Diffusion time-related structure-function coupling reveals differential association with inter-individual variations in body mass index
Body mass index (BMI) is an indicator of obesity, and recent neuroimaging studies have demonstrated that inter-individual variations in BMI are associated with altered brain structure and function. However, the mechanism underlying the alteration of structure-function correspondence according to BMI...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-05-01
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| Series: | NeuroImage |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811924000855 |
| _version_ | 1827288835131703296 |
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| author | Jong Young Namgung Yeongjun Park Yunseo Park Chae Yeon Kim Bo-yong Park |
| author_facet | Jong Young Namgung Yeongjun Park Yunseo Park Chae Yeon Kim Bo-yong Park |
| author_sort | Jong Young Namgung |
| collection | DOAJ |
| description | Body mass index (BMI) is an indicator of obesity, and recent neuroimaging studies have demonstrated that inter-individual variations in BMI are associated with altered brain structure and function. However, the mechanism underlying the alteration of structure-function correspondence according to BMI is under-investigated. In this study, we studied structural and functional connectivity derived from diffusion MRI tractography and inter-regional correlations of functional MRI time series, respectively. We combined the structural and functional connectivity information using the Riemannian optimization approach. First, the low-dimensional principal eigenvectors (i.e., gradients) of the structural connectivity were generated by applying diffusion map embedding with varying diffusion times. A transformation was identified so that the structural and functional embeddings share the same coordinate system, and subsequently, the functional connectivity matrix was simulated. Then, we generated gradients from the simulated functional connectivity matrix. We found the most apparent cortical hierarchical organization differentiating between low-level sensory and higher-order transmodal regions in the middle of the diffusion time, indicating that the hierarchical organization of the brain may reflect the intermediate mechanisms of mono- and polysynaptic communications. Associations between the functional gradients and BMI were strongest when the hierarchical structure was the most evident. Moreover, the gradient-BMI association map was related to the microstructural features, and the findings indicated that the BMI-related structure-function coupling was significantly associated with brain microstructure, particularly in higher-order transmodal areas. Finally, transcriptomic association analysis revealed the potential biological underpinnings specifying gene enrichment in the striatum, hypothalamus, and cortical cells. Our findings provide evidence that structure-function correspondence is strongly coupled with BMI when hierarchical organization is the most apparent and that the associations are related to the multiscale properties of the brain, leading to an advanced understanding of the neural mechanisms related to BMI. |
| first_indexed | 2024-04-24T11:38:24Z |
| format | Article |
| id | doaj.art-738a751f11b943a18b3e92b9b8b745ec |
| institution | Directory Open Access Journal |
| issn | 1095-9572 |
| language | English |
| last_indexed | 2024-04-24T11:38:24Z |
| publishDate | 2024-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj.art-738a751f11b943a18b3e92b9b8b745ec2024-04-10T04:28:40ZengElsevierNeuroImage1095-95722024-05-01291120590Diffusion time-related structure-function coupling reveals differential association with inter-individual variations in body mass indexJong Young Namgung0Yeongjun Park1Yunseo Park2Chae Yeon Kim3Bo-yong Park4Department of Data Science, Inha University, Incheon, Republic of KoreaDepartment of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Republic of KoreaDepartment of Data Science, Inha University, Incheon, Republic of KoreaDepartment of Data Science, Inha University, Incheon, Republic of KoreaDepartment of Data Science, Inha University, Incheon, Republic of Korea; Department of Statistics and Data Science, Inha University, Incheon, Republic of Korea; Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea; Corresponding author at: Department of Data Science, Inha University, Incheon, Republic of KoreaBody mass index (BMI) is an indicator of obesity, and recent neuroimaging studies have demonstrated that inter-individual variations in BMI are associated with altered brain structure and function. However, the mechanism underlying the alteration of structure-function correspondence according to BMI is under-investigated. In this study, we studied structural and functional connectivity derived from diffusion MRI tractography and inter-regional correlations of functional MRI time series, respectively. We combined the structural and functional connectivity information using the Riemannian optimization approach. First, the low-dimensional principal eigenvectors (i.e., gradients) of the structural connectivity were generated by applying diffusion map embedding with varying diffusion times. A transformation was identified so that the structural and functional embeddings share the same coordinate system, and subsequently, the functional connectivity matrix was simulated. Then, we generated gradients from the simulated functional connectivity matrix. We found the most apparent cortical hierarchical organization differentiating between low-level sensory and higher-order transmodal regions in the middle of the diffusion time, indicating that the hierarchical organization of the brain may reflect the intermediate mechanisms of mono- and polysynaptic communications. Associations between the functional gradients and BMI were strongest when the hierarchical structure was the most evident. Moreover, the gradient-BMI association map was related to the microstructural features, and the findings indicated that the BMI-related structure-function coupling was significantly associated with brain microstructure, particularly in higher-order transmodal areas. Finally, transcriptomic association analysis revealed the potential biological underpinnings specifying gene enrichment in the striatum, hypothalamus, and cortical cells. Our findings provide evidence that structure-function correspondence is strongly coupled with BMI when hierarchical organization is the most apparent and that the associations are related to the multiscale properties of the brain, leading to an advanced understanding of the neural mechanisms related to BMI.http://www.sciencedirect.com/science/article/pii/S1053811924000855Structure-function couplingRiemannian optimizationSynaptic communicationDiffusion timeBody mass index |
| spellingShingle | Jong Young Namgung Yeongjun Park Yunseo Park Chae Yeon Kim Bo-yong Park Diffusion time-related structure-function coupling reveals differential association with inter-individual variations in body mass index NeuroImage Structure-function coupling Riemannian optimization Synaptic communication Diffusion time Body mass index |
| title | Diffusion time-related structure-function coupling reveals differential association with inter-individual variations in body mass index |
| title_full | Diffusion time-related structure-function coupling reveals differential association with inter-individual variations in body mass index |
| title_fullStr | Diffusion time-related structure-function coupling reveals differential association with inter-individual variations in body mass index |
| title_full_unstemmed | Diffusion time-related structure-function coupling reveals differential association with inter-individual variations in body mass index |
| title_short | Diffusion time-related structure-function coupling reveals differential association with inter-individual variations in body mass index |
| title_sort | diffusion time related structure function coupling reveals differential association with inter individual variations in body mass index |
| topic | Structure-function coupling Riemannian optimization Synaptic communication Diffusion time Body mass index |
| url | http://www.sciencedirect.com/science/article/pii/S1053811924000855 |
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