NCS-FO: Collaborative Research: Relationship of Cortical Field Anatomy to Network Vulnerability and Behavior

NCS-FO：协作研究：皮质场解剖与网络漏洞和行为的关系

• 批准号: 1734913
• 负责人: Wanpracha Chaovalitwongse
• 金额: $ 15万
• 依托单位: University of Arkansas
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1734913&HistoricalAwards=false
• 关键词: NCS; FO; Collaborative; Research; Relationship

Cognitive abilities such as memory and attention are supported by specialized brain networks made up of specific patches of the cerebral cortex called cortical fields. Cortical fields are thought to be anatomically distinct, with neurons connecting between them. Until recently, cortical fields could only be identified after death, by microscopic examination of autopsy brain tissue. Their number, function, and location in individual brains have been unknown. Now however, Magnetic resonance imaging (MRI) can detect neural activity in the cerebral cortex with relatively high resolution, and diffusion MRI (dMRI) can detect white-matter fibers that connect brain regions. Networks made up of cortical fields become active when individuals accomplish a task, and also spontaneously, when the mind is "at rest." We will use all this information to delineate the specific cortical fields in individual brains as well as patterns of connectivity between them. Cortical fields vary in size up to threefold from person to person, and we intend to study whether this variability is reflected in individual abilities or susceptibilities. The overarching goal is to test the idea that the size of cortical fields matters to the strength and vulnerability of brain networks. We use the MRI approaches outlined above to measure network strength, and we temporarily disrupt networks with transcranial magnetic stimulation (TMS) to assess network vulnerability. The work is important because it will allow us to better understand the reasons people have variable mental abilities. The project focuses on two established brain networks: the default mode network (DMN) and the lateral frontoparietal network (LFPN), which have components in the inferior parietal lobes. Connectivity-based parcellation distinguishes two angular gyrus fields, PgA and PgP, which are nodes within the LFPN and DMN networks, respectively. We will use dMRI to parcellate the cortex using a probabilistic parcel atlas of the Human Connectome Project data as prior information. Using functional connectivity, we will evaluate if PgP belongs to DMN, and PgA to LFPN. We will also analyze the strength of functional connectivity across network nodes in resting state fMRI using the dual-regression approach and ascertain the degree to which cortical field size variability across subjects is correlated with network-size variability. We will evaluate whether connectivity-defined cortical parcels maximize fMRI task contrast and show higher levels of EEG gamma and theta activities. Finally we relate the variability of cortical parcel size to task vulnerability by applying transcranial magnetic stimulations (TMS) to PgP and PgA. We hypothesize that low-frequency repetitive TMS (rTMS) over PgA will impair task performance on a working memory task and on a flanker task, and more so for individuals with smaller surface area of PgA. Furthermore, because endogenous reduction of DMN activity is associated with successful deployment of attentional resources, we also hypothesize that rTMS over DMN nodes will positively affect performance on the same tasks, and more so for individuals with smaller surface areas of these nodes. This project is funded by Integrative Strategies for Understanding Neural and Cognitive Systems (NSF-NCS), a multidisciplinary program jointly supported by the Directorates for Computer and Information Science and Engineering (CISE), Education and Human Resources (EHR), Engineering (ENG), and Social, Behavioral, and Economic Sciences (SBE).

记忆和注意力等认知能力是由专门的大脑网络支持的，这些网络由大脑皮层的特定区域组成，称为皮层区域。皮质区被认为在解剖学上是不同的，它们之间有神经元连接。直到最近，只有在死后才能通过尸检脑组织的显微镜检查来识别皮层区域。它们的数量、功能和在个体大脑中的位置一直是未知的。 然而现在，磁共振成像（MRI）可以以相对较高的分辨率检测大脑皮层中的神经活动，而弥散MRI（dMRI）可以检测连接大脑区域的白质纤维。当个体完成一项任务时，由大脑皮层区域组成的网络就会活跃起来，当大脑处于“休息状态”时，网络也会自发地活跃起来。“我们将利用所有这些信息来描绘个体大脑中的特定皮质区域以及它们之间的连接模式。大脑皮层区域的大小因人而异，最多可达三倍，我们打算研究这种变异性是否反映在个人能力或能力上。总体目标是测试皮质区域的大小与大脑网络的强度和脆弱性有关的想法。我们使用上面概述的MRI方法来测量网络强度，并使用经颅磁刺激（TMS）暂时破坏网络以评估网络脆弱性。这项工作很重要，因为它将使我们能够更好地理解人们具有可变心理能力的原因。该项目的重点是两个已建立的大脑网络：默认模式网络（DMN）和外侧额顶叶网络（LFPN），它们在下顶叶中有组件。 基于连接性的包裹区分两个角回领域，PgA和PgP，这是LFPN和DMN网络内的节点，分别。我们将使用人类连接组计划数据的概率包裹图谱作为先验信息，使用dMRI包裹皮质。使用功能连接性，我们将评估PgP是否属于DMN，PgA是否属于LFPN。我们还将使用双回归方法分析静息状态fMRI中网络节点之间的功能连接强度，并确定受试者之间的皮质场大小变异性与网络大小变异性的相关程度。我们将评估是否连接定义的皮层包裹最大化功能磁共振成像任务对比度，并显示更高水平的脑电图伽马和θ活动。最后，我们将经颅磁刺激（TMS）应用于PgP和PgA的皮质包裹大小的变化与任务脆弱性。我们假设，低频率重复TMS（rTMS）超过PgA会损害工作记忆任务和侧翼任务的任务表现，PgA表面积较小的个体更是如此。此外，由于内源性DMN活动的减少与注意力资源的成功部署有关，我们还假设DMN节点上的rTMS会对相同任务的表现产生积极影响，对于这些节点表面积较小的个体来说更是如此。 该项目由理解神经和认知系统的综合策略（NSF-NCS）资助，这是一个由计算机和信息科学与工程（CISE），教育和人力资源（EHR），工程（ENG）以及社会，行为和经济科学（SBE）董事会共同支持的多学科计划。

项目成果

Regularizing the Deepsurv Network Using Projection Loss for Medical Risk Assessment

• DOI: 10.1109/access.2022.3142032
• 发表时间: 2022
• 期刊: IEEE Access
• 影响因子: 3.9
• 作者: Phawis Thammasorn;S. Schaub;D. Hippe;M. Spraker;J. Peeken;L. Wootton;Paul Kinahan;S. Combs;W. Chaovalitwongse;Matthew Nyflot

Nearest Neighbor-Based Strategy to Optimize Multi-View Triplet Network for Classification of Small-Sample Medical Imaging Data

• DOI: 10.1109/tnnls.2021.3059635
• 发表时间: 2021-03
• 期刊: IEEE Transactions on Neural Networks and Learning Systems
• 影响因子: 10.4
• 作者: Phawis Thammasorn;W. Chaovalitwongse;D. Hippe;L. Wootton;Eric Ford;M. Spraker;S. Combs;J. Peeken;Matthew Nyflot