APPLICATION OF PSYCHOPHYSICAL MODELS TO VISUAL DISORDERS

描述（由申请人提供）：本研究项目的长期功能是将视觉缺陷与疾病过程的潜在细胞病理生理学联系起来，目前仅关注青光眼。拟议的研究应用定量皮质神经池模型来分析青光眼引起的周边损害，目的是减少周边变异性和改善青光眼损害的临床措施之间的关系。有三个具体目标：具体目的1）使用视野检查的定量神经模型，优化青光眼患者的对比敏感度视野检查（CSP）。我们的神经模型将用于优化CSP参数和算法的四个因素：筛选（识别缺陷），测试-重测（识别进展），表征（识别模式的损坏），和结构措施的关系。具体目的2）使用定量神经模型分析英国青光眼治疗研究（UKGTS）数据中常规自动视野检查（CAP）和成像测量之间的关系。一个大型的前瞻性纵向数据集将进行分析的模型预测相关的周边灵敏度与结果从四个不同的成像测试。具体目的3）使用视野定量神经模型评估昏迷性损害的视野和结构测量内和之间的长期波动与进展。将进行一项前瞻性纵向研究，以测试CSP与标准临床测量（包括视野测量和成像）之间关系的模型预测。 公共卫生相关性：视野计测量整个视野的视觉功能，并常规用于诊断和随访青光眼患者，青光眼是美国和全球失明的主要原因之一。拟议的研究将产生对视野检查的更深入的科学理解，并将导致在临床研究，治疗试验和个体患者护理中使用视野检查的改进方法。考虑到青光眼患者数量庞大，潜在的公共卫生益处是巨大的。

DESCRIPTION (provided by applicant): The long-term function of this research program is to relate visual deficits to the underlying cellular pathophysiology of disease processes, with the current focus exclusively on glaucoma. The proposed research applies a quantitative cortical neural pooling model to analysis of perimetric damage produced by glaucoma, with the goals of reducing perimetric variability and improving relations between clinical measures of glaucomatous damage. There are three Specific Aims: Specific Aim 1) To optimize contrast sensitivity perimetry (CSP) for clinical use in patients with glaucoma, using a quantitative neural model for perimetry. Our neural model will be used to optimize CSP parameters and algorithms in terms of four factors: screening (identify defects), test-retest (identify progression), characterization (identify pattern of damage), and relations with structural measures. Specific Aim 2) To analyze relations between conventional automated perimetry (CAP) and imaging measures in data from the United Kingdom Glaucoma Treatment Study (UKGTS), using a quantitative neural model. A large prospective longitudinal dataset will be analyzed in terms of model predictions relating perimetric sensitivity with results from four different imaging tests. Specific Aim 3) To assess long-term fluctuation versus progression within and between perimetric and structural measures of glaucomatous damage, using a quantitative neural model for perimetry. A prospective longitudinal study will be conducted to test predictions of the model concerning relations between CSP and standard clinical measures, both perimetric and imaging. PUBLIC HEALTH RELEVANCE: Perimetry measures visual function across the visual field, and is used routinely for diagnosing and following patients with glaucoma, one of the leading causes of blindness in the US and globally. The proposed research will produce a deeper scientific understanding of perimetry, and will lead to improved methods for using perimetry in clinical studies, treatment trials and care of individual patients. The potential public health benefit is substantial, given the large number of patients with glaucoma.