APPLICATION OF PSYCHOPHYSICAL MODELS TO VISUAL DISORDERS

描述(由申请人提供)：该研究计划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，目前的重点仅限于青光眼。这项研究应用了一个定量的皮质神经池模型来分析青光眼引起的周界损害，目的是降低周界变异性，改善青光眼损害的临床指标之间的关系。具体目标有三个：1)优化青光眼患者对比敏感度视野检查(CSP)，使用定量神经模型进行视野检查。我们的神经模型将被用来根据四个因素来优化CSP参数和算法：筛选(识别缺陷)、测试-重测(识别进程)、表征(识别损伤模式)以及与结构测量的关系。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根据将视野敏感度与四种不同成像测试的结果相关联的模型预测进行分析。具体目的3)使用视野测量的定量神经模型，评估青光眼损害的周界和结构性指标内以及两者之间的长期波动与进展。将进行一项前瞻性的纵向研究，以测试关于CSP和标准临床测量(包括视野和成像)之间的关系的模型的预测。

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.