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Publications

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4453 Total Publications

Multilocus genetic profiling to empower drug trials and predict brain atrophy.
Kohannim, O., Hua, X., Rajagopalan, P., Hibar, D. P., Jahanshad, N., Grill, J. D., … Thompson, P. M.
PMID: 24179834 ; PMCID:3777716 ; 2013; Journal Neuroimage: Clinical; vol. 2; pp. 827-35; doi:10.1016/j.nicl.2013.05.007

Advanced Psychometric Analysis and the Alzheimer's Disease Neuroimaging Initiative: Reports from the 2011 Friday Harbor Conference
Dan Mungas,1 Paul K. Crane,2 Laura E. Gibbons,2 Jennifer J. Manly,3 M. Maria Glymour,4 and Richard N. Jones5
PMID: 23232798 ; PMCID:3532555 ; 2013; Journal Brain Imaging Behavior; vol. 6; no. 4; pp. 485–488; doi:10.1007/s11682-012-9211-2

Alzheimer’s Disease Risk Assessment Using Large-Scale Machine Learning Methods
Casanova, R., Hsu, F.-C., Sink, K. M., Rapp, S. R., Williamson, J. D., Resnick, S. M., & Espeland, M. a.
PMID: 24250789 ; PMCID:3826736 ; 2013; Journal PloS One; vol. 8; pp. e77949; doi:10.1371/journal.pone.0077949

Automated analysis of FDG PET as a tool for single-subject probabilistic prediction and detection of Alzheimer’s disease dementia
Arbizu, J., Prieto, E., Martínez-Lage, P., Martí-Climent, J. M., García-Granero, M., Lamet, I., … Weiner, M. W.
PMID: 23715905 ; 2013; Journal European Journal of Nuclear Medicine and Molecular Imaging; vol. 40; no. 9; pp. 1394-1405; doi:10.1007/s00259-013-2458-z

GWAS of Cerebrospinal Fluid Tau Levels Identifies Risk Variants for Alzheimer’s Disease
Cruchaga, C., Kauwe, J. S. K., Harari, O., Jin, S. C., Cai, Y., Karch, C. M., … Goate, A. M.
PMID: 23562540 ; PMCID:3664945 ; 2013; Journal Neuron; vol. 78; no. 2; pp. 256-68; doi:10.1016/j.neuron.2013.02.026

Disease progression model in subjects with mild cognitive impairment from the Alzheimer’s disease neuroimaging initiative: CSF biomarkers predict population subtypes.
Samtani, M. N., Raghavan, N., Shi, Y., Novak, G., Farnum, M., Lobanov, V., … Narayan, V. a.
2013; Journal British Journal of Clinical Pharmacology; vol. 75; no. 1; pp. 146-161; doi:10.1111/j.1365-2125.2012.04308.x

Prediction of Alzheimer’s disease and mild cognitive impairment using cortical morphological patterns.
Wee, C.-Y., Yap, P.-T., & Shen, D.
2013; Journal Human Brain Mapping; vol. 34; no. 12; pp. 3411-3425; doi:10.1002/hbm.22156

Cerebral atrophy in mild cognitive impairment and Alzheimer disease: rates and acceleration.
Leung, K. K., Bartlett, J. W., Barnes, J., Manning, E. N., Ourselin, S., & Fox, N. C.
2013; Journal Neurology; vol. 80; no. 7; pp. 648-54; doi:10.1212/WNL.0b013e318281ccd3

Structural interactions within the default mode network identified by Bayesian network analysis in Alzheimer’s disease.
Wang, Y., Chen, K., Yao, L., Jin, Z., & Guo, X.
2013; Journal PloS One; vol. 8; no. 8; pp. e74070; doi:10.1371/journal.pone.0074070

White matter hyperintensities and cerebral amyloidosis: Necessary and sufficient for clinical expression of Alzheimer’s disease?
Provenzano, F. A., Muraskin, J., Tosto, G., Narkhede, A., Wasserman, B. T., Griffith, E. Y., … Brickman, A. M.
PMID: 23420027 ; PMCID:4124641 ; 2013; Journal JAMA Neurology; vol. 70; no. 4; pp. 455-461; doi:10.1001/jamaneurol.2013.1321