Global Network Analysis of Alzheimer's Disease with Minimum Spanning Trees

Edgar Canario, Donna Chen, Ying Han, Haijing Niu, Bharat Biswal

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Background: A minimum spanning tree (MST) is a unique efficient network comprising the necessary connections needed to connect all regions in a network while retaining the lowest possible cost of connection weight. Objective: This study aimed to utilize functional near-infrared spectroscopy (fNIRS) to analyze brain activity in different regions and then construct MST-based regions to characterize the brain topologies of participants with Alzheimer's disease (AD), mild cognitive impairment (MCI), and normal controls (NC). Methods: A 46 channel fNIRS setup was used on all participants, with correlation being calculated for each channel pair. An MST was constructed from the resulting correlation matrix, from which graph theory measures were calculated. The average number of connections within a lobe in the left versus right hemisphere was calculated to identify which lobes displayed and abnormal amount of connectivity. Results: Compared to those in the MCI group, the AD group showed a less integrated network structure, with a higher characteristic path length, but lower leaf fraction, maximum degree, and degree divergence. The AD group also showed a higher number of connections in the frontal lobe within the left hemisphere and a lower number between hemispheric frontal lobes as compared to MCI. Conclusion: These results indicate a deviation in network structure and connectivity within patient groups that is consistent with the theory of dysconnectivity for AD. Additionally, the AD group showed strong correlations between the Hamilton depression rating scale and different graph metrics, suggesting a link between network organization and the recurrence of depression in AD.

Original languageEnglish (US)
Pages (from-to)571-581
Number of pages11
JournalJournal of Alzheimer's Disease
Issue number2
StatePublished - Aug 1 2022

All Science Journal Classification (ASJC) codes

  • General Neuroscience
  • Clinical Psychology
  • Geriatrics and Gerontology
  • Psychiatry and Mental health


  • Amyloid
  • cognitive decline
  • depression
  • functional neuroimaging


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