Principles of Functional Magnetic Resonance Imaging and its Applications in Cognitive Neuroscience

Functional magnetic resonance imaging (fMRI) is a neuroimaging technique that provides brain activation maps with a spatial resolution of a few millimeters. The BOLD (blood oxygenation level dependent) fMRI method is the most commonly used technique. It measures the hemodynamic response to neural activity. The BOLD fMRI signal is based on the magnetic properties of the oxygenated / deoxygenated hemoglobin which is the oxygen carrier in blood. FMRI is noninvasive, and unlike in positron emission tomography (PET) individuals are not exposed to radiation. This allows data collection from the same individual over multiple sessions. The relatively high temporal resolution of fMRI compared to PET provides flexibility in experimental designs of cognitive tasks. In this paper we review the key principles of MRI physics, and the underlying metabolic, hemodynamic, and electrophysiological mechanisms of BOLD signal. We introduce frequently used experimental design paradigms and present examples. Next, we give an overview of theoretical considerations and applications of analysis methods in fMRI time series. Neural network modeling based on fMRI data is also discussed. Finally, we present an ongoing study in our laboratory to demonstrate the application of design types and analysis method