John Muschelli

Artificial Intelligence · 2014–2021

A researcher in the Science corpus: 4 papers; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom John Muschelli trusts overall

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

  1. Elizabeth R. DeLong
  2. Daniel Veltri
  3. Tom Fawcett
  4. Trevor J. Hastie
  5. Fabian Pedregosa
  6. David M. DeLong
  7. Uday Kamath
  8. Oliver Sander
  9. Michael N. Hallquist
  10. Jonathan D. Power

Who trusts John Muschelli overall

  1. Thomas T. Liu
  2. Raimon H. R. Pruim
  3. Linden Parkes
  4. Rastko Ciric
  5. Alican Nalci

Papers from John Muschelli's perspective

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

  1. The impact of global signal regression on resting state correlations: Are anti-correlated networks introduced? (NeuroImage)
  2. Correlations and anticorrelations in resting-state functional connectivity MRI: A quantitative comparison of preprocessing strategies (NeuroImage)
  3. A component based noise correction method (CompCor) for BOLD and perfusion based fMRI (NeuroImage)
  4. An Improved Framework for Confound Regression and Filtering for Control of Motion Artifact in the Preprocessing of Resting-State Functional Connectivity Data (NeuroImage)
  5. Anticorrelations in resting state networks without global signal regression (NeuroImage)
  6. Image‐based method for retrospective correction of physiological motion effects in fMRI: RETROICOR (Magnetic Resonance in Medicine)
  7. Neural basis of global resting-state fMRI activity (Proceedings of the National Academy of Sciences of the United States of America)
  8. Matplotlib: A 2D Graphics Environment
  9. Methods to detect, characterize, and remove motion artifact in resting state fMRI (NeuroImage)
  10. Non-white noise in fMRI: Does modelling have an impact? (NeuroImage)

Their papers