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 选择性注意是一种基本的认知能力，它允许我们有效地处理相关问题并采取行动 信息，而忽略了令人分心的事件。自上而下涉及额叶和顶叶皮质的网络 注意控制，被称为背部注意网络(DAN)，在空间和非空间活动中都是活跃的 空间(基于特征的)注意力。然而，我们对注意控制的精细结构知之甚少 丹的活动，这个结构如何改变以代表不同的刺激特征，如何 DAN内部的连接，以及DAN和感觉皮质之间的连接在处理不同的功能时发生变化， 或者这些自上而下的过程及其对感觉皮质的影响是如何随着时间的推移而展开的。我们的这一差距 对于我们的注意力模型和理论来说，知识是一个关键问题，因为注意力缺陷 涉及多种神经精神障碍，包括自闭症、注意力缺陷障碍、痴呆症、 和精神分裂症。 指导本研究的工作模式是基于不同被关注对象的自上而下的注意控制 刺激属性，是由DAN和前额叶皮质内较小规模的神经精细结构引导的 与视觉皮质的特定区域建立特定的联系，编码所关注的属性。此外， 丹内活动与感觉皮质活动的时间进程遵循自上而下的级联。 模型，最早出现在额叶，然后是顶叶皮质，最后是感觉皮质，用于准备，自愿， 注意力控制。 识别不同形式注意的注意控制功能网络，并确定它们的时间 课程，本项目使用创新的同步记录脑电(EEG)和功能 磁共振成像(FMRI)数据。高级信号处理和建模，包括多变量 模式分析(MVPA)、图论连通性分析和格兰杰因果分析将用于 揭示注意控制和选择的精细功能解剖和时间进程。该项目包括 三个从空间位置到刺激特征的不同刺激属性的实验 (色彩和运动)，追求三个目标。目标1是揭示自上而下的准备工作的精细结构 对不同注意刺激特征的注意控制。目标2是阐明特定的连接性 DAN中预备性注意控制的精细结构与其靶感觉结构之间的关系 感觉皮层。目标三是揭示不同被照看对象自上而下注意控制的时间进程 刺激属性。