The heritability and structural correlates of resting-state fMRI complexity
Yi Zhen,
Yaqian Yang,
Yi Zheng,
Xin Wang,
Longzhao Liu,
Zhiming Zheng,
Hongwei Zheng,
Shaoting Tang
Affiliations
Yi Zhen
School of Mathematical Sciences, Beihang University, Beijing 100191, China; Key laboratory of Mathematics, Informatics and Behavioral Semantics, Beihang University, Beijing 100191, China
Yaqian Yang
School of Mathematical Sciences, Beihang University, Beijing 100191, China; Key laboratory of Mathematics, Informatics and Behavioral Semantics, Beihang University, Beijing 100191, China
Yi Zheng
School of Mathematical Sciences, Beihang University, Beijing 100191, China; Key laboratory of Mathematics, Informatics and Behavioral Semantics, Beihang University, Beijing 100191, China
Xin Wang
Institute of Artificial Intelligence, Beihang University, Beijing 100191, China; Key laboratory of Mathematics, Informatics and Behavioral Semantics, Beihang University, Beijing 100191, China; Zhongguancun Laboratory, Beijing 100094, China; Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University, Beijing 100191, China; PengCheng Laboratory, Shenzhen 518055, China
Longzhao Liu
Institute of Artificial Intelligence, Beihang University, Beijing 100191, China; Key laboratory of Mathematics, Informatics and Behavioral Semantics, Beihang University, Beijing 100191, China; Zhongguancun Laboratory, Beijing 100094, China; Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University, Beijing 100191, China; PengCheng Laboratory, Shenzhen 518055, China
Zhiming Zheng
Institute of Artificial Intelligence, Beihang University, Beijing 100191, China; Key laboratory of Mathematics, Informatics and Behavioral Semantics, Beihang University, Beijing 100191, China; Institute of Medical Artificial Intelligence, Binzhou Medical University, Yantai 264003, China; Zhongguancun Laboratory, Beijing 100094, China; Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University, Beijing 100191, China; PengCheng Laboratory, Shenzhen 518055, China; State Key Lab of Software Development Environment, Beihang University, Beijing 100191, China
Hongwei Zheng
Beijing Academy of Blockchain and Edge Computing, Beijing 100085, China; Correspondence to: 18, 3rd South Street, Zhongguancun, Haidian District, Beijing, 100085, P.R. China.
Shaoting Tang
Institute of Artificial Intelligence, Beihang University, Beijing 100191, China; Key laboratory of Mathematics, Informatics and Behavioral Semantics, Beihang University, Beijing 100191, China; Institute of Medical Artificial Intelligence, Binzhou Medical University, Yantai 264003, China; Zhongguancun Laboratory, Beijing 100094, China; Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University, Beijing 100191, China; PengCheng Laboratory, Shenzhen 518055, China; State Key Lab of Software Development Environment, Beihang University, Beijing 100191, China; Correspondence to: 37, Xueyuan Road, Haidian District, Beijing, 100191, P.R. China.
The complexity of fMRI signals quantifies temporal dynamics of spontaneous neural activity, which has been increasingly recognized as providing important insights into cognitive functions and psychiatric disorders. However, its heritability and structural underpinnings are not well understood. Here, we utilize multi-scale sample entropy to extract resting-state fMRI complexity in a large healthy adult sample from the Human Connectome Project. We show that fMRI complexity at multiple time scales is heritable in broad brain regions. Heritability estimates are modest and regionally variable. We relate fMRI complexity to brain structure including surface area, cortical myelination, cortical thickness, subcortical volumes, and total brain volume. We find that surface area is negatively correlated with fine-scale complexity and positively correlated with coarse-scale complexity in most cortical regions, especially the association cortex. Most of these correlations are related to common genetic and environmental effects. We also find positive correlations between cortical myelination and fMRI complexity at fine scales and negative correlations at coarse scales in the prefrontal cortex, lateral temporal lobe, precuneus, lateral parietal cortex, and cingulate cortex, with these correlations mainly attributed to common environmental effects. We detect few significant associations between fMRI complexity and cortical thickness. Despite the non-significant association with total brain volume, fMRI complexity exhibits significant correlations with subcortical volumes in the hippocampus, cerebellum, putamen, and pallidum at certain scales. Collectively, our work establishes the genetic basis and structural correlates of resting-state fMRI complexity across multiple scales, supporting its potential application as an endophenotype for psychiatric disorders.
