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Diffusion time-related structure-function coupling reveals differential association with inter-individual variations in body mass index.
Namgung, Jong Young; Park, Yeongjun; Park, Yunseo; Kim, Chae Yeon; Park, Bo-Yong.
Affiliation
  • Namgung JY; Department of Data Science, Inha University, Incheon, Republic of Korea.
  • Park Y; Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Republic of Korea.
  • Park Y; Department of Data Science, Inha University, Incheon, Republic of Korea.
  • Kim CY; Department of Data Science, Inha University, Incheon, Republic of Korea.
  • Park BY; Department 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. Electronic address: boyong.park@inha.ac.kr
Neuroimage ; 291: 120590, 2024 May 01.
Article in En | MEDLINE | ID: mdl-38548036
ABSTRACT
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.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Brain / Diffusion Tensor Imaging Limits: Humans Language: En Journal: Neuroimage Journal subject: DIAGNOSTICO POR IMAGEM Year: 2024 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Brain / Diffusion Tensor Imaging Limits: Humans Language: En Journal: Neuroimage Journal subject: DIAGNOSTICO POR IMAGEM Year: 2024 Document type: Article