AVNIEL S GHUMAN (2016-05-01 to 2018-04-30) Neural basis of local and circuit-level spontaneous and task-evoked hemodynamic brain activity. Amount: $423500
? DESCRIPTION (provided by applicant) Understanding how neural regions interact, both during behavioral tasks and spontaneously (e.g. at rest), is critical for studying healthy and disordered brain networks. Many studies have measured hemodynamic brain activity (fMRI), but the neural basis of hemodynamic functional connectivity remains unclear. For spontaneous functional connectivity in particular, hemodynamic measures of functional connectivity are in a low frequency (< 0.1 Hz) range while the corresponding networks found by electrophysiological measures show distinct frequency selectivity at a much faster time scale (>1 Hz). A critical conundrum for understanding spontaneous functional connectivity is: do these slow hemodynamic fluctuations arise simply as the result of the non- specific temporal smoothing that results from the slow biomechanical response of blood vessels (e.g. the hemodynamic impulse response function) or do these slow hemodynamic oscillations reflect frequency-specific neural oscillations (e.g. specific neural sub-types) or specifically low frequency neural events? Furthermore, do these spontaneous neural-vascular relationships arise from the same mechanisms as evoked brain activity or do these involve a different subset of neural interactions? Previous studies have been limited by inferring the neural underpinning of hemodynamic functional connectivity based on general spatial overlap of circuits, only examining temporal correspondence between measures, or being unable to examine the neural response across distributed circuits. We will use the approach of simultaneous multimodal recordings of electrophysiological and hemodynamic fluctuations via concurrent magnetoencephalography (MEG) and functional near infrared spectroscopy (fNIRS). In conjunction with concurrent fNIRS/fMRI/EEG, this innovative multimodal approach affords a unique opportunity to simultaneously record and co-localize neural and hemodynamic activity during interregional communication in the human brain, overcoming many limitations of previous studies. The objective in this application is to describe the correspondence between the neural and hemodynamic signals during both spontaneous and evoked tasks in two important brain networks, a circuit in the somatomotor network and one in the frontoparietal network. We propose the following two specific aims: 1. Define the regional relationship between the hemodynamic activity and the spectral properties of spontaneous and evoked electrophysiological activity. 2. Define the spatiotemporal circuit-level relationship between spontaneous and evoked hemodynamic and electrophysiological activity. The significance of this work is that its successful completion will provide a direct connection between the neural and hemodynamic underpinnings of two critical brain circuit phenomena: spontaneous brain activity and interregional communication. Determining the electrophysiological underpinnings of the brain's hemodynamic functional organization is a key step in understanding the biological basis and interpretation of hemodynamic measures of functional connectivity.
？描述（由申请人提供）了解神经区域在行为任务和自发（例如在休息）期间如何相互作用对于研究健康和无序的脑网络是至关重要的。许多研究已经测量了血流动力学大脑活动（fMRI），但血流动力学功能连接的神经基础仍不清楚。特别是对于自发功能连接，功能连接的血液动力学测量在低频（<0.1Hz）范围内，而通过电生理测量发现的相应网络在更快的时间尺度（> 1Hz）显示出不同的频率选择性。理解自发功能连接的一个关键难题是：这些缓慢的血流动力学波动是由于血管生物力学反应缓慢（例如血流动力学脉冲反应功能）导致的非特异性时间平滑的结果，还是这些慢血流动力学振荡反映频率特定的神经振荡（例如特定的神经亚型）或特定的低频神经事件？此外，这些自发的神经 - 血管关系是否来自与诱发大脑活动相同的机制，还是涉及不同的神经相互作用子集？以前的研究受限于基于电路的一般空间重叠推断血流动力学功能连接的神经基础，仅检查测量之间的时间对应，或者无法检查分布式电路中的神经响应。我们将使用同时多模式记录电生理和血流动力学波动的方法，通过并发脑磁图（MEG）和功能性近红外光谱（fNIRS）。与并行的fNIRS / fMRI / EEG相结合，这种创新的多模式方法提供了一个独特的机会，可以在人类大脑的区域间通信中同时记录和共同定位神经和血液动力学活动，克服了以往研究的许多局限性。本申请的目的是描述两个重要脑网络中的自发和诱发任务期间神经和血液动力学信号之间的对应关系，即躯体运动网络中的电路和前额叶网络中的电路。我们提出以下两个具体目标：1。确定血流动力学活动与自发和诱发电生理活动的光谱特性之间的区域关系。 2.定义自发性和诱发性血液动力学和电生理活动之间的时空回路水平关系。这项工作的重要性在于它的成功完成将提供两个关键脑回路现象的神经和血液动力学基础之间的直接联系：自发性大脑活动和区域间通信。确定大脑血液动力学功能组织的电生理学基础是理解功能连接的血液动力学测量的生物学基础和解释的关键步骤。
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