Individual Variability in the Structural Connectivity Architecture of the Human Brain

The human brain exhibits a high degree of individual variability in both its structure and function, which underlies intersubject differences in cognition and behavior. It was previously shown that functional connectivity is more variable in the heteromodal association cortex but less variable in the unimodal cortices. Structural connectivity (SC) is the anatomical substrate of functional connectivity, but the spatial and temporal patterns of individual variability in SC (IVSC) remain largely unknown. In the present study, we discovered a detailed and robust chart of IVSC obtained by applying diffusion MRI and tractography techniques to 1,724 adults (770 males and 954 females) from multiple imaging datasets. Our results showed that the SC exhibited the highest and lowest variability in the limbic regions and the unimodal sensorimotor regions, respectively. With increased age, higher IVSC was observed across most brain regions. Moreover, the specific spatial distribution of IVSC is related to the cortical laminar differentiation and myelination content. Finally, we proposed a modified ridge regression model to predict individual cognition and generated idiographic brain mapping, which was significantly correlated with the spatial pattern of IVSC. Overall, our findings further contribute to the understanding of the mechanisms of individual variability in brain SC and link to the prediction of individual cognitive function in adult subjects.

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Publication Details

Journal
Journal of Neuroscience
Published
2024-12-12
DOI
https://doi.org/10.1523/jneurosci.2139-23.2024
Citations
6
Primary Topic
Advanced Neuroimaging Techniques and Applications
Type
article
Field-Weighted Citation Impact
2.43

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article

Individual Variability in the Structural Connectivity Architecture of the Human Brain

Guangfang Liu, Guozheng Feng, Zhenzhao Liu, Xinyi Dong et al.
6 citations
Journal of Neuroscience
Advanced Neuroimaging Techniques and Applications
2.43
article

Individual Variability in the Structural Connectivity Architecture of the Human Brain

Guangfang Liu, Guozheng Feng, Zhenzhao Liu, Xinyi Dong, Aocai Yang, Weijie Huang, Ni Shu, Zhanjun Zhang, Amir Shmuel, Li Su, Haojie Chen, Guolin Ma
article en
6 citations

Abstract

The human brain exhibits a high degree of individual variability in both its structure and function, which underlies intersubject differences in cognition and behavior. It was previously shown that functional connectivity is more variable in the heteromodal association cortex but less variable in the unimodal cortices. Structural connectivity (SC) is the anatomical substrate of functional connectivity, but the spatial and temporal patterns of individual variability in SC (IVSC) remain largely unknown. In the present study, we discovered a detailed and robust chart of IVSC obtained by applying diffusion MRI and tractography techniques to 1,724 adults (770 males and 954 females) from multiple imaging datasets. Our results showed that the SC exhibited the highest and lowest variability in the limbic regions and the unimodal sensorimotor regions, respectively. With increased age, higher IVSC was observed across most brain regions. Moreover, the specific spatial distribution of IVSC is related to the cortical laminar differentiation and myelination content. Finally, we proposed a modified ridge regression model to predict individual cognition and generated idiographic brain mapping, which was significantly correlated with the spatial pattern of IVSC. Overall, our findings further contribute to the understanding of the mechanisms of individual variability in brain SC and link to the prediction of individual cognitive function in adult subjects.

Journal of NeuroscienceVol. 45(5)
Montreal Neurological Institute and Hospital (CA), Peking University (CN), Beijing Normal University (CN), China-Japan Friendship Hospital (CN), Neuroscience Institute (IT), Insigneo (GB), McGill University (CA)
National Natural Science Foundation of China, State Key Laboratory of Cognitive Neuroscience and Learning, Fundamental Research Funds for the Central Universities
Quality Education
Openalex Percentile: Top 10%
Advanced Neuroimaging Techniques and Applications
2.43
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