Donna L. Dierker

Cognitive Neuroscience · 2008–2016

A researcher in the Science corpus: 5 papers; trusts 11 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

Whom Donna L. Dierker trusts overall

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

  1. D. V. Van Essen
  2. Stephen M. Smith
  3. Arthur W. Toga
  4. David C. Van Essen
  5. Bruce Fischl
  6. Randy L. Buckner
  7. Robert F. Dougherty
  8. Doris Y. Tsao

Who trusts Donna L. Dierker overall

  1. Olaf Sporns
  2. Matthew F. Glasser
  3. David C. Van Essen
  4. Jonathan D. Power
  5. D. V. Van Essen
  6. Timothy O. Laumann

Papers from Donna L. Dierker's perspective

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

  1. Measuring the thickness of the human cerebral cortex from magnetic resonance images. (Proceedings of the National Academy of Sciences of the United States of America)
  2. Probabilistic independent component analysis for functional magnetic resonance imaging (IEEE Transactions on Medical Imaging)
  3. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest (NeuroImage)
  4. A voxel-based morphometric study of ageing in 465 normal adult human brains (5th IEEE EMBS International Summer School on Biomedical Imaging, 2002.)
  5. Comparative mapping of higher visual areas in monkeys and humans. (Trends in Cognitive Sciences)
  6. A Population-Average, Landmark- and Surface-based (PALS) atlas of human cerebral cortex (NeuroImage)
  7. Investigations into resting-state connectivity using independent component analysis (Philosophical Transactions of the Royal Society B: Biological Sciences)
  8. The global signal and observed anticorrelated resting state brain networks. (Journal of Neurophysiology)
  9. Dynamic mapping of human cortical development during childhood through early adulthood. (Proceedings of the National Academy of Sciences of the United States of America)
  10. Threshold-free cluster enhancement: Addressing problems of smoothing, threshold dependence and localisation in cluster inference (NeuroImage)

Their papers