Mechanisms of attentional control: Structure and dynamics from simultaneous EEG-fMRI and machine learning

注意力控制机制：同步脑电图-功能磁共振成像和机器学习的结构和动力学

• 批准号: 10115818
• 负责人: MINGZHOU DING
• 金额: $ 53.03万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-06-08 至 2023-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10115818
• 关键词: Anatomy; Attention; Attention Deficit Disorder; Attentional deficit; Brain; Code; Color; Cues; Data; Dementia; Discrimination; Dorsal; Etiology; Event; Face; Functional Magnetic Resonance Imaging; Graph; Human; Inferior; Knowledge; Location; Machine Learning; Modeling; Motion; Neurosciences; Parietal Lobe; Pattern; Perception; Physiological; Prefrontal Cortex; Process; Property; Research; Schizophrenia; Sensory; Specific qualifier value; Specificity; Stimulus; Structure; Testing; Time; Visual; Visual Cortex; Work; attentional control; autism spectrum disorder; base; cognitive ability; data integration; experimental study; extrastriate visual cortex; frontal lobe; indexing; innovation; mental function; neuropsychiatric disorder; predictive modeling; relating to nervous system; selective attention; sensory cortex; signal processing; theories; tool

PROJECT SUMMARY/ABSTRACT Selective attention is an essential cognitive ability that permits us to effectively process and act upon relevant information while ignoring distracting events. A network involving frontal and parietal cortex for top-down attentional control, referred to as the Dorsal Attention Network (DAN), is active during both spatial and non- spatial (feature-based) attention. However, we know very little about the fine structure of attentional control activity in the DAN, how this structure changes to represent different to-be-attended stimulus features, how the connectivity within the DAN, and between the DAN and sensory cortex shifts when attending different features, or how these top-down processes and their influence in sensory cortex unfold over time. This gap in our knowledge is a critical problem for our models and theories of attention, and because attentional deficits are involved in a wide variety of neuropsychiatric disorders including autism, attention deficit disorder, dementia, and schizophrenia. The working model guiding this research is that top-down attentional control, based on different to-be-attended stimulus attributes, is guided by a smaller-scale neural fine structure within the DAN and prefrontal cortex that makes specific connections with specialized areas of visual cortex coding the attended attributes. Moreover, the time course of activity within the DAN in relation to that in sensory cortex follows a top-down cascading model, being earliest in frontal, then parietal cortex, and finally sensory cortex for preparatory, voluntary, attentional control. To identify the functional networks for attentional control for different forms of attention, and to define their time courses, this project uses innovative simultaneous recording of electroencephalographic (EEG) and functional magnetic resonance imaging (fMRI) data. Advanced signal processing and modeling, including multivariate pattern analysis (MVPA), graph theoretic connectivity analysis, and Granger causality analysis will be used to reveal the fine functional anatomy and time course of attentional control and selection. The project includes three experiments that vary the to-be-attended stimulus attributes from spatial location to stimulus features (color and motion), and pursues three aims. Aim 1 is to reveal the fine structure of top-down preparatory attentional control for different to-be-attended stimulus features. Aim 2 is to elucidate the specific connectivity between fine structures for preparatory attentional control in the DAN and their target sensory structures in sensory cortex. Aim 3 is to reveal the time course of top-down attentional control for different to-be-attended stimulus attributes.

项目摘要/摘要 选择性关注是一种基本的认知能力，允许我们有效地处理并采取相关的行动 信息同时忽略分心的事件。涉及自上而下的额叶和顶叶皮层的网络 注意控制（称为背注意网络（DAN））在空间和非 - 空间（基于特征）的注意力。但是，我们对注意力控制的良好结构知之甚少 在DAN中的活动，该结构如何变化以表示不同的刺激特征 DAN内的连接性以及DAN和感觉皮质之间的连通性在参加不同的功能时会移动 或这些自上而下的过程及其在感觉皮层中的影响如何随着时间的流逝而展开。我们的差距 知识对于我们的模型和关注理论是一个关键问题，因为注意力缺陷是 参与各种神经精神疾病，包括自闭症，注意力缺陷障碍，痴呆症， 和精神分裂症。 指导这项研究的工作模型是，基于不同的人的自上而下的注意力控制 刺激属性是由DAN和前额叶皮层内的较小尺度神经结构引导的 与专门的视觉皮层编码的专门连接进行了特定的连接。而且， DAN内部活动的时间过程与感觉皮层中的活动时间遵循自上而下的级联 模型最早在额叶，然后是顶叶皮层，最后是感觉皮层，以进行预备，自愿， 注意控制。 确定用于不同形式注意力的注意力控制的功能网络，并定义其时间 课程，该项目使用脑电图（EEG）和功能性的创新记录 磁共振成像（fMRI）数据。高级信号处理和建模，包括多元 模式分析（MVPA），图理论连通性分析和Granger因果关系分析将用于 揭示注意力控制和选择的精细功能解剖结构和时间过程。该项目包括 从空间位置到刺激特征的三个实验将变化的刺激属性改变 （颜色和运动），并追求三个目标。目标1是揭示自上而下预备的精细结构 注意力控制不同的刺激特征。 AIM 2是阐明特定连通性 在精细的结构之间，以进行DAN的准备注意力控制及其目标感觉结构 感觉皮层。 AIM 3是揭示自上而下的注意力控制的时间过程 刺激属性。