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Publications

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3740 Total Publications

Cognitive dysfunction and greater visit-to-visit systolic blood pressure variability.
Epstein, N. U., Lane, K. A., Farlow, M. R., Risacher, S. L., Saykin, A. J., Gao, S., … Gao, S.
2013; Journal Journal of the American Geriatrics Society; vol. 61; no. 12; pp. 2168-2173; doi:10.1111/jgs.12542

Statistical analysis of longitudinal neuroimage data with Linear Mixed Effects models.
Bernal-Rusiel, J. L., Greve, D. N., Reuter, M., Fischl, B., & Sabuncu, M. R.
2013; Journal Neuroimage; vol. 66; pp. 249-260; doi:10.1016/j.neuroimage.2012.10.065

Dimensionality reduced cortical features and their use in predicting longitudinal changes in Alzheimer’s disease.
Park, H., Yang, J. J., Seo, J., & Lee, J. M.
2013; Journal Neuroscience Letters; vol. 550; pp. 17-22; doi:10.1016/j.neulet.2013.06.042

Whole-exome sequencing and imaging genetics identify functional variants for rate of change in hippocampal volume in mild cognitive impairment.
Nho, K., Corneveaux, J. J., Kim, S., Lin, H., Risacher, S. L., Shen, L., … Saykin, A. J.
2013; Journal Molecular Psychiatry; vol. 18; no. 7; pp. 781-7; doi:10.1038/mp.2013.24

Maximizing power to track Alzheimer’s disease and MCI progression by LDA-based weighting of longitudinal ventricular surface features.
Gutman, B. a., Hua, X., Rajagopalan, P., Chou, Y. Y., Wang, Y., Yanovsky, I., … Thompson, P. M.
2013; Journal Neuroimage; vol. 70; pp. 386-401; doi:10.1016/j.neuroimage.2012.12.052

Polymorphism in the TOMM40 gene modifies the risk of developing sporadic inclusion body myositis and the age of onset of symptoms
Mastaglia, F. L., Rojana-udomsart, A., James, I., Needham, M., Day, T. J., Kiers, L., … Roses, A. D.
2013; Journal Neuromuscular Disorders; vol. 23; no. 12; pp. 969-74; doi:10.1016/j.nmd.2013.09.008

Effects of baseline CSF alpha-synuclein on regional brain atrophy rates in healthy elders, mild cognitive impairment and Alzheimer’s disease.
Mattsson, N., Insel, P., Tosun, D., Zhang, J., Jack Jr., C. R., Galasko, D., … Weiner, M.
2013; Journal PloS One; vol. 8; no. 12; pp. e85443; doi:10.1371/journal.pone.0085443

Meta-analysis based SVM classification enables accurate detection of Alzheimer’s disease across different clinical centers using FDG-PET and MRI.
Dukart, J., Mueller, K., Barthel, H., Villringer, A., Sabri, O., & Schroeter, M. L.
2013; Journal Psychiatry Research-Neuroimaging; vol. 212; no. 3; pp. 230-236; doi:10.1016/j.pscychresns.2012.04.007

Genome-wide scan for copy number variation association with age at onset of Alzheimer’s disease.
Szigeti, K., Lal, D., Li, Y., Doody, R. S., Wilhelmsen, K., Yan, L., … Ma, C.
2013; Journal Journal of Alzheimer's Disease; vol. 33; no. 2; pp. 517-23; doi:10.3233/JAD-2012-121285

Structural covariance of the default network in healthy and pathological aging.
Spreng, R. N., & Turner, G. R.
2013; Journal Journal of Neuroscience; vol. 33; no. 38; pp. 15226-34; doi:10.1523/JNEUROSCI.2261-13.2013