Cortical Mechanisms of Visual Category Recognition and Learning

拟议研究的总结和相关性 人类有一种令人印象深刻的能力来识别感官刺激的类别成员。这种能力， 大脑的活动会被大脑疾病和病症破坏，如阿尔茨海默病，精神分裂症， 中风和注意力缺陷障碍是至关重要的，因为它使我们能够对刺激做出适当的反应， 我们在环境中遇到的事件。我们并不是天生就有一个类别库，比如 “桌子”和“椅子”，我们被预先编程识别。相反，我们学会了识别熟悉的 通过经验分类。我们最近的研究表明，后顶叶皮层（PPC）和 前额叶皮层（PFC）参与分类决策。我们记录了前额叶皮层和前额叶皮层的神经元 在执行视觉运动分类任务期间。这些记录显示， 区域根据它们学习到的类别成员关系对刺激进行鲁棒编码，这表明两个区域 参与计算和表示关于视觉刺激的抽象分类信息。我们也 显示PPC中的活性与分类决策有因果关系，使用可逆失活。这 该项目使用新的大脑记录技术来监测大脑中大量神经元的活动。 外侧顶内区、额叶视野和上级丘。这 将使我们对这三个区域的神经元之间的相互作用有一个机械的理解， 能够进行将视觉特征编码转换为分类决策的计算。这项工作还将 确定多种行为功能是如何由这个大脑网络介导的，包括眼球运动， 空间注意力，以及评估每个大脑区域对分类决策的因果意义。 虽然我们对大脑如何处理视觉特征（如颜色、方向和方向）已经有了很多了解， 运动），较少了解大脑如何学习和代表的意义，或类别，刺激。一 更好地理解视觉分类对于解决一些脑部疾病至关重要， 条件（如中风，阿尔茨海默病，注意力缺陷障碍，精神分裂症和中风），离开 需要视觉学习、识别和/或评估和响应的日常任务受损的患者 与感官信息相匹配该项目的长期目标是指导下一代 通过帮助发展对这些大脑疾病和紊乱的详细了解， 学习记忆和认知的大脑机制这些研究也与 理解和解决学习障碍，如注意力缺陷障碍和诵读困难， 相当一部分学龄儿童和年轻人。因此，详细了解基本的 分类决策和注意力的大脑机制可能会对原因提供重要的见解， 对涉及这些认知和感知能力的疾病的潜在治疗。

Summary and Relevance of Proposed Research Humans have an impressive capacity to recognize the category membership of sensory stimuli. This ability, which is disrupted by a brain-based diseases and conditions such as Alzheimer’s disease, schizophrenia, stroke, and attention deficit disorder, is critical because it allows us to respond appropriately to the stimuli and events that we encounter in the environment. We are not born with an innate library of categories, such as “tables” and “chairs”, which we are preprogrammed to recognize. Instead, we learn to recognize familiar categories through experience. Our recent work has shown that both the posterior parietal cortex (PPC) and prefrontal cortex (PFC) are involved in categorical decisions. We recorded from neurons in PPC and PFC during performance of visual motion categorization tasks. These recordings revealed that neurons in both areas robustly encoded stimuli according to their learned category membership, suggesting that both regions are involved in computing and representing abstract categorical information about visual stimuli. We also showed that activity in PPC is causally related to categorical decisions, using reversible inactivation. This project uses novel brain recording techniques to monitor the activity of large neuronal populations of neurons in the lateral intraparietal area, frontal eye field, and superior colliculus during visual categorical decisions. This will allow us to gain a mechanistic understanding of how interactions between neurons in these three regions enable computations which transform visual feature encoding into categorical decisions. This work will also determine how multiple behavioral functions are mediated by this brain network, including eye movements and spatial attention, as well assess the causal significance of each brain area to categorical decisions. While much is known about how the brain processes visual features (such as color, orientation, and direction of motion), less is known about how the brain learns and represents the meaning, or category, of stimuli. A greater understanding of visual categorization is critical for addressing a number of brain diseases and conditions (e.g. stroke, Alzheimer’s disease, attention deficit disorder, schizophrenia, and stroke) that leave patients impaired in everyday tasks that require visual learning, recognition and/or evaluating and responding appropriately to sensory information. The long-term goal of this project is to guide the next generation of treatments for these brain-based diseases and disorders by helping to develop a detailed understanding of the brain mechanisms that underlie learning, memory and recognition. These studies also have relevance for understanding and addressing learning disabilities, such as attention deficit disorder and dyslexia, which affect a substantial fraction of school age children and young adults. Thus, a detailed understanding of the basic brain mechanisms of categorical decisions and attention will likely give important insights into the causes and potential treatments for disorders involving these cognitive and perceptual abilities.