Detecting Alzheimer’s disease using directed graphs

Jianjia Wang*, Richard C. Wilson, Edwin R. Hancock

*Corresponding author for this work

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

9 Citations (Scopus)


The neurobiology of Alzheimer’s disease (AD) has been extensively studied by applying network analysis techniques to activation patterns in fMRI images. However, the structure of the directed networks representing the activation patterns, and their differences in healthy and Alzheimer’s people remain poorly understood. In this paper, we aim to identify the differences in fMRI activation network structure for patients with AD, late mild cognitive impairment (LMCI) and early mild cognitive impairment (EMCI). We use a directed graph theoretical approach combined with entropic measurements to distinguish subjects falling into these three categories and the normal healthy control (HC) group. We explore three methods. The first is based on applying linear discriminant analysis to vectors representing the in and out degree statistics of different anatomical regions. The second uses an entropic measure of node assortativity to gauge the asymmetries in the node with in and out degree. The final approach selects the most salient anatomical brain regions and uses the degree statistics of the connecting directed edges.

Original languageEnglish
Title of host publicationGraph-Based Representations in Pattern Recognition - 11th IAPR-TC-15 International Workshop, GbRPR 2017, Proceedings
EditorsPasquale Foggia, Mario Vento, Cheng-Lin Liu
PublisherSpringer Verlag
Number of pages11
ISBN (Print)9783319589602
Publication statusPublished - 2017
Externally publishedYes
Event11th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2017 - Anacapri, Italy
Duration: 16 May 201718 May 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10310 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference11th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2017


  • Alzheimer’s disease (AD)
  • Directed graphs entropy
  • FMRI Networks


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