A Bayesian hierarchical spatial point process model for multi-type neuroimaging meta-analysis

A Bayesian Hierarchical Spatial Point Process Model for Multi-type Neuroimaging Meta-analysis.

Neuroimaging meta-analysis is an important tool for finding consistent effects over studies that each usually have 20 or fewer subjects. Interest in meta-analysis in brain mapping is also driven by a recent focus on so-called "reverse inference": where as traditional "forward inference" identifies the regions of the brain involved in a task, a reverse inference identifies the cognitive processe...

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...

Bayesian Meta-analysis with Hierarchical Modeling

Multi-Class Sparse Bayesian Regression for Neuroimaging Data Analysis

The use of machine learning tools is gaining popularity in neuroimaging, as it provides a sensitive assessment of the information conveyed by brain images. In particular, finding regions of the brain whose functional signal reliably predicts some behavioral information makes it possible to better understand how this information is encoded or processed in the brain. However, such a prediction is...

A multi-objective optimization model for process targeting

Customers and consumers are the necessities for the survival of industries and organizations. Trying to improve the process in order to increase consumer satisfaction is the most important aim. The survival of an organization depends on its ability to continue the activities in compliance with the demands of customers to meet their legitimate needs. An organization is successful when it exactly...