Biophysical Basis of Functional Connectivity by MRI

总结/摘要 本研究的总体目标是验证静息状态下区域间的相关性 MRI信号波动（rsfMRI）可靠地测量大脑区域之间的功能连接（FC）， 量化来自MRI的调节rsFC的因素，并验证神经生物学和行为学 具体干预措施后rsFC变化的相关性。我们的目标是继续我们的研究功能 非人灵长类动物（NHP）感觉运动系统的结构，使用多模式测量 神经回路受到干扰前后的神经活动。我们将建立fMRI数据如何与 使用光遗传学和电生理学技术获得的连接性的其他度量， 由特定的、有针对性的干预引起的神经回路的变化，沿着它们的功能 后果这些研究对于解释人类的功能磁共振成像研究是重要的， 广泛使用，但以前没有得到适当的验证。这些研究可以使用 只有在大脑结构类似人类的动物身上才有侵入性技术。我们将使用高分辨率 （亚毫米）功能磁共振成像在9.4T，以评估介观尺度网络内的一个明确的功能区域， 猴子的躯体感觉皮层，在那里我们可以测量休息状态相关性的空间模式， 皮质层，并验证其解释与电生理信号和解剖示踪剂。我们将： (1)定量S1、S2、丘脑和半球间亚区rsFC的层分辨模式 区域，并将振动触觉和层特异性微电极刺激与rsFC进行比较 数据大脑皮层呈现层状结构，但rsFC的层状分布知之甚少。我们 将证实CBV比BOLD提供更忠实的精细尺度连接性度量：（2）量化 选择性去传入的输入（i）脊髓（ii）丘脑，和（iii）区3b的S1，对模式和 rsFC和行为的优势。我们将展示驾驶员输入的中断如何改变rsfMRI之间的相关性。 （3）确定和比较参与的网络， 使用rsFC数据的不同细胞群体的光遗传学刺激。通过比较光遗传学和功能磁共振成像 通过比较不同转染病毒的rsFC反应，我们可以评估选择性转染病毒对rsFC的相对贡献。 兴奋性锥体或抑制性中间神经元的激活，或兴奋性神经元的抑制，局部在S2 在相互连接的大脑区域的网站和网络水平。对于每一组实验，我们将获得 在相同动物中进行rsfMRI和侵入性多电极测量，以定量比较不同的 神经活动和解剖连接的指标。我们还将熟练地测量动物的行为 用于确定干预后和恢复后rsFC变化的具体影响。我们认为 所提出的研究对于验证静息状态功能的神经基础具有相当重要的意义。 连接的措施，并对人类功能磁共振成像研究及其应用的直接影响。

SUMMARY / ABSTRACT The overall goals of the research proposed are to verify whether inter-regional correlations in resting state fluctuations of MRI signals (rsfMRI) reliably measure functional connectivity (FC) between brain regions, to quantify factors that modulate rsFC derived from MRI, and to validate the neurobiological and behavioral relevance of changes in rsFC following specific interventions. We aim to continue our studies of the functional architecture of the sensorimotor system in non-human primates (NHPs) using multi-modal measurements of neural activity before and after perturbations of neural circuits. We will establish how fMRI data correlate with other metrics of connectivity obtained using optogenetic and electrophysiological techniques, and quantify changes in neural circuits that result from specific, targeted interventions, along with their functional consequences. These studies are important for the interpretation of fMRI studies in humans that are in widespread use but which have not previously been properly validated. Such studies can be performed using only invasive techniques in animals whose brain architecture resembles humans. We will use high resolution (sub-millimeter) fMRI at 9.4T to assess mesoscopic scale networks within a well defined functional region of somatosensory cortex in monkeys, where we can measure spatial patterns of resting state correlations in cortical layers and validate their interpretation with electrophysiological signals and anatomic tracers. We will: (1) Quantify laminar-resolved patterns of rsFC in sub-regions of S1, S2, thalamus and inter-hemispheric regions, and compare networks engaged by vibrotactile and layer-specific microelectrode stimulation with rsFC data. Cerebral cortex exhibits a laminar structure, but the laminar distribution of rsFC is poorly understood. We will confirm that CBV provides more faithful metrics of fine-scale connectivity than BOLD: (2) Quantify effects of selective deafferentation of inputs from (i) spinal cord (ii) thalamus, and (iii) area 3b of S1, on the patterns and strengths of rsFC and behavior. We will show how disruption of driver inputs alters rsfMRI correlations between regions in a layer-specific and functionally-relevant manner: (3) Identify and compare networks engaged by optogenetic stimulation of different cell populations with rsFC data. By comparing optogenetic vs fMRI responses for different transfection viruses we can assess the relative contributions to rsFC of selective activation of excitatory pyramidal or inhibitory interneurons, or inhibition of excitatory neurons, locally at the S2 site and at the network level at interconnected brain regions. For each set of experiments we will acquire rsfMRI and invasive multi-electrode measurements in the same animals to quantitatively compare different metrics of neural activity and anatomical connections. We will also measure animal behaviors in skilled hand use to identify specific effects of changes in rsFC after intervention and with recovery. We believe that the proposed studies have considerable importance for validating the neural basis of resting state functional connectivity measures, and have direct implications for human fMRI studies and their applications.