Constructing multi-frequency high-order functional connectivity network for diagnosis of mild cognitive impairment

Yu Zhang, Han Zhang, Xiaobo Chen, Dinggang Shen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

Human brain functional connectivity (FC) networks, estimated based on resting-state functional magnetic resonance imaging (rs-fMRI), has become a promising tool for imaging-based brain disease diagnosis. Conventional low-order FC network (LON) usually characterizes pairwise temporal correlation of rs-fMRI signals between any pair of brain regions. Meanwhile, high-order FC network (HON) has provided an alternative brain network modeling strategy, characterizing more complex interactions among low-order FC sub-networks that involve multiple brain regions. However, both LON and HON are usually constructed within a fixed and relatively wide frequency band, which may fail in capturing (sensitive) frequency-specific FC changes caused by pathological attacks. To address this issue, we propose a novel “multi-frequency HON construction” method. Specifically, we construct not only multiple frequency-specific HONs (intra-spectrum HONs), but also a series of cross-frequency interaction-based HONs (inter-spectrum HONs) based on the low-order FC sub-networks constructed at different frequency bands. Both types of these HONs, together with the frequency-specific LONs, are used for the complex network analysis-based feature extraction, followed by sparse regression-based feature selection and the classification between mild cognitive impairment (MCI) patients and normal aging subjects using a support vector machine. Compared with the previous methods, our proposed method achieves the best diagnosis accuracy in early diagnosis of Alzheimer’s disease.

Original languageEnglish
Title of host publicationConnectomics in NeuroImaging - 1st International Workshop, CNI 2017 Held in Conjunction with MICCAI 2017, Proceedings
EditorsLeonardo Bonilha, Guorong Wu, Paul Laurienti, Brent C. Munsell
PublisherSpringer Verlag
Pages9-16
Number of pages8
ISBN (Print)9783319671581
DOIs
Publication statusPublished - 2017
Externally publishedYes
Event1st International Workshop on Connectomics in NeuroImaging, CNI 2017 held in conjunction with the 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017 - Quebec City, Canada
Duration: 2017 Sep 142017 Sep 14

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10511 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other1st International Workshop on Connectomics in NeuroImaging, CNI 2017 held in conjunction with the 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017
Country/TerritoryCanada
CityQuebec City
Period17/9/1417/9/14

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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