Neuroimaging
Research in this area focuses on developing novel statistical methods to analyze functional MRI data as well as validation techniques for newly developed methods. Our specific contributions are in the areas of multivariate analysis, independent component analysis and nonparametric methods. Applications focus on identifying neuroimaging markers for cognitive decline in the aging population.
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Faculty Publications
- Nandy R, Cordes D. A semi-parametric approach to estimate the family-wise error rate in fMRI using resting-state data. Neuroimage. 2007 Feb 15;34(4):1562-76. doi: 10.1016/j.neuroimage.2006.10.025. Epub 2006 Dec 28. PMID: 17196400.
- Nandy RR, Cordes D. Novel ROC-type method for testing the efficiency of multivariate statistical methods in fMRI. Magn Reson Med. 2003 Jun;49(6):1152-62. doi: 10.1002/mrm.10469. PMID: 12768594.
- Zhuang X, Yang Z, Curran T, Byrd R, Nandy R, Cordes D. A family of locally constrained CCA models for detecting activation patterns in fMRI. Neuroimage. 2017 Apr 1;149:63-84. doi: 10.1016/j.neuroimage.2016.12.081. Epub 2016 Dec 29. PMID: 28041980; PMCID: PMC5493994.
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