Rogier A. Feis

Cognitive Neuroscience · 2015

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Rogier A. Feis trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Stephen M. Smith
  2. Christian F. Beckmann
  3. Mark Jenkinson
  4. Aapo Hyvärinen
  5. Michael D. Fox
  6. Douglas N. Greve
  7. Michael D. Greicius
  8. Mark William Woolrich
  9. Gholamreza Salimi Khorshidi
  10. Thomas E. Nichols

Who trusts Rogier A. Feis overall

  1. Meichen Yu

Papers from Rogier A. Feis's perspective

Ordered by how strongly the researchers Rogier A. Feis trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Probabilistic independent component analysis for functional magnetic resonance imaging (IEEE Transactions on Medical Imaging)
  2. Threshold-free cluster enhancement: Addressing problems of smoothing, threshold dependence and localisation in cluster inference (NeuroImage)
  3. Accurate and Robust Brain Image Alignment using Boundary-based Registration (NeuroImage)
  4. Fast and robust fixed-point algorithms for independent component analysis
  5. Accurate, Robust, and Automated Longitudinal and Cross-Sectional Brain Change Analysis (NeuroImage)
  6. Functional connectivity in the resting brain: A network analysis of the default mode hypothesis (Proceedings of the National Academy of Sciences of the United States of America)
  7. A global optimisation method for robust affine registration of brain images (Medical Image Anal.)
  8. fMRI resting state networks define distinct modes of long-distance interactions in the human brain (NeuroImage)
  9. Automatic Denoising of Functional MRI Data: Combining Independent Component Analysis and Hierarchical Fusion of Classifiers
  10. Distinct patterns of brain activity in young carriers of the APOE-ε4 allele (Proceedings of the National Academy of Sciences of the United States of America)

Their papers