Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Journal articles
  4. Comparing connectomes across subjects and populations at different scales
 
research article

Comparing connectomes across subjects and populations at different scales

Meskaldji, Djalel Eddine
•
Fischi-Gomez, Elda
•
Griffa, Alessandra
Show more
April 28, 2013
NeuroImage

Brain connectivity can be represented by a network that enables the comparison of the different patterns of struc- tural and functional connectivity among individuals. In the literature, two levels ofstatistical analysis have been con- sidered in comparing brain connectivity across groups and subjects: 1) the global comparison where a single measure that summarizes the information ofeach brain is used in a statistical test; 2) the local analysis where a sin- gle test is performed either for each node/connection which implies a multiplicity correction, or for each group of nodes/connections where each subset is summarized by one single test in order to reduce the number of tests to avoid a penalizing multiplicity correction. We comment on the different levels of analysis and present some methods that have been proposed at each scale. We highlight as well the possible factors that could influence the statistical results and the questions that have to be addressed in such an analysis

  • Details
  • Metrics
Type
research article
DOI
10.1016/j.neuroimage.2013.04.084
Author(s)
Meskaldji, Djalel Eddine
Fischi-Gomez, Elda
Griffa, Alessandra
Hagmann, Patric
Morgenthaler, Stephan
Thiran, Jean-Philippe
Date Issued

2013-04-28

Published in
NeuroImage
Volume

80

Start page

416

End page

425

Subjects

Brain connectivity

•

Magnetic resonance imaging (MRI)

•

Diffusion imaging

•

Multiple testing Multiple comparisons

•

Bonferroni

•

Family-wise error rate (FWER)

•

False discovery rate FDR

•

Graph theory

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LTS5  
STAP  
Available on Infoscience
November 16, 2018
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/151471
Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés