NeuroMechFly v2: simulating embodied sensorimotor control in adult Drosophila

IF 36.1 1区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Nature Methods Pub Date : 2024-11-12 DOI:10.1038/s41592-024-02497-y
Sibo Wang-Chen, Victor Alfred Stimpfling, Thomas Ka Chung Lam, Pembe Gizem Özdil, Louise Genoud, Femke Hurtak, Pavan Ramdya
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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. NeuroMechFly v2 extends the capabilities of the original neuromechanical modeling platform for Drosophila, NeuroMechFly, by including sensory input, motor feedback and the ability to simulate complex terrains.

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NeuroMechFly v2:模拟成年果蝇的感知运动控制。
发现动物行为控制的基本原理需要实验与神经机械模型之间的紧密对话。这些模型主要用于研究运动控制,而较少强调大脑和运动系统在分层传感运动控制过程中如何协同工作。NeuroMechFly v2 拓展了果蝇神经机械模型,实现了视觉、嗅觉、上升运动反馈和可利用腿部粘附导航的复杂地形。我们通过构建受生物启发的控制器来说明它的功能,这些控制器使用上升反馈来执行路径整合和头部稳定。在加入视觉和嗅觉后,我们使用强化学习训练控制器,以执行多模态导航任务。最后,我们展示了更逼真的生物建模,涉及复杂的气味羽流导航,以及使用连接体约束视觉网络的苍蝇-苍蝇跟随。NeuroMechFly 可用于加速发现神经系统的解释模型,并为自主人工代理和机器人开发基于机器学习的控制器。
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来源期刊
Nature Methods
Nature Methods 生物-生化研究方法
CiteScore
58.70
自引率
1.70%
发文量
326
审稿时长
1 months
期刊介绍: Nature Methods is a monthly journal that focuses on publishing innovative methods and substantial enhancements to fundamental life sciences research techniques. Geared towards a diverse, interdisciplinary readership of researchers in academia and industry engaged in laboratory work, the journal offers new tools for research and emphasizes the immediate practical significance of the featured work. It publishes primary research papers and reviews recent technical and methodological advancements, with a particular interest in primary methods papers relevant to the biological and biomedical sciences. This includes methods rooted in chemistry with practical applications for studying biological problems.
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