Publications on Google scholar


Significant Works

  • Winkler, AM, Greve, DN, Bjuland, KJ, Nichols, TE, Sabuncu, MR, Håberg, AK, Skranes, J,
  • Rimol, LM, Joint analysis of area and thickness as a replacement for the analysis of cortical
  • volume. Cerebral Cortex 2018, vol 28 (2), 738-749
  • Greve, D.N., Fischl, B., False positive rates in surface-based anatomical analysis.
  • Neuroimage 171, 6-14, 2017.
  • Bernal-Rusiel, JL, Reuter, M, Greve, DN, Fischl, B, Sabuncu, MR, Spatiotemporal linear mixed effects modeling for the mass-univariate analysis of longitudinal neuroimage data, NeuroImage, 2015.
  • Greve, DN., Van der Haegen, L, Cai, Q., Stufflebeam, S., Sabuncu, MR, Fischl, B, and Bysbaert, M. “A surface-based analysis of language lateralization and cortical asymmetry.” (2013). Journal of Cognitive
  • Greve, D. N. and B. Fischl (2009). “Accurate and robust brain image alignment using boundary-based registration.” Neuroimage (48) 63-72. PMID: 19573611.
  • Salat, D. H.; Greve, D. N.; Pacheco, J. L.; Quinn, B. T.; Helmer, K. G.; Buckner, R. L.; Fischl, B. Regional white matter volume differences in nondemented aging and Alzheimer’s disease. Neuroimage 2009, 44, 1247-1258.
  • Westlye, L. T.; Walhovd, K. B.; Dale, A. M.; Espeseth, T.; Reinvang, I.; Raz, N.; Agartz, I.; Greve, D. N.; Fischl, B.; Fjell, A. M. Increased sensitivity to effects of normal aging and Alzheimer’s disease on cortical thickness by adjustment for local variability in gray/white contrast: a multi-sample MRI study. Neuroimage 2009, 47, 1545-1557.
  • Lindemer, E. R.; Salat, D. H.; Smith, E. E.; Nguyen, K.; Fischl, B.; Greve, D. N.; Alzheimer’s Disease Neuroimaging, I. White matter signal abnormality quality differentiates mild cognitive impairment that converts to Alzheimer’s disease from nonconverters. Neurobiology of aging 2015, 36, 2447-2457.
  • Lindemer, E.R., Greve, D.N., Fischl, B.R., Augustinack, J.C., Salat, D.H. 2017. Regional staging of whitematter signal abnormalities in aging and Alzheimer’s disease. Neuroimage Clin 14, 156-165.
  • Greve, D.N., C. Svarer, P.M. Fisher, L. Feng, A.E. Hansen, W. Baare, et al. Cortical surface
  • based analysis reduces bias and variance in kinetic modeling of brain PET data. Neuroimage 92: 225-236, 2014.
  • Beliveau, V.; Svarer, C.; Frokjaer, V. G.; Knudsen, G. M.; Greve, D. N. (joint senior authorship); Fisher, P. M. Functional connectivity of the dorsal and median raphe nuclei at rest. Neuroimage 2015.
  • Greve, D.N., Salat, D.H., Bowen, S.L., Izquierdo-Garcia, D., Schultz, A.P., Catana, C., Becker, J.A., Svarer, C., Knudsen, G.M., Sperling, R.A., Johnson, K.A., Different partial volume correction methods lead to different conclusions: An (18)F-FDG-PET study of aging. Neuroimage 132, 334-343, 2016.
  • Ganz, M., Feng, L., Hansen, H.D., Beliveau, V., Svarer, C., Knudsen, G.M., Greve, D.N., Cerebellar heterogeneity and its impact on PET data quantification of 5-HT receptor radioligands. J Cereb Blood Flow Metab, 2017.