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

电连接组学：一种剖析行为状态背后的大脑机制的创新方法

• 批准号: 10001808
• 负责人: Rainbo Hultman
• 金额: $ 231.75万
• 依托单位: UNIVERSITY OF IOWA
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-07 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10001808
• 关键词: Attention deficit hyperactivity disorder; Base of the Brain; Behavior; Behavioral; Behavioral Assay; Biological; Biomedical Research; Brain; Brain Diseases; Brain region; Cells; Coupled; Data; Development; Disease; Dose; Etiology; Fibromyalgia; General Population; Hypersensitivity; Machine Learning; Maps; Measurable; Measurement; Mental disorders; Migraine; Modeling; Network-based; Pathology; Perceptual Disorders; Pharmacology; Play; Public Health; Role; Route; Schizophrenia; Sensory; Site; Testing; autism spectrum disorder; cell type; effective therapy; hypersensitivity desensitization; in vivo; innovation; insight; mouse model; nervous system disorder; novel; novel therapeutics; optogenetics; pre-clinical; relating to nervous system; response; sensory stimulus; single-cell RNA sequencing; tool

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.

项目概要： 了解大脑编码行为的机制是一个重大挑战 用于开发治疗神经和精神疾病的有效疗法。的 在哺乳动物模型中开发全脑神经连接测量方法 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， 通过前所未有的互联大脑收集和整合这些数据 用于阐明疾病中感觉处理改变的机制的区域。 许多神经和精神疾病是由感觉刺激引发或加剧的。 刺激，但很少有人了解这种感觉超/低， 致敏感觉处理在以下疾病的病理学中起着重要作用：自闭症谱系 自闭症（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。偏头痛尤其代表了 令人信服的感觉超敏模型，因为对感觉刺激的反应是明确的，剂量- 依赖性和可测量性。使用最先进的，多位点的体内记录在一个良好的- 特征偏头痛模型，再加上机器学习，我们将开发全网络 偏头痛背后的感觉超敏反应的电子地图。这些网络将 使用多种行为测定和偏头痛相关的 药理学操作。我们还将剖析潜在的机制， 偏头痛小鼠模型感觉超敏性脑状态的光遗传学研究 操作以及单细胞RNA-Seq，目的是确定 特定的电路、细胞和分子到这种状态。预计这一做法将大大 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被测试的感觉超敏大脑状态的工具 对于各种疾病共有的机制，2）脑电网络的特征图， 作为关于感觉超敏性大脑网络的路径的强有力的假设， 3）了解特定细胞类型和分子对细胞增殖的贡献。 大脑高度敏感总的来说，这项研究预计将提供深入了解病因 偏头痛和其他感觉过敏性疾病，这将是至关重要的发展大脑 基于网络的治疗方法。