Electrical connectomics: an innovative approach for dissecting brain mechanisms underlying behavioral states

项目总结： 了解大脑编码行为的机制是一个重大挑战 开发治疗神经和精神疾病的有效疗法。这个 哺乳动物模型中全脑神经连接性测量的发展 克服这一挑战的巨大潜力。在这里，我们提出了一种创新的方法 在数量空前的互联大脑中收集和集成这些数据 用于阐明疾病中感官处理发生改变的机制的区域。 许多神经和精神障碍是由感官引发或加重的 刺激，但对这种感觉高/低的大脑连接知之甚少。 敏化。感觉处理在自闭症谱系的病理中起主要作用 精神障碍(ASD)、精神分裂症、纤维肌痛、注意缺陷多动障碍(ADHD)、 感觉知觉障碍(SPD)和偏头痛。偏头痛尤其代表着一种 感官过敏的引人注目的模型，因为对感官刺激的反应是明确的，剂量- 依赖的，可衡量的。使用最先进的多地点活体记录- 特征偏头痛模型，再加上机器学习，我们将在全网范围内发展 偏头痛背后的感觉过敏的电子地图。这些网络将成为 使用多种行为分析和偏头痛相关指标验证它们在偏头痛中的作用 药理操控。此外，我们还将剖析 用光遗传回路研究偏头痛小鼠模型的感觉超敏反应脑状态 以及单细胞RNA-Seq，目的是确定 这种状态的特定电路、细胞和分子。这种方法预计将在很大程度上 促进在生物医学研究中使用基于神经振荡的大脑网络，以及 提供：1)一种用于快速识别可测试的感觉过敏性大脑状态的工具 对于跨障碍共享的机制，2)脑电网络功能图，这是 作为关于感觉超敏感脑网络的路径的强有力的假设 以及3)洞察特定细胞类型和分子对 大脑高度敏感的状态。总而言之，这项研究有望为病因学提供见解 偏头痛和其他感觉过敏障碍对大脑发育至关重要 这些疾病的基于网络的治疗。

Project Summary: Understanding the mechanisms by which the brain encodes behavior presents a major challenge for developing effective therapies with which to treat neurological and psychiatric disorders. The development of brain-wide measurements of neural connectivity in mammalian models holds great potential for overcoming this challenge. Here we propose an innovative approach for collecting and integrating such data across an unprecedented number of interconnected brain regions for use in elucidating the mechanisms by which sensory processing is altered in disease. A number of neurological and psychiatric disorders are triggered or exacerbated by sensory stimuli, yet little is understood about the brain connectivity underlying such sensory hyper/hypo- sensitization. Sensory processing plays a major role in the pathology of: autism spectrum disorders (ASD), schizophrenia, fibromyalgia, attention deficit hyperactivity disorder (ADHD), sensory perception disorders (SPDs), and migraine. Migraine in particular represents a compelling model of sensory hypersensitization, as the response to sensory stimuli is clear, dose- dependent, and measurable. Using state-of-the-art, multi-site in vivo recordings in a well- characterized migraine model, coupled with machine learning, we will develop network-wide electrical maps of the sensory hypersensitivity that underlies migraine. These networks will be validated for their roles in migraine using multiple behavioral assays and migraine-related pharmacological manipulations. We will additionally dissect the mechanisms underlying the sensory hypersensitivity brain state in a mouse model of migraine using optogenetic circuit manipulations as well as single-cell RNA-Seq, with the aim of identifying the contributions of specific circuits, cells, and molecules to this state. This approach is expected to substantially facilitate the use of neural oscillation-based brain networks in biomedical research, as well as provide: 1) a tool for rapid identification of a sensory hypersensitive brain state that can be tested for mechanisms shared across disorders, 2) a map of features of electrical brain networks, which serve as strong hypotheses regarding the routes whereby sensory hypersensitivity brain networks are regulated, and 3) insight into the contributions of specific cell types and molecules to the hypersensitive brain state. Collectively, this study is expected to provide insights into the etiology of migraine and other sensory hypersensitivity disorders that will be critical to developing brain network-based therapies for these diseases.