1 citations · 1 across the 2 of their papers we have counts for
7 papers
Spectral Dynamic Causal Modelling of Resting-State fMRI: Relating Effective Brain Connectivity in the Default Mode Network to Genetics
Yunlong Nie, Eugene Opoku, Laila Yasmin +8
We conduct an imaging genetics study to explore how effective brain connectivity in the default mode network (DMN) may be related to genetics within the context of Alzheimer's dise…
A Bayesian Spatial Model for Imaging Genetics
Yin Song, Shufei Ge, Jiguo Cao +2
We develop a Bayesian bivariate spatial model for multivariate regression analysis applicable to studies examining the influence of genetic variation on brain structure. Our model…
Feature Learning and Classification in Neuroimaging: Predicting Cognitive Impairment from Magnetic Resonance Imaging
Shan Shi, Farouk Nathoo
Due to the rapid innovation of technology and the desire to find and employ biomarkers for neurodegenerative disease, high-dimensional data classification problems are routinely en…
A Better (Bayesian) Interval Estimate for Within-Subject Designs
Farouk S. Nathoo, Robyn E. Kilshaw, Michael E. J. Masson
We develop a Bayesian highest-density interval (HDI) for use in within-subject designs. This credible interval is based on a standard noninformative prior and a modified posterior…
Bayesian Analysis of fMRI data with Spatially-Varying Autoregressive Orders
Ming Teng, Farouk S. Nathoo, Timothy D. Johnson
Statistical modeling of fMRI data is challenging as the data are both spatially and temporally correlated. Spatially, measurements are taken at thousands of contiguous regions, cal…
Regularization Parameter Selection for a Bayesian Multi-Level Group Lasso Regression Model with Application to Imaging Genomics
Farouk S. Nathoo, Keelin Greenlaw, Mary Lesperance
We investigate the choice of tuning parameters for a Bayesian multi-level group lasso model developed for the joint analysis of neuroimaging and genetic data. The regression model…