Neural Basis of Categories

类别的神经基础

• 批准号: 6622851
• 负责人: EARL K MILLER
• 金额: $ 36.1万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-04-01 至 2007-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6622851
• 关键词: Macaca mulatta; brain electrical activity; brain mapping; cell population study; computer data analysis; discrimination learning; electroencephalography; experience; form /pattern perception; hippocampus; histology; imagery; magnetic resonance imaging; neural information processing; neurons; neuropsychological tests; neuropsychology; neuroregulation; prefrontal lobe /cortex; sensory discrimination; statistics /biometry; stimulus /response; temporal lobe /cortex; visual perception

DESCRIPTION: (provided by applicant) While much is understood about neural mechanisms that analyze the physical attributes of the visual environment, little is known about the culmination of these analyses: the assignment of categories that give stimuli meaning. Our group has developed a novel paradigm for studying visual categories. A morphing system is used to blend prototypes of "cats" and "dogs" into single images, with each image having a certain proportion of cat vs. dog. This allows us to continuously vary shape and precisely define a category boundary. Monkeys are trained to judge whether two successively presented images are from the same category. We recently found a neural correlate of category information in the prefrontal cortex (PFC): single neurons that show a sharp change in neural activity at the boundary between categories but relatively little differences in activity within a category. We now plan to use this paradigm to address fundamental questions about category representations. Using multiple electrode techniques, we will simultaneously record neural activity from the PFC and the inferior temporal cortex (TIC), a visual cortical area thought to be important for visual categories. This will allow us to directly compare and contrast their neural properties and relative timing and thus afford a precise assessment of the respective contributions to category-based behaviors. We will also test for category-coding in the hippocampus, a region that shares a close anatomical and functional relationship with the TIC and PFC. To explore whether categorization and identification have common neural substrates, we will record PFC and ITC activity while monkeys switch back and forth between categorizing stimuli and identifying individual category members. To determine if category-coding neurons are highly specialized (like "face cells"), we will test them with a wide range of real world stimuli. To determine whether multiple category memberships are represented by separate neural ensembles or instead multiplexed onto single neurons, we will record while monkeys switch between categorizing a set of stimuli under two different category schemes. Because categorization is central to cognition, data from this project has the potential to impact on a wide range of behaviors and human disorders. The ability to quickly glean concepts and meaning from experience is disrupted in a variety of neuro psychiatric disorders such as autism and schizophrenia. By identifying brain structures important for these abilities, discerning their relative roles, and uncovering their neural mechanisms, we can open a path to drug and behavioral therapies designed to alleviate their dysfunction.

描述：（由申请人提供）虽然对分析视觉环境的物理属性的神经机制有很多了解，但 关于这些分析的结晶知之甚少：分配 具有刺激意义的类别。我们的小组开发了一个新颖的范式 用于研究视觉类别。变形系统用于混合原型 “猫”和“狗”的单位图像，每个图像都有一定的 猫与狗的比例。这使我们能够不断变化，并且 精确定义类别边界。猴子经过训练以判断是否两个 依次呈现的图像来自同一类别。我们最近发现了 前额叶皮层（PFC）中类别信息的神经相关性：单个 神经元在边界之间的神经活动发生急剧变化 类别，但类别中的活动差异相对较小。 我们现在计划使用此范式来解决基本问题 关于类别表示。使用多个电极 技术，我们将同时记录来自PFC和PFC的神经活动 下颞皮层（TIC），视觉皮质区域被认为很重要 用于视觉类别。这将使我们能够直接比较和对比 它们的神经特性和相对时机，因此得到了精确的 评估对基于类别的行为的各自贡献。我们将 还测试海马中的类别编码 与TIC和PFC的解剖学和功能关系。探索是否 分类和识别具有共同的神经底物，我们将记录 猴子在分类之间来回切换时PFC和ITC活动 刺激并确定各个类别成员。确定是否 类别编码神经元高度专业化（例如“面细胞”），我们将 用广泛的现实世界刺激进行测试。确定是否 多类成员资格由单独的神经合奏或 相反，多路复用到单个神经元，我们将在猴子开关时记录 在两个不同类别方案下对一组刺激进行分类之间。 由于分类对于认知至关重要，因此该项目的数据具有 影响广泛的行为和人类疾病的潜力。这 能够快速收集概念和经验意义的能力在 自闭症和精神分裂症等神经精神疾病的多种多样。经过 确定对这些能力重要的大脑结构 相对角色，并揭示其神经机制，我们可以打开通往 旨在减轻其功能障碍的药物和行为疗法。