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3740 Total Publications

SUCLG2 identified as both a determinator of CSF Aβ1-42 levels and an attenuator of cognitive decline in Alzheimer's disease
Ramirez, A., van der Flier, W. M., Herold, C., Ramonet, D., Heilmann, S., Lewczuk, P., … Nöthen, M. M.
PMID: 25027320 ; PMCID:4240204 ; 2014; Journal Human Molecular Genetics; vol. 23; no. 24; pp. 6644-6658; doi:10.1093/hmg/ddu372
Variants in PPP3R1 and MAPT are associated with more rapid functional decline in Alzheimer's disease: the Cache County Dementia Progression Study.
Peterson, D., Munger, C., Crowley, J., Corcoran, C., Cruchaga, C., Goate, A. M., … Kauwe, J. S. K.
PMID: 23727081 ; PMCID:3809344 ; 2014; Journal Alzheimer's and Dementia; vol. 10; no. 3; pp. 366-371; doi:10.1016/j.jalz.2013.02.010
Multi-atlas segmentation of the whole hippocampus and subfields using multiple automatically generated templates
Pipitone J1, Park MT2, Winterburn J2, Lett TA3, Lerch JP4, Pruessner JC5, Lepage M6, Voineskos AN7, Chakravarty MM8; Alzheimer's Disease Neuroimaging Initiative
PMID: 24784800 ; 2014; Journal Neuroimage; vol. 101; pp. 494-512; doi:10.1016/j.neuroimage.2014.04.054
Fully Automated Segmentation of the Pons and Midbrain Using Human T1 MR Brain Images
Nigro, S., Cerasa, A., Zito, G., Perrotta, P., Chiaravalloti, F., Donzuso, G., … Quattrone, A.
PMID: 24489664 ; PMCID:3904850 ; 2014; Journal PloS One; vol. 9; no. 1; pp. e85618; doi:10.1371/journal.pone.0085618
Variables associated with hippocampal atrophy rate in normal aging and mild cognitive impairment
Nosheny, R. L., Insel, P. S., Truran, D., Schuff, N., Jack, C. R., Aisen, P. S., … Weiner, M. W.
PMID: 25175807 ; PMCID:5832349 ; 2014; Journal Neurobiology of Aging; pp. 273-282; doi:10.1016/j.neurobiolaging.2014.07.036
Group-constrained sparse fMRI connectivity modeling for mild cognitive impairment identification.
Wee, C.-Y., Yap, P.-T., Zhang, D., Wang, L., & Shen, D.
2014; Journal Brain Structure and Function; vol. 219; no. 2; pp. 641-56; doi:10.1007/s00429-013-0524-8
Shape abnormalities of subcortical and ventricular structures in mild cognitive impairment and Alzheimer’s disease: Detecting, quantifying, and predicting.
Tang, X., Holland, D., Dale, A. M., Younes, L., & Miller, M. I.
2014; Journal Human Brain Mapping; vol. 35; no. 8; pp. 3701-3725; doi:10.1002/hbm.22431
Reduced FDG-PET brain metabolism and executive function predict clinical progression in elderly healthy subjects.
Ewers, M., Brendel, M., Rizk-Jackson, A., Rominger, A., Bartenstein, P., Schuff, N., & Weiner, M. W.
2014; Journal Neuroimage: Clinical; vol. 4; pp. 45-52; doi:10.1016/j.nicl.2013.10.018
Statistical normalization techniques for magnetic resonance imaging.
Shinohara, R. T., Sweeney, E. M., Goldsmith, J., Shiee, N., Mateen, F. J., Calabresi, P. a, … Crainiceanu, C. M.
2014; Journal Neuroimage: Clinical; vol. 6; pp. 9-19; doi:10.1016/j.nicl.2014.08.008
Regularized 3D functional regression for brain image data via Haar wavelets.
Wang, X., Nan, B., Zhu, J., & Koeppe, R.
2014; Journal Annals of Applied Statistics; vol. 8; no. 2; pp. 1045-1064; doi:10.1214/14-AOAS736