Spatial Bayesian modelling of neuroimaging meta-analysis data

Bayesian Prediction in Spatial Data Analysis

Bayesian Analysis of Survival Data with Spatial Correlation

Often in practice the data on the mortality of a living unit correlation is due to the location of the observations in the study‎. ‎One of the most important issues in the analysis of survival data with spatial dependence‎, ‎is estimation of the parameters and prediction of the unknown values in known sites based on observations vector‎. ‎In this paper to analyze this type of survival‎, ‎Cox...

Meta Analysis of Functional Neuroimaging Data via Bayesian Spatial Point Processes.

As the discipline of functional neuroimaging grows there is an increasing interest in meta analysis of brain imaging studies. A typical neuroimaging meta analysis collects peak activation coordinates (foci) from several studies and identifies areas of consistent activation. Most imaging meta analysis methods only produce null hypothesis inferences and do not provide an interpretable fitted mode...

Meta-analysis of neuroimaging data.

As the number of neuroimaging studies that investigate psychological phenomena grows, it becomes increasingly difficult to integrate the knowledge that has accrued across studies. Meta-analyses are designed to serve this purpose, as they allow the synthesis of findings not only across studies but also across laboratories and task variants. Meta-analyses are uniquely suited to answer questions a...

Bayesian analysis of neuroimaging data in FSL

Typically in neuroimaging we are looking to extract some pertinent information from imperfect, noisy images of the brain. This might be the inference of percent changes in blood flow in perfusion FMRI data, segmentation of subcortical structures from structural MRI, or inference of the probability of an anatomical connection between an area of cortex and a subthalamic nucleus using diffusion MR...