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Annals of Indian Academy of Neurology
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ARTICLE
Year : 2014  |  Volume : 17  |  Issue : 5  |  Page : 113-119

Magnetoencephalography recording and analysis


Department of Neurology, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India

Correspondence Address:
Sanjib Sinha
National Institute of Mental Health and Neurosciences (NIMHANS),Hosur Road, Bangalore - 560 029, Karnataka
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0972-2327.128678

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Magnetoencephalography (MEG) non-invasively measures the magnetic field generated due to the excitatory postsynaptic electrical activity of the apical dendritic pyramidal cells. Such a tiny magnetic field is measured with the help of the biomagnetometer sensors coupled with the Super Conducting Quantum Interference Device (SQUID) inside the magnetically shielded room (MSR). The subjects are usually screened for the presence of ferromagnetic materials, and then the head position indicator coils, electroencephalography (EEG) electrodes (if measured simultaneously), and fiducials are digitized using a 3D digitizer, which aids in movement correction and also in transferring the MEG data from the head coordinates to the device and voxel coordinates, thereby enabling more accurate co-registration and localization. MEG data pre-processing involves filtering the data for environmental and subject interferences, artefact identification, and rejection. Magnetic resonance Imaging (MRI) is processed for correction and identifying fiducials. After choosing and computing for the appropriate head models (spherical or realistic; boundary/finite element model), the interictal/ictal epileptiform discharges are selected and modeled by an appropriate source modeling technique (clinically and commonly used - single equivalent current dipole - ECD model). The equivalent current dipole (ECD) source localization of the modeled interictal epileptiform discharge (IED) is considered physiologically valid or acceptable based on waveform morphology, isofield pattern, and dipole parameters (localization, dipole moment, confidence volume, goodness of fit). Thus, MEG source localization can aid clinicians in sublobar localization, lateralization, and grid placement, by evoking the irritative/seizure onset zone. It also accurately localizes the eloquent cortex-like visual, language areas. MEG also aids in diagnosing and delineating multiple novel findings in other neuropsychiatric disorders, including Alzheimer's disease, Parkinsonism, Traumatic brain injury, autistic disorders, and so oon.


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