Neural computation from retina to visual cortex

描述(由申请人提供)：这是两个在视觉系统生物学(Meister)和统计和动力学过程理论(Fisher)方面具有互补专业知识的研究小组在计算神经科学方面的合作研究提案。目的是对早期视觉系统从视网膜到初级视觉皮质的信息处理有更好的量化理解。具体地说，该项目将改进视网膜神经细胞对视觉输入的反应的数学模型。然后，这些模型将被用来探索构成人类视觉表现的后续大脑回路中神经计算的本质。这项工作的结果将导致对视觉的更好理解，特别是区分视网膜和大脑的后续阶段在决定什么可以被感知方面扮演着什么角色。这种基本的理解最终将有助于对视觉功能障碍的认识。 这项研究将涉及实验和理论之间的密切互动。使用多电极阵列，将从火蜥蜴或兔子的视网膜神经节细胞记录视觉反应。动态系统模型将被开发来模拟观察到的视觉输入和神经输出之间的关系。当两个或更多的模型看起来可信时，就会出现新的实验建议，以进行更多的测试。这些努力的目标是对视网膜如何编码各种刺激进行紧凑的数学描述。第二个目标是探索在视觉系统的后续回路中可能发生的计算。如何组合来自不同神经节细胞的信号来提取特定特征，如物体的准确位置和轨迹？视网膜功能模型将被用来模拟供给外侧膝状体和初级视觉皮质的棘波序列。这些反应的结构极大地限制了神经系统可以用它们计算什么以及如何计算，而组合视网膜输出信号的不同算法预测了非常不同的性能。与动物和人类的实际知觉表现进行比较，可以区分早期视觉系统中用于计算的不同假设。

DESCRIPTION (provided by applicant): This is a proposal for collaborative research in computational neuroscience, between two research groups having complementary expertise in the biology of the visual system (Meister) and the theory of statistical and dynamical processes (Fisher). The object is a better quantitative understanding of information processing in the early visual system, from retina to primary visual cortex. Specifically, the project will produce improved mathematical models for how nerve cells in the retina respond to visual input. Then those models will be used to explore the nature of neural computation in subsequent brain circuits that underlie human visual performance. Results from this work will lead to a better understanding of vision, specifically to distinguish what role the retina and subsequent stages of the brain play in determining what can be perceived. This basic understanding will eventually aid in the recognition of visual dysfunctions. The research will involve close interplay between experiment and theory. Visual responses will be recorded from ganglion cells of the isolated retina of salamander or rabbit, using a multi-electrode array. Dynamical systems models will be developed to emulate the relationship between the observed visual input and neural output. When two or more models appear plausible, suggestions for new experiments will emerge to apply additional tests. The goal of these efforts is a compact mathematical description of how the retina encodes a wide variety of stimuli. A second goal is to explore what computations might occur in subsequent circuits of the visual system. How can signals from different ganglion cells be combined to extract specific features, such as the precise location and trajectory of an object? The models of retinal function will be used to simulate spike trains that feed the lateral geniculate nucleus and primary visual cortex. The structure of those responses greatly constrains what and how the nervous system can compute with them, and different algorithms for combining retinal output signals predict very different performance. Comparison with the actual perceptual performance of animals and humans will distinguish between different hypotheses for computation in the early visual system.