Multiscale Modeling of the Neural Subcircuits in the Outer-Plexiform Layer of the Retina

视网膜是中枢神经系统的一部分，是研究大脑信息处理的理想区域。它是可访问的，有很好的记录，并由跨越临床、实验和理论科学的研究人员研究。视网膜的图像处理始于外丛状层，在那里双极细胞、水平细胞和光感受器细胞相互作用。这项研究的目的是对外丛层子电路进行详细的数学建模，捕捉两个空间尺度上的时空动力学：单个突触的尺度和感受野的尺度。电生理、解剖学和分子生物学数据的可获得性为开发复杂的多尺度系统模型提供了难得的机会。数学建模将被用来发现各种电路元件的功能影响，就像实验者对选择性药物所做的那样，只是并不是所有需要的药物都实际存在。一个主要的目标是探索两种相互竞争的假说来解释在视网膜外丛状层实验中观察到的突触反馈效应。具体地说，该项目将调查锥体光感受器突触中的反馈效应是由电机制还是化学机制驱动，还是两者兼而有之。从这个项目中对视网膜回路的理解的新见解将影响健康和医学方面的研究，包括生物医学工程、图像处理、视觉心理物理学和药理学。该项目产生的建模和计算技术将为应用数学和工程中的其他问题领域提供有效和创新的方法。

The retina is part of the central nervous system and an ideal region to study information processing in the brain. It is accessible, well documented, and studied by researchers spanning the clinical, experimental, and theoretical sciences. Image processing in the retina begins in the outer plexiform layer, where bipolar, horizontal, and photoreceptor cells interact. The goal of this research is to mathematically model, in detail, the subcircuits of the outer plexiform layer, capturing spatio-temporal dynamics on two spatial scales: the scale of an individual synapse and the scale of the receptive field. The availability of electrophysiological, anatomical, and molecular biological data provides a rare opportunity to develop a complex multiscale model for the system. Mathematical modeling will be used to discover the functional impact of various circuitry elements, much the way an experimentalist does with selective pharmacological agents, except that not all the agents that are needed actually exist. A primary objective is to explore two competing hypotheses for explaining synaptic feedback effects that are observed experimentally in the outer plexiform layer of the retina. Specifically, the project will investigate if feedback effects in the cone photoreceptor's synapse are driven by electrical or chemical mechanisms, or both. New insights into the understanding of retinal circuitry from this project will impact research in health and medicine, including biomedical engineering, image processing, visual psychophysics, and pharmacology. The modeling and computational techniques resulting from this project will provide efficient and innovative approaches for other problem areas in applied mathematics and engineering.