ReviewNeuron2019
Computational Neuroethology: A Call to Action.
Review in Neuron, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 226 papers.
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
226 citing papers in PubMed.
- Experience-dependent emergence of multi-scale spatial organization during foraging in freely moving marmosets.iScience · 2026Article
- Immersive Social Interaction Assay (ISIA) for Studying Voluntary and Long-Term Social Behavior in Mice.Bio-protocol · 2026Article
- Early-life adversity shapes anomalous spontaneous behavior in mice heterozygous for Cntnap2.Translational psychiatry · 2026Article
- Automated analysis of C. elegans behavior by LabGym: an open-source, AI-powered platform.G3 (Bethesda, Md.) · 2026Article
- Ecological Visual Processing in the Mouse.Annual review of neuroscience · 2026Review
- Beast3D: Animal behavioral analysis and neural encoding from multi-view video via Gaussian splatting.ArXiv · 2026Article
- Automated Profiling of Social Behaviors to Assess the Genetic Basis of Evolution of Aggressive Behaviors in Astyanax mexicanus.Journal of experimental zoology. Part A, Ecological and integrative physiology · 2026Article
- Using timescale as a state coordinate reveals the metastable geometry of behavior.bioRxiv : the preprint server for biology · 2026Article
- A Machine Learning Framework Integrating DeepLabCut and SimBA for Quantifying Aggressive Behavior in Swimming CrabAnimals : an open access journal from MDPI · 2026Article
- AVATAR: AI Vision Analysis for Three-dimensional Action in Real-time.Experimental neurobiology · 2026Article
- Predictive pursuit emerges in high-dimensional recurrent neural networks.bioRxiv : the preprint server for biology · 2026Article
- Mid-superior temporal sulcus encodes spatial context and behavioral state in freely moving macaques.bioRxiv : the preprint server for biology · 2026Article
- Article
- Adoption of MMPose, a general purpose pose estimation library, for animal tracking.bioRxiv : the preprint server for biology · 2026Article
- Integrating supervised and unsupervised machine learning for behavior segmentation reveals latent frailty signatures and improves aging clocks in isogenic and outbred mice.bioRxiv : the preprint server for biology · 2026Article
- Visualizing and sonifying neurodata (ViSoND) for enhanced observation.bioRxiv : the preprint server for biology · 2026Article
- A spinal substrate for modular control of natural behavior.bioRxiv : the preprint server for biology · 2026Article
- Lifelong behavioral screen reveals an architecture of vertebrate aging.Science (New York, N.Y.) · 2026Article
- Article
- Article
166 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
5 authors.
Funding
Abstract
The brain is worthy of study because it is in charge of behavior. A flurry of recent technical advances in measuring and quantifying naturalistic behaviors provide an important opportunity for advancing brain science. However, the problem of understanding unrestrained behavior in the context of neural recordings and manipulations remains unsolved, and developing approaches to addressing this challenge is critical. Here we discuss considerations in computational neuroethology-the science of quantifying naturalistic behaviors for understanding the brain-and propose strategies to evaluate progress. We point to open questions that require resolution and call upon the broader systems neuroscience community to further develop and leverage measures of naturalistic, unrestrained behavior, which will enable us to more effectively probe the richness and complexity of the brain.
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.