Resting-state Neural Networks in Awake Rodents

项目摘要/摘要 大脑是一个高度互联的网络系统，由分布的大脑区域协调维持 正常的大脑功能和调节复杂的行为。越来越清楚的是，改变的大脑网络 属性是精神疾病的基础，但导致这些大规模网络变化的神经底物 仍然不为人所知。一个关键的假设是大脑中枢区域的功能障碍。中枢是大脑中具有 与大脑网络的其余部分高度相连。由于它们的核心作用，中枢功能障碍 结节可以改变全球整合过程，并被假设为大脑改变的直接原因 脑部疾病的网络功能和病理生理学。然而，在人类身上直接测试这一假设是 具有挑战性，因为选择性地操纵中枢中的活动并剖析其对大脑网络的因果影响是 很难。我们将使用尖端工具来操作中心的活动，并监控 利用静息状态功能磁共振成像研究这些手法对脑网络的影响 (RsfMRI)和清醒大鼠模型的行为。在当前的赠款周期中，我们建立了rsfmri方法。 在清醒的大鼠中，这使得我们能够可靠地测量静息状态功能连接(RSFC)并表征 大鼠的脑网络特性。我们在清醒大鼠rsfMRI方法的基础上加入了Designer 由特制药物(DREADD)、光遗传学、电生理学和动物专属激活的受体 行为。有了这些能力，我们可以因果地操纵中枢大脑区域的活动，并测量 相应的全脑网络重新配置。利用光遗传学，我们可以操纵神经活动 毫秒的时间尺度，使用DREADD，我们可以在几小时的时间尺度上操纵神经活动 一直到几天。最后，同步电生理学-功能磁共振成像将使我们能够直接将大脑网络和行为联系起来 他们的神经基础发生了变化。我们的目标是阐明操纵枢纽区域活动对 用rsfMRI、DREADDS、光遗传学和放射免疫法研究清醒大鼠的脑网络组织、功能和行为 电生理学。在目标1中，我们将记录网络属性的更改，包括网络拓扑 大脑中枢半急性抑制引起的组织和全脑RSFC动力学。有了这个细胞- DREADDS的类型特异性，我们将研究大脑中枢兴奋和抑制平衡的作用 网络动态。阐明网络节点的活动与特定脑网络之间的关系 功能，在目标2中，我们将剖析默认模式网络中每个节点的功能角色以及相关的 大鼠的行为。在目标3中，我们将进一步确定慢性抑制枢纽对长期 网络重组和行为。成功完成拟议的研究将阐明原因。 中枢的短期和长期功能障碍与脑网络重构的关系 将有助于理解引起大规模大脑网络变化的神经底物。

Project Summary/Abstract The brain is a highly inter-connected network system, with distributed brain regions orchestrating to maintain normal brain function and mediate complex behavior. It is becoming increasingly clear that altered brain network properties underlie mental illness, but the neural substrates causing these large-scale network changes remain unknown. A key hypothesis is the dysfunction of brain hub regions. Hubs are brain regions that have high degrees of connections with the rest of the brain network. Because of their central roles, dysfunction of hub nodes can change global integrative process, and has been hypothesized to be a direct cause of altered brain network function and pathophysiology of brain disorders. However, directly testing this hypothesis in humans is challenging, as selectively manipulating activity in a hub and dissecting its causal impact on brain networks is difficult. We will bridge this critical gap using cutting-edge tools to manipulate the activity of a hub, and monitor the impact of these manipulations on brain networks using resting state functional magnetic resonance imaging (rsfMRI) and behavior in an awake rat model. In the current grant cycle we have established the rsfMRI approach in awake rats, which allows us to reliably measure resting-state functional connectivity (RSFC) and characterize brain network properties in rats. We have built on our awake rat rsfMRI approach by incorporating Designer Receptors Exclusively Activated by Designer Drugs (DREADDs), optogenetics, electrophysiology and animal behaviors. With these capacities, we can causally manipulate the activity in a hub brain region, and measure the corresponding brain-wide network reconfigurations. Using optogenetics, we can manipulate neural activity on the millisecond timescale, and using DREADDs, we can manipulate neural activity on the times scales of hours to days. Finally, concurrent electrophysiology-fMRI will allow us to directly relate brain network and behavioral changes to their neural basis. Our goal is to elucidate the causal impact of manipulating hub region activity on brain network organization, function and behavior in awake rats using rsfMRI, DREADDs, optogenetics and electrophysiology. In Aim 1, we will document changes in network properties including the network topological organization and brain-wide RSFC dynamics induced by semi-acute suppression of a brain hub. With the cell- type specificity of DREADDs, we will examine the role of the balance of excitation and inhibition in a hub in brain network dynamics. To elucidate the relationship between activity of a network node and specific brain network function, in Aim 2 we will dissect the functional role of each node in the default mode network and related behaviors in rats. In Aim 3, we will further determine the impact of chronic suppression of a hub on long-term network reorganization and behavior. Successful completion of the proposed research will elucidate the causal relationship between short-term and long-term dysfunction of a hub and brain network reconfigurations, which will help understand the neural substrates causing large-scale brain network changes.