Evidence map›Paper›PMID 41356068›Full record

ArticleArXiv2025

MIMIC-MJX: Neuromechanical Emulation of Animal Behavior.

Charles Y Zhang, Yuanjia Yang, Aidan Sirbu, Elliott T T Abe, Emil Wärnberg, Eric J Leonardis, Diego E Aldarondo, Adam Lee, Aaditya Prasad, Jason Foat and 16 more

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PubMed Full text at PMC
In one paragraph

Article in ArXiv, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

26 authors.

Charles Y ZhangDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA.
Yuanjia YangComputational Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA.
Aidan SirbuMila, Montréal, QC, Canada.
Elliott T T AbeBiology Department, University of Washington, Seattle, WA, USA.
Emil WärnbergDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA.
Eric J LeonardisComputational Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA.
Diego E AldarondoDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA.
Adam LeeDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA.
Aaditya PrasadDepartment of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
Jason FoatComputational Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA.
Kaiwen BianComputational Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA.
Joshua ParkComputational Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA.
Rusham BhattComputational Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA.
Hutton SaundersComputational Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA.
Akira NagamoriMolecular Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA.
Ayesha R ThanawallaMolecular Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA.
Kee Wui HuangMolecular Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA.
Fabian PlumDepartment of Bioengineering, Imperial College London, London, United Kingdom.
Hendrik K BeckDepartment of Bioengineering, Imperial College London, London, United Kingdom.
Steven W FlavellDepartment of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
David LabonteDepartment of Bioengineering, Imperial College London, London, United Kingdom.
Blake A RichardsMila, Montréal, QC, Canada.
Bingni W BruntonBiology Department, University of Washington, Seattle, WA, USA.
Eiman AzimMolecular Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA.
Bence P ÖlveczkyDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA.
Talmo D PereiraComputational Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA.

Funding

Understanding Sensorimotor Control Through Realistic Neuro-Biomechanical SimulationU01NS136507 · NINDS · HARVARD UNIVERSITY · PI Bingni Wen Brunton, Bence P Olveczky · 2024 to 2026
$7.1M
Defining the anatomical, molecular and functional logic of internal copy circuits involved in dexterous forelimb behaviorsR01NS111479 · NINDS · SALK INSTITUTE FOR BIOLOGICAL STUDIES · PI AZIM, EIMAN · 2019 to 2023
$2.9M
Functional dissection of cerebellar output circuits that orchestrate limb motor controlR01NS128898 · NINDS · SALK INSTITUTE FOR BIOLOGICAL STUDIES · PI EIMAN AZIM, Albert Chen · 2025 to 2026
$1.3M
Defining the contributions of proprioception to goal-directed reaching movementsF32NS126231 · NINDS · SALK INSTITUTE FOR BIOLOGICAL STUDIES · PI NAGAMORI, AKIRA · 2022 to 2024
$177k
Evaluating the functional organization of forelimb and hindlimb internal copy pathways in the lateral reticular nucleusF32NS120998 · NINDS · SALK INSTITUTE FOR BIOLOGICAL STUDIES · PI HUANG, KEE WUI · 2021 to 2022
$124k
NINDS NIH HHS F32 NS120998NINDS NIH HHS F32 NS126231NINDS NIH HHS R01 NS111479NINDS NIH HHS R01 NS128898NINDS NIH HHS U01 NS136507
6 · The paper itself

Abstract

The primary output of the nervous system is movement and behavior. While recent advances have democratized pose tracking during complex behavior, kinematic trajectories alone provide only indirect access to the underlying control processes. Here we present MIMIC-MJX, a framework for learning biologically-plausible neural control policies from kinematics. MIMIC-MJX models the generative process of motor control by training neural controllers that learn to actuate biomechanically-realistic body models in physics simulation to reproduce real kinematic trajectories. We demonstrate that our implementation is accurate, fast, data-efficient, and generalizable to diverse animal body models. Policies trained with MIMIC-MJX can be utilized to both analyze neural control strategies and simulate behavioral experiments, illustrating its potential as an integrative modeling framework for neuroscience.

Identifiers

PMID41356068
PMCPMC12676414

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Registered trials

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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.