Firing feature-driven neural circuits with scalable memristive neurons for robotic obstacle avoidance.

Journal: Nature communications
PMID: 38773067

Abstract

Neural circuits with specific structures and diverse neuronal firing features are the foundation for supporting intelligent tasks in biology and are regarded as the driver for catalyzing next-generation artificial intelligence. Emulating neural circuits in hardware underpins engineering highly efficient neuromorphic chips, however, implementing a firing features-driven functional neural circuit is still an open question. In this work, inspired by avoidance neural circuits of crickets, we construct a spiking feature-driven sensorimotor control neural circuit consisting of three memristive Hodgkin-Huxley neurons. The ascending neurons exhibit mixed tonic spiking and bursting features, which are used for encoding sensing input. Additionally, we innovatively introduce a selective communication scheme in biology to decode mixed firing features using two descending neurons. We proceed to integrate such a neural circuit with a robot for avoidance control and achieve lower latency than conventional platforms. These results provide a foundation for implementing real brain-like systems driven by firing features with memristive neurons and put constructing high-order intelligent machines on the agenda.

Authors

  • Yue Yang
    Department of Nephrology, China-Japan Friendship Hospital, Beijing 100029, China.
  • Fangduo Zhu
    State Key Laboratory of Integrated Chips and Systems, Frontier Institute of Chip and System, Fudan University, Shanghai, 200433, China.
  • Xumeng Zhang
    Department of Electrical and Computer Engineering, University of Massachusetts, 100 Natural Resources Road, Amherst, Massachusetts, 01003, USA.
  • Pei Chen
    Wired Informatics, 265 Franklin Street, Suite 1702, Boston, MA 02110, USA.
  • Yongzhou Wang
    Key Laboratory of Microelectronics Device & Integrated Technology, Institute of Microelectronics of Chinese Academy of Sciences, Beijing, 100029, China.
  • Jiaxue Zhu
    Key Laboratory of Microelectronic Devices & Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China.
  • Yanting Ding
    School of Life Sciences, Shanghai University, Shanghai 200444, China.
  • Lingli Cheng
    Key Laboratory of Microelectronics Device & Integrated Technology, Institute of Microelectronics of Chinese Academy of Sciences, Beijing, 100029, China.
  • Chao Li
    McGill University Health Centre, McGill Adult Unit for Congenital Heart Disease Excellence, Montreal, Québec, Canada.
  • Hao Jiang
    Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences , 555 Zuchongzhi Road, Shanghai 201203, China.
  • Zhongrui Wang
    Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China.
  • Peng Lin
    Zhejiang Key Laboratory of Excited-State Energy Conversion and Energy Storage, Department of Chemistry, Zhejiang University, Hangzhou 310058, China.
  • Tuo Shi
    Key Laboratory of Microelectronic Devices & Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, China; Zhejiang Laboratory, Hangzhou 311122, China.
  • Ming Wang
    Brain center, Zhejiang Hospital, Hangzhou, China.
  • Qi Liu
    National Institute of Traditional Chinese Medicine Constitution and Preventive Medicine, Beijing University of Chinese Medicine, Beijing, China.
  • Ningsheng Xu
    State Key Laboratory of Integrated Chips and Systems, Frontier Institute of Chip and System, Fudan University, Shanghai, 200433, China.
  • Ming Liu
    School of Land Engineering, Chang'an University, Xi'an 710064, China; Xi'an Key Laboratory of Territorial Spatial Information, School of Land Engineering, Chang'an University, Xi'an 710064, China. Electronic address: mingliu@chd.edu.cn.

Keywords

External Resources

Popular Topics
Recent Journals