COLLABORATIVE RESEARCH: Categorization and Expertise in Human Visual Cognition II

合作研究：人类视觉认知 II 的分类和专业知识

• 批准号: 0094491
• 负责人: Michael Tarr
• 金额: $ 36.37万
• 依托单位: Brown University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-05-01 至 2005-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0094491&HistoricalAwards=false
• 关键词: COLLABORATIVE; RESEARCH; Categorization; Expertise; Human

Visual object recognition occurs at different levels of abstraction ranging from categorical levels, e.g., "dog," to the more specific individual level, e.g., "my English hound." Moreover, we can develop "expertise" at one of these levels for a given category; for instance, bird watchers are experts at the species level. This research will continue to investigate the roles of level of categorization and perceptual expertise in the development of cognitive and neural mechanisms selective for object categories (such as faces or birds). Because different methods offer different strengths and weaknesses, this research will involve converging evidence, including behavioral psychophysics, functional brain imaging (fMRI), and event related potentials (ERPs) in normal humans, as well as extending these techniques to brain-injured individuals. The research program is divided into four sections addressing different questions:1) How do people become perceptual experts? A first set of experiments will manipulate whether subjects rely on their own observations or require feedback and supervision. A second set of studies will examine whether non-visual knowledge about objects contributes to the learning process and affects the organization of category-specific areas. Other experiments will test the plasticity of the brain regions, which support object recognition, investigating whether damage to one area can be compensated for by reorganization of other areas. 2) What are the computational roles of different brain areas within the network that mediates expertise with visually-similar objects? Experiments using a combination of fMRI, ERP, and behavioral measures will investigate how different category-selective brain areas support identification at the categorical, subordinate, and individual levels. 3) What is the capacity of perceptual expertise? Experiments will test whether one can become an expert with many different classes of objects (e.g., birds, dogs, cars, faces, flowers, etc.), as well as whether there is interference when objects from different expertise domains are processed at the same time. 4) Can perceptual expertise be acquired more easily with some object geometries? In particular, adaptive pressures for accurate face recognition may have "biased" the system to prefer face-like configurations. By manipulating the visual structure of stimulus objects, behavioral and fMRI experiments will investigate the geometric constraints on the acquisition of expertise.Overall, these experiments should help us to better understand the nature of visual object recognition, elucidating how a single system can support the wide range of recognition tasks we are able to perform. The implications of these findings vary from possible protocols for the rehabilitation of brain-injured individuals to the better education of learning-impaired children (e.g., as in autism) to the development of more effective and robust machine vision systems for face and object recognition.

视觉对象识别发生在不同的抽象级别，从分类级别，例如，“狗”，到更具体的个体水平，例如，“我的英国猎犬此外，我们还可以为某一特定类别培养其中一个层次的“专业知识”;例如，鸟类观察者是物种层次的专家。 本研究将继续探讨分类水平和知觉专业知识在对象类别（如面孔或鸟类）选择性认知和神经机制发展中的作用。 由于不同的方法提供了不同的优势和劣势，这项研究将涉及汇聚证据，包括行为心理物理学，功能性脑成像（fMRI）和正常人的事件相关电位（ERP），以及将这些技术扩展到脑损伤个体。 该研究计划分为四个部分，解决不同的问题：1）人们如何成为感知专家？ 第一组实验将操纵受试者是依赖自己的观察还是需要反馈和监督。 第二组研究将检查有关物体的非视觉知识是否有助于学习过程，并影响特定类别区域的组织。 其他实验将测试支持物体识别的大脑区域的可塑性，研究一个区域的损伤是否可以通过重组其他区域来补偿。2)在这个网络中，不同的大脑区域在协调视觉相似物体的专业知识方面扮演着什么样的计算角色？ 使用fMRI，ERP和行为测量相结合的实验将研究不同的类别选择性脑区如何支持分类，从属和个体水平的识别。3)什么是知觉专门知识的能力？ 实验将测试一个人是否可以成为许多不同类别对象的专家（例如，鸟、狗、汽车、脸、花等），以及当同时处理来自不同专业领域的对象时是否存在干扰。4)对于某些物体的几何形状，是否可以更容易地获得知觉专业知识？ 特别是，准确的面部识别的自适应压力可能会使系统“偏向”偏好面部配置。 通过操纵刺激物的视觉结构，行为和功能磁共振成像实验将研究获得专业知识的几何约束。总的来说，这些实验应该帮助我们更好地理解视觉物体识别的本质，阐明单个系统如何支持我们能够执行的广泛识别任务。这些发现的意义各不相同，从脑损伤个体的康复到学习障碍儿童的更好教育（例如，如在自闭症中）到开发用于面部和物体识别的更有效和鲁棒的机器视觉系统。