Exploring brain structure-function relationship using constant-block PLSC via MRI data

Xiaoyu Zhao; Yanping Li; Yuan Yang; Yanlong Fu; Chenhong Yang

doi:10.1117/12.3011380

8 November 2023 Exploring brain structure-function relationship using constant-block PLSC via MRI data

Xiaoyu Zhao, Yanping Li, Yuan Yang, Yanlong Fu, Chenhong Yang

Proceedings Volume 12923, Third International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2023); 129231U (2023) https://doi.org/10.1117/12.3011380
Event: 3rd International Conference on Artificial Intelligence, Virtual Reality and Visualization (AIVRV 2023), 2023, Chongqing, China

Abstract

Brain structure-function relationships are becoming an important topic in neuroscience. The structure-function correlation can be performed at the scales of voxels, connections, networks, and so on. Most of the studies have been carried out based on brain structural and functional connections. Actually, if the studies are performed based on whole-brain voxels, which maybe lead to more interesting findings. The present work analyzed the relation of structural magnetic resonance imaging (sMRI) data-based whole-brain mean gray matter volume with resting-state functional magnetic resonance imaging (fMRI) data-based whole-brain voxel activity by adopting constant-block partial least squares correlation (PLSC) across the lifespan. Additionally, the resting-state networks, consisting of default mode, auditory, dorsal attention and sensorimotor networks have been identified by brain structure-functional relation analysis. According to our results, the whole-brain mean gray matter volume lays the foundation for brain function, which also contributes to the implementation of different activities.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xiaoyu Zhao, Yanping Li, Yuan Yang, Yanlong Fu, and Chenhong Yang "Exploring brain structure-function relationship using constant-block PLSC via MRI data", Proc. SPIE 12923, Third International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2023), 129231U (8 November 2023); https://doi.org/10.1117/12.3011380

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