Neural computation from retina to visual cortex

从视网膜到视觉皮层的神经计算

基本信息

批准号：
7187404
负责人：
MARKUS MEISTER
金额：
$ 24.34万
依托单位：
HARVARD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2003
资助国家：
美国
起止时间：
2003-03-01 至 2009-02-28
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7187404
关键词：
Advertisements Age Algorithms Animals Attention Biological Models Biology Brain Characteristics Code Computer information processing Computers Confidentiality Consent Data Data Set Devices Discrimination Documentation Electrodes Financial compensation Functional disorder Gender Goals Health Hour Human Image Individual Informed Consent Instruction Joints Knowledge Lateral Geniculate Body Lead Learning Link Localized Location Measurement Minority Modeling Movement Mus Nature Nervous system structure Neurons Numbers Oryctolagus cuniculus Output Perception Performance Play Population Prejudice Process Publications Purpose Recruitment Activity Research Research Ethics Committees Research Personnel Respondent Retina Retinal Risk Role Salamander Signal Transduction Simulate Source Staging Stimulus Structure Students Suggestion Testing Thalamic structure Time Training Vision Visual Visual Cortex Visual Perception Visual system structure Work Writing aged area striata computational neuroscience computer monitor day feeding ganglion cell human subject improved insight mathematical model member programs relating to nervous system research study response sex theories tv watching university student vision science visual performance visual process visual processing visual stimulus volunteer

项目摘要

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.

描述（由申请人提供）：这是计算神经科学协作研究的一项建议，在两个具有互补专业知识的研究小组（MEISTER）（MEISTER）（MEISTER）和统计和动力学过程（Fisher）之间。该对象是对早期视觉系统中信息处理的更好的定量理解，从视网膜到主要视觉皮层。具体而言，该项目将为视网膜中的神经细胞如何响应视觉输入而产生改进的数学模型。然后，这些模型将用于探索人类视觉表现的后续大脑回路中神经计算的性质。这项工作的结果将导致对视觉的更好理解，特别是区分视网膜的作用以及大脑在确定可以看出的内容方面发挥的作用。这种基本的理解最终将有助于识别视觉功能障碍。该研究将涉及实验与理论之间的密切相互作用。视觉反应将使用多电极阵列从sal或兔子的分离的视网膜的神经节细胞记录。将开发动态系统模型，以模拟观察到的视觉输入和神经输出之间的关系。当两个或多个模型看起来合理时，将出现针对新实验的建议，以应用其他测试。这些努力的目的是对视网膜如何编码各种刺激的紧凑数学描述。第二个目标是探索视觉系统后续电路中可能发生的计算。如何合并来自不同神经节细胞的信号以提取特定特征，例如对象的精确位置和轨迹？视网膜功能的模型将用于模拟尖峰序列，以供应侧向基因核和原代视皮层。这些响应的结构极大地限制了神经系统如何与它们进行计算，以及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感知表现进行比较，将区分早期视觉系统中计算的不同假设。