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Journal Article

Diagnosis of Early Mild Cognitive Impairment Based on Associated High-Order Functional Connection Network Generated by Multimodal MRI

Authors

Wang,  Weiping

Zhang,  Shunqi

Wang,  Zhen

Luo,  Xiong

Luan,  Ping

Hramov,  Alexander

/persons/resource/Juergen.Kurths

Kurths,  Jürgen
Potsdam Institute for Climate Impact Research;

He,  Chang

Li,  Jianwu

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Citation

Wang, W., Zhang, S., Wang, Z., Luo, X., Luan, P., Hramov, A., Kurths, J., He, C., Li, J. (2024): Diagnosis of Early Mild Cognitive Impairment Based on Associated High-Order Functional Connection Network Generated by Multimodal MRI. - IEEE Transactions on Cognitive and Developmental Systems, 16, 2, 618-627.
https://doi.org/10.1109/TCDS.2023.3283406


Cite as: https://publications.pik-potsdam.de/pubman/item/item_30101
Abstract
Mild cognitive impairment (MCI) is highly likely to convert to Alzheimer’s disease (AD). The main approach to identifying MCI is using a functional connection network (FCN). Traditional FCN is used to study the correlation between two brain regions, but it lacks deeper brain interaction information. Neuroscientists found the internal functional activity pattern in the human brain is characterized by sparse, modular, and overlapping structures, and the FCN is restricted by the brain structural connection network (SCN). They can improve the estimation accuracy of FCN. Therefore, this article first constructs low order FCN (LFCN) based on brain sparse, modular, and overlapping activity patterns. Then, new high-order FCN (HFCN) is proposed based on the restrictive relationship between SCN and FCN. To combine high robustness of LFCN with high sensitivity of HFCN, a new combination strategy of LFCN and HFCN is proposed. It integrates the idea of brain modular and overlapping with the restricted relationship between SCN and FCN. Finally, the experimental results show that in early MCI (EMCI) recognition the best classification performance is acquired with an accuracy of 91.42%, which is better than similar methods. This method will be instrumental in the early recognition of clinical MCI.