Reverse engineering the brain by mimicking the structure and function of neuronal networks on a silicon integrated circuit was the original goal of neuromorphic engineering, but remains a distant prospect. The focus of neuromorphic engineering has thus been relaxed from rigorous brain mimicry to designs inspired by qualitative features of the brain, including event-driven signalling and in-memory information processing. Here we examine current approaches to neuromorphic engineering and provide a vision that returns neuromorphic electronics to its original goal of reverse engineering the brain. The essence of this vision is to ‘copy’ the functional synaptic connectivity map of a mammalian neuronal network using advanced neuroscience tools and then ‘paste’ this map onto a high-density three-dimensional network of solid-state memories. Our copy-and-paste approach could potentially lead to silicon integrated circuits that better approximate computing traits of the brain, including low power, facile learning, adaptation, and even autonomy and cognition.

通过模仿硅集成电路上神经元网络的结构和功能对大脑进行逆向工程是神经形态工程的最初目标，但仍然是一个遥远的前景。因此，神经形态工程的重点已经从严格的大脑模仿放松到受大脑定性特征启发的设计，包括事件驱动的信号传递和记忆中的信息处理。在这里，我们研究了神经形态工程的当前方法，并提供了一种愿景，使神经形态电子学回归其对大脑进行逆向工程的最初目标。这一愿景的本质是使用先进的神经科学工具“复制”哺乳动物神经元网络的功能性突触连接图，然后将该图“粘贴”到固态记忆的高密度三维网络上。