ReviewFrontiers in behavioral neuroscience2017
Supervised and Unsupervised Learning Technology in the Study of Rodent Behavior.
Review in Frontiers in behavioral neuroscience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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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
14 citing papers in PubMed.
- Real-time behavioral monitoring of C57BL/6J mice during reproductive cycle.Frontiers in neuroscience · 2025Article
- Simple Behavioral Analysis (SimBA) as a platform for explainable machine learning in behavioral neuroscience.Nature neuroscience · 2024Article
- Automatic identification of stone-handling behaviour in Japanese macaques using LabGym artificial intelligence.Primates; journal of primatology · 2024Article
- Behavioral decomposition reveals rich encoding structure employed across neocortex in rats.Nature communications · 2023Article
- Shortwave infrared fluorescence imaging of peripheral organs in awake and freely moving mice.Frontiers in neuroscience · 2023Article
- Male and female mice display consistent lifelong ability to address potential life-threatening cues using different post-threat coping strategies.BMC biology · 2022Article
- Affective State Recognition in Livestock-Artificial Intelligence Approaches.Animals : an open access journal from MDPI · 2022Review
- PyRAT: An Open-Source Python Library for Animal Behavior Analysis.Frontiers in neuroscience · 2022Article
- A hierarchical 3D-motion learning framework for animal spontaneous behavior mapping.Nature communications · 2021Article
- Machine Learning in Modeling of Mouse Behavior.Frontiers in neuroscience · 2021Article
- Rage Against the Machine: Advancing the study of aggression ethology via machine learning.Psychopharmacology · 2020Review
- Robust mouse tracking in complex environments using neural networks.Communications biology · 2019Article
- Decision-making behaviors: weighing ethology, complexity, and sensorimotor compatibility.Current opinion in neurobiology · 2018Review
- Exhaustive Multi-Parametric Assessment of the Behavioral Array of Daily Activities of Mice Using Cluster and Factor Analysis.Frontiers in behavioral neuroscience · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Quantifying behavior is a challenge for scientists studying neuroscience, ethology, psychology, pathology, etc. Until now, behavior was mostly considered as qualitative descriptions of postures or labor intensive counting of bouts of individual movements. Many prominent behavioral scientists conducted studies describing postures of mice and rats, depicting step by step eating, grooming, courting, and other behaviors. Automated video assessment technologies permit scientists to quantify daily behavioral patterns/routines, social interactions, and postural changes in an unbiased manner. Here, we extensively reviewed published research on the topic of the structural blocks of behavior and proposed a structure of behavior based on the latest publications. We discuss the importance of defining a clear structure of behavior to allow professionals to write viable algorithms. We presented a discussion of technologies that are used in automated video assessment of behavior in mice and rats. We considered advantages and limitations of supervised and unsupervised learning. We presented the latest scientific discoveries that were made using automated video assessment. In conclusion, we proposed that the automated quantitative approach to evaluating animal behavior is the future of understanding the effect of brain signaling, pathologies, genetic content, and environment on behavior.
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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.