The integrated roles of regions and networks in frontal lobe organization

额叶组织中区域和网络的综合作用

• 批准号: 9911123
• 负责人: Savannah Cookson
• 金额: $ 6.74万
• 依托单位: UNIVERSITY OF CALIFORNIA BERKELEY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-01-09 至 2023-01-08
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9911123
• 关键词: Address; Adopted; Area; Behavior; Behavioral; Brain; Data; Etiology; Functional Magnetic Resonance Imaging; Goals; Individual; Lateral; Learning; Light; Link; Magnetism; Measures; Methods; Modeling; Parietal; Participant; Pathway Analysis; Physiologic pulse; Population; Positioning Attribute; Process; Reporting; Research; Rest; Role; Series; Site; Structure; Techniques; Testing; Time; Transcranial magnetic stimulation; Work; base; causal model; cognitive change; cognitive control; cognitive function; frontal lobe; graph theory; member; network models; novel; recruit; support network; tenure track

PROJECT SUMMARY. The organization of cognitive control processes in lateral frontal cortex (LFC) has been described in both regional and network models. Regionally, different types of control are organized hierarchically along a rostrocaudal axis2-8. At the network level, LFC is segregated into two functional networks, the fronto- parietal (FP) and cingulo-opercular (CO), which support control at two different timescales9-10. Despite similarities between the these models, there is no parsimonious model that accounts for both scales. A novel perspective that allows networks to overlap (i.e., share regions) can serve as a basis for their reconciliation13. Based on evidence from a preliminary analysis of overlapping network membership in LFC, I have proposed a novel two- scale model of LFC functional organization. LFC regions form a previously unidentified "task" network that overlaps the FP and CO networks. The task network supports tasks that engage the LFC, and connects LFC regions hierarchically. This proposal will test this model and its overlapping networks by (1) comparing changes in network integration and regional hierarchical influence at rest and during tasks with different control demands, and (2) causally testing how overlapping network membership predicts changes in network connectivity after regional perturbation. In Aim 1, I will partially replicate a previous study18 to assess task-related network integration between the task network and FP and CO networks and its relationship with hierarchical strength between LFC regions. I will collect resting state data in 32 participants as well as two sessions of fMRI data recorded during a behavioral task whose conditions have different control demands and therefore engage distinct LFC regions. Graph theory measures of integration will be applied to task data within each condition11-12. For this analysis, I predict that integration of the task network with the FP and/or CO networks will be greater in conditions with demands that recruit LFC regions in each network. I will also correlate the change in network-specific integration from rest to each task condition with the change in regional hierarchical strength in each region. For this analysis, I predict that the change in FP and CO network integration with the task network will be positively correlated with the hierarchical strength of the LFC regions they contain. For Aim 2, I will expand on previously reported work from our lab23 to assess how network connectivity changes when regions with different overlapping network membership profiles are perturbed with transcranial magnetic stimulation (TMS). I will collect three sessions of fMRI data in 32 participants. Session 1 will be used to identify separate TMS targets in the FP network that are and are not a part of the task network. In sessions 2 and 3, I will collect data before and after stimulation of one of these targets. I predict that TMS to the site that is part of the task network will replicate the previous results, while TMS to the site that is not will cause changes limited to the FP network. The proposed studies will provide support for my novel model of LFC, and will be the first direct tests of the relationship between functional organization of regions and networks.

项目摘要。认知控制过程在外侧额叶皮层（LFC）的组织已经被证明是一个重要的研究领域。 在区域和网络模型中描述。在区域上，不同类型的控制是分层组织的 沿着喙尾轴2 -8。在网络层面，物流中心分为两个功能网络，前端网络和后端网络。 顶叶（FP）和扣带-盖（CO），支持在两个不同的时间尺度9 -10的控制。尽管相似 在这些模型中，没有一个简约模型同时考虑到这两个尺度。新颖的视角 其允许网络重叠（即，共享区域）可以作为其对账的基础13。基于 证据重叠网络成员在LFC的初步分析，我提出了一个新的两个- LFC职能组织的规模模型。LFC区域形成了一个以前未识别的“任务”网络， 与FP和CO网络重叠。任务网络支持涉及LFC的任务，并连接LFC 区域等级。本提案将通过以下方式测试该模型及其重叠网络：（1）比较 在静止和具有不同控制需求任务期间的网络集成和区域分级影响中， 以及（2）因果地测试重叠网络成员关系如何预测在 区域扰动在目标1中，我将部分重复先前的研究18，以评估任务相关网络 任务网络与FP和CO网络的整合及其与层级强度的关系 LFC地区之间。我将收集32名参与者的静息状态数据以及两次fMRI数据 在行为任务期间记录，其条件具有不同的控制需求，因此参与不同的控制需求。 LFC地区。整合的图论测量将应用于每个条件下的任务数据11 -12。为此 分析，我预测，在条件下，任务网络与FP和/或CO网络的集成将更大 具有在每个网络中招募LFC区域的需求。我还将把特定于网络的 从休息到每个任务条件的整合，以及每个区域中区域等级强度的变化。为 通过这一分析，我预测FP和CO网络与任务网络整合的变化将是积极的。 与它们所包含的LFC区域的等级强度相关。对于目标2，我将扩展以前的内容 报告了我们实验室23的工作，以评估当区域具有不同的重叠时，网络连接如何变化 用经颅磁刺激（TMS）扰乱网络成员简档。我会收集三个 32名参与者的fMRI数据。会话1将用于确定FP中的单独TMS目标 网络的一部分和不是任务网络的一部分。在第2和第3节课中，我将收集前后的数据， 刺激这些目标之一。我预测，TMS到作为任务网络一部分的站点将复制 以前的结果，而TMS的网站，这是不是将造成的变化仅限于FP网络。拟议 这些研究将为我的LFC新模型提供支持，并将是第一次直接测试LFC和LFC之间的关系。 区域和网络的职能组织。