Kim Jimin, Florman Jeremy T, Santos Julia A, Alkema Mark J, Shlizerman Eli
ArXiv. 2025 Jun 3:arXiv:2504.18073v2.
Computational approaches which emulate in-vivo nervous system are needed to investigate mechanisms of the brain to orchestrate behavior. Such approaches must integrate a series of biophysical models encompassing the nervous system, muscles, biomechanics to allow observing the system in its entirety while supporting model variations. Here we develop modWorm: a modular modeling framework for the nematode C. elegans. modWorm allows for construction of a model as an integrated series of configurable, exchangeable modules each describing specific biophysical processes across different modalities. Utilizing modWorm, we propose a base neuro-mechanical model for C. elegans built upon the complete connectome. The model integrates a series of 7 modules: i) intra-cellular dynamics, ii) electrical and iii) chemical extra-cellular neural dynamics, iv) translation of neural activity to muscle calcium dynamics, v) muscle calcium dynamics to muscle forces, vi) muscle forces to body postures and vii) proprioceptive feedback. We validate the base model by in-silico injection of constant currents into neurons known to be associated with locomotion behaviors and by applying external forces to the body. Applications of in-silico neural stimuli experimentally known to modulate locomotion show that the model can recapitulate natural behavioral responses such as forward and backward locomotion as well as mid-locomotion responses such as avoidance and turns. Furthermore, through in-silico ablation surveys, the model can infer novel neural circuits involved in sensorimotor behaviors. To further dissect mechanisms of locomotion, we utilize modWorm to introduce empirical based model variations and model optimizations to elucidate their effects on simulated locomotion. Our results show that modWorm can be utilized to identify neural circuits which control, mediate and generate natural behavior.
需要采用模拟体内神经系统的计算方法来研究大脑协调行为的机制。此类方法必须整合一系列生物物理模型，涵盖神经系统、肌肉、生物力学，以便在支持模型变化的同时整体观察该系统。在此，我们开发了modWorm：一种用于秀丽隐杆线虫的模块化建模框架。modWorm允许将模型构建为一系列可配置、可交换的模块，每个模块描述不同模态下的特定生物物理过程。利用modWorm，我们基于完整的连接体提出了一种秀丽隐杆线虫的基础神经力学模型。该模型整合了7个模块：i）细胞内动力学，ii）电和iii）化学细胞外神经动力学，iv）神经活动向肌肉钙动力学的转化，v）肌肉钙动力学向肌肉力的转化，vi）肌肉力向身体姿势的转化，以及vii）本体感受反馈。我们通过在计算机模拟中将恒定电流注入已知与运动行为相关的神经元，并对身体施加外力来验证基础模型。应用已知可调节运动的计算机模拟神经刺激表明，该模型可以重现自然行为反应，如向前和向后运动，以及运动中的反应，如回避和转弯。此外，通过计算机模拟消融调查，该模型可以推断参与感觉运动行为的新神经回路。为了进一步剖析运动机制，我们利用modWorm引入基于经验的模型变化和模型优化，以阐明它们对模拟运动的影响。我们的结果表明，modWorm可用于识别控制、介导和产生自然行为的神经回路。
