Skip to main content
SpringerLink
Log in

Brain networks

Complex topology meets simple statistics

  • News & Views
  • Published:

From Nature Neuroscience

View current issue Submit your manuscript

In this issue, Shinn et al. demonstrate a close relationship between complex brain network topology and lower-level statistical properties of neuroimaging data. They also highlight the potential of these statistical measures, which capture similarity in space and time, to provide imaging-based markers of aging and pharmacological states.

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

Fig. 1: Illustration of spatial and temporal autocorrelation in fMRI measurements of the human brain.

References

  1. Bullmore, E. & Sporns, O. Nat. Rev. Neurosci. 10, 186–198 (2009).

    Article  CAS  PubMed  Google Scholar 

  2. Shinn, M. et al. Nat. Neurosci. https://doi.org/10.1038/s41593-023-01299-3 (2023).

    Article  PubMed  Google Scholar 

  3. Fallon, J. et al. Netw. Neurosci. 4, 788–806 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Uddin, L. Q. Trends Cogn. Sci. 24, 734–746 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Friston, K. J. et al. Neuroimage 2, 45–53 (1995).

    Article  CAS  PubMed  Google Scholar 

  6. McDonough, I. M. & Nashiro, K. Front. Hum. Neurosci. 8, 409 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  7. Zou, Q. H. et al. J. Neurosci. Methods 172, 137–141 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Huntenburg, J. M., Bazin, P. L. & Margulies, D. S. Trends Cogn. Sci. 22, 21–31 (2018).

    Article  PubMed  Google Scholar 

  9. Bijsterbosch, J. D. et al. eLife 7, e32992 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Kong, R. et al. Cereb. Cortex 31, 4477–4500 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Yousefi, B., Shin, J., Schumacher, E. H. & Keilholz, S. D. Neuroimage 167, 297–308 (2018).

    Article  PubMed  Google Scholar 

  12. Roberts, J. A. et al. Nat. Commun. 10, 1056 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  13. Das, A., Murphy, K. & Drew, P. J. Phil. Trans. R. Soc. Lond. B 376, 20190635 (2021).

    Article  Google Scholar 

  14. Sadaghiani, S. & Wirsich, J. Netw. Neurosci. 4, 1–29 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Martin, C. G., He, B. J. & Chang, C. Neuroimage 244, 118590 (2021).

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

The authors acknowledge support from NIH RF1MH125931.

Author information

Authors and Affiliations

  1. Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA

    Shiyu Wang & Catie Chang

  2. Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA

    Catie Chang

  3. Department of Computer Science, Vanderbilt University, Nashville, TN, USA

    Catie Chang

Authors
  1. Shiyu Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Catie Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Catie Chang.

Ethics declarations

Competing Interests

The authors have no competing interests.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, S., Chang, C. Complex topology meets simple statistics. Nat Neurosci 26, 732–734 (2023). https://doi.org/10.1038/s41593-023-01295-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41593-023-01295-7

  • Springer Nature America, Inc.

Search

Navigation