Randomized parcellation based inference

Neuroimage. 2014 Apr 1;89:203-15. doi: 10.1016/j.neuroimage.2013.11.012. Epub 2013 Nov 19.

Abstract

Neuroimaging group analyses are used to relate inter-subject signal differences observed in brain imaging with behavioral or genetic variables and to assess risks factors of brain diseases. The lack of stability and of sensitivity of current voxel-based analysis schemes may however lead to non-reproducible results. We introduce a new approach to overcome the limitations of standard methods, in which active voxels are detected according to a consensus on several random parcellations of the brain images, while a permutation test controls the false positive risk. Both on synthetic and real data, this approach shows higher sensitivity, better accuracy and higher reproducibility than state-of-the-art methods. In a neuroimaging-genetic application, we find that it succeeds in detecting a significant association between a genetic variant next to the COMT gene and the BOLD signal in the left thalamus for a functional Magnetic Resonance Imaging contrast associated with incorrect responses of the subjects from a Stop Signal Task protocol.

Keywords: Group analysis; Multiple comparisons; Parcellation; Permutations; Reproducibility.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brain / anatomy & histology*
  • Catechol O-Methyltransferase / genetics*
  • Cluster Analysis
  • Computer Simulation
  • Genetic Association Studies
  • Humans
  • Magnetic Resonance Imaging*
  • Neuroimaging*
  • Polymorphism, Single Nucleotide

Substances

  • COMT protein, human
  • Catechol O-Methyltransferase