ReviewNature protocols2024
Characterizing the structure of mouse behavior using Motion Sequencing.
Review in Nature protocols, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 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.
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Who cites it
22 citing papers in PubMed.
- Tail-rattling in rodents: more than a threat display.Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology · 2026Review
- Considerations for the selection and phenotyping of mouse models for the study of Alzheimer's disease.STAR protocols · 2026Review
- TweetyBERT: Automated parsing of birdsong through self-supervised machine learning.Patterns (New York, N.Y.) · 2026Article
- Article
- Neural Bases of Collective Social Behavior and Group Interactions across Species.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026Review
- Multiple subject tracking in long-term, behavioral studies of rodents.Frontiers in molecular neuroscience · 2026Review
- Unsupervised learning-based optimization of college students' fundamental capacity evaluation method.Frontiers in physiology · 2026Article
- Electroconvulsive Therapy Induces Dopaminergic Axon Regeneration, Corticostriatal Remodeling, and Restoration of Motor Function in Parkinsonian Mice.bioRxiv : the preprint server for biology · 2025Article
- Hunger modulates exploration through suppression of dopamine signaling in the tail of the striatum.Neuron · 2025Article
- REVS: A new open-source platform for high-resolution analysis of rodent wheel running behavior.Journal of neuroscience methods · 2025Article
- Elevated synaptic PKA activity and abnormal striatal dopamine signaling in Akap11 mutant mice, a genetic model of schizophrenia and bipolar disorder.Nature communications · 2025Article
- Functional synaptic connectivity of engrafted spinal cord neurons with hindlimb motor circuitry in the injured spinal cord.Nature communications · 2025Article
- Elevated synaptic PKA activity and abnormal striatal dopamine signaling inbioRxiv : the preprint server for biology · 2025Article
- Rodent Social Behavior Recognition Using a Global Context-Aware Vision Transformer Network.AI (Basel, Switzerland) · 2025Article
- Comprehensive behavioral characterization and impaired hippocampal synaptic transmission in R1117X Shank3 mutant mice.Translational psychiatry · 2025Article
- MoSeq based 3D behavioral profiling uncovers neuropathic behavior changes in diabetic mouse model.Scientific reports · 2025Article
- Social context restructures behavioral syntax in mice.Frontiers in behavioral neuroscience · 2025Article
- Article
- Spinal neuron diversity scales exponentially with swim-to-limb transformation during frog metamorphosis.bioRxiv : the preprint server for biology · 2024Article
- Keypoint-MoSeq: parsing behavior by linking point tracking to pose dynamics.bioRxiv : the preprint server for biology · 2023Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Spontaneous mouse behavior is composed from repeatedly used modules of movement (e.g., rearing, running or grooming) that are flexibly placed into sequences whose content evolves over time. By identifying behavioral modules and the order in which they are expressed, researchers can gain insight into the effect of drugs, genes, context, sensory stimuli and neural activity on natural behavior. Here we present a protocol for performing Motion Sequencing (MoSeq), an ethologically inspired method that uses three-dimensional machine vision and unsupervised machine learning to decompose spontaneous mouse behavior into a series of elemental modules called 'syllables'. This protocol is based upon a MoSeq pipeline that includes modules for depth video acquisition, data preprocessing and modeling, as well as a standardized set of visualization tools. Users are provided with instructions and code for building a MoSeq imaging rig and acquiring three-dimensional video of spontaneous mouse behavior for submission to the modeling framework; the outputs of this protocol include syllable labels for each frame of the video data as well as summary plots describing how often each syllable was used and how syllables transitioned from one to the other. In addition, we provide instructions for analyzing and visualizing the outputs of keypoint-MoSeq, a recently developed variant of MoSeq that can identify behavioral motifs from keypoints identified from standard (rather than depth) video. This protocol and the accompanying pipeline significantly lower the bar for users without extensive computational ethology experience to adopt this unsupervised, data-driven approach to characterize mouse 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.