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Human Brainnetome Atlas and Its Potential Applications in Brain-Inspired Computing

  • Lingzhong Fan
  • Hai Li
  • Shan Yu
  • Tianzi JiangEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10087)

Abstract

Brain atlases are considered to be the cornerstone of neuroscience, but most available brain atlases lack fine-grained parcellation results and do not provide information about functionally important connectivity. Recently, novel methodologies and computerized brain mapping techniques could be used to explore the structure, function, and spatio-temporal changes in the human brain. The human Brainnetome Atlas is an in vivo map that includes fine-grained functional brain subregions and detailed anatomical and functional connection patterns for each area. These features should enable researchers to describe the large scale architecture of the human brain more accurately. Using the human Brainnetome Atlas, researchers could simulate and model brain networks using informatics and simulation technologies to elucidate the basic organizing principles of the brain. Others could use this same atlas to design novel neuromorphic systems that are inspired by the architecture of the brain. Therefore, this cutting-edge human Brainnetome Atlas paves the way for constructing an even more fine-grained atlas of the human brain and offers the potential for applications in brain-inspired computing.

Keywords

Brainnetome Atlas Connectivity Diffusion tensor imaging Brain-inspired computing 

Notes

Acknowledgements

We thank Yu Zhang, Yong Yang, Junjie Zhuo, and Jiaojian Wang for their help with manuscript preparation and Rhoda E. and Edmund F. Perozzi for editing assistance and discussions. This work was partially supported by the National Key Basic Research and Development Program (973) (Grant No. 2011CB707801 and 2012CB720702), the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDB02030300), the Natural Science Foundation of China (Grant Nos. 91432302, 91132301, 31620103905, 81270020 and 81501179).

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Lingzhong Fan
    • 1
  • Hai Li
    • 1
    • 2
  • Shan Yu
    • 1
    • 3
  • Tianzi Jiang
    • 1
    • 2
    • 3
    • 4
    • 5
    Email author
  1. 1.Brainnetome Center, Institute of AutomationChinese Academy of SciencesBeijingChina
  2. 2.National Laboratory of Pattern Recognition, Institute of AutomationChinese Academy of SciencesBeijingChina
  3. 3.CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of AutomationChinese Academy of SciencesBeijingChina
  4. 4.Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
  5. 5.The Queensland Brain InstituteUniversity of QueenslandBrisbaneAustralia

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