Aging Pattern Research On Brain Network Topology Based On Multimodal Magnetic Resonance Imaging

The process of development and aging is usually accompanied by complex structural and functional changes of human brain.Studying the aging pattern of the human brain is of vital importance to understand the cognitive ability of the brain as well as the abnormal pathological features of brain diseases.In recent years,the development of Magnetic Resonance Imaging(MRI)technology has promoted the exploration and research of brain microstructure and function.Network neuroscience provides a theoretical basis for revealing the topological structure of the human brain.It abstracts the brain as a complex network with different brain regions interconnected and working together.The nodes in the network mean different regions,and edges represent the connections between different regions in terms of function,objective structure or morphology.Brain networks include functional networks constructed by functional Magnetic Resonance Imaging(f MRI)and morphological networks constructed by structural Magnetic Resonance Imaging(s MRI),etc.Combined with multimodal brain neuroimaging technology,investigating the internal mechanism of brain through the framework of network neurology has garnered considerable attention as a key area of interest in the realm of brain science.Modeling and studying the brain network based on multimodal magnetic resonance imaging data and exploring the healthy aging pattern of network topology from different perspectives are of great significance for a deeper understanding of the aging principle of human brain and the pathological characteristics of related neurodegenerative diseases.In addition,rational and effective use of multimodal information to better understand the relationship between brain anatomy and physiological function in the aging process will also develop a new direction for brain aging research.The research work of this paper mainly includes the following three parts:First,with the basis of the traditional group-level brain function network and full account for the individual difference information of the module structure,the module guided weighted group-level network is applied to the analysis of aging patterns of healthy adults.This work constructed the weighted functional networks for three age groups respectively,and combined the network topology indicators to explore the differences in the group-level modular structure and age-related alteration patterns.The study found that the strength of connections within and between modules was negatively correlated with age,indicating that with the growth of age,functional separation and integration were weakened,and the efficiency of information exchange of brain network was reduced.The transformation and age-related trajectory of hub nodes in two age stages(young-middle age stage and middle-old age stage)were analyzed,revealing the specific spatiotemporal changes of brain functional networks during adult development and aging.These findings provide new perspectives and useful information for our understanding of the healthy aging patterns of brain networks.Second,the divergence is introduced as the similarity measure of the distribution of morphological measurement,and the morphological similarity network is constructed at the individual level to study the healthy aging pattern of human brain.Using multiple public datasets,this work constructed individual-level morphological networks based on Jensen-Shannon divergence and analyzed the relevant topological metrics.This work systematically studied the healthy aging pattern of brain morphological network topological organization from the global and local perspectives,respectively.The research found that group-level hubs were mainly distributed in the default mode network,visual network and sensorimotor network,and were stable across different age groups.Further nodal-level analysis showed the evolution trajectory of different node module attributes,indicating that they play different types of topological roles in the aging process of morphological networks.The research results show that the brain morphological network is reconstructed in the process of development and aging,which also provides a valuable basis for better understanding the aging process of the brain.Third,by integrating multimodal magnetic resonance data,this work used the Spearman rank correlation of structural network and functional network as the structure-function(SC-FC)coupling to describe the cortical topology of structurefunction coupling and explore its aging mode.It is found that the SC-FC coupling strength was not evenly distributed in the whole brain,and there were obvious spatial/subnet differences.The SC-FC coupling of visual network was the strongest,and the coupling strength of limbic network and subcortical network was the weakest.The SC-FC coupling strength of whole brain and age was significantly negatively correlated,and there was also a significant age-dependence of regional SC-FC coupling.This study demonstrates that the underlying structure of the brain provides the basis for function,and explores the cognitive neural remodeling pattern in the aging process,which brings more evidence for the study of brain physical structure and physiological connection.