Systematic Psychophysical Investigation of Visual Learning

视觉学习的系统心理物理学研究

• 批准号: 7789450
• 负责人: Takeo Watanabe
• 金额: $ 36.2万
• 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 2013-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7789450
• 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; public health relevance; research study; response; sensitivity training; stem; visual learning

DESCRIPTION (provided by applicant): 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, 00, 450 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). PUBLIC HEALTH RELEVANCE: Visual learning is regarded as plasticity of visual and brain processing. The proposed research on visual learning has potential for clinical applications by contributing to scientific knowledge leading to improved diagnosis of, and rehabilitative therapies for, brain disorders and lesions, in particular those related to visual function.

描述(申请人提供)：视觉学习(VL)被定义为由于对视觉特征的训练或接触而导致的表现增强，并被视为视觉和大脑处理过程中可塑性的表现。由于不同的研究者倾向于使用不同的参数集作为他们进行语言学习研究的刺激、任务等，这种做法使得在研究结果之间进行直接比较和寻找语言学习的一般规律变得非常困难。然而，还没有做出强有力的努力来组织这些不同的结果，并确定任何可能的一般规则(S)。在本建议中，我们旨在通过在同一框架内研究VL的各个方面来澄清VL的一般规则。在所有建议的实验中，我们将检查训练特征值及其周围的特征值(例如，方向上的-45、00、450)的敏感度是如何作为训练的结果而改变的(敏感度调节函数改变)。具体地说，我们将考察不同类型的训练(检测、辨别和暴露)、训练的时间进程和对受试者的反馈(反应反馈、块反馈和错误反馈)对灵敏度调节函数形状的影响。到目前为止，在大多数研究中，三个基本因素(训练、时间进程和反馈)以及不同的子因素(如训练中的检测、辨别和暴露)对VL的影响都是独立研究的，没有明确的相互联系。在本方案中，通过系统研究这些不同的因素/子因素对灵敏度调节函数变化的影响，我们将测试这些影响是否可能是由灵敏度调节函数变化中的两个分量模式中的一个或两个所反映的共同的潜在机制变化、在训练的特征值处和接近训练的特征值处的性能提高(中心增加)以及在更大范围的特征值范围内的性能降低(大范围降低)所导致的。与公共健康相关：视觉学习被认为是视觉和大脑处理的可塑性。拟议的视觉学习研究具有临床应用的潜力，因为它促进了科学知识，从而改善了对大脑疾病和损伤的诊断和康复治疗，特别是与视觉功能有关的疾病和损伤。