Functional magnetic resonance imaging (fMRI), a noninvasive neuroimaging method that
provides an indirect measure of neuronal activity by detecting blood flow changes, has …

Transcriptome-wide time series expression profiling is used to characterize the cellular
response to environmental perturbations. The first step to analyzing transcriptional response …

A spatiotemporal nonparametric Bayesian model of multi-subject fMRI data Page 1 The Annals
of Applied Statistics 2016, Vol. 10, No. 2, 638–666 DOI: 10.1214/16-AOAS926 © Institute of …

Group studies of functional magnetic resonance imaging datasets are usually based on the
computation of the mean signal across subjects at each voxel (random effects analyses) …

Data sets involving multiple groups with shared characteristics frequently arise in practice. In
this paper we extend hierarchical Dirichlet processes to model such data. Each group is …

We propose a probabilistic model for analyzing spatial activation patterns in multiple
functional magnetic resonance imaging (fMRI) activation images such as repeated …

Background We present an infinite mixture-of-experts model to find an unknown number of
sub-groups within a given patient cohort based on survival analysis. The effect of patient …

For many applications pertaining to neuroimaging, social science, international relations,
chemometrics, genomics and molecular-omics, datasets often involve variables which are …

An important challenge in neuroimaging multi-subject studies is to take into account that
different brains cannot be aligned perfectly. To this end, we extend the classical mass …

Our work is motivated by the geometric study of lower back pain from patient CT images. In
this paper, we take a first step towards that goal by introducing a data-driven way of …