Defining Neuronal Circuits and Cellular Processes Underlying Resting fMRI Signals

定义静息 fMRI 信号下的神经元回路和细胞过程

• 批准号: 9206010
• 负责人: Michael Peter Milham
• 金额: $ 96.21万
• 依托单位: NATHAN S. KLINE INSTITUTE FOR PSYCH RES
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-22 至 2021-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9206010
• 关键词: Activity Cycles; Anatomy; Architecture; Area; Brain; Cell physiology; Cells; Clinical; Complex; Computing Methodologies; Coupled; Coupling; Data; Electric Stimulation; Electrodes; Electroencephalography; Electrophysiology (science); Employee Strikes; Epilepsy; Face; Frequencies; Functional Magnetic Resonance Imaging; Goals; Hand; Human; Link; Maps; Measures; Mental Health; Metabolic; Methods; Microscopic; Modeling; Monkeys; Neurons; Neurosciences; Nodal; Operative Surgical Procedures; Patients; Pattern; Phase; Population; Process; Property; Reproducibility; Reproducibility of Results; Research; Rest; Role; Scalp structure; Signal Transduction; Source; Specific qualifier value; System; Task Performances; Testing; Variant; Work; biomarker discovery; blood oxygen level dependent; density; electric field; indexing; innovation; interest; neural circuit; neuromechanism; neuronal circuitry; neuronal patterning; neurophysiology; neuroregulation; novel; relating to nervous system

Intrinsic ‘functional connectivity’ (iFC), a measure of correlation between spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal, reliably distinguish networks of cortical and subcortical areas during both rest and active task performance. iFC methods can map the functional architecture of the human brain in both healthy and pathological conditions, in high detail using as little as 5 minutes of data. Striking reproducibility and test-retest reliability of findings across centers have fueled a widespread application of iFC measures in clinical neuroscience, biomarker discovery, and human connectomics. However, the neural circuits and cellular processes underlying BOLD-iFC remain poorly specified. BOLD amplitude itself appears related to neural activity in the high gamma (HG) range (~70-200 Hz), and thus to an extent, with neuronal firing. However, BOLD’s relationship to the lower frequencies is controversial. This is a critical disconnect, as oscillatory activities below 40Hz reflect ongoing cell-circuit excitability fluctuations that control neuronal firing; i.e., the amplitude of neural population firing is “coupled” to oscillatory phase. In this, the simplest form of such phase-amplitude coupling (PAC), amplitude variations in higher frequency activity (e.g., firing or HG) are coupled to the phase of a lower frequency (e.g., theta). PAC operates both pairwise and recursively over the spectrum, from the range of neuronal firing down to the slow/infraslow (<1Hz) range where BOLD amplitude fluctuations are observed using resting state fMRI (R-fMRI). Thus PAC may provide a key to connecting resting BOLD fluctuations to activity cycles in the underlying cell circuits. In our framework: 1) At a microscopic, cortical cell-circuit level, a complex of excitatory and inhibitory interactions between neurons generate rhythmic excitability fluctuations (oscillations). 2) PAC organizes slow (0.5-12) Hz and mid-range (13-40Hz) oscillations hierarchically, ultimately controlling temporal patterns of neuronal firing. 3) Infraslow (0.01-0.1 Hz) neural activity fluctuations synchronize to form the macroscale intrinsic connectivity networks (ICN) indexed by R- fMRI, and use PAC to orchestrate faster activity within a network. Our broad goal is to use integrated human and monkey studies to investigate the relationship between macroscale BOLD-derived iFC patterns, and their underlying mechanisms at the microscale cell-circuit level. We will study the sensorimotor network, as its “nodal” organization and other properties are well understood, and it shows good human-simian correspondence. Focusing on key nodes in this network (e.g., face and hand areas), we will recapitulate prior work tying R-FMRI iFC to macroscale scalp EEG and mesoscale stereotactic (S)-EEG, and will use innovative laminar multielectrode methods to establish novel links to the cell circuit level. Established modeling and computational methods will help to construct a comprehensive model that connects macroscale iFC to underlying microscale, cell circuit activity.

内在功能连接性(IFC)，一种衡量血液中自发波动之间的相关性的指标 氧水平依赖(BOLD)信号，可靠地区分皮层和皮质下区域的网络 休息和积极的任务表现。IFC方法可以绘制出人脑的功能结构图 健康和病理情况，使用短短5分钟的数据进行高细节分析。引人注目 各中心调查结果的重复性和重测可靠性推动了国际金融公司的广泛应用 在临床神经科学、生物标记物发现和人类连接学方面的措施。然而，神经 BOLD-IFC背后的电路和细胞过程仍然没有得到很好的说明。显示粗体幅度本身 与高伽马(HG)范围(~70-200赫兹)的神经活动有关，因此在一定程度上与神经元有关 开火。然而，博尔德与较低频率的关系存在争议。这是一个严重的脱节，因为 40赫兹以下的振荡活动反映了控制神经元放电的持续细胞电路兴奋性波动； 也就是说，神经群体放电的幅度与振荡相位“耦合”。在这种情况下，这种最简单的形式 相位-幅度耦合(PAC)、高频活动(例如，放电或HG)中的幅度变化 耦合到较低频率(例如，θ)的相位。PAC以成对和递归方式在 频谱，从神经元放电范围向下到慢/次流(&lt；1赫兹)范围，其中粗大幅度 使用静息功能磁共振成像(R-fMRI)观察波动。因此，PAC可以提供连接休眠的钥匙 基础细胞电路中活动周期的剧烈波动。在我们的框架中：1)在微观上， 皮层细胞电路水平，神经元之间兴奋性和抑制性相互作用的复合体，产生节律性 兴奋性波动(振荡)。2)PAC组织慢(0.5-12)赫兹和中频(13-40赫兹)振荡 分级地，最终控制神经元放电的时间模式。3)红外线(0.01-0.1赫兹)神经 活动波动同步形成R-索引的宏观内在连通性网络(ICN) FMRI，并使用PAC在网络中协调更快的活动。我们的宏伟目标是用完整的人类 和猴子研究，以调查宏观粗体衍生的IFC模式与其 微尺度电池-电路层面的潜在机制。我们将研究感觉运动网络，因为它的 “节点”组织和其他属性被很好地理解，并显示出良好的人猿 通信。聚焦于该网络中的关键节点(例如，面部和手部区域)，我们将重述之前 将R-fMRI IFC与宏观头皮脑电和中尺度立体定向(S)-脑电捆绑在一起，并将使用创新的 层流多电极方法建立到电池电路级的新链接。已建立建模和 计算方法将有助于构建一个全面的模型，将宏观国际金融公司与 潜在的微尺度，细胞电路活动。