MHSA: A Multi-scale Hypergraph Network for Mild Cognitive Impairment Detection via Synchronous and Attentive Fusion

Manman Yuan, Weiming Jia, Xiong Luo, Jiazhen Ye, Peican Zhu, Junlin Li

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The precise detection of mild cognitive impairment (MCI) is of significant importance in preventing the deterioration of patients in a timely manner. Although hypergraphs have enhanced performance by learning and analyzing brain networks, they often only depend on vector distances between features at a single scale to infer interactions. In this paper, we deal with a more arduous challenge, hypergraph modelling with synchronization between brain regions, and design a novel framework, i.e., A Multi-scale Hypergraph Network for MCI Detection via Synchronous and Attentive Fusion (MHSA), to tackle this challenge. Specifically, our approach employs the Phase-Locking Value (PLV) to calculate the phase synchronization relationship in the spectrum domain of regions of interest (ROIs) and designs a multi-scale feature fusion mechanism to integrate dynamic connectivity features of functional magnetic resonance imaging (fMRI) from both the temporal and spectrum domains. To evaluate and op-timize the direct contribution of each ROI to phase synchronization in the temporal domain, we structure the PLV coefficients dynamically adjust strategy, and the dynamic hypergraph is modelled based on a comprehensive temporal-spectrum fusion matrix. Experiments on the real-world dataset indicate the effectiveness of our strategy. The code is available at https://github.com/Jia-Weiming/MHSA.

Original languageEnglish
Title of host publicationProceedings - 2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024
EditorsMario Cannataro, Huiru Zheng, Lin Gao, Jianlin Cheng, Joao Luis de Miranda, Ester Zumpano, Xiaohua Hu, Young-Rae Cho, Taesung Park
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2808-2815
Number of pages8
ISBN (Electronic)9798350386226
DOIs
StatePublished - 2024
Event2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024 - Lisbon, Portugal
Duration: 3 Dec 20246 Dec 2024

Publication series

NameProceedings - 2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

Conference

Conference2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024
Country/TerritoryPortugal
CityLisbon
Period3/12/246/12/24

Keywords

  • Brain networks
  • Hyper-graphs
  • Mild cognitive impairment
  • Multi-scale feature fusion
  • Phase-Locking Value

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