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Magnetoencephalography recording and analysis
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 Quan...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Medknow Publications & Media Pvt Ltd
2014
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4001226/ https://www.ncbi.nlm.nih.gov/pubmed/24791077 http://dx.doi.org/10.4103/0972-2327.128678 |
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author | Velmurugan, Jayabal Sinha, Sanjib Satishchandra, Parthasarathy |
author_facet | Velmurugan, Jayabal Sinha, Sanjib Satishchandra, Parthasarathy |
author_sort | Velmurugan, Jayabal |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4001226 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Medknow Publications & Media Pvt Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-40012262014-05-01 Magnetoencephalography recording and analysis Velmurugan, Jayabal Sinha, Sanjib Satishchandra, Parthasarathy Ann Indian Acad Neurol Article 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. Medknow Publications & Media Pvt Ltd 2014-03 /pmc/articles/PMC4001226/ /pubmed/24791077 http://dx.doi.org/10.4103/0972-2327.128678 Text en Copyright: © Annals of Indian Academy of Neurology http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Article Velmurugan, Jayabal Sinha, Sanjib Satishchandra, Parthasarathy Magnetoencephalography recording and analysis |
title | Magnetoencephalography recording and analysis |
title_full | Magnetoencephalography recording and analysis |
title_fullStr | Magnetoencephalography recording and analysis |
title_full_unstemmed | Magnetoencephalography recording and analysis |
title_short | Magnetoencephalography recording and analysis |
title_sort | magnetoencephalography recording and analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4001226/ https://www.ncbi.nlm.nih.gov/pubmed/24791077 http://dx.doi.org/10.4103/0972-2327.128678 |
work_keys_str_mv | AT velmuruganjayabal magnetoencephalographyrecordingandanalysis AT sinhasanjib magnetoencephalographyrecordingandanalysis AT satishchandraparthasarathy magnetoencephalographyrecordingandanalysis |