Inter-Network High-Order Functional Connectivity (IN-HOFC) and its Alteration in Patients with Mild Cognitive Impairment

Han Zhang, Panteleimon Giannakopoulos, Sven Haller, Seong Whan Lee, Shijun Qiu, Dinggang Shen

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


Little is known about the high-order interactions among brain regions measured by the similarity of higher-order features (other than the raw blood-oxygen-level-dependent signals) which can characterize higher-level brain functional connectivity (FC). Previously, we proposed FC topographical profile-based high-order FC (HOFC) and found that this metric could provide supplementary information to traditional FC for early Alzheimer’s disease (AD) detection. However, whether such findings apply to network-level brain functional integration is unknown. In this paper, we propose an extended HOFC method, termed inter-network high-order FC (IN-HOFC), as a useful complement to the traditional inter-network FC methods, for characterizing more complex organizations among the large-scale brain networks. In the IN-HOFC, both network definition and inter-network FC are defined in a high-order manner. To test whether IN-HOFC is more sensitive to cognition decline due to brain diseases than traditional inter-network FC, 77 mild cognitive impairments (MCIs) and 89 controls are compared among the conventional methods and our IN-HOFC. The result shows that IN-HOFCs among three temporal lobe-related high-order networks are dampened in MCIs. The impairment of IN-HOFC is especially found between the anterior and posterior medial temporal lobe and could be a potential MCI biomarker at the network level. The competing network-level low-order FC methods, however, either revealing less or failing to detect any group difference. This work demonstrates the biological meaning and potential diagnostic value of the IN-HOFC in clinical neuroscience studies.

Original languageEnglish
Pages (from-to)547-561
Number of pages15
Issue number4
Publication statusPublished - 2019 Oct 1

Bibliographical note

Funding Information:
This work is supported in part by NIH grants (EB006733, EB008374, EB009634, MH100217, AG041721, AG049371 and AG042599). We have no conflict of interest to declare.

Publisher Copyright:
© 2019, Springer Science+Business Media, LLC, part of Springer Nature.


  • Alzheimer’s disease (AD)
  • Brain network
  • Functional connectivity
  • Functional magnetic resonance imaging (fMRI)
  • High-order
  • Mild cognitive impairment (MCI)

ASJC Scopus subject areas

  • Software
  • General Neuroscience
  • Information Systems


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