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Detection of abnormal resting-state networks in individual patients suffering from focal epilepsy: an initial step toward individual connectivity assessment.

Author(s): Dansereau CL, Bellec P, Lee K, Pittau F, Gotman J, Grova C

Front Neurosci. 2014;8:419 Authors: Dansereau CL, Bellec P, Lee K, Pittau F, Gotman J, Grova C

Article GUID: 25565949
Detection and Magnetic Source Imaging of Fast Oscillations (40-160 Hz) Recorded with Magnetoencephalography in Focal Epilepsy Patients.

Author(s): von Ellenrieder N, Pellegrino G, Hedrich T, Gotman J, Lina JM, Grova C, Kobayashi E

Brain Topogr. 2016 Mar;29(2):218-31 Authors: von Ellenrieder N, Pellegrino G, Hedrich T, Gotman J, Lina JM, Grova C, Kobayashi E

Article GUID: 26830767
SPARK: Sparsity-based analysis of reliable k-hubness and overlapping network structure in brain functional connectivity.

Author(s): Lee K, Lina JM, Gotman J, Grova C

Neuroimage. 2016 07 01;134:434-449 Authors: Lee K, Lina JM, Gotman J, Grova C

Article GUID: 27046111
Disruption, emergence and lateralization of brain network hubs in mesial temporal lobe epilepsy.

Author(s): Lee K, Khoo HM, Lina JM, Dubeau F, Gotman J, Grova C

Neuroimage Clin. 2018;20:71-84 Authors: Lee K, Khoo HM, Lina JM, Dubeau F, Gotman J, Grova C

Article GUID: 30094158
Automatic classification and removal of structured physiological noise for resting state functional connectivity MRI analysis.

Author(s): Lee K, Khoo HM, Fourcade C, Gotman J, Grova C

Magn Reson Imaging. 2019 05;58:97-107 Authors: Lee K, Khoo HM, Fourcade C, Gotman J, Grova C

Article GUID: 30695721
Title:Detection and Magnetic Source Imaging of Fast Oscillations (40-160 Hz) Recorded with Magnetoencephalography in Focal Epilepsy Patients.
Authors:von Ellenrieder N,  Pellegrino G,  Hedrich T,  Gotman J,  Lina JM,  Grova C,  Kobayashi E
Link:https://www.ncbi.nlm.nih.gov/pubmed/26830767?dopt=Abstract
DOI:10.1007/s10548-016-0471-9
Category:Brain Topogr
PMID:26830767
Dept Affiliation: PERFORM
1 Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada.
2 Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, 3775 University Street, Montreal, QC, H3A 2B4, Canada.
3 LEICI, CONICET - Universidad Nacional de La Plata, Calle 116 y 48, 1900, La Plata, Argentina.
4 Département de Génie Électrique, École de Technologie Supérieure, 1100 Notre-Dame Street West, Montreal, QC, H3C 1K3, Canada.
5 Centre de Recherches Mathematiques, Univeristé de Montréal, 2920 Chemin de la tour, Montreal, QC, H3T 1J4, Canada.
6 Center for Advanced Research on Sleep Medecine, Centre de Rech. de l'Hôpital du Sacré-Cœur de Montréal, 5400 W Gouin Blvd, Montreal, QC, H4J 1J5, Canada.
7 Physics Department and PERFORM Centre, Concordia University, 7141 Sherbrooke Street West, Montreal, QC, H4B 1R6, Canada.
8 Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada. eliane.kobayashi@mcgill.ca.

Description:

Detection and Magnetic Source Imaging of Fast Oscillations (40-160 Hz) Recorded with Magnetoencephalography in Focal Epilepsy Patients.

Brain Topogr. 2016 Mar;29(2):218-31

Authors: von Ellenrieder N, Pellegrino G, Hedrich T, Gotman J, Lina JM, Grova C, Kobayashi E

Abstract

We present a framework to detect fast oscillations (FOs) in magnetoencephalography (MEG) and to perform magnetic source imaging (MSI) to determine the location and extent of their generators in the cortex. FOs can be of physiologic origin associated to sensory processing and memory consolidation. In epilepsy, FOs are of pathologic origin and biomarkers of the epileptogenic zone. Seventeen patients with focal epilepsy previously confirmed with identified FOs in scalp electroencephalography (EEG) were evaluated. To handle data deriving from large number of sensors (275 axial gradiometers) we used an automatic detector with high sensitivity. False positives were discarded by two human experts. MSI of the FOs was performed with the wavelet based maximum entropy on the mean method. We found FOs in 11/17 patients, in only one patient the channel with highest FO rate was not concordant with the epileptogenic region and might correspond to physiologic oscillations. MEG FOs rates were very low: 0.02-4.55 per minute. Compared to scalp EEG, detection sensitivity was lower, but the specificity higher in MEG. MSI of FOs showed concordance or partial concordance with proven generators of seizures and epileptiform activity in 10/11 patients. We have validated the proposed framework for the non-invasive study of FOs with MEG. The excellent overall concordance with other clinical gold standard evaluation tools indicates that MEG FOs can provide relevant information to guide implantation for intracranial EEG pre-surgical evaluation and for surgical treatment, and demonstrates the important added value of choosing appropriate FOs detection and source localization methods.

PMID: 26830767 [PubMed - indexed for MEDLINE]