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，以量化癫痫活性，并在完整的幼虫斑马鱼中心神经中使用神经元分辨率 系统。 灯场显微镜的最新进展以及大型神经成像数据集的分析中的理论和算法进步使我们的研究成为可能。 灯表显微镜具有出色的空间和时间分辨率，并且能够几乎完全对幼虫斑马鱼中枢神经系统的体积覆盖。 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，抑制性神经元种群通常围绕激发区域，保护大脑免受癫痫发作形成时产生的失控兴奋性（ICTAL）活性。 然而，反复的发作性活性波可以分解周围的抑制，从而使癫痫发作传播。 通过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相干性无性活性与周围抑制作用（通常称为“抑制性约束”）是大脑对癫痫发作的反应。 对连贯性激发与中间神经元种群中的相互作用和下降抑制方式的精确理解将为空间和时间干预的癫痫发作形成和传播提供强大的控制范式。 此外，尽管已经使用解剖学数据中的详细突触连通性重建进行了计算机模拟，但在同一生物体中得出的模拟，将是对癫痫发作的研究和对神经科学的更一般性研究的变革性贡献。 这项研究将神经科学研究的实验，理论和验证方面结合在一起，首次研究了大型完整神经元网络的整体。 尽管出于技术原因，这种方法仅限于幼虫斑马鱼，一种透明的小生物，它可以从根本上提高我们对脊椎动物中肾小管神经元系统中保护机制的理解。 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，手术组织去除或药物靶向神经元种群和突触的药物靶向，最有效地防止癫痫发作和传播。 参与我们计划的研究生和博士后的教育和培训将与研究的各个方面集成。 本科生将参与研究并受到指导。 该调查是多机构的，并建立在工程，发育神经科学，癫痫和数学方面的现有跨学科合作的基础上。