Guo Tianruo, Tsai David, Morley John W, Suaning Gregg J, Kameneva Tatiana, Lovell Nigel H, Dokos Socrates
Graduate School of Biomedical Engineering, UNSW Australia, Sydney, NSW 2052, Australia.
J Neural Eng. 2016 Apr;13(2):025005. doi: 10.1088/1741-2560/13/2/025005. Epub 2016 Feb 23.
Retinal ganglion cells (RGCs) demonstrate a large range of variation in their ionic channel properties and morphologies. Cell-specific properties are responsible for the unique way RGCs process synaptic inputs, as well as artificial electrical signals such as that from a visual prosthesis. A cell-specific computational modelling approach allows us to examine the functional significance of regional membrane channel expression and cell morphology.
In this study, an existing RGC ionic model was extended by including a hyperpolarization activated non-selective cationic current as well as a T-type calcium current identified in recent experimental findings. Biophysically-defined model parameters were simultaneously optimized against multiple experimental recordings from ON and OFF RGCs.
With well-defined cell-specific model parameters and the incorporation of detailed cell morphologies, these models were able to closely reconstruct and predict ON and OFF RGC response properties recorded experimentally.
The resulting models were used to study the contribution of different ion channel properties and spatial structure of neurons to RGC activation. The techniques of this study are generally applicable to other excitable cell models, increasing the utility of theoretical models in accurately predicting the response of real biological neurons.
视网膜神经节细胞(RGCs)在离子通道特性和形态上表现出很大的差异。细胞特异性特性决定了RGCs处理突触输入以及人工电信号(如来自视觉假体的信号)的独特方式。一种细胞特异性计算建模方法使我们能够研究区域膜通道表达和细胞形态的功能意义。
在本研究中,通过纳入超极化激活的非选择性阳离子电流以及最近实验发现中确定的T型钙电流,扩展了现有的RGC离子模型。针对来自ON和OFF RGCs的多个实验记录,同时优化了生物物理定义的模型参数。
通过定义明确的细胞特异性模型参数并纳入详细的细胞形态,这些模型能够紧密重建并预测实验记录的ON和OFF RGC反应特性。
所得模型用于研究不同离子通道特性和神经元空间结构对RGC激活的贡献。本研究的技术通常适用于其他可兴奋细胞模型,提高了理论模型在准确预测真实生物神经元反应方面的效用。