Poster No:
1388
Submission Type:
Abstract Submission
Authors:
Jie Xia1, Jiao Li1, Huafu Chen1, Wei Liao1
Institutions:
1University of Electronic Science and Technology of China, Chengdu, Sichuan
First Author:
Jie Xia
University of Electronic Science and Technology of China
Chengdu, Sichuan
Co-Author(s):
Jiao Li
University of Electronic Science and Technology of China
Chengdu, Sichuan
Huafu Chen
University of Electronic Science and Technology of China
Chengdu, Sichuan
Wei Liao
University of Electronic Science and Technology of China
Chengdu, Sichuan
Introduction:
The human brain is an intricate network organized across multiple spatial scales [1,2]. Multiscale structural organization arises from complex biological mechanisms and provides the anatomical foundation for functional interactions [3,4]. However, the extent to which multiscale structural connectome constrains functional activity remains largely uncharted. Here, we deciphered the relationship between multiscale structural connectome and cortical activity using graph signal processing.
Methods:
By leveraging multimodal magnetic resonance imaging (MRI) datasets, we constructed an in vivo multiscale structural connectome model integrating features of white matter tractography, cortico–cortical proximity, and microstructural similarity [3,4]. Spontaneous and diverse task-evoked cortical activity derived from functional MRI was decomposed into a weighted linear combination of orthogonal eigenmodes of multiscale structural connectome [5]. We introduced multimodal structure-function decoupling (MSFD) to quantify the (de)coupling strength between functional activity and the underlying multiscale connectome [6,7]. Additionally, we investigated the potential neurobiological mechanism underlying these decoupling patterns.
Results:
We found that multiscale fusion connectome eigenmodes provide a more compact representation of spontaneous and task-evoked cortical activity, outperforming eigenmodes derived from any single connectome (Fig. 1). Moreover, the multimodal structure-function relationship was gradually decoupled from the primary sensorimotor areas to higher-order transmodal cortices, reflecting microscale structural features and macroscale functional hierarchies (Fig. 2).

·Fig. 1 Multiscale structural connectome eigenmodes constrain human brain activity.

·Fig. 2 The spatial pattern of multimodal structure-function decoupling (MSFD).
Conclusions:
These findings highlight that the multiscale cortical wiring diagram serves as a powerful anatomical scaffold in shaping macroscale intrinsic human brain function, further advancing our understanding of multiscale structure-function relationship.
Modeling and Analysis Methods:
fMRI Connectivity and Network Modeling 1
Methods Development 2
Novel Imaging Acquisition Methods:
Multi-Modal Imaging
Keywords:
Computational Neuroscience
Modeling
Tractography
Other - eigenmodes
1|2Indicates the priority used for review
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Please indicate below if your study was a "resting state" or "task-activation” study.
Resting state
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Healthy subjects
Was this research conducted in the United States?
No
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
NOTE: Any human subjects studies without IRB approval will be automatically rejected.
Yes
Were any animal research approved by the relevant IACUC or other animal research panel?
NOTE: Any animal studies without IACUC approval will be automatically rejected.
Not applicable
Please indicate which methods were used in your research:
Functional MRI
Structural MRI
Diffusion MRI
Computational modeling
For human MRI, what field strength scanner do you use?
3.0T
Which processing packages did you use for your study?
FSL
Free Surfer
Provide references using APA citation style.
[1] Betzel, R. F., & Bassett, D. S. (2017). Multi-scale brain networks. Neuroimage, 160, 73-83.
[2] van den Heuvel, M. P., Scholtens, L. H., & Kahn, R. S. (2019). Multiscale neuroscience of psychiatric disorders. Biological Psychiatry, 86(7), 512-522.
[3] Paquola, C., Seidlitz, J., Benkarim, O., Royer, J., Klimes, P., Bethlehem, R. A., & Bernhardt, B. C. (2020). A multi-scale cortical wiring space links cellular architecture and functional dynamics in the human brain. PLoS biology, 18(11), e3000979.
[4] Park, B. Y., Paquola, C., Bethlehem, R. A., Benkarim, O., Neuroscience in Psychiatry Network (NSPN) Consortium, Mišić, B., & Bernhardt, B. C. (2022). Adolescent development of multiscale structural wiring and functional interactions in the human connectome. Proceedings of the National Academy of Sciences, 119(27), e2116673119.
[5] Huang, W., Bolton, T. A., Medaglia, J. D., Bassett, D. S., Ribeiro, A., & Van De Ville, D. (2018). A graph signal processing perspective on functional brain imaging. Proceedings of the IEEE, 106(5), 868-885.
[6] Preti, M. G., & Van De Ville, D. (2019). Decoupling of brain function from structure reveals regional behavioral specialization in humans. Nature communications, 10(1), 4747.
[7] Xia, J., Liu, C., Li, J., Meng, Y., Yang, S., Chen, H., & Liao, W. (2024). Decomposing cortical activity through neuronal tracing connectome-eigenmodes in marmosets. Nature Communications, 15(1), 2289.
No