Abstract

Functional MRI (fMRI) data analysis aims to characterize neuronal dynamics by using observations of the hemodynamic phenomena associated with neuronal activity. These observations are indirect and highly “noisy” and commonly require different models for data interpretation. Many techniques have been developed in recent years for analyzing fMRI data. Despite advances in fMRI, there are some limitations that have to be considered in obtaining successful characterization of neuronal activity from fMRI data. In this chapter, the fundamentals of fMRI data analysis are described. Initially, the basis of the hemodynamic phenomena associated with neuronal activity is presented. This is followed by a description of the principal models used to perform fMRI data analysis. Finally, some of the most critical aspects of fMRI data analysis are covered.

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