Seidlitz, J. et al. Morphometric similarity networks detect microscale cortical organization and predict inter-individual cognitive variation. Neuron 97, 231–247 (2018). This paper introduced morphometric similarity networks as a proxy for axonal connectivity by benchmarking morphometric similarity network metrics of similarity with tract-tracing data on axonal connectivity in animal models.

Article  CAS  PubMed  Google Scholar 

Sebenius, I. et al. Robust estimation of cortical similarity networks from brain MRI. Nat. Neurosci. 26, 1461–1471 (2023). This paper introduced morphometric inverse divergence (MIND) as a flexible framework for measuring single-subject cortical similarity networks from one or more diverse MRI features, and validated MIND network phenotypes as heritable and closely coupled to cortically patterned gene expression.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zhou, L. et al. Hierarchical anatomical brain networks for MCI prediction: revisiting volumetric measures. PLoS ONE 6, e21935 (2011).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Homan, P. et al. Structural similarity networks predict clinical outcome in early-phase psychosis. Neuropsychopharmacology 44, 915–922 (2019).

Article  PubMed  PubMed Central  Google Scholar 

Tijms, B. M., Seriès, P., Willshaw, D. J. & Lawrie, S. M. Similarity-based extraction of individual networks from gray matter MRI scans. Cereb. Cortex 22, 1530–1541 (2012). This work was one of the first to generate single-subject structural MRI similarity networks and characterize their network properties.

Article  PubMed  Google Scholar 

Kong, X.-Z. et al. Mapping individual brain networks using statistical similarity in regional morphology from MRI. PLoS ONE 10, e0141840 (2015).

Article  PubMed  PubMed Central  Google Scholar 

Batalle, D. et al. Normalization of similarity-based individual brain networks from gray matter MRI and its association with neurodevelopment in infants with intrauterine growth restriction. NeuroImage 83, 901–911 (2013).

Article  PubMed  Google Scholar 

Paquola, C. et al. Microstructural and functional gradients are increasingly dissociated in transmodal cortices. PLoS Biol. 17, e3000284 (2019). This paper introduced microstructural profile covariance networks and validated them anatomically against microscopic histological benchmarks from the BigBrain dataset.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Cai, M. et al. Individual-level brain morphological similarity networks: current methodologies and applications. CNS Neurosci. Ther. 29, 3713–3724 (2023).

Article  PubMed  PubMed Central  Google Scholar 

Wang, J., Jin, S. & Li, J. Brain connectome from neuronal morphology. Preprint at Research Square https://doi.org/10.21203/rs.3.rs-3913903/v1 (2024).

Wang, J. & He, Y. Toward individualized connectomes of brain morphology. Trends Neurosci. 47, 106–119 (2024).

Article  CAS  PubMed  Google Scholar 

Lanciego, J. L. & Wouterlood, F. G. Neuroanatomical tract-tracing techniques that did go viral. Brain Struct. Funct. 225, 1193–1224 (2020).

Article  PubMed  PubMed Central  Google Scholar 

Rubinov, M., Ypma, R. J., Watson, C. & Bullmore, E. T. Wiring cost and topological participation of the mouse brain connectome. Proc. Natl Acad. Sci. USA 112, 10032–10037 (2015).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Mori, S. & Zhang, J. Principles of diffusion tensor imaging and its applications to basic neuroscience research. Neuron 51, 527–539 (2006).

Article  CAS  PubMed  Google Scholar 

Jbabdi, S. & Johansen-Berg, H. Tractography: where do we go from here? Brain Connect. 1, 169–183 (2011).

Article  PubMed  PubMed Central  Google Scholar 

Alexander-Bloch, A., Giedd, J. N. & Bullmore, E. Imaging structural co-variance between human brain regions. Nat. Rev. Neurosci. 14, 322–336 (2013).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Sporns, O., Tononi, G. & Kötter, R. The human connectome: a structural description of the human brain. PLoS Comput. Biol. 1, e42 (2005).

Article  PubMed  PubMed Central  Google Scholar 

García-Cabezas, M. Á., Zikopoulos, B. & Barbas, H. The structural model: a theory linking connections, plasticity, pathology, development and evolution of the cerebral cortex. Brain Struct. Funct. 224, 985–1008 (2019).

Article  PubMed  PubMed Central  Google Scholar 

Barbas, H. & Rempel-Clower, N. Cortical structure predicts the pattern of corticocortical connections. Cereb. Cortex 7, 635–646 (1997).

Article  CAS  PubMed  Google Scholar 

Barbas, H. General cortical and special prefrontal connections: principles from structure to function. Annu. Rev. Neurosci. 38, 269–289 (2015).

Article  CAS  PubMed  Google Scholar 

Dauguet, J. et al. Comparison of fiber tracts derived from in-vivo DTI tractography with 3D histological neural tract tracer reconstruction on a macaque brain. NeuroImage 37, 530–538 (2007).

Article  PubMed  Google Scholar 

Donahue, C. J. et al. Using diffusion tractography to predict cortical connection strength and distance: a quantitative comparison with tracers in the monkey. J. Neurosci. 36, 6758–6770 (2016).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Gajwani, M. et al. Can hubs of the human connectome be identified consistently with diffusion MRI? Netw. Neurosci. 7, 1326–1350 (2023).

Article  PubMed  PubMed Central  Google Scholar 

Cieslak, M. et al. QSIPrep: an integrative platform for preprocessing and reconstructing diffusion MRI data. Nat. Methods 18, 775–778 (2021).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Maier-Hein, K. H., Neher, P. F., Houde, J. C. & Others The challenge of mapping the human connectome based on diffusion tractography. Nat. Commun. 8, 1349 (2017).

Article  PubMed  PubMed Central  Google Scholar 

Thomas, C. et al. Anatomical accuracy of brain connections derived from diffusion MRI tractography is inherently limited. Proc. Natl Acad. Sci. USA 111, 16574–16579 (2014).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Walker, L. et al. Diffusion tensor imaging in young children with autism: biological effects and potential confounds. Biol. Psychiatry 72, 1043–1051 (2012).

Article  PubMed  PubMed Central  Google Scholar 

Lerch, J. P. et al. Mapping anatomical correlations across cerebral cortex (MACACC) using cortical thickness from MRI. NeuroImage 31, 993–1003 (2006).

Article  PubMed  Google Scholar 

Váša, F. et al. Adolescent tuning of association cortex in human structural brain networks. Cereb. Cortex 28, 281–294 (2018).

Article  PubMed  Google Scholar 

Stauffer, E.-M. et al. The genetic relationships between brain structure and schizophrenia. Nat. Commun. 14, 7820 (2023).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wright, I. C. et al. Supra-regional brain systems and the neuropathology of schizophrenia. Cereb. Cortex 9, 366–378 (1999).

Article  CAS  PubMed  Google Scholar 

Hawrylycz, M. J. et al. An anatomically comprehensive atlas of the adult human brain transcriptome. Nature 489, 391–399 (2012).

Article