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: 10368957
• 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 2025-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10368957
• 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.

项目总结/摘要 选择性注意是一种基本的认知能力，它使我们能够有效地处理相关信息并采取行动。 信息而忽略分散注意力的事件。一个涉及额叶和顶叶皮层的网络， 注意力控制，被称为背部注意力网络（DAN），在空间和非空间过程中都很活跃。 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 DAN中的活动，这种结构如何变化以代表不同的被关注刺激特征， DAN内的连接，以及DAN和感觉皮层之间的连接在关注不同特征时发生变化， 或者这些自上而下的过程及其对感觉皮层的影响如何随着时间的推移而展开。我们之间的差距 知识是我们注意力模型和理论的关键问题，因为注意力缺陷是 涉及多种神经精神障碍，包括自闭症，注意力缺陷障碍，痴呆， 和精神分裂症 指导本研究的工作模型是自上而下的注意控制，基于不同的被关注者， 刺激属性，由DAN和前额叶皮层内的较小尺度神经精细结构引导， 与编码关注属性的视觉皮层专门区域建立特定联系。此外，委员会认为， 与感觉皮层的活动相关的DAN内活动的时间过程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，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，并确定其时间 课程，该项目采用创新的同步记录脑电图（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关系分析将用于 揭示注意力控制和选择的精细功能解剖和时间过程。该项目包括 三个实验，从空间位置到刺激特征改变待关注的刺激属性 （颜色和运动），并追求三个目标。目的1是揭示自顶向下预备体的精细结构 注意力控制不同的被关注的刺激特征。目的2是阐明特定的连通性 DAN中用于准备性注意力控制的精细结构与 感觉皮层目的三是揭示不同被关注者自上而下注意控制的时程 刺激属性

项目成果

Role of Inferior Frontal Junction (IFJ) in the Control of Feature versus Spatial Attention.

额下交界处（IFJ）在特征与空间注意力控制中的作用。

• DOI: 10.1523/jneurosci.2883-20.2021
• 发表时间: 2021
• 期刊: The Journal of neuroscience : the official journal of the Society for Neuroscience
• 作者: Meyyappan,Sreenivasan;Rajan,Abhijit;Mangun,GeorgeR;Ding,Mingzhou
• 通讯作者: Ding,Mingzhou

The Microstructure of Attentional Control in the Dorsal Attention Network.

• DOI: 10.1162/jocn_a_01710
• 发表时间: 2021-05-01
• 期刊: Journal of cognitive neuroscience
• 影响因子: 3.2
• 作者: Rajan A;Meyyappan S;Liu Y;Samuel IBH;Nandi B;Mangun GR;Ding M
• 通讯作者: Ding M

Theta Oscillations Index Frontal Decision-Making and Mediate Reciprocal Frontal-Parietal Interactions in Willed Attention.

• DOI: 10.1093/cercor/bhy149
• 发表时间: 2018-06
• 期刊: Cerebral cortex
• 影响因子: 3.7
• 作者: A. Rajan;S. Siegel;Yuelu Liu;J. Bengson;G. Mangun;M. Ding

Time Courses of Attended and Ignored Object Representations.

• DOI: 10.1162/jocn_a_01972
• 发表时间: 2023-04-01
• 期刊: JOURNAL OF COGNITIVE NEUROSCIENCE
• 影响因子: 3.2
• 作者: Noah, Sean;Meyyappan, Sreenivasan;Ding, Mingzhou;Mangun, George R. R.
• 通讯作者: Mangun, George R. R.

Neural Mechanisms of Attentional Control for Objects: Decoding EEG Alpha When Anticipating Faces, Scenes,and Tools.

物体注意力控制的神经机制：在预期面孔、场景和工具时解码脑电图阿尔法。

• DOI: 10.1523/jneurosci.2685-19.2020
• 发表时间: 2020
• 期刊: The Journal of neuroscience : the official journal of the Society for Neuroscience
• 作者: Noah,Sean;Powell,Travis;Khodayari,Natalia;Olivan,Diana;Ding,Mingzhou;Mangun,GeorgeR
• 通讯作者: Mangun,GeorgeR