FUNCTIONAL CONNECTIVITY IN THE BRAIN: A NEW APPROACH

描述（由申请人提供）：在没有任何明显的外部驱动因素的情况下，人脑内的氧气水平会发生波动。出乎意料的是，这些内在的波动在遥远的区域之间相互关联，形成“静止状态网络”。这些网络似乎与大脑功能有关。静息状态数据可以为大脑区域之间的功能连接提供证据。行为表现的各个方面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的异常有关。尽管静息态网络对于理解正常和紊乱的认知具有潜在的重要性，但它在人类认知神经科学中仍然是一个知之甚少的现象。我们寻求更好地了解相关的氧气波动的起源和意义，通过表征它们在高的空间和时间分辨率，并确定与他们在休息和任务执行过程中的电生理信号。我们将以一种新的方式使用氧极谱法。在静息状态fMRI扫描的引导下，我们将多个铂微电极插入猕猴大脑，以验证和表征氧浓度的相关波动。我们将同时记录来自这些电极的电生理信号，并询问电生理频谱的哪一部分（慢皮层电位、局部场电位、多单位活动）与任务驱动和/或静息态相关的氧波动相关。为了实现这一点，我们将利用极谱法优于功能磁共振成像的优势，包括共同定位和同时的氧和电信号，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氧波动的传递函数，以及该传递函数是否是网络特异性的，取决于皮质层 记录或反映动物的正在进行的行为状态（例如，工作、睡眠和麻醉）。这项工作的临床意义在于，它将导致更好地使用功能磁共振成像信息的诊断，预后和脑疾病的病因。在高层次上，它的科学意义在于它将为我们理解大规模大脑结构和认知过程提供信息。

DESCRIPTION (provided by applicant): 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 activit) 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-scae brain architecture and cognitive processing.