ERG & VEP: FIELD TOPOGRAPHY & SOURCE IDENTIFICATION

诱发电位场的形态与反应有关 关于小刺激在视野中的位置。字段 地形是用一种同时刺激一种 大量的位置和从本地响应中提取的 单一响应信号。这类研究的技术一直是 开发和测试。 目标1：确定现场地形的亮度和图案 ERG及其组件。这些地形与 视网膜感受器和神经节细胞密度。主题间 将对差异进行研究，以建立临床试验的基线 评估。 目标2：开发一项客观的局部视网膜功能测试 目的是对患者进行筛查、诊断和监测。田野 情节将来自特定病因的患者(青光眼， 高眼压、黄斑病变)。这些情节将与眼底相比较。 图像确定视网膜ERG异常区域的准确位置 回应。ERG场将与心理物理场进行比较，以 评估其在检测局部病变方面的敏感性。 目标3：确定和表征来自 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：识别不同视觉区域的视觉诱发电位成分 大脑皮层。其来源的功能表征基于 非线性系统分析。 由于复杂的视觉诱发电位，视觉诱发电位的视野形态非常复杂。 皮质解剖学。对于每个刺激位置，相对贡献 对不同皮层来源的反应是不同的。一位校长 成分分析(SVD)将应用于以下地点的响应 视野中的可比偏心率，以确定子空间 由来自不同来源的组件跨越。的核心结构 非线性响应将被用来识别和表征 此子空间中的组件。各分量之间的不变性 受试者将接受测试，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.