On the Extraction and Analysis of Graphs From Resting-State fMRI to Support a Correct and Robust Diagnostic Tool for Alzheimer's Disease

Claudia Bachmann*, Heidi I. L. Jacobs, PierGianLuca Porta Mana, Kim Dillen, Nils Richter, Boris von Reutern, Julian Dronse, Oezguer A. Onur, Karl-Josef Langen, Gereon R. Fink, Juraj Kukolja, Abigail Morrison

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Original languageEnglish
Article number528
Number of pages24
JournalFrontiers in Neuroscience
Volume12
DOIs
Publication statusPublished - 28 Sep 2018

Keywords

  • Alzheimer's disease
  • MCI
  • graph theory
  • resting-state fMRI
  • diagnosis
  • model by sufficiency
  • negative surprise
  • DISRUPTED FUNCTIONAL CONNECTIVITY
  • BRAIN CONNECTIVITY
  • PET DATA
  • NETWORKS
  • IMAGES
  • SEGMENTATION
  • REGISTRATION
  • INFORMATION
  • MODEL
  • DISINTEGRATION

Cite this

Bachmann, C., Jacobs, H. I. L., Mana, P. P., Dillen, K., Richter, N., von Reutern, B., Dronse, J., Onur, O. A., Langen, K-J., Fink, G. R., Kukolja, J., & Morrison, A. (2018). On the Extraction and Analysis of Graphs From Resting-State fMRI to Support a Correct and Robust Diagnostic Tool for Alzheimer's Disease. Frontiers in Neuroscience, 12, [528]. https://doi.org/10.3389/fnins.2018.00528