MULTIELECTRODE & IMAGING ANALYSIS OF CULTURED NETWORKS

多电极

• 批准号: 6574749
• 负责人: Steve M Potter
• 金额: $ 4.15万
• 依托单位: GEORGIA 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/6574749
• 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，体内行为学研究还存在较大差距。 学习和记忆以及细胞机制的体外研究 突触可塑性。 将创建一个神经科学研究工具 通过提供培养的皮质神经元网络来弥补这一差距 具有计算机模拟的身体和虚拟现实 表现。 这种体外学习研究的新范式是通过 计算能力和多电极阵列基板的最新进展。 计算机和培养神经元之间的长期双向接口 将创建网络。 识别紧急情况的软件工具 将开发网络活动模式并用于触发 实时分布电刺激模式。 这 该感觉运动反馈环路的影响将在 使用我们定制的高速光学记录毫秒时间尺度 CCD 相机。 神经元连接和形态的变化将 使用我们的 2 光子以分钟、小时和天为单位进行跟踪 激光扫描显微镜。 双光子显微镜允许扩展高 活细胞的高分辨率成像，而不伤害它们或漂白细胞 荧光标签。 很明显，神经系统以某种方式处理和存储信息。 分布式时尚。 单单元神经生理学研究可能 错过了分布式信息的许多新特性 加工。 通过结合多单元电生理学和光学 在体外系统中使用非破坏性 2 光子成像进行记录 有行为和学习能力，将有可能观察到变化 学习背后的亚细胞、细胞和网络特性 和记忆。 通过研究信息加工的机制 神经元小网络中的存储，精神障碍模型 疾病或衰老可以以前所未有的细节进行检查。 信息 关于活体神经网络的功能将如何促进创造 更加人性化的计算系统。