Complex Pattern Detection by the Retina

视网膜的复杂模式检测

• 批准号: 7498453
• 负责人: MICHAEL J BERRY
• 金额: $ 37.57万
• 依托单位: PRINCETON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-30 至 2012-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7498453
• 关键词: Brain; Collaborations; Complex; Computer Simulation; Data; Detection; Development; Electrodes; Fire - disasters; Goals; Image; Knowledge; Learning; Motion; Neurosciences; Noise; Nonlinear Dynamics; Pattern; Periodicity; Pharmacology; Population; Process; Property; Range; Retina; Retinal; Retinal Ganglion Cells; Stimulus; Testing; Thinking; Vision; Visual; cell type; design; ganglion cell; interest; neural circuit; relating to nervous system; research study; response; retinal prosthesis; visual stimulus

DESCRIPTION (provided by applicant): The broad goals of this project are to understand the scope and sophistication of retinal processing. This project builds on preliminary data showing that the retina can quickly learn simple patterns in the visual stimulus, such as a temporal periodicity or a smooth motion trajectory, so that a subset of ganglion cells fires selectively after a violation of the predicted pattern. Such cognitively loaded phenomena are typically thought to arise only in the cortex, but observing them in the retina both enhances our appreciation of the computational capabilities of neural circuits and also allows us to explore the mechanisms responsible, a task that often cannot be carried out in more central neural circuits. The Specific Aims are: 1) exploring the properties of retinal pattern detection with multi-electrode array experiments; 2) studying the mechanisms of temporal pattern detection using designed stimuli, pharmacology, and computational models; 3) studying the properties of and mechanisms behind the retina's ability to detect motion discontinuities. A detailed knowledge of how the population of retinal ganglion cells represents the visual world is of fundamental interest to neuroscience and is also important for guiding the development of a retinal prosthesis to restore vision successfully.

描述（由申请人提供）：这个项目的主要目标是了解视网膜加工的范围和复杂性。该项目建立在初步数据的基础上，这些数据显示视网膜可以快速学习视觉刺激中的简单模式，例如时间周期性或平滑运动轨迹，因此神经节细胞子集在违反预测模式后选择性地放电。这种认知负载现象通常被认为只出现在皮层中，但在视网膜中观察它们既增强了我们对神经回路计算能力的欣赏，也使我们能够探索相关机制，这一任务通常无法在更多的中枢神经回路中完成。