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人类普遍存在的特征。 不同物种的大脑，在多种神经系统疾病中都存在异常。大脑网络缓慢 波动对跨长时间尺度的行为至关重要：随着几分钟内觉醒的漂移， 因为我们有能力在外部参与和内部转向之间切换来规划我们未来的行动， 专注于最近的经历。尽管缓慢的大脑网络波动对行为的贡献已经 通常通过将一种网络测量与一种行为联系起来进行研究，该项目旨在更广泛地 通过以下方式了解健康人类参与者的缓慢波动： i) 深入描述他们之间的关系 同时测量大脑活动、生理、行为和认知的多种测量值 ii) 因果地操纵认知控制和唤醒的关键因素，假设这些因素是协调的 缓慢的网络波动与持续行为或模式之间的切换之间的关系 外部注意力与内部注意力。为了实现这些目标，目标 1 将进行深入的研究 通过收集广泛的多模式神经和生理学来表征缓慢的网络波动 健康人类参与者的录音。同步功能磁共振成像、脑电图、皮肤电活动、瞳孔测量、 当参与者执行一系列扩展任务时，将记录呼吸、心电图和肌电图，这些任务包括： 非结构化（休息）到高度结构化的需要注意力的任务。经验抽样将使我们能够评估 持续认知的内容。这个丰富的数据集将使我们能够以前所未有的方式测量和 将多种模式的缓慢波动联系起来，将它们与外部导向的行为的关系映射出来 任务和内部认知的内容。虽然目标 1 将检验缓慢波动与 在刺激驱动的任务中表现出色，我们内部引导注意力的能力可能具有适应性优势， 面向外部的基于实验室的任务通常不会捕获该功能。目标 2a 将直接填补这一空白 评估缓慢的大脑网络波动对支持有益的内部处理的贡献 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 规划任务，并评估这些任务的持续内部处理的神经和行为标记 在随后的一段时间内。这将使我们能够将缓慢的网络波动与收益直接联系起来 与内部导向的认知相关，并衡量内部与外部之间的权衡 定向的认知模式。另一个主要问题涉及缓慢网络波动的监管。目标 2b 将评估两个关键因素（认知控制和唤醒）的潜在因果作用，以减缓 波动及其对行为和认知的影响。这些因素将独立 通过任务要求和双盲药物管理来评估他们的独特贡献。 这些实验将极大地促进我们对大脑网络缓慢波动的作用的理解 协调适应性行为和认知。