Beth A. Verchinski

Cognitive Neuroscience · 2003–2010

A researcher in the Science corpus: 6 papers; trusts 4 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

Whom Beth A. Verchinski trusts overall

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

  1. John Ashburner
  2. Michael Egan
  3. Catriona D. Good
  4. Karl J. Friston
  5. Alan M. Frieze
  6. Sophie Achard
  7. Olaf Sporns
  8. E. Bullmore
  9. D. Bassett

Who trusts Beth A. Verchinski overall

  1. D. Bassett
  2. E. Bullmore
  3. Martijn P. van den Heuvel
  4. Olaf Sporns
  5. Andrew Zalesky
  6. Gaolang Gong
  7. Jinhui Wang
  8. Xiao-Jing Wang
  9. Alan C. Evans
  10. Bruce S. McEwen

Papers from Beth A. Verchinski's perspective

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

  1. A voxel-based morphometric study of ageing in 465 normal adult human brains (5th IEEE EMBS International Summer School on Biomedical Imaging, 2002.)
  2. Collective dynamics of ‘small-world’ networks
  3. Theoretical neuroanatomy: relating anatomical and functional connectivity in graphs and cortical connection matrices. (Cerebral Cortex)
  4. Anatomical connectivity defines the organization of clusters of cortical areas in the macaque monkey and the cat. (Philosophical transactions of the Royal Society of London. Series B, Biological sciences)
  5. The BDNF val66met polymorphism affects activity-dependent secretion of BDNF and human memory and hippocampal function. (Cell)
  6. Efficient behavior of small-world networks. (Physical Review Letters)
  7. Automated Talairach Atlas labels for functional brain mapping
  8. Effect of COMT Val108/158 Met genotype on frontal lobe function and risk for schizophrenia (Proceedings of the National Academy of Sciences of the United States of America)
  9. Wiring optimization in cortical circuits. (Neuron)
  10. A Resilient, Low-Frequency, Small-World Human Brain Functional Network with Highly Connected Association Cortical Hubs (Journal of Neuroscience)

Their papers