Neuronal mechanisms of selective attention in early vision

早期视觉选择性注意的神经机制

• 批准号: 8448250
• 负责人: Jose Manuel Alonso
• 金额: $ 9.8万
• 依托单位: STATE COLLEGE OF OPTOMETRY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-04-01 至 2015-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8448250
• 关键词: Aging-Related Process; Area; Attention; Attention Deficit Disorder; Autistic Disorder; Biological; Blindness; Brain; Cells; Cerebral cortex; Color; Contrast Sensitivity; Data; Drug Targeting; Elements; Frequencies; Future; Generations; Global Change; Goals; Health; Human; Image; Individual; Knowledge; Location; Measures; Methods; Modeling; Monkeys; Motion; Movement; Neighborhoods; Neurons; One-Step dentin bonding system; Patients; Peripheral; Phase; Play; Population; Property; Research; Role; Sampling; Space Perception; Specificity; Technology; Testing; Training; Traumatic Brain Injury; V1 neuron; Variant; Vision; Visual; Visual Perception; Visual attention; Width; area MT; area V1; attentional modulation; awake; cell type; clinically relevant; clinically significant; computerized data processing; distraction; excitatory neuron; extrastriate; inhibitory neuron; interest; neglect; new technology; novel; receptive field; response; selective attention; spatiotemporal; statistics; virtual; visual learning

ABSTRACT: Neuronal mechanisms of selective attention in early vision The mechanisms of selective attention have been intensively investigated over the past two decades. As a consequence, there is now a better understanding of the network of brain areas that are involved in visual attention and the responses of individual neurons to attentional shifts. Current models of attention are also one step closer to providing a general framework of attentional circuits that could have direct clinical significance. However, a major limitation of current models is the lack of cellular specificity. Most current models treat each cell within a given cortical area as if it was taken from a random sample of neurons that simply differ in the spatial location of their receptive fields and their selectivity for line orientation and direction of movement. The existence of different cell types with possible different functions is completely neglected. Neurons in different layers, neurons making local and long-range connections and, until very recently, inhibitory and excitatory neurons are all treated equally by models. The main goal of this proposal is to provide the biological data on cell selectivity that is needed to build more realistic and clinically relevant models of visual attention. We aim to characterize the different cell types that are involved in attentional networks in area V1. We also aim to identify populations of neurons with different functions in attention: those involved in enhancing vision at the focus of attention and those involved in suppressing distraction in surrounding areas. We will use state-of-the-art technology to densely sample individual neurons and populations of neurons through the cortical depths of area V1. Our novel technology allows us to study the properties of a given population of neurons for days or months, if necessary. We aim to take advantage of this technology to provide a detailed characterization of attention circuits at different cortical depths of area V1 and identify the task parameters that make attentional modulations strongest.

摘要：早期视力中选择性注意的神经元机制 在过去的二十年中，对选择性注意的机制进行了深入研究。作为 结果，现在对参与视觉的大脑区域网络有了更好的了解 注意和单个神经元对注意力转移的反应。当前的关注模型也是一种 更近于提供可能具有直接临床意义的注意电路的一般框架。 但是，当前模型的主要局限性是缺乏细胞特异性。大多数当前型号处理每个模型 在给定皮质区域内的细胞，好像是从一个随机的神经元样本中获取的，这些神经元在 其接收场的空间位置及其对线方向和运动方向的选择性。这 具有不同功能的不同细胞类型的存在被完全忽略。神经元不同 层，神经元建立局部和远程连接，直到最近，抑制性和兴奋性 神经元都通过模型平等处理。 该提案的主要目标是提供有关细胞选择性的生物学数据，以建立更多 现实和临床相关的视觉关注模型。我们的目的是表征不同的单元格 参与V1区域的注意网络。我们还旨在确定具有不同的神经元种群 注意力的功能：那些参与注意力重点和参与的人 抑制周围地区的分心。我们将使用最先进的技术进行密集采样 通过区域V1的皮质深度，神经元的单个神经元和群体。我们的新技术 允许我们在必要时研究给定神经元人群的特性几天或几个月。我们的目标 利用这项技术在不同的皮质上提供注意电路的详细表征 区域V1的深度并确定使注意调制最强的任务参数。