Manninen Tiina, Havela Riikka, Linne Marja-Leena
Computational Neuroscience Group, BioMediTech Institute and Faculty of Biomedical Sciences and Engineering, Tampere University of Technology, Tampere, Finland.
Front Comput Neurosci. 2018 Apr 4;12:14. doi: 10.3389/fncom.2018.00014. eCollection 2018.
The computational neuroscience field has heavily concentrated on the modeling of neuronal functions, largely ignoring other brain cells, including one type of glial cell, the astrocytes. Despite the short history of modeling astrocytic functions, we were delighted about the hundreds of models developed so far to study the role of astrocytes, most often in calcium dynamics, synchronization, information transfer, and plasticity , but also in vascular events, hyperexcitability, and homeostasis. Our goal here is to present the state-of-the-art in computational modeling of astrocytes in order to facilitate better understanding of the functions and dynamics of astrocytes in the brain. Due to the large number of models, we concentrated on a hundred models that include biophysical descriptions for calcium signaling and dynamics in astrocytes. We categorized the models into four groups: single astrocyte models, astrocyte network models, neuron-astrocyte synapse models, and neuron-astrocyte network models to ease their use in future modeling projects. We characterized the models based on which earlier models were used for building the models and which type of biological entities were described in the astrocyte models. Features of the models were compared and contrasted so that similarities and differences were more readily apparent. We discovered that most of the models were basically generated from a small set of previously published models with small variations. However, neither citations to all the previous models with similar core structure nor explanations of what was built on top of the previous models were provided, which made it possible, in some cases, to have the same models published several times without an explicit intention to make new predictions about the roles of astrocytes in brain functions. Furthermore, only a few of the models are available online which makes it difficult to reproduce the simulation results and further develop the models. Thus, we would like to emphasize that only via reproducible research are we able to build better computational models for astrocytes, which truly advance science. Our study is the first to characterize in detail the biophysical and biochemical mechanisms that have been modeled for astrocytes.
计算神经科学领域一直高度专注于神经元功能的建模,很大程度上忽略了其他脑细胞,包括一种神经胶质细胞——星形胶质细胞。尽管对星形胶质细胞功能进行建模的历史较短,但我们很高兴看到目前已经开发出数百个模型来研究星形胶质细胞的作用,这些研究大多集中在钙动力学、同步性、信息传递和可塑性方面,不过也涉及血管事件、过度兴奋和内环境稳态。我们在此的目标是介绍星形胶质细胞计算建模的最新进展,以便更好地理解星形胶质细胞在大脑中的功能和动态。由于模型数量众多,我们重点关注了一百个模型,这些模型包含了对星形胶质细胞钙信号和动力学的生物物理描述。我们将这些模型分为四类:单个星形胶质细胞模型、星形胶质细胞网络模型、神经元 - 星形胶质细胞突触模型和神经元 - 星形胶质细胞网络模型,以便于在未来的建模项目中使用。我们根据构建模型所使用的早期模型以及星形胶质细胞模型中描述的生物实体类型对模型进行了表征。对模型的特征进行了比较和对比,以便更清楚地看出异同。我们发现,大多数模型基本上是在一小部分先前发表的模型基础上进行微小改动生成的。然而,既没有引用所有具有相似核心结构的先前模型,也没有解释在先前模型基础上构建了什么,这使得在某些情况下,相同的模型可能会多次发表,却并非有意对星形胶质细胞在脑功能中的作用做出新的预测。此外,只有少数模型可以在线获取,这使得难以重现模拟结果并进一步开发这些模型。因此,我们想强调的是,只有通过可重复研究,我们才能构建出更好的星形胶质细胞计算模型,从而真正推动科学发展。我们的研究首次详细表征了为星形胶质细胞建模的生物物理和生化机制。