Neuromorphic electronics based on copying and pasting the brain

被引:1
|
作者
Ham, Donhee [1 ,2 ]
Park, Hongkun [3 ,4 ]
Hwang, Sungwoo [2 ,5 ]
Kim, Kinam [5 ]
机构
[1] Harvard Univ, John A Paulson Sch Engn & Appl Sci, Cambridge, MA 02138 USA
[2] Samsung Adv Inst Technol, Samsung Elect, Suwon, South Korea
[3] Harvard Univ, Dept Chem & Chem Biol, Cambridge, MA 02138 USA
[4] Harvard Univ, Dept Phys, Cambridge, MA 02138 USA
[5] Samsung Elect, Hwaseong, South Korea
关键词
CMOS NANOELECTRODE ARRAY; MEMRISTOR; CIRCUIT; NETWORK; NEUROSCIENCE; DESIGN; DEVICE;
D O I
10.1038/s41928-021-00646-1
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This Perspective explores the potential of an approach to neuromorphic electronics in which the functional synaptic connectivity map of a mammalian neuronal network is copied using a silicon neuro-electronic interface and then pasted onto a high-density three-dimensional network of solid-state memories. 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.
引用
收藏
页码:635 / 644
页数:10
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