A Computational Framework for Realistic Retina Modeling
A Computational Framework for Realistic Retina Modeling
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DOI：
10.1142/s0129065716500301
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发表时间：
2016-11-01
影响因子：
8
通讯作者：
Pelayo, Francisco
中科院分区：
文献类型：
--
作者：
Martinez-Canada, Pablo;Morillas, Christian;Pelayo, Francisco
对视网膜的计算机模拟已经导致了对其神经元活动和处理原理的生物物理学的有价值的见解。为了再现不同视觉处理途径的行为多样性，人们提出了大量的视网膜模型。虽然这些模型中的许多都有共同的计算阶段，但以前的努力更多地集中在适应特定的视网膜功能上，而不是将它们推广到特定模型之外。在这里，我们定义了一组计算视网膜微电路，可以用作不同视网膜机制建模的基本构建块。为了验证在不同的视网膜功能中可能重复发现相似的处理结构的假设，我们简单地通过组合这些计算的视网膜微电路实现了一系列视网膜模型。通过对已发表的电生理记录进行拟合，评估了视网膜模型捕捉神经行为的准确性，这些记录描述了视网膜中观察到的一些最著名的现象：适应平均光强度和时间对比度，以及差异运动敏感性。视网膜微电路是一个新的软件平台的一部分，用于从单细胞到大规模的高效计算视网膜建模。它包括一个与刺激性神经网络的接口，允许模拟神经节细胞的刺激性反应并与更高视觉区域的模型集成。
Computational simulations of the retina have led to valuable insights about the biophysics of its neuronal activity and processing principles. A great number of retina models have been proposed to reproduce the behavioral diversity of the different visual processing pathways. While many of these models share common computational stages, previous efforts have been more focused on fitting specific retina functions rather than generalizing them beyond a particular model. Here, we define a set of computational retinal microcircuits that can be used as basic building blocks for the modeling of different retina mechanisms. To validate the hypothesis that similar processing structures may be repeatedly found in different retina functions, we implemented a series of retina models simply by combining these computational retinal microcircuits. Accuracy of the retina models for capturing neural behavior was assessed by fitting published electrophysiological recordings that characterize some of the best-known phenomena observed in the retina: adaptation to the mean light intensity and temporal contrast, and differential motion sensitivity. The retinal microcircuits are part of a new software platform for efficient computational retina modeling from single-cell to large-scale levels. It includes an interface with spiking neural networks that allows simulation of the spiking response of ganglion cells and integration with models of higher visual areas.