Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Correspondence
  • Published:

Reply to ‘Issues of parcellation in the calculation of structure–function coupling’

Nature Reviews Neuroscience volume 26, page 61 (2025)Cite this article

Subjects

Access through your institution
Buy or subscribe

We appreciate the thoughtful Correspondence from A. Turnbull, F. V. Lin and Z. Zhang about our recent Review (Fotiadis, P. et al. Structure–function coupling in macroscale human brain networks. Nat. Rev. Neurosci. 25, 688–704; 2024)1, in which we synthesized recent work assessing the dynamic relationship between structural and functional connectivity in the human brain, commonly referred to as structure–function coupling (SFC). We focused in the Review on studies that quantify this relationship by correlating each brain region’s structural and functional connectivity towards all other brain regions. In their Correspondence, the authors emphasize an important methodological limitation of this approach, which is that it depends on the definition of brain regions — and by extension, the brain parcellation — used (Turnbull, A., Lin, F. V. & Zhang, Z. Issues of parcellation in the calculation of structure–function coupling. Nat. Rev. Neurosci. https://doi.org/10.1038/s41583-024-00877-z; 2024)2. To address this limitation, they propose an alternative methodology to quantify SFC that does not rely upon a pre-defined parcellation scheme. The proposed surface-based approach instead projects the structural and functional connectivity to the grey matter–white matter boundary, allowing the computation of SFC at a high spatial resolution3.

Although there is merit to approaches that use few assumptions, there is also something to be learned by examining SFC using brain parcellations with different definitions of brain regions4. For instance, the use of a brain parcellation whose parcels (brain regions) have been defined using cyto-architectonic5 or myelo-architectonic6 features would allow us to study how structural connectivity shapes functional connectivity in the brain using established anatomical criteria, rather than imaging modality-defined features, such as voxel size. Beyond this point, examining SFC at different spatial scales, using brain parcellations of varying granularities, could also yield valuable intuitions. In a recent study, for instance, we investigated how intracortical myelination and excitation–inhibition balance collectively shape SFC across the cortical hierarchy; notably, we assessed this relationship at different spatial resolutions, ranging from the coarser atlas-based level to the substantially more fine-grained voxel-based level7. This approach allowed us to show that the relationship between the three variables remained qualitatively similar across scales, and thus did not depend on the spatial resolution used. More broadly, reporting on the potential dependence between SFC and the underlying spatial scale can provide critical information on whether this variable exhibits scale-free properties. Furthermore, such an exploration could elucidate how the dynamic coupling between structural and functional connectivity changes as we traverse from mesoscale to macroscale definitions of brain regions, enabling us to potentially pinpoint emergent dynamics. In the same vein, it would be particularly interesting to inspect whether SFC is more immune to the underlying spatial scale than its individual components: structural and functional connectivity. Such a finding could further identify SFC as a more robust marker of brain dynamics than structural or functional connectivity alone.

This is a preview of subscription content, access via your institution

Access options

Access through your institution

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

References

  1. Fotiadis, P. et al. Structure–function coupling in macroscale human brain networks. Nat. Rev. Neurosci. 25, 688–704 (2024).

    Article  PubMed  Google Scholar 

  2. Turnbull, A., Lin, F. V. & Zhang, Z. Issues of parcellation in the calculation of structure–function coupling. Nat. Rev. Neurosci. https://doi.org/10.1038/s41583-024-00877-z (2024).

    Article  PubMed  Google Scholar 

  3. Cole, M. et al. Surface‐based connectivity integration: an atlas‐free approach to jointly study functional and structural connectivity. Hum. Brain Mapp. 42, 3481–3499 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Fotiadis, P. & Bassett, D. S. in Connectome Analysis (eds. Schirmer, M. D. et al.) 71–105 (Academic, 2023).

  5. Amunts, K. & Zilles, K. Architectonic mapping of the human brain beyond Brodmann. Neuron 88, 1086–1107 (2015).

    Article  PubMed  Google Scholar 

  6. Glasser, M. F. & Van Essen, D. C. Mapping human cortical areas in vivo based on myelin content as revealed by T1- and T2-weighted MRI. J. Neurosci. 31, 11597–11616 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  7. Fotiadis, P. et al. Myelination and excitation-inhibition balance synergistically shape structure-function coupling across the human cortex. Nat. Commun. 14, 6115 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Panagiotis Fotiadis

  2. Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA

    Panagiotis Fotiadis & Dani S. Bassett

  3. Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA

    Panagiotis Fotiadis

  4. Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Dani S. Bassett

  5. Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Dani S. Bassett

  6. Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA

    Dani S. Bassett

  7. Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, PA, USA

    Dani S. Bassett

  8. Santa Fe Institute, Santa Fe, NM, USA

    Dani S. Bassett

  9. Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada

    Dani S. Bassett

Authors
  1. Panagiotis Fotiadis
    View author publications

    Search author on:PubMed Google Scholar

  2. Dani S. Bassett
    View author publications

    Search author on:PubMed Google Scholar

Corresponding authors

Correspondence to Panagiotis Fotiadis or Dani S. Bassett.

Ethics declarations

Competing interests

The authors declare no competing interests.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fotiadis, P., Bassett, D.S. Reply to ‘Issues of parcellation in the calculation of structure–function coupling’. Nat. Rev. Neurosci. 26, 61 (2025). https://doi.org/10.1038/s41583-024-00878-y

Download citation

  • Published:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41583-024-00878-y

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing