MULTIELECTRODE & IMAGING ANALYSIS OF CULTURED NETWORKS

目前，在动物体内行为研究方面存在很大差距。 学习和记忆，以及细胞机制的体外研究 突触可塑性。将创建一种神经科学研究工具， 通过提供培养的皮质神经元网络来弥合这一差距 拥有计算机模拟的身体，以及虚拟现实，在其中 举止得体。这一研究体外学习的新范式是通过 计算能力和多电极阵列基板的最新进展。 计算机和培养的神经之间的长期双向接口 将创建网络。识别紧急事件的软件工具 将开发网络活动模式，并用于触发 实时电刺激的分布式模式。这个 这种感觉-运动反馈环路的影响将在 使用我们定制的高速光学记录进行毫秒时间刻度 Ccd摄像机。神经元连接和形态的变化将是 然后使用我们的双光子以分钟、小时和天为尺度 激光扫描显微镜。双光子显微镜允许扩展的高分辨率 在不损害活细胞或漂白细胞的情况下进行分辨率成像 荧光标签。 显然，神经系统处理和存储信息是在 分布式时尚。单一单位的神经生理学研究可能会 忽略了分布式信息的许多新特性 正在处理。通过将多单位电生理学和光学相结合 体外系统中的非破坏性双光子成像记录 有行为能力和学习能力，就有可能观察变化 在作为学习基础的亚细胞、细胞和网络属性中 和记忆。通过对信息处理机制的研究，提出了一种新的信息处理机制 在小型神经元网络中的存储，来自 疾病或衰老可以以前所未有的详细程度进行检查。信息 关于活的神经网络如何运作将促进创造 更像人类的计算系统。

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.