Skip to main content
SpringerLink
Log in

Developing Neuroimaging Biomarker for Brain Diseases with a Machine Learning Framework and the Brainnetome Atlas

  • RESEARCH HIGHLIGHT
  • Published:
Neuroscience Bulletin Aims and scope Submit manuscript

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

References

  1. Li A, Zalesky A, Yue W, Howes O, Yan H, Liu Y. A neuroimaging biomarker for striatal dysfunction in schizophrenia. Nat Med 2020, 26: 558–565.

    Article  CAS  Google Scholar 

  2. Lee JJ, Kim HJ, Čeko M, Park BY, Lee SA, Park H, et al. A neuroimaging biomarker for sustained experimental and clinical pain. Nat Med 2021, 27: 174–182.

    Article  CAS  Google Scholar 

  3. Gaskin DJ, Richard P. The economic costs of pain in the United States. J Pain 2012, 13: 715–724.

    Article  Google Scholar 

  4. Lindquist MA, Xu Y, Nebel MB, Caffo BS. Evaluating dynamic bivariate correlations in resting-state fMRI: A comparison study and a new approach. Neuroimage 2014, 101: 531–546.

    Article  Google Scholar 

  5. Fan L, Li H, Zhuo J, Zhang Y, Wang J, Chen L, et al. The human brainnetome atlas: A new brain atlas based on connectional architecture. Cereb Cortex 2016, 26: 3508–3526.

    Article  Google Scholar 

  6. Eickhoff SB, Stephan KE, Mohlberg H, Grefkes C, Fink GR, Amunts K, et al. A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data. Neuroimage 2005, 25: 1325–1335.

    Article  Google Scholar 

  7. Diedrichsen J, Maderwald S, Küper M, Thürling M, Rabe K, Gizewski ER, et al. Imaging the deep cerebellar nuclei: A probabilistic atlas and normalization procedure. Neuroimage 2011, 54: 1786–1794.

    Article  CAS  Google Scholar 

  8. Hastie T, Tibshirani R, Friedman J. The elements of statistical learning: data mining, inference, and prediction. Springer Science & Business Media, 2009.

  9. He B, Cao L, Xia XL, Zhang BG, Zhang D, You B, et al. Fine-grained topography and modularity of the macaque frontal pole cortex revealed by anatomical connectivity profiles. Neurosci Bull 2020, 36: 1454–1473.

    Article  Google Scholar 

  10. Zhan Y, Wei J, Liang J, Xu X, He R, Robbins TW, et al. Diagnostic classification for human autism and obsessive-compulsive disorder based on machine learning from a primate genetic model. Am J Psychiatry 2021, 178: 65–76.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Weiyang Shi, Lingzhong Fan & Tianzi Jiang

  2. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Weiyang Shi, Lingzhong Fan & Tianzi Jiang

  3. School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China

    Weiyang Shi, Lingzhong Fan & Tianzi Jiang

  4. CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Lingzhong Fan & Tianzi Jiang

  5. School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China

    Tianzi Jiang

  6. The Queensland Brain Institute, University of Queensland, Brisbane, QLD, 4072, Australia

    Tianzi Jiang

Authors
  1. Weiyang Shi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lingzhong Fan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tianzi Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tianzi Jiang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shi, W., Fan, L. & Jiang, T. Developing Neuroimaging Biomarker for Brain Diseases with a Machine Learning Framework and the Brainnetome Atlas. Neurosci. Bull. 37, 1523–1525 (2021). https://doi.org/10.1007/s12264-021-00722-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12264-021-00722-8

Search

Navigation