Systematic Psychophysical Investigation of Visual Learning

视觉学习的系统心理物理学研究

• 批准号: 8249468
• 负责人: Takeo Watanabe
• 金额: $ 4.75万
• 依托单位: BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-04-01 至 2012-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8249468
• 关键词: Brain; Computer-Assisted Image Analysis; Data; Detection; Development; Diagnosis; Discrimination; Exposure to; Feedback; Investigation; Knowledge; Lead; Lesion; Measures; Modeling; Motion; Neurons; Pattern; Performance; Process; Psychophysiology; Rehabilitation therapy; Research; Research Personnel; Shapes; Staging; Stimulus; Testing; Time; Training; Vision; Visual; base; brain disorder therapy; clinical application; improved; research study; response; sensitivity training; stem; visual learning

Visual learning (VL) is defined as performance enhancement as a result of training on or exposure to a visual feature and is regarded as manifestation of plasticity in visual and brain processing. Since different researchers have tended to use different sets of parameters as their stimuli, tasks, etc in conducting their VL studies, this practice has made it very difficult to make direct comparisons between the findings and to find, if any, general rules of VL. Nevertheless, there have not been strong efforts to organize these divergent results and to identify any possible general rule(s). In the present proposal, we aim to clarify general rules of VL by examining various aspects of VL within the same framework. In all the proposed experiments, we will examine how sensitivity to feature values (e.g., -45, 0¿, 45¿ in orientation) at and around a trained feature value is changed as a result of training (sensitivity tuning function changes). Specifically, we will examine effects of different types of training (detection, discrimination and exposure), time-course of training and feedback to subjects (response feedback, block feedback and incorrect feedback) on sensitivity tuning function shapes. To date, in most studies, effects of the three fundamental factors (training, time-course and feedback) and different sub-factors (e.g., detection, discrimination and exposure in training) on VL have been studied independently without clearly relating to each other. In the current proposal, by systematic investigations of effects of these different factors/ sub-factors on sensitivity tuning function changes, we will test whether these effects may result from common underlying mechanism changes that are reflected by one or both of two component patterns in sensitivity tuning function changes, performance increase at and close to the trained feature value (center increase) and performance decrease within a wider range of feature values (wide-range decrease).

视觉学习（VL）被定义为性能增强， 训练或暴露于视觉特征，被认为是可塑性的表现 在视觉和大脑处理过程中。由于不同的研究人员倾向于使用不同的 参数集作为他们的刺激，任务等，在进行他们的VL研究，这种做法 这使得很难直接比较这些发现， 任何VL的一般规则。尽管如此，还没有作出强有力的努力， 这些不同的结果，并确定任何可能的一般规则。本 建议，我们的目的是通过审查VL的各个方面，澄清VL的一般规则 在同一个框架内。在所有提出的实验中，我们将研究如何 对特征值的敏感性（例如，-45，0 <$，45 <$定向）在一个受过训练的 特征值作为训练的结果而改变（灵敏度调节函数改变）。 具体来说，我们将研究不同类型的培训（检测， 歧视和暴露）、培训的时间进程和对受试者的反馈 （响应反馈、阻塞反馈和错误反馈） 函数形状。到目前为止，在大多数研究中，三个基本因素的影响 （培训、时间进程和反馈）和不同的子因素（例如，检测， 歧视和培训中的暴露）对VL的独立研究， 显然是相互关联的。在目前的建议中，通过系统调查， 这些不同因素/子因素对灵敏度调谐函数变化的影响，我们 将测试这些影响是否可能是由共同的潜在机制变化引起的 由灵敏度调谐函数中的两个分量图案中的一个或两个反射 变化，性能在训练特征值处或接近训练特征值（中心 增加）和性能降低 减少）。