseases.Journal of neurodevelopmental disorders · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Detailed behavioral analysis is key to understanding the brain-behavior relationship. Here, we present deep learning-based methods for analysis of behavior imaging data in mice and humans. Specifically, we use three different convolutional neural network architectures and five different behavior tasks in mice and humans and provide detailed instructions for rapid implementation of these methods for the neuroscience community. We provide examples of three dimensional (3D) kinematic analysis in the food pellet reaching task in mice, three-chamber test in mice, social interaction test in freely moving mice with simultaneous miniscope calcium imaging, and 3D kinematic analysis of two upper extremity movements in humans (reaching and alternating pronation/supination). We demonstrate that the transfer learning approach accelerates the training of the network when using images from these types of behavior video recordings. We also provide code for post-processing of the data after initial analysis with deep learning. Our methods expand the repertoire of available tools using deep learning for behavior analysis by providing detailed instructions on implementation, applications in several behavior tests, and post-processing methods and annotated code for detailed behavior analysis. Moreover, our methods in human motor behavior can be used in the clinic to assess motor function during recovery after an injury such as stroke.
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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.