Functional Magnetic Resonance Imaging (fMRI) is an imaging modality that demonstrates brain activation dependent on the blood oxygen level (BOLD). With this method, the perfusion of neural tissues with activation and the temporal changes of these processes can be monitored. With the new fast sequences, fMRG shooting times have been very short and the availability of today has increased considerably. The research conducted by the so-called default mode network (DMN) has been defined as a highly compatible interacting region and other brain networks. Currently, the determination of the dominant hemisphere in patients with epilepsy in fMRI is used to determine the neuronal dysfunctions, in the eloquent area-related tumors before surgery, to evaluate the functionality in the neurodegenerative and psychiatric diseases, to evaluate the effectiveness of the treatment and the drug. General linear model (GML), independent variable analysis -Independent Component Analysis (ICA), multivariate pattern analysis -Multi Variative Pattern Analysis (MVPA) analysis methods can be used to evaluate the data. However, the size, variety, and statistical studies of the errors in the field of fMRG studies affect the value of the data and decrease the confidence in the results of the studies. Statistical errors should be minimized, and the data quality should be increased. Despite its limitations and statistical difficulties, fMRI contributes to the study of brain function is going on.