Biological constraints for parameter values of large-scale biologically plausible human Neuroscience models

This dataset contains 1.) time constants of excitatory and inhibitory neocortical neurons, collated from the NeuroElectro database, 2.) spike thresholds of excitatory and inhibitory neurons, collated from the NeuroElectro database, and 3.) posterior distributions of parameters of large-scale biologically plausible models of human Neuroscience data, estimated using likelihood-free inference (LFI) methods to fit these models to Magnetoencephalography (MEG) resting-state data (N=75) in Williams et al. (2023), NeuroImage paper 4.) Data used to perform Prior Predictive Checks in Williams et al. (2023), NeuroImage paper, 5.) Data used to perform Posterior Predictive Checks in Williams et al. (2023), NeuroImage paper. We used pooled versions of the time constants and spike threshold values in this dataset along with other biological constraints, to set prior distributions of parameters of large-scale biologically plausible models of human Neuroscience data. We then used LFI methods to estimate posterior distributions of these parameters from MEG resting-state data (N=75) - we have also shared the posterior distributions in this dataset. Examples of parameters for which we have shared posterior distributions include strengths of connections within and between excitatory and inhibitory neuronal populations, time constants of excitatory and inhibitory neuronal populations, and firing thresholds of excitatory and inhibitory neuronal populations. These posterior distributions could be used by other research groups to set prior distributions of parameters of their biologically plausible models, in both experimental and modeling studies.本数据集包含以下5类内容：1. 从NeuroElectro数据库（NeuroElectro Database）整理得到的兴奋性与抑制性新皮层神经元的时间常数；2. 同样源自该数据库的兴奋性与抑制性神经元的锋电位阈值；3. 基于Williams等人2023年发表于《神经图像（NeuroImage）》的研究论文，通过无似然推断（likelihood-free inference, LFI）方法，将大规模生物合理性人类神经科学数据模型拟合至75例静息态脑磁图（Magnetoencephalography, MEG）数据后，得到的模型参数后验分布；4. Williams等人2023年《神经图像（NeuroImage）》论文中用于执行先验预测检验（Prior Predictive Checks）的数据；5. 该论文中用于执行后验预测检验（Posterior Predictive Checks）的数据。本数据集整合了时间常数与锋电位阈值的汇总版本，并结合其他生物学约束条件，用于设定上述大规模生物合理性人类神经科学数据模型的参数先验分布。随后，研究团队通过无似然推断方法，从75例静息态脑磁图数据中估计得到这些参数的后验分布，相关后验分布也已收录至本数据集中。本次共享的参数后验分布示例包括：兴奋性与抑制性神经元群体内部及群体间的连接强度、兴奋性与抑制性神经元群体的时间常数，以及兴奋性与抑制性神经元群体的放电阈值。这些后验分布可供其他研究团队在实验与建模研究中，用于设定其自身生物合理性模型的参数先验分布。