MULTIELECTRODE & IMAGING ANALYSIS OF CULTURED NETWORKS

多电极

• 批准号: 2839944
• 负责人: Steve M Potter
• 金额: $ 31.11万
• 依托单位: CALIFORNIA INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-04-01 至 2003-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2839944
• 关键词: animal tissue; cerebral cortex; charge coupled device camera; computational neuroscience; computer program /software; electrophysiology; laboratory rat; learning; memory; microelectrodes; neural information processing; neurons; neurophysiology; technology /technique development; time resolved data; tissue /cell culture

At present, there is a large gap between in vivo behavioral studies of learning and memory, and in vitro studies of the cellular mechanisms of synaptic plasticity. A neuroscience research tool will be created that bridges this gap by providing a network of cultured cortical neurons with a computer-simulated body, and a virtual reality in which to behave. This new paradigm for studying learning in vitro is enabled by recent advances in computing power and multi-electrode array substrates. A long-term, 2-way interface between a computer and a cultured neural network will be created. Software tools that recognize emergent patterns of network activity will be developed, and used to trigger distributed patterns of electrical stimulation in real time. The effects of this sensory-motor feedback loop will be studied at the millisecond time scale by optical recording using our custom high-speed CCD camera. Changes in neuronal connectivity and morphology will be followed on the scale of minutes, hours and days using our 2-photon laser scanning microscope. Two-photon microscopy allows extended high- resolution imaging of living cells without harming them or bleaching the fluorescent label. It is clear that neural systems process and store information in a distributed fashion. Single-unit neurophysiology research is likely to miss many of the emergent properties of distributed information processing. By combining many-unit electrophysiology and optical recording with non-destructive 2-photon imaging in an in vitro system capable of behaving and learning, it will be possible to observe changes in subcellular, cellular, and network properties that underlie learning and memory. By studying the mechanisms of information processing and storage in small networks of neurons, models of mental impairment from disease or aging can be examined with unprecedented detail. Information about how living neural networks function will promote the creation of more human-like computing systems.

目前，体内行为研究之间存在很大差距 学习和记忆，以及对细胞机制的体外研究 突触可塑性。 将创建神经科学研究工具 通过提供培养的皮质神经元网络来桥接这一差距 具有计算机模拟的身体，以及一个虚拟现实 表现。 这种用于在体外学习学习的新范式由 计算功率和多电极阵列基板的最新进展。 计算机和培养的神经之间的长期2路接口 将创建网络。 识别出现的软件工具 将开发网络活动的模式，并用于触发 实时的电刺激的分布模式。 这 将研究此感觉运动反馈回路的效果 使用我们的自定义高速记录，通过光学记录来毫秒尺度 CCD相机。 神经元连通性和形态的变化将是 随后使用我们的2光子进行数分钟，小时和几天的规模 激光扫描显微镜。 两光子显微镜允许延长 分辨率成像活细胞而不会损害它们或漂白 荧光标签。 显然，神经系统处理并将信息存储在一个 分布式时尚。 单单元神经生理学研究可能会 错过分布式信息的许多新兴属性 加工。 通过组合多个单元电生理学和光学 在体外系统中使用非破坏性2光子成像记录 有能力表现和学习，可以观察变化 在学习基础的亚细胞，细胞和网络属性中 和内存。 通过研究信息处理的机制和 在小型神经元网络中存储，心理障碍模型 疾病或衰老可以用前所未有的细节检查。 信息 关于生活神经网络的功能如何促进创建 更类似人类的计算系统。