Psychophysical analyses of perceptual learning

知觉学习的心理物理学分析

• 批准号: 42133-2013
• 负责人: Bennett, Patrick
• 金额: $ 3.42万
• 依托单位: McMaster University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=593117
• 关键词: Psychophysical; analyses; perceptual; learning

My research examines the factors that determine how we perceive visual patterns, and the way those factors are affected by perceptual learning. Perceptual learning refers to the fact that our ability to detect, discriminate, and identify patterns improves as a result of practice. Studying perceptual learning can provide insights into the general principles of learning and memory, and into the ways our brain adapts and changes as a function of experience. This knowledge could be used to devise ways of improving skills in applied areas requiring a high degree of visual skill (e.g., radiology and medical imaging), or perhaps to alleviate visual deficits associated with neural disorders such as amblyopia, brain injuries, or the effects of aging. Many experiments examine how perceptual learning improves our ability to perform simple discrimination tasks that require us to two patterns that differ on a single dimension (e.g., orientation). However, my research examines how learning alters our ability to identify complex patterns like faces. learning on identification, rather than discrimination, of spatially complex targets like textures and faces. One obvious reason for using more complex patterns is that they may provide better insights into the way learning affects our perception of naturalistic patterns, textures, and objects (as well as important classes of "artificial" patterns such as radiographic images). Also, investigating learning with progressively more complex stimuli and/or tasks is necessary to determine how theories of learning must be altered to account for learning in a variety of conditions. Therefore, the current proposal describes several projects that examine the similarities and differences between perceptual learning obtained with simple and complex stimuli and tasks to clarify the nature of the processes that underlie perception and how those processes are altered by practice.

我的研究考察了决定我们如何感知视觉模式的因素，以及这些因素受到感知学习影响的方式。感知学习指的是我们检测、区分和识别模式的能力在实践中得到提高。研究知觉学习可以让我们深入了解学习和记忆的一般原理，以及我们的大脑如何适应和改变经验。这些知识可用于设计提高需要高度视觉技能的应用领域（例如放射学和医学成像）的技能的方法，或者可能用于减轻与弱视、脑损伤或衰老影响等神经疾病相关的视觉缺陷。许多实验研究了感知学习如何提高我们执行简单区分任务的能力，这些任务需要我们在单一维度（例如，方向）上区分两个不同的模式。然而，我的研究考察了学习如何改变我们识别复杂模式（如面孔）的能力。学习识别，而不是辨别，空间复杂的目标，如纹理和面孔。使用更复杂模式的一个明显原因是，它们可以更好地了解学习如何影响我们对自然模式、纹理和物体的感知（以及重要的“人工”模式类别，如放射图像）。此外，研究越来越复杂的刺激和/或任务的学习是必要的，以确定学习理论必须如何改变，以解释各种条件下的学习。因此，目前的提案描述了几个项目，这些项目检查了通过简单和复杂的刺激和任务获得的感知学习之间的异同，以澄清构成感知的过程的本质，以及这些过程如何被实践改变。