FmriVisualsystem

The human brain, though one organ in the human system, contains a huge number of detailed networks of neurons running in it. Through years of progress in neuroscience and neuroimaging, we have been drawn closer to an idea about its complex functionality. The more paradigm-shifting techniques in this domain include functional Magnetic Resonance Imaging or fMRI. Beyond these mainstream applications, however, fMRI data have nowadays started to play an important role in developing brain-computer interfaces, which are hard or software systems designed to bridge the gap between human cognition and any external device to which a person would like to be able to control, communicate with, or even interact with in revolutionary ways. What is fMRI? Functional magnetic resonance imaging, or fMRI, is a special type of MRI that measures and maps brain activity by detecting changes in blood flow. When any given part of the brain is more active, it uses more oxygen; hence, more blood flows to it. FMRI

Functional magnetic resonance imaging has changed the existing view of the human brain. Because it is non-invasive, access to neural activity is acquired through blood flow changes. Thus, fMRI provides a window into the neural underpinnings of cognition and behaviour. However, the real power of fMRI is harnessed from sophisticated image analysis techniques that translate data into meaningful insights. A. Preprocessing: Preprocessing in fMRI data analysis is one of the most critical steps that aim at noise and artefact reduction in the data while aligning it in a standard anatomical space. Necessary preprocessing steps include: Motion Correction: The fMRI data are sensitive to the movement of the patient. Realignment belongs to one of those techniques that modify the motion by aligning each volume of the brain to a reference volume. Algorithms used for this purpose include SPM-Statistical Parametric Mapping-or FSL-FMRIB Software Library. Slice Timing Correction: Since the slices of fu