Sources and Functional Consequences of Individual Differences in Human Functional Brain Networks Related to Controlled Behavior

与受控行为相关的人类功能大脑网络个体差异的来源和功能后果

• 批准号: 10750297
• 负责人: Caterina Gratton
• 金额: $ 72.4万
• 依托单位: FLORIDA STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10750297
• 关键词: Sources; Functional; Consequences; Individual; Differences

Project Summary Large-scale networks of the human brain can be measured non-invasively using functional Magnetic Resonance Imaging (fMRI). While most previous work has focused on group descriptions of functional networks, recent findings suggest that the study of highly-sampled single participants can reveal novel aspects of brain organization specific to an individual. Here, we focus on atypical locations where an individual’s functional networks do not match the group, which we call network variants. Preliminary data demonstrates that network variants are present across all individuals, but differ in location, number, and network assignment. Variants are most often associated with systems of the brain linked to goal-directed “controlled” processing. This observation is intriguing, given that individual differences in control functions are known to be large and heritable, and in extreme cases can be central contributions to pathology in disorders such as schizophrenia. Based on these preliminary findings, we develop a model, wherein we suggest that stable factors (e.g., genetics, long-term experience) reprioritize the functions of cortical areas, leading to the creation of network variants, altered task activations, and behavior. Our goal is to test this model by examining the sources and consequences of variants. Given that variants are most associated with regions related to controlled tasks, we focus our tests on control- related activations and behavior. We will test the following hypotheses: (Aim 1) variants represent stable, heritable, endophenotypes for individual differences in brain organization, (Aim 2) variants relate to individual differences in brain activations in control tasks, and (Aim 3) variants relate to individual differences in behavior in control tasks. In Aim 1 we propose addressing the trait-like nature of variants by measuring variant stability across states, and the similarity of variant patterns across unrelated individuals, mono-, and dizygotic twins. In Aim 2, we propose using a precision fMRI approach to measure variant activations across a range of control- related task contexts. Finally, in Aim 3 we propose examining whether variants are related to differences in control-related behavior. This proposal is innovative: it adopts cutting-edge methods for reliably characterizing networks in single individuals to study atypical components of brain networks (rather than group descriptions) and provides a new window into possible mechanisms underlying individual differences in brain organization, activations, and behavior. This proposal will impact (1) basic science, by expanding our understanding of individual variability in brain networks and their relationship to brain function and behavior, and (2) translational research, by laying groundwork for the study of extreme forms of individual differences in control found in psychopathology, potentially with future utility in personalized medicine. Thus, this proposal addresses RDoC goals by investigating (1) individual differences at multiple levels (brain organization, physiology, and behavior), (2) genetic and environmental sources for individual differences, and (3) potential biomarkers of dimensional individual differences linked to psychopathology.

项目概要 使用功能磁共振可以非侵入性地测量人脑的大规模网络 成像（功能磁共振成像）。虽然之前的大多数工作都集中在功能网络的群体描述上，但最近的 研究结果表明，对高样本单一参与者的研究可以揭示大脑的新方面 特定于个人的组织。在这里，我们关注个人功能的非典型位置 网络与组不匹配，我们称之为网络变体。初步数据表明，网络 变体存在于所有个体中，但在位置、数量和网络分配方面有所不同。变体是 最常与与目标导向的“控制”处理相关的大脑系统相关。这一观察 很有趣，因为众所周知，控制功能的个体差异很大并且是可遗传的，并且 极端情况可能是精神分裂症等疾病病理学的核心贡献。基于这些 根据初步发现，我们开发了一个模型，其中我们建议稳定因素（例如遗传、长期 经验）重新排列皮质区域的功能，导致网络变体的创建，改变任务 激活和行为。我们的目标是通过检查变体的来源和后果来测试这个模型。 鉴于变异与受控任务相关的区域最相关，我们将测试重点放在控制上 相关的激活和行为。我们将测试以下假设：（目标 1）变体代表稳定， 大脑组织个体差异的可遗传的内表型，（目标 2）变异与个体相关 控制任务中大脑激活的差异，以及（目标 3）与个体行为差异相关的变异 在控制任务中。在目标 1 中，我们建议通过测量变异稳定性来解决变异的类性状性质 各州之间的差异，以及无关个体、单卵双胞胎和异卵双胞胎之间变异模式的相似性。在 目标 2，我们建议使用精确的功能磁共振成像方法来测量一系列控制范围内的变异激活 相关的任务上下文。最后，在目标 3 中，我们建议检查变异是否与差异相关 与控制相关的行为。该提案具有创新性：它采用尖端方法来可靠地表征 单个个体的网络来研究大脑网络的非典型组成部分（而不是群体描述） 并为了解大脑组织个体差异的可能机制提供了一个新的窗口， 激活和行为。该提案将通过扩大我们对基础科学的理解来影响（1）基础科学 大脑网络的个体差异及其与大脑功能和行为的关系，以及（2）转化 研究，通过为研究在控制中发现的极端形式的个体差异奠定基础 精神病理学，未来可能在个性化医疗中发挥作用。因此，该提案解决了 RDoC 通过调查（1）多个层面（大脑组织、生理学和行为）的个体差异来实现目标， （2）个体差异的遗传和环境来源，以及（3）维度的潜在生物标志物 个体差异与精神病理学有关。