The brain is perhaps the most advanced and robust computation system known. We are creating a method to study how information is processed and encoded in living cultured neuronal networks by interfacing them to a computer-generated animal, the Neurally-Controlled Animat, within a virtual world. Cortical neurons from rats are dissociated and cultured on a surface containing a grid of electrodes (multi-electrode arrays, or MEAs) capable of both recording and stimulating neural activity. Distributed patterns of neural activity are used to control the behavior of the Animat in a simulated environment. The computer acts as its sensory system providing electrical feedback to the network about the Animat's movement within its environment. Changes in the Animat's behavior due to interaction with its surroundings are studied in concert with the biological processes (e.g., neural plasticity) that produced those changes, to understand how information is processed and encoded within a living neural network. Thus, we have created a hybrid real-time processing engine and control system that consists of living, electronic, and simulated components. Eventually this approach may be applied to controlling robotic devices, or lead to better real-time silicon-based information processing and control algorithms that are fault tolerant and can repair themselves.

中文翻译：

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神经控制的动画：与模拟身体一起作用的生物大脑。

大脑可能是已知的最先进和最强大的计算系统。我们正在创建一种方法，通过在虚拟世界中将信息与计算机生成的动物（神经控制动画）连接，来研究信息如何在活体培养的神经网络中处理和编码。来自大鼠的皮层神经元在包含能够记录和刺激神经活动的电极网格（多电极阵列或 MEA）的表面上分离和培养。神经活动的分布式模式用于控制 Animat 在模拟环境中的行为。计算机充当其感觉系统，向网络提供有关 Animat 在其环境中的运动的电反馈。动画中的变化' 与产生这些变化的生物过程（例如，神经可塑性）一起研究由于与周围环境相互作用而产生的行为，以了解信息是如何在活的神经网络中处理和编码的。因此，我们创建了一个混合实时处理引擎和控制系统，由生活、电子和模拟组件组成。最终，这种方法可能会应用于控制机器人设备，或者导致更好的基于硅的实时信息处理和控制算法，这些算法具有容错性并且可以自我修复。电子元件和模拟元件。最终，这种方法可能会应用于控制机器人设备，或者导致更好的基于硅的实时信息处理和控制算法，这些算法具有容错性并且可以自我修复。电子元件和模拟元件。最终，这种方法可能会应用于控制机器人设备，或者导致更好的基于硅的实时信息处理和控制算法，这些算法具有容错性并且可以自我修复。