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FUNCTIONAL CONNECTIVITY IN THE BRAIN: A NEW APPROACH

大脑的功能连接：一种新方法

基本信息

批准号：
8994301
负责人：
Lawrence H Snyder
金额：
$ 38万
依托单位：
WASHINGTON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-02-01 至 2019-01-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8994301
关键词：
Acute Address Anesthesia procedures Animals Architecture Area Autistic Disorder Behavior Behavioral Brain Brain Diseases Brain region Child Clinical Cognition Disorders Cognitive Conscious Data Development Diagnosis Disease Distant Electrochemistry Electrodes Electrophysiology (science)Environment Etiology Event Explosion Frequencies Functional Magnetic Resonance Imaging Future Grant Health Human Individual Differences Lead Link MRI Scans Macaca Magnetic Resonance Imaging Maps Measures Mental disorders Methods Microelectrodes Modeling Morphologic artifacts Movement Neurologic Neurons Neurosciences Nuclear Physics Oxygen Pathology Patients Pattern Performance Phase Platinum Polarography Process Resistance Rest Role Schizophrenia Signal Transduction Sleep Stimulus Stroke Structure Task Performances Techniques Testing Time Tissues Work alertness awake base blood oxygen level dependent clinically significant cognitive neuroscience cognitive process disease diagnosis gray matter improved nervous system disorder neurotransmission nonhuman primate novel novel strategies outcome forecast relating to nervous system research study statistics temporal measurement

项目摘要

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.

描述（由申请人提供）：人脑中的氧含量在没有任何明显外部驱动的情况下波动。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“静息状态网络”。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联系提供证据。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。尽管静息状态网络对理解正常和无序认知具有潜在的重要性，但在人类认知神经科学中，静息状态网络仍然是一个知之甚少的现象。为了更好地理解相关氧波动的起源和意义，我们以高空间和时间分辨率对其进行表征，并识别在休息和任务执行过程中与之相关的电生理信号。我们将以一种新颖的方式使用氧极谱法。在静息状态fMRI扫描的引导下，我们将在猕猴大脑中插入多个铂微电极，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、多单元活动）与任务驱动和/或静息状态相关的氧波动有关。为了实现这一目标，我们将利用极谱相对于功能磁共振成像的优势，包括共定位和同步的氧和电信号，更高的空间和时间分辨率，对运动伪影的抵抗，以及在清醒行为的动物中易于使用。我们的总体目标是确定将电生理信号映射到氧波动上的传递函数，以及这种传递函数是否具有网络特异性，取决于皮质层