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.

项目概要/摘要 选择性注意是一种重要的认知能力，使我们能够有效地处理相关内容并采取行动 信息，同时忽略分散注意力的事件。涉及额叶和顶叶皮层的自上而下的网络 注意力控制，称为背侧注意力网络（DAN），在空间和非注意力期间都很活跃。 空间（基于特征）注意力。然而，我们对注意力控制的精细结构知之甚少 DAN 中的活动，该结构如何变化以代表不同的待关注刺激特征， DAN 内部以及 DAN 和感觉皮层之间的连接在关注不同特征时会发生变化， 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。我们的这个差距 知识对于我们的注意力模型和理论来说是一个关键问题，因为注意力缺陷是 涉及多种神经精神疾病，包括自闭症、注意力缺陷障碍、痴呆症、 和精神分裂症。 指导本研究的工作模型是自上而下的注意力控制，基于不同的待关注对象 刺激属性，由 DAN 和前额皮质内较小规模的神经精细结构引导， 与编码所关注属性的视觉皮层的专门区域建立特定的联系。而且， DAN 内的活动时间进程与感觉皮层的活动时间进程遵循自上而下的级联 模型，最早位于额叶皮层，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。 识别不同形式注意力的注意力控制功能网络，并定义它们的时间 课程中，该项目使用创新的脑电图 (EEG) 和功能同步记录 磁共振成像（fMRI）数据。先进的信号处理和建模，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 三个实验改变了要注意的刺激属性，从空间位置到刺激特征 （颜色和运动），并追求三个目标。目标1是揭示自上而下准备工作的精细结构 对不同待关注刺激特征的注意力控制。目标 2 是阐明特定的连接性 DAN 中用于准备注意力控制的精细结构与其目标感觉结构之间的关系 感觉皮层。目标3是揭示不同被关注者自上而下注意力控制的时间过程 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。

• 发表时间: 2021
• 作者: Meyyappan, Sreenivasan;Rajan, Abhijit;Mangun, George R;Ding, Mingzhou
• 通讯作者: Ding, Mingzhou

Decoding attention control and selection in visual spatial attention.

解码视觉空间注意中的注意控制和选择。

• 发表时间: 2020
• 影响因子: 4.8
• 作者: Hong, Xiangfei;Bo, Ke;Meyyappan, Sreenivasan;Tong, Shanbao;Ding, Mingzhou
• 通讯作者: Ding, Mingzhou

Top-Down Biasing of Visual Cortical Activity Encodes Attended Information and Facilitates Behavioral Performance in Visual Spatial Attention.

视觉皮层活动的自上而下的偏向编码参与信息并促进视觉空间注意力的行为表现。

• 发表时间: 2023-08-07
• 作者: Meyyappan, Sreenivasan;Rajan, Abhijit;Yang, Qiang;Mangun, George R;Ding, Mingzhou
• 通讯作者: Ding, Mingzhou

The Microstructure of Attentional Control in the Dorsal Attention Network.

背侧注意网络中注意控制的微观结构。

• 发表时间: 2021
• 影响因子: 3.2
• 作者: Rajan, Abhijit;Meyyappan, Sreenivasan;Liu, Yuelu;Samuel, Immanuel Babu Henry;Nandi, Bijurika;Mangun, George R;Ding, Mingzhou
• 通讯作者: Ding, Mingzhou

Top-down control of the left visual field bias in cued visual spatial attention.

自上而下控制提示视觉空间注意力中的左视野偏差。

• 发表时间: 2023-04-25
• 作者: Meyyappan, Sreenivasan;Rajan, Abhijit;Mangun, George R;Ding, Mingzhou
• 通讯作者: Ding, Mingzhou