3911 Total Publications
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
Critical ages in the life course of the adult brain: nonlinear subcortical aging.
Fjell, A. M., Westlye, L. T., Grydeland, H., Amlien, I., Espeseth, T., Reinvang, I., … Walhovd, K. B.
2013; Journal Neurobiology of Aging; vol. 34; no. 10; pp. 2239-47;
doi:10.1016/j.neurobiolaging.2013.04.006
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
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
Brain development and aging: Overlapping and unique patterns of change.
Tamnes, C. K., Walhovd, K. B., Dale, A. M., Østby, Y., Grydeland, H., Richardson, G., … Fjell, A. M.
2013; Journal Neuroimage; vol. 68; no. 2013; pp. 63-74;
doi:10.1016/j.neuroimage.2012.11.039