ArticleNature methods2024
NeuroMechFly v2: simulating embodied sensorimotor control in adult Drosophila.
Article in Nature methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Whole-body 3D kinematics of freely behavingbioRxiv : the preprint server for biology · 2026Article
- Centralized brain networks controlling antennal grooming coordination.Nature communications · 2026Article
- The digital sphinx: Can a worm brain control a fly body?bioRxiv : the preprint server for biology · 2026Article
- Glutamate receptor composition atbioRxiv : the preprint server for biology · 2026Article
- Proprioceptive limit detectors contribute to sensorimotor control of the Drosophila leg.Nature communications · 2026Article
- Synaptic-resolution connectomics: towards large brains and connectomic screening.Nature reviews. Neuroscience · 2026Review
- Inhibitory circuits control leg movements duringeLife · 2026Article
- Article
- Inhibitory circuits control leg movements duringbioRxiv : the preprint server for biology · 2025Article
- Foot placement control underlies stable locomotion across species.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Artificial embodied circuits uncover neural architectures of vertebrate visuomotor behaviors.Science robotics · 2025Article
- Embodied sensorimotor control: computational modeling of the neural control of movement.ArXiv · 2025Article
- Article
- Article
- Sensorimotor delays constrain robust locomotion in a 3D kinematic model of fly walking.bioRxiv : the preprint server for biology · 2025Article
- I2Bot: an open-source tool for multi-modal and embodied simulation of insect navigation.Journal of the Royal Society, Interface · 2025Article
- Review
- Mechanosensory and command contributions to the Drosophila grooming sequence.Current biology : CB · 2024Article
- Mechanosensory and command contributions to thebioRxiv : the preprint server for biology · 2023Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Discovering principles underlying the control of animal behavior requires a tight dialogue between experiments and neuromechanical models. Such models have primarily been used to investigate motor control with less emphasis on how the brain and motor systems work together during hierarchical sensorimotor control. NeuroMechFly v2 expands Drosophila neuromechanical modeling by enabling vision, olfaction, ascending motor feedback and complex terrains that can be navigated using leg adhesion. We illustrate its capabilities by constructing biologically inspired controllers that use ascending feedback to perform path integration and head stabilization. After adding vision and olfaction, we train a controller using reinforcement learning to perform a multimodal navigation task. Finally, we illustrate more bio-realistic modeling involving complex odor plume navigation, and fly-fly following using a connectome-constrained visual network. NeuroMechFly can be used to accelerate the discovery of explanatory models of the nervous system and to develop machine learning-based controllers for autonomous artificial agents and robots.
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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.