FUNCTIONAL CONNECTIVITY IN THE BRAIN: A NEW APPROACH

摘要 人脑内的氧气水平会在没有任何明显的外部驱动因素的情况下波动。 出乎意料的是，这些内在波动在遥远的区域之间是相关的，形成了“静止” 国家网络”。这些网络似乎与大脑功能相关。静息状态数据可以 为大脑区域之间的功能连接提供证据。行为方面 性能可以通过缓慢相关的 BOLD 波动的持续水平来预测。 最后，包括自闭症和精神分裂症在内的多种神经和精神疾病 与静息状态网络异常有关。 尽管休息对于理解正常和紊乱的认知具有潜在的重要性，但 状态网络在人类认知神经科学中仍然是一个知之甚少的现象。我们 寻求更好地理解相关氧波动的起源和意义 以高空间和时间分辨率表征它们并识别 在休息和执行任务期间与它们相关的电生理信号。 我们将以一种新颖的方式使用氧极谱法。最初通过静息态功能磁共振成像扫描引导， 我们将在猕猴大脑中插入多个铂微电极来验证和表征 氧气浓度的相关波动。我们将同步录制 来自这些电极的电生理信号，并询问电生理信号的哪一部分 电生理谱（慢皮质电位、局部场电位、多单元活动） 与任务驱动和/或与静息态相关的氧波动相关。至 为了实现这一目标，我们将利用极谱法相对于功能磁共振成像的优势，包括共同 局部和同步的氧气和电信号，更高的空间和时间 分辨率、对运动伪影的抵抗力以及在清醒行为动物中的易用性。 我们的总体目标是确定将电生理信号映射到的传递函数 氧气波动，以及该传递函数是否特定于网络，取决于 记录或反映动物正在进行的行为状态的皮质层（例如， 从事任务、睡眠和麻醉状态）。这项工作的临床意义在于 将改进功能磁共振成像信息在脑部疾病诊断、预后和病因学中的应用 失调。从高层次来看，其科学意义在于它将帮助我们理解 大规模的大脑结构和认知处理。

ABSTRACT Oxygen levels within the human brain fluctuate without any apparent external driver. Unexpectedly, these intrinsic fluctuations are correlated among distant regions, forming "resting state networks". These networks appear to be relevant to brain function. Resting state data can provide evidence for functional connections between brain regions. Aspects of behavioral performance can be predicted by the ongoing level of slow correlated BOLD fluctuations. Finally, multiple neurological and psychiatric disorders including autism and schizophrenia are associated with abnormalities in resting state networks. Despite their potential importance for understanding normal and disordered cognition, resting state networks remain a poorly understood phenomenon in human cognitive neuroscience. We seek to better understand the origin and significance of correlated oxygen fluctuations by characterizing them at high spatial and temporal resolution and identifying the electrophysiological signals associated with them both at rest and during task performance. We will use oxygen polarography in a novel way. Guided initially by resting state fMRI scans, we will insert multiple platinum microelectrodes into a macaque brain to verify and characterize correlated fluctuations in oxygen concentration. We will record simultaneous electrophysiological signals from these electrodes and ask what portion of the electrophysiological spectrum (slow cortical potentials, local field potentials, multi-unit activity) is associated with task-driven and/or with resting-state correlated oxygen fluctuations. To accomplish this, we will exploit the advantages of polarography over fMRI, including co- localized and simultaneous oxygen and electrical signals, higher spatial and temporal resolution, resistance to movement artifacts, and ease of use in awake behaving animals. Our overall aim is to determine the transfer function mapping electrophysiology signals onto oxygen fluctuations, and whether this transfer function is network-specific, depends on the cortical layer being recorded from, or reflects the ongoing behavioral state of the animal (e.g., task-engaged, sleeping and under anesthesia). The clinical significance of this work is that it will lead to improved use of fMRI information for the diagnosis, prognosis and etiology of brain disorders. The scientific significance, at a high level, is that it will inform our understanding of large-scale brain architecture and cognitive processing.