ReviewBMC biology2018
Measuring behavior across scales.
Review in BMC biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 102 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
102 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic review of artificial intelligence use in behavioral analysis of invertebrate and larval model organisms: methods, applications and future recommendations.Frontiers in artificial intelligence · 2026Pooled it
- Article
- Deep-Pose-Tracker: an automated behavioural analysis framework for Caenorhabditis elegans.Scientific reports · 2026Article
- Alterations in the Multivariate Organization of Plasma Fatty Acid Profiles and Spontaneous Behavior in an AlClBiology · 2026Article
- Semi-automated detection of cleaning interactions using supervised machine learning.Scientific reports · 2026Article
- Using timescale as a state coordinate reveals the metastable geometry of behavior.bioRxiv : the preprint server for biology · 2026Article
- A modular multi-color fluorescence microscope for simultaneous tracking of cellular activity and behavior.Nature communications · 2026Article
- Virtual Mice, Real Errors: A Sensor-Aware Generative Framework for In Silico Ethology.Sensors (Basel, Switzerland) · 2026Article
- A dataset of fine-grained zebrafish interactions in health and disease.Scientific data · 2026Article
- Comparative Evaluation of DeepLabCut Convolutional Neural Network Architectures for High-Precision Markerless Tracking in the Mouse Staircase Test.Bioengineering (Basel, Switzerland) · 2026Article
- Identifying the factors governing internal state switches during nonstationary sensory decision-making.Nature communications · 2025Article
- FERAL: A Video-Understanding System for Direct Video-to-Behavior Mapping.bioRxiv : the preprint server for biology · 2025Article
- DISSeCT: An unsupervised framework for high-resolution mapping of rodent behavior using inertial sensors.PLoS biology · 2025Article
- Beyond Binary: A Machine Learning Framework for Interpreting Organismal Behavior in Cancer Diagnostics.Biomedicines · 2025Review
- Article
- Balancing ethics and statistics: machine learning facilitates highly accurate classification of mice according to their trait anxiety with reduced sample sizes.Translational psychiatry · 2025Article
- Two modes in the absolute velocity statistics in cautious walks of laboratory rodents.Biophysical journal · 2025Article
- Applying movement ecology models to comparative cognition experiments: a field test in hummingbirds.Proceedings. Biological sciences · 2025Article
- An oxytocin receptor gene polymorphism is associated with distinct neural responses to mating encounters in male prairie voles.Hormones and behavior · 2025Article
- Behavioral sequences across multiple animal species in the wild share common structural features.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
42 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
The need for high-throughput, precise, and meaningful methods for measuring behavior has been amplified by our recent successes in measuring and manipulating neural circuitry. The largest challenges associated with moving in this direction, however, are not technical but are instead conceptual: what numbers should one put on the movements an animal is performing (or not performing)? In this review, I will describe how theoretical and data analytical ideas are interfacing with recently-developed computational and experimental methodologies to answer these questions across a variety of contexts, length scales, and time scales. I will attempt to highlight commonalities between approaches and areas where further advances are necessary to place behavior on the same quantitative footing as other scientific fields.
Indexed as
Identifiers
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.