Nicola Filippini

Cognitive Neuroscience · 2009–2017

A researcher in the Science corpus: 6 papers; trusts 6 researchers and is trusted by 26 researchers here, as inferred from the citation graph.

Subfields

Whom Nicola Filippini trusts overall

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

  1. Stephen M. Smith
  2. Christian F. Beckmann
  3. Mark William Woolrich
  4. Mark Jenkinson
  5. L. R. Squire
  6. Michael D. Greicius
  7. Jesper L. R. Andersson
  8. Aapo Hyvärinen
  9. Michael D. Fox
  10. Marilena DeLuca

Who trusts Nicola Filippini overall

  1. Stephen M. Smith
  2. Maarten Mennes
  3. Raimon H. R. Pruim
  4. Robert Leech
  5. Elena A. Allen
  6. Christian F. Beckmann
  7. F. X. Castellanos
  8. Amanda V. Utevsky
  9. Xi-Nian Zuo
  10. Clare Kelly

Papers from Nicola Filippini's perspective

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

  1. Fast robust automated brain extraction
  2. Multiplexed Echo Planar Imaging for Sub-Second Whole Brain FMRI and Fast Diffusion Imaging (PLoS ONE)
  3. Multiband Multislice GE-EPI at 7 Tesla, With 16-Fold Acceleration Using Partial Parallel Imaging With Application to High Spatial and Temporal Whole-Brain FMRI (Magnetic Resonance in Medicine)
  4. The global signal and observed anticorrelated resting state brain networks. (Journal of Neurophysiology)
  5. Default-mode network activity distinguishes Alzheimer's disease from healthy aging: Evidence from functional MRI (Proc. Natl. Acad. Sci. USA)
  6. Accurate and Robust Brain Image Alignment using Boundary-based Registration (NeuroImage)
  7. Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data (NeuroImage)
  8. Impact of In-Scanner Head Motion on Multiple Measures of Functional Connectivity: Relevance for Studies of Neurodevelopment in Youth (NeuroImage)
  9. Threshold-free cluster enhancement: Addressing problems of smoothing, threshold dependence and localisation in cluster inference (NeuroImage)
  10. Multilevel linear modelling for FMRI group analysis using Bayesian inference

Their papers