Spatial and temporal pattern of structure-function coupling of human brain connectome with development

Reviewer #1 (Public Review):

Summary:
This work studies spatiotemporal patterns of structure-function coupling in developing brains, using a large set of imaging data acquired from children and young adults aged 5-22. Magnetic resonance imaging data of brain structure and function were obtained from a publicly available database, from which structural and functional features and measures were derived. The authors examined the spatial patterns of structure-function coupling and how they evolve with brain development. This work further examined correlations between brain structure-function coupling and behaviour, and explored evolutionary, microarchitectural and genetic bases that could potentially account for the observed patterns.

Strengths:
The strength of this work is the use of currently available state-of-the-art analysis methods, along with a large set of high-quality imaging data, and comprehensive examination of structure-function coupling in developing brains. The results are comprehensive and illuminative.

Weakness:
As in most other studies, transcriptomic and cellular architectures of structure-function coupling were characterized only on the basis of a common atlas in this work.

The authors have achieved their aims in this study, and the findings provide mechanistic insights into brain development, which could inspire further basic and clinical studies along this line.

Reviewer #2 (Public Review):

Summary:
Feng et al. investigated dynamic changes in functional and structural connectivity relationships across a broad age range from childhood to early adulthood (6-22 years) using the large open-source HCP-Development database of multimodal magnetic resonance imaging (MRI). Employing a multilinear model, the study integrates three white-matter structural descriptors derived from diffusion tractography with 'microstructure profile covariance' (MPC) descriptors of relationships between cortical regions in terms of regional T1w/T2w ratio, and evaluates the coupling between these structural connectome (SC) descriptors and functional connectivity (FC) as adjusted coefficients of determination, i.e. how well the structural descriptors correspond to the functional connectivity derived from resting-state functional MRI.

The findings reveal a global increase in SC-FC coupling over development. At a regional level, coupling exhibited distinct profiles of age-related increases and decreases within and between functional networks. Individual variability captured by the presented measures of SC-FC coupling was implicated as a potential marker for the prediction of general intelligence scores. Additionally, the investigation extended to associating changes in SC-FC coupling with age to regional gene expression profiles (derived from Allen Human Brain Atlas that analysed six neurotypical adult brains), suggesting positive associations with oligodendrocyte-related pathways and negative associations with astrocyte-related genes.

Strengths:
Overall, the paper offers an interesting and valuable contribution to our understanding of structure-function relationships in the context of brain development. The commendable efforts to assess robustness across various methodologies, including brain parcellation and tractography, and reproducibility analyses on different data subsets enhance the paper's credibility. Combining cortical MPC with more usual white-matter descriptors of structural connectivity is interesting and provides (potentially) complementary information for the study of structure-function relationships with age. Analysing the changes in SC-FC coupling in relation to profiles of evolutionary expansion and functional principal gradients shows a good effort to position the present observations on SC-FC coupling within the previously described work.

Weaknesses:
Although the paper has many strengths, some aspects of the analysis need to be clarified to further support the proposed conclusions. In particular:

* The authors propose that combining cortical and white-matter connectivity measures yields a more comprehensive descriptor of SC-FC coupling. While this is likely true, the claim is not directly tested by assessing different descriptors separately and then in combination to compare the benefits of incorporating additional information for the description of SC-FC coupling.

* The authors report changes in SC-FC coupling with myelin content (reporting a positive association of coupling with regional myelin) and report positive associations between SC-FC correlation with age and expression of oligodendrocyte-related genes. Given that the computation of SC-FC coupling involves the T1w/T2w ratios within cortical regions (recognised as a myelin marker), it's plausible that these findings may be influenced by potential bias introduced by myelin-related measures in the coupling computation process.

* The authors investigate the predictive power of SC-FC coupling, suggesting non-random (but weak) prediction of individual variability in general intelligence (after age correction). However, again the benefit of using SC-FC coupling measures over using each modality alone is not evaluated. Such comparison might indicate whether the coupling is an informative measure in itself or whether it might be informative only to the extent to which it is a proxy measure of SC and FC (in case the predictive power of each separate modality is much higher).

* Generally, more information on quality assessment of tractography and parcellations (including potential age effects on processing given the wide age range of the participants), additional details on the distribution of cognitive scores used in the predictive section, and further clarifications regarding the design choices and validation strategy would provide the reader with a more detailed understanding of the cohort and proposed analytical pipeline (these minor comments are included in the private recommendations to authors).