Li Shangchen, Liu Yaoyao, Hua Sihan, Wang Yu, Sun Shutong, Jiang Longhui, Lu Chengji, Liu Juntao, Shi Huaizhang, Wu Pei, Cai Xinxia, Luo Jinping
State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190, China.
School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China.
Adv Sci (Weinh). 2025 Sep;12(33):e08120. doi: 10.1002/advs.202508120. Epub 2025 Jul 23.
In pursuit of low-power consumption and surpassing computational limitations of silicon-based chips, people are beginning to seek more efficient computing devices, such as Wetware Computing. The cutting-edge approach uses living biological tissues, specifically neuronal networks, to perform computational tasks. This computing method, which is a mixture of hardware, software, and biology, is an emerging computing method that has received a lot of attention in recent years. As an important branch of organ-on-a-chip, brain-on-a-chip, which combines Micro-Electro-Mechanical System technology, electronic technology, and tissue engineering, can provide a powerful research platform for Wetware Computing. In this paper, the brain-on-a-chip for Wetware Computing is reviewed. This paper summarizes the methods for establishing a brain-on-a-chip for Wetware Computing, including the brain organoids cultured in vitro, microelectrode arrays, electrophysiology interfaces, and microfluidic platforms that make up the brain-on-a-chip. In addition, the data processing methods of brain-on-a-chip are reviewed, including encoding and decoding methods. In this paper, the focus is also on the application and the prospect of brain-on-a-chip in Wetware Computing.
为了追求低功耗并突破硅基芯片的计算限制，人们开始寻求更高效的计算设备，比如湿件计算。这种前沿方法利用活的生物组织，特别是神经网络，来执行计算任务。这种计算方法是硬件、软件和生物学的混合体，是近年来备受关注的一种新兴计算方法。作为芯片上器官的一个重要分支，结合了微机电系统技术、电子技术和组织工程的芯片上大脑，能够为湿件计算提供一个强大的研究平台。本文对用于湿件计算的芯片上大脑进行了综述。本文总结了构建用于湿件计算的芯片上大脑的方法，包括体外培养的脑类器官、微电极阵列、电生理接口以及构成芯片上大脑的微流控平台。此外，还综述了芯片上大脑的数据处理方法，包括编码和解码方法。本文还重点关注了芯片上大脑在湿件计算中的应用及前景。
