Macroscale physiology and functional correlates of slow network fluctuations

缓慢网络波动的宏观生理学和功能相关性

• 批准号: 10639544
• 负责人: Michael Peter Milham
• 金额: $ 34.31万
• 依托单位: NATHAN S. KLINE INSTITUTE FOR PSYCH RES
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-04-15 至 2028-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10639544
• 关键词: Adaptive Behaviors; Address; Adult; Affect; Archives; Area; Arousal; Attention; Back; Behavior; Behavioral; Brain; Cognition; Cognitive; Coupled; Data; Data Set; Dimensions; Double-Blind Method; Electrocardiogram; Electroencephalography; Event; Feedback; Functional Magnetic Resonance Imaging; Future; Goals; Heart; Human; Impairment; Investigation; Learning; Link; Maps; Measures; Memory; Mind; Modality; Neurobiology; Participant; Pattern; Performance; Pharmaceutical Preparations; Phase; Physiological; Physiology; Placebos; Probability; Property; Reaction Time; Recurrence; Regulation; Respiration; Rest; Ritalin; Role; Sampling; Signal Transduction; Specific qualifier value; Stimulus; Structure; Task Performances; Testing; Time; Variant; behavioral response; biophysical model; cognitive benefits; cognitive control; data format; data standards; design; directed attention; experience; experimental study; functional magnetic resonance imaging/electroencephalography; indexing; memory consolidation; memory encoding; memory retention; movie; multimodality; nervous system disorder; network models; neural; visual tracking

ABSTRACT. Slow fluctuations in behavioral, cognitive, and neural states are an omnipresent feature of the brain across species and are aberrant in multiple disorders of the nervous system. Slow brain network fluctuations critically organize behavior across extended timescales: as drifts in arousal over minutes, as well as our ability to switch between attending externally versus turning internally to plan our future actions and dwell on recent experiences. Although the contribution of slow brain network fluctuations to behavior have typically been studied by linking one network measure to one behavior, this project seeks to more broadly understand slow fluctuations in healthy human participants by i) deeply characterizing their relationship across multiple measures of brain activity, physiology, behavior, and cognition measured simultaneously and ii) causally manipulating key factors of cognitive control and arousal which are hypothesized to orchestrate relationships between slow network fluctuations and ongoing behavior or switching between modes of externally versus internally oriented attention. To achieve these goals, Aim 1 will perform a deep characterization of slow network fluctuations by collecting extensive multimodal neural and physiological recordings in healthy human participants. Simultaneous fMRI, EEG, electrodermal activity, pupillometry, respiration, ECG, and EMG will be recorded as participants perform an extended array of tasks ranging from unstructured (rest) to highly structured attention-demanding tasks. Experience sampling will allow us to assess the contents of ongoing cognition. This rich dataset will allow us to, in an unprecedented manner, measure and link slow fluctuations across multiple modalities, map their relationship with behavior on externally-oriented tasks and to the contents of internal cognition. While Aim 1 will examine the relevance of slow fluctuations to performance on stimulus- driven tasks, our ability to direct attention internally likely has adaptive benefits, a feature not typically captured in externally-oriented lab-based tasks. Aim 2a will fill in this gap by directly assessing the contributions of slow brain network fluctuations to supporting internal processing that benefits our subsequent behavior. Specifically we will measure brain patterns associated with learning and goal planning tasks, and assess neural and behavioral markers of continued internal processing on these tasks during a subsequent time period. This will allow us to directly link slow network fluctuations to benefits associated with internally-oriented cognition, and measure trade-offs between internally- versus externally- oriented modes of cognition. Another major question relates to regulation of slow network fluctuations. Aim 2b will assess the potential causal contributions of two key factors, cognitive control and arousal, to slow fluctuations and their resulting impact on behavior and cognition. These factors will be independently manipulated via task demands and double-blind drug administration to assess their distinct contributions. These experiments will dramatically advance our understanding of the role of slow brain network fluctuations in orchestrating adaptive behavior and cognition.

抽象的。行为，认知和神经状态的缓慢波动是无处不在的特征 跨物种的大脑，在神经系统的多种疾病中异常。慢速大脑网络 波动批判性地整理了跨越长时间尺度的行为：随着唤醒时间在几分钟内漂移 随着我们在参加外部与内部进行计划的能力，以计划未来的行动和 居住在最近的经验上。尽管缓慢的大脑网络波动对行为的贡献具有 通常，通过将一个网络度量与一种行为联系起来，研究了该项目，以更广泛的范围 通过i）深入了解健康参与者的缓慢波动 同时测量的大脑活动，生理，行为和认知的多种测量和II） 有因果操纵认知控制和唤醒的关键因素，这些因素被认为是编排的 缓慢的网络波动与持续行为或在模式之间切换之间的关系 外部与内部关注。为了实现这些目标，AIM 1将执行深度 通过收集广泛的多模式神经和生理学来表征慢网络波动的表征 健康参与者的录音。同时fMRI，脑电图，电肌活动，瞳孔测定法， 呼吸，ECG和EMG将被记录为参与者执行延长的任务。 非结构化（休息）到高度结构化的注意任务。经验抽样将使我们能够评估 持续认知的内容。这个富裕的数据集将使我们以前所未有的方式，衡量和 链接跨多种方式的慢速波动，在面向外部的行为上绘制其与行为的关系 任务和内部认知内容。而目标1将检查缓慢波动与 在刺激驱动的任务上的表现，我们在内部引导注意力的能力可能具有适应性好处， 功能通常不会在基于外部实验室的任务中捕获。 AIM 2A将通过直接填补此空白 评估慢速大脑网络波动对支持内部处理的贡献 我们随后的行为。具体来说，我们将测量与学习和目标相关的大脑模式 计划任务，并评估持续内部处理这些任务的神经和行为标记 在随后的时间段内。这将使我们能够将慢速网络波动与利益联系起来 与内部的认知相关，并在内部与外部之间的权衡 - 定向认知模式。另一个主要问题涉及缓慢网络波动的调节。目标2B 将评估两个关键因素（认知控制和唤醒）的潜在因果贡献，以减缓 波动及其对行为和认知的影响。这些因素将是独立的 通过任务要求和双盲药物管理来评估其不同的贡献。 这些实验将极大地提高我们对慢速大脑网络波动的作用的理解 编排适应性行为和认知。