ERG & VEP: FIELD TOPOGRAPHY & SOURCE IDENTIFICATION

诱发电位的场地形图是反应的依赖 一个小刺激在视野中的位置。 领域 拓扑结构是用同时刺激 大量的位置和提取的本地响应， 单响应信号。 这种研究的技术已经 开发和测试。 目标1：确定亮度和图案的场形貌 ERG及其组成部分。 这些地形与 视网膜受体和神经节细胞的密度。 主体间 将对差异进行研究，以建立临床 评价 目标2：开发一种针对糖尿病患者的局部视网膜功能的客观测试方法。 筛查、诊断和监测患者的目的。 领域 图将从具有特定病因的患者（青光眼， 高眼压、黄斑病变）。 图将与眼底进行比较 图像以确定ERG异常视网膜区域的准确位置 应答 ERG场将与心理物理场进行比较， 评估它们在检测局部病理变化方面的灵敏度。 目标3：识别和表征视网膜电图组分， 不同的视网膜层 这将通过不同的模式来实现， 模式模拟和非线性系统分析技术。 目标4：识别来自不同视觉区域的VEP成分 皮层 根据以下方面对其来源进行功能性描述： 非线性系统分析 由于VEP的复杂性， 皮质解剖学 对于每个刺激位置， 对不同皮层来源的反应是不同的。 一个主要 成分分析（SVD）将应用于以下位置的响应： 在视野中的偏心率，以确定子空间 由不同来源的组件组成。 的内核结构 非线性响应将用于识别和表征 这个子空间里的组件 之间的分量的不变性 将对受试者进行测试以确认分解情况。

The field topography of evoked potentials is the dependent of the responses on the location of a small stimulus in the visual field. Field topographies are derived with a method of simultaneous stimulation of a large number of locations and extraction of the local responses from a single response signal. The techniques for such studies have been developed and tested. Goal 1: Determination of the field topography of the luminance and pattern ERGs and their components. Correlation of these topographies with densities of retinal receptors and ganglion cells. Inter-subject differences will be studied to establish a baseline for a clinical evaluation. Goal 2: Development of an objective test of local retinal function for the purpose of screening, diagnosis and monitoring of patients. The field plots will be derived from patients with specific etiologies (glaucoma, ocular hypertension, maculopathy). The plots will be compared with fundus images to establish the exact location of retinal areas with abnormal ERG responses. ERG fields will be compared with psychophysical fields to assess their sensitivity in the detection of local pathological changes. Goal 3: Identification and characterization of ERG components from different retinal layers. This will be achieved with different modes of pattern stimulation and techniques of nonlinear systems analysis. Goal 4: Identification of VEP components from different visual areas of cortex. Functional characterization of their sources on the basis of nonlinear systems analysis. The field topography of the VEP is very complex due to the convoluted cortical anatomy. For each stimulus location, the relative contributions to the response from various cortical sources are different. A principal component analysis (SVD) will be applied to the responses at locations of comparable eccentricity in the visual field, to determine the subspace spanned by the components from different sources. The kernel structure of the nonlinear responses will be used to identify and characterize the components within this subspace. The invariance of the components between subjects will be tested to confirm the decomposition.