ArticleeLife2022
Selfee, self-supervised features extraction of animal behaviors.
Article in eLife, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Artificial Intelligence-Based Decoding of Animal Micro-Expressions: A Review of Methodological Advances and Translational Applications.Animals : an open access journal from MDPI · 2026Review
- Semi-automated detection of cleaning interactions using supervised machine learning.Scientific reports · 2026Article
- Beast3D: Animal behavioral analysis and neural encoding from multi-view video via Gaussian splatting.ArXiv · 2026Article
- Animal behavioral analysis and neural encoding with transformer-based self-supervised pretraining.ArXiv · 2026Article
- EyeInvaS: Lowering Barriers to Public Participation in Invasive Alien Species Monitoring Through Deep Learning.Animals : an open access journal from MDPI · 2025Article
- OpenLabCluster: active learning based clustering and classification of animal behaviors based on kinematic body keypoints.Frontiers in systems neuroscience · 2025Article
- Analysis of behavioral flow resolves latent phenotypes.Nature methods · 2024Article
- Keypoint-MoSeq: parsing behavior by linking point tracking to pose dynamics.Nature methods · 2024Article
- Recovery from social isolation requires dopamine in males, but not the autism-related geneRoyal Society open science · 2024Article
- A System for Monitoring Animals Based on Behavioral Information and Internal State Information.Animals : an open access journal from MDPI · 2024Article
- The effect of microbiome on social spacing inmicroPublication biology · 2024Article
- SaLSa: A Combinatory Approach of Semi-Automatic Labeling and Long Short-Term Memory to Classify Behavioral Syllables.eNeuro · 2023Article
- Noninvasive Tracking of Every Individual in Unmarked Mouse Groups Using Multi-Camera Fusion and Deep Learning.Neuroscience bulletin · 2023Article
- Article
- Using deep learning to study emotional behavior in rodent models.Frontiers in behavioral neuroscience · 2022Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Fast and accurately characterizing animal behaviors is crucial for neuroscience research. Deep learning models are efficiently used in laboratories for behavior analysis. However, it has not been achieved to use an end-to-end unsupervised neural network to extract comprehensive and discriminative features directly from social behavior video frames for annotation and analysis purposes. Here, we report a self-supervised feature extraction (Selfee) convolutional neural network with multiple downstream applications to process video frames of animal behavior in an end-to-end way. Visualization and classification of the extracted features (Meta-representations) validate that Selfee processes animal behaviors in a way similar to human perception. We demonstrate that Meta-representations can be efficiently used to detect anomalous behaviors that are indiscernible to human observation and hint in-depth analysis. Furthermore, time-series analyses of Meta-representations reveal the temporal dynamics of animal behaviors. In conclusion, we present a self-supervised learning approach to extract comprehensive and discriminative features directly from raw video recordings of animal behaviors and demonstrate its potential usage for various downstream applications.
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