Systematic Psychophysical Investigation of Visual Learning

视觉学习的系统心理物理学研究

• 批准号: 8058738
• 负责人: Takeo Watanabe
• 金额: $ 34.75万
• 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 2013-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8058738
• 关键词: Brain; Computer-Assisted Image Analysis; Data; Detection; Development; Diagnosis; Discrimination; Exposure to; Feedback; Health; 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

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（由申请人提供）：视觉学习（Visual learning， VL）被定义为由于训练或接触视觉特征而导致的表现增强，被认为是视觉和大脑处理可塑性的表现。由于不同的研究人员在进行VL研究时倾向于使用不同的参数集作为他们的刺激、任务等，这种做法使得很难在研究结果之间进行直接比较，也很难找到VL的一般规则。然而，还没有作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。在本提案中，我们旨在通过在同一框架内检查VL的各个方面来澄清VL的一般规则。在所有提出的实验中，我们将研究如何在训练特征值处和周围对特征值（例如，方向上的-45,00,450）的灵敏度作为训练的结果而改变（灵敏度调谐函数改变）。具体而言，我们将研究不同类型的训练（检测、辨别和暴露）、训练的时间过程和对受试者的反馈（响应反馈、块反馈和错误反馈）对灵敏度调谐函数形状的影响。迄今为止，在大多数研究中，三个基本因素（训练、时间过程和反馈）和不同子因素（如训练中的检测、歧视和暴露）对VL的影响都是独立研究的，彼此之间的关系并不明确。在本方案中，通过系统研究这些不同因素/子因素对灵敏度调谐函数变化的影响，我们将检验这些影响是否可能是由共同的潜在机制变化引起的，这些机制变化是由灵敏度调谐函数变化中的两种成分模式中的一种或两种模式反映的，性能在训练特征值附近和附近增加（中心增加），性能在更大范围的特征值内下降（宽范围减少）。公共卫生相关性：视觉学习被认为是视觉和大脑加工的可塑性。这项关于视觉学习的研究具有临床应用的潜力，有助于提高大脑疾病和病变的诊断和康复治疗，特别是与视觉功能有关的疾病和病变。