CRCNS: Quantitation of Network Dysfunction in Epilepsy-Understanding the Inhibitory Restraint

CRCNS：癫痫网络功能障碍的定量 - 了解抑制性约束

• 批准号: 8837173
• 负责人: Scott C Baraban
• 金额: $ 33.14万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-15 至 2019-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8837173
• 关键词: Animal Experiments; Brain; Calcium; Computational Technique; Computer Analysis; Computer Simulation; Data; Data Analyses; Data Set; Depressed mood; Development; Dose; Drug Targeting; DsRed; Electric Stimulation; Engineering; Epilepsy; Excision; Failure; Future; Image; Individual; Interneurons; Intervention; Investigation; Label; Light; Mathematics; Measurement; Measures; Mentors; Methods; Microscope; Microscopy; Modeling; Nature; Nervous system structure; Neuraxis; Neurons; Neurosciences; Operative Surgical Procedures; Organism; Population; Postdoctoral Fellow; Principal Investigator; Research; Resolution; Runaway; Seizures; Series; Simulate; Societies; Structure; Synapses; System; Techniques; Testing; Time; Tissues; Training and Education; Transgenic Organisms; Transplantation; Validation; Vertebrates; Zebrafish; base; design; graduate student; improved; inhibitory neuron; interdisciplinary collaboration; network dysfunction; neural circuit; prevent; programs; reconstruction; relating to nervous system; research study; response; restraint; simulation; spatiotemporal; undergraduate student

DESCRIPTION (provided by applicant): We propose a theoretical-experimental program to quantitate seizure activity with neuronal resolution in the intact larval zebrafish central nervous system. Our study is made possible by recent advances in light-sheet microscopy, and theoretical and algorithmic advances in the analysis of large neural imaging datasets. Light-sheet microscopy has both excellent spatial and temporal resolution and is capable of virtually complete volumetric coverage of the larval zebrafish central nervous system. This, along with advanced statistical and computational techniques, allows us to quantify neural dynamics in the zebrafish brain with unprecedented accuracy. Because of the structure of neural circuits, inhibitory neuronal populations typically surround excited regions, protecting the brain from runaway excitatory (ictal) activity that is generated when a seizure forms. However, repeated waves of ictal activity can break down the surround inhibition, allowing a seizure to propagate. With high-resolution microscopy and state-of-the-art computational analysis and simulation methods, we will study how coherent ictal activity generated during seizures interacts with the surround inhibition (often called the 'inhibitory restraint') that is the brain's response to the seizure. A precise understanding of how coherent excitations interact with and depress inhibition in interneuron populations would provide a powerful control paradigm for spatial and temporal intervention in seizure formation and propagation. Furthermore, although computer simulations have been performed using detailed synaptic connectivity reconstructions from anatomical data, simulations derived, then validated in the same organism would be a transformative contribution to the study of seizures and more generally to neuroscience. This study combines the experimental, theoretical, and validation aspects of a neuroscience investigation into a unified whole in the study of a large, intact neuronal network for the first time. Although, for technical reasons, this approach is limited to the larval zebrafish, a small, transparent organism, it could radically improve our understanding of how protective mechanisms in meso-scale neuronal systems can fail in vertebrates. Our proposed study will provide information that could guide future seizure interventions such as neuron transplantation, electrical stimulation, surgical tissue removal or drug targeting of neuronal populations and synapses that most effectively prevent seizure formation and propagation. The education and training of the graduate students and postdocs involved in our program will be integrated with every aspect of the research. Undergraduate students will be involved in the research and mentored. The investigation is multi-institutional and builds on existing interdisciplinary collaborations in engineering, developmental neuroscience, epilepsy and mathematics.

描述（由申请人提供）：我们提出了一个理论实验计划，通过完整幼虫斑马鱼中枢神经的神经元分辨率来定量癫痫发作活动 系统。 我们的研究是由于光片显微镜的最新进展以及大型神经成像数据集分析的理论和算法的进步而成为可能的。 光片显微镜具有出色的空间和时间分辨率，并且能够几乎完全覆盖幼虫斑马鱼中枢神经系统。 这与先进的统计和计算技术一起，使我们能够以前所未有的精度量化斑马鱼大脑中的神经动力学。 由于神经回路的结构，抑制性神经元群通常围绕兴奋区域，保护大脑免受癫痫发作时产生的失控兴奋（发作）活动的影响。 然而，重复的发作活动会破坏周围抑制，导致癫痫发作蔓延。 借助高分辨率显微镜和最先进的计算分析和模拟方法，我们将研究癫痫发作期间产生的连贯发作活动如何与周围抑制（通常称为“抑制性抑制”）相互作用，周围抑制是大脑对癫痫发作的反应。发作。 精确理解相干激发如何与中间神经元群体相互作用并抑制抑制，将为癫痫形成和传播的空间和时间干预提供强大的控制范式。 此外，尽管计算机模拟是使用解剖数据中详细的突触连接重建来进行的，但在同一生物体中导出并验证的模拟将对癫痫研究乃至更广泛的神经科学做出变革性贡献。 这项研究首次将神经科学研究的实验、理论和验证方面结合成一个统一的整体，研究大型、完整的神经元网络。 尽管由于技术原因，这种方法仅限于斑马鱼幼虫（一种小型透明生物体），但它可以从根本上提高我们对脊椎动物中尺度神经元系统保护机制如何失效的理解。 我们提出的研究将提供可以指导未来癫痫发作干预措施的信息，例如神经元移植、电刺激、手术组织切除或针对神经元群和突触的药物靶向，最有效地防止癫痫发作形成和传播。 参与我们项目的研究生和博士后的教育和培训将融入研究的各个方面。 本科生将参与研究并接受指导。 这项调查是多机构合作的，建立在工程、发育神经科学、癫痫和数学领域现有的跨学科合作的基础上。