Being able to replicate real experiments with computational simulations is a unique opportunity to refine and validate models with experimental data and redesign the experiments based on simulations. However, since it is technically demanding to model all components of an experiment, traditional approaches to modeling reduce the experimental setups as much as possible. In this study, our goal is to replicate all the relevant features of an experiment on motor control and motor rehabilitation after stroke. To this aim, we propose an approach that allows continuous integration of new experimental data into a computational modeling framework. First, results show that we could reproduce experimental object displacement with high accuracy via the simulated embodiment in the virtual world by feeding a spinal cord model with experimental registration of the cortical activity. Second, by using computational models of multiple granularities, our preliminary results show the possibility of simulating several features of the brain after stroke, from the local alteration in neuronal activity to long-range connectivity remodeling. Finally, strategies are proposed to merge the two pipelines. We further suggest that additional models could be integrated into the framework thanks to the versatility of the proposed approach, thus allowing many researchers to achieve continuously improved experimental design.

中文翻译：

---

中风后运动控制和恢复的实验和计算研究：在实验和虚拟体现神经科学之间建立建设性循环

能够通过计算模拟复制真实实验是一个独特的机会，可以用实验数据改进和验证模型，并根据模拟重新设计实验。但是，由于对实验的所有组件进行建模在技术上要求很高，因此传统的建模方法会尽可能地减少实验设置。在这项研究中，我们的目标是复制中风后运动控制和运动康复实验的所有相关特征。为此，我们提出了一种方法，允许将新的实验数据持续集成到计算建模框架中。第一的，结果表明，我们可以通过在虚拟世界中的模拟实施例，通过为脊髓模型提供皮层活动的实验记录来高精度地再现实验对象位移。其次，通过使用多个粒度的计算模型，我们的初步结果显示了模拟中风后大脑的几个特征的可能性，从神经元活动的局部改变到远程连接重塑。最后，提出了合并两条流水线的策略。我们进一步建议，由于所提出方法的多功能性，可以将其他模型集成到框架中，从而使许多研究人员能够不断改进实验设计。我们的初步结果显示了模拟中风后大脑的几个特征的可能性，从神经元活动的局部改变到远程连接重塑。最后，提出了合并两条流水线的策略。我们进一步建议，由于所提出方法的多功能性，可以将其他模型集成到框架中，从而使许多研究人员能够不断改进实验设计。我们的初步结果显示了模拟中风后大脑的几个特征的可能性，从神经元活动的局部改变到远程连接重塑。最后，提出了合并两条流水线的策略。我们进一步建议，由于所提出方法的多功能性，可以将其他模型集成到框架中，从而使许多研究人员能够不断改进实验设计。