6 citations · 6 across the 5 of their papers we have counts for
6 papers
Nested MCMC for Uncertainty Propagation in Spatial Modeling of Temporal Long-Memory in Resting-State fMRI
Yasaman Shahhosseini, Cédric Beaulac, Farouk S. Nathoo +1
Resting-state functional magnetic resonance imaging (rs-fMRI) signals exhibit long-range temporal dependence, characterized by a slow power-law decay of autocorrelation. This scale…
Locatability and Locatability Robustness of Visual Variables in Single Target Localization
Wei Wei, Miguel A. Nacenta, Michelle F. Miranda +1
Finding a particular object in a display is important for viewers in many visualizations, for example, when reacting to brushing or to a highlighted object. This can be enabled by…
A Wavelet-Based Framework for Mapping Long Memory in Resting-State fMRI: Age-Related Changes in the Hippocampus from the ADHD-200 Dataset
Yasaman Shahhosseini, Cédric Beaulac, Farouk S. Nathoo +1
Functional magnetic resonance imaging (fMRI) time series are known to exhibit long-range temporal dependencies that challenge traditional modeling approaches. In this study, we pro…
A canonical polyadic tensor basis for fast Bayesian estimation of multi-subject fMRI activation patterns
Michelle F. Miranda
Task-evoked functional magnetic resonance imaging studies, such as the Human Connectome Project (HCP), are a powerful tool for exploring how brain activity is influenced by cogniti…
Bayesian Semiparametric Functional Mixed Models for Serially Correlated Functional Data, with Application to Glaucoma Data
Wonyul Lee, Michelle F. Miranda, Phlip Rausch +4
Glaucoma, a leading cause of blindness, is characterized by optic nerve damage related to intraocular pressure (IOP), but its full etiology is unknown. Researchers at UAB have devi…
Bayesian spatial transformation models with applications in neuroimaging data
Michelle F. Miranda, Hongtu Zhu, Joseph G. Ibrahim
The aim of this paper is to develop a class of spatial transformation models (STM) to spatially model the varying association between imaging measures in a three-dimensional (3D) v…