Description
Title: Magnetoencephalography (MEG) and Its Clinical Applications: A Short Introduction
Abstract: The diagnosis of brain disorders relies heavily on magnetoencephalography (MEG). We looked into possible MEG applications for analyzing brain disorders in this review. Since MEG has a higher signal-to-noise ratio and spatial resolution than EEG (SRMEG = 2-3 mm, SREEG = 7-10 mm), it may be possible to monitor cortical activity accurately using MEG. We discovered that the direct electrophysiological MEG signals were crucial for identifying diseases because they accurately reflected the physiological status of neurological disorders. Neurological disorders like epilepsy, Alzheimer’s, Parkinsonism, autism, and schizophrenia have been diagnosed using single-channel connectivity as well as brain network analysis using MEG data collected during resting state and a specific task. There is also discussion of the MEG workflow and its potential use in disease diagnosis and treatment planning. We predict that in the future, computer-aided algorithms will be widely used in the diagnosis and prediction of neurological diseases. The results of this narrative review will help scientists use MEG for diagnostic purposes.
Keywords: magnetoencephalography (MEG); clinical application; brain network; brain connectivity; neurological disorder; electrophysiology; diagnostic; therapeutic; computer-aided algorithms
Paper Quality: SCOPUS / Web of Science Level Research Paper
Subject: Biology
Writer Experience: 20+ Years
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