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Neuroscience and Network Dynamics Toward Brain-Inspired Intelligence

  • Bin Hu
  • , Zhi-Hong Guan*
  • , Guanrong Chen
  • , C. L. Philip Chen
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

This article surveys the interdisciplinary research of neuroscience, network science, and dynamic systems, with emphasis on the emergence of brain-inspired intelligence. To replicate brain intelligence, a practical way is to reconstruct cortical networks with dynamic activities that nourish the brain functions, instead of using only artificial computing networks. The survey provides a complex network and spatiotemporal dynamics (abbr. network dynamics) perspective for understanding the brain and cortical networks and, furthermore, develops integrated approaches of neuroscience and network dynamics toward building brain-inspired intelligence with learning and resilience functions. Presented are fundamental concepts and principles of complex networks, neuroscience, and hybrid dynamic systems, as well as relevant studies about the brain and intelligence. Other promising research directions, such as brain science, data science, quantum information science, and machine behavior are also briefly discussed toward future applications.
Original languageEnglish
Pages (from-to)10214-10227
JournalIEEE Transactions on Cybernetics
Volume52
Issue number10
Online published28 Apr 2021
DOIs
Publication statusPublished - Oct 2022

Research Keywords

  • Artificial intelligence (AI)
  • Brain modeling
  • complex network
  • Complex networks
  • dynamic resilience
  • hybrid dynamic system
  • learning
  • Neurons
  • neuroscience
  • Sociology
  • Spatiotemporal phenomena
  • Statistics

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