Title of article :
Statistical Analysis Methods for the fMRI Data
Author/Authors :
behroozi, m. iran university of science and technology, تهران, ايران , daliri, m.r. iran university of science and technology, تهران, ايران , boyaci, h. department of psychology, bilkent university, Turkey
From page :
67
To page :
74
Abstract :
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.
Keywords :
Fmri , General Linear Model (GLM) , Independent Component Analysis (ICA) , Machine learning , Multi , voxel pattern analysis (mvpa) , Principal Component Analysis (PCA)
Journal title :
Basic and Clinical Neuroscience
Journal title :
Basic and Clinical Neuroscience
Record number :
2548343
Link To Document :
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