ArticleeLife2020
Real-time, low-latency closed-loop feedback using markerless posture tracking.
Article in eLife, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 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
85 citing papers in PubMed, 1 synthesis or guideline pooled it.
- On the (limited) use of touchscreen-based behavioural and cognitive research with dogs: potential causes and future directions.Animal cognition · 2026Pooled it
- Real-time closed-loop feedback system for mouse mesoscale cortical signal and movement control.eLife · 2026Article
- Hoverfly responses to looming stimuli depend on elevation and speed.The Journal of experimental biology · 2026Article
- Continuous contributions of the dorsolateral striatum to movement initiation and execution.Science advances · 2026Article
- Visual uncertainty and task demands shape active sensing strategies in mice.Current biology : CB · 2026Article
- SqueakPose Studio, an end-to-end platform for pose estimation and real-time edge-AI deployment.eLife · 2026Article
- Dexterous single sniffs for ethological active olfaction.Science advances · 2026Article
- Visual uncertainty and task demands shape active sensing strategies in mice.bioRxiv : the preprint server for biology · 2026Article
- EthoPy provides an accessible platform for reproducible behavioral neuroscience.Cell reports methods · 2026Article
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- Video-based Detection of Delirium in Hospitalized Adults.medRxiv : the preprint server for health sciences · 2026Article
- The anterior cingulate cortex modulates pupil-linked arousal.Science advances · 2026Article
- Video-based detection of Delirium in hospitalized adults.PLOS digital health · 2026Article
- AVATAR: AI Vision Analysis for Three-dimensional Action in Real-time.Experimental neurobiology · 2026Article
- Article
- Integration of learned artificial sensation with vision during freely moving navigation.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Corticothalamic communication for action coordination in a skilled motor behavior.Nature neuroscience · 2026Article
- Edge AI-Based Gait-Phase Detection for Closed-Loop Neuromodulation in SCI Mice.Sensors (Basel, Switzerland) · 2026Article
- YORU: Animal behavior detection with object-based approach for real-time closed-loop feedback.Science advances · 2026Article
- Argument for the pharmacokinetically-informed preclinical researcher: A commentary for Alcohol.Alcohol (Fayetteville, N.Y.) · 2026Article
25 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
The ability to control a behavioral task or stimulate neural activity based on animal behavior in real-time is an important tool for experimental neuroscientists. Ideally, such tools are noninvasive, low-latency, and provide interfaces to trigger external hardware based on posture. Recent advances in pose estimation with deep learning allows researchers to train deep neural networks to accurately quantify a wide variety of animal behaviors. Here, we provide a new <monospace>DeepLabCut-Live!</monospace> package that achieves low-latency real-time pose estimation (within 15 ms, >100 FPS), with an additional forward-prediction module that achieves zero-latency feedback, and a dynamic-cropping mode that allows for higher inference speeds. We also provide three options for using this tool with ease: (1) a stand-alone GUI (called <monospace>DLC-Live! GUI</monospace>), and integration into (2) <monospace>Bonsai,</monospace> and (3) <monospace>AutoPilot</monospace>. Lastly, we benchmarked performance on a wide range of systems so that experimentalists can easily decide what hardware is required for their needs.
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What OpenQuestion holds
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.