Statistical Analysis Methods for the fMRI Data

• Main Authors: Mehdi Behroozi, Mohammad Reza Daliri, Huseyin Boyaci
• Format: Article
• Language: English
• Published: Iran University of Medical Sciences 2011-08-01
• Series: Basic and Clinical Neuroscience
• Subjects: fMRI; Machine Learning; Multi-Voxel Pattern Analysis(MVPA); General Linear Model (GLM); Independent ComponentAnalysis (ICA); Principal Component Analysis(PCA).
• Online Access: http://bcn.iums.ac.ir/browse.php?a_code=A-10-1-78&slc_lang=en&sid=1

Functional magnetic resonance imaging (fMRI) is a safe and non-invasive way to assess brain functions by using signal changes associated with brain activity. The technique has become a ubiquitous tool in basic, clinical and cognitive neuroscience. This method can measure little metabolism changes that occur in active part of the brain. We process the fMRI data to be able to find the parts of brain that are involve in a mechanism, or to determine the changes that occur in brain activities due to a brain lesion. In this study we will have an overview over the methods that are used for the analysis of fMRI data.