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Accuracy and spatial properties of distributed magnetic source imaging techniques in the investigation of focal epilepsy patients.

Author(s): Pellegrino G, Hedrich T, Porras-Bettancourt M, Lina JM, Aydin Ü, Hall J, Grova C, Kobayashi E

Hum Brain Mapp. 2020 May 09;: Authors: Pellegrino G, Hedrich T, Porras-Bettancourt M, Lina JM, Aydin Ü, Hall J, Grova C, Kobayashi E

Article GUID: 32386115
Magnetoencephalography resting state connectivity patterns as indicatives of surgical outcome in epilepsy patients.

Author(s): Aydin Ü, Pellegrino G, Bin Ka'b Ali O, Abdallah C, Dubeau F, Lina JM, Kobayashi E, Grova C

J Neural Eng. 2020 Mar 18;: Authors: Aydin Ü, Pellegrino G, Bin Ka'b Ali O, Abdallah C, Dubeau F, Lina JM, Kobayashi E, Grova C

Article GUID: 32191632
Influence of Head Tissue Conductivity Uncertainties on EEG Dipole Reconstruction.

Author(s): Vorwerk J, Aydin Ü, Wolters CH, Butson CR

Front Neurosci. 2019;13:531 Authors: Vorwerk J, Aydin Ü, Wolters CH, Butson CR

Article GUID: 31231178
Zoomed MRI Guided by Combined EEG/MEG Source Analysis: A Multimodal Approach for Optimizing Presurgical Epilepsy Work-up and its Application in a Multi-focal Epilepsy Patient Case Study.

Author(s): Aydin Ü, Rampp S, Wollbrink A, Kugel H, Cho J-, Knösche TR, Grova C, Wellmer J, Wolters CH

Brain Topogr. 2017 Jul;30(4):417-433 Authors: Aydin Ü, Rampp S, Wollbrink A, Kugel H, Cho J-, Knösche TR, Grova C, Wellmer J, Wolters CH

Article GUID: 28510905
Reproducibility of EEG-MEG fusion source analysis of interictal spikes: Relevance in presurgical evaluation of epilepsy.

Author(s): Chowdhury RA, Pellegrino G, Aydin Ü, Lina JM, Dubeau F, Kobayashi E, Grova C

Hum Brain Mapp. 2018 02;39(2):880-901 Authors: Chowdhury RA, Pellegrino G, Aydin Ü, Lina JM, Dubeau F, Kobayashi E, Grova C

Article GUID: 29164737
Title:Magnetoencephalography resting state connectivity patterns as indicatives of surgical outcome in epilepsy patients.
Authors:Aydin Ü,  Pellegrino G,  Bin Ka'b Ali O,  Abdallah C,  Dubeau F,  Lina JM,  Kobayashi E,  Grova C
Link:https://www.ncbi.nlm.nih.gov/pubmed/32191632?dopt=Abstract
DOI:10.1088/1741-2552/ab8113
Category:J Neural Eng
PMID:32191632
Dept Affiliation: PERFORM
1 Multimodal Functional Imaging Lab, Department of Physics and PERFORM Centre, Concordia University, Montreal, Québec, Canada. Authors to whom any correspondence should be addressed.

Description:

Magnetoencephalography resting state connectivity patterns as indicatives of surgical outcome in epilepsy patients.

J Neural Eng. 2020 Mar 18;:

Authors: Aydin Ü, Pellegrino G, Bin Ka'b Ali O, Abdallah C, Dubeau F, Lina JM, Kobayashi E, Grova C

Abstract

OBJECTIVE: Focal epilepsy is a disorder affecting several brain networks; however, epilepsy surgery usually targets a restricted region, the so-called epileptic focus. There is a growing interest in embedding resting state (RS) connectivity analysis into pre-surgical workup.

APPROACH: In this retrospective study, we analyzed Magnetoencephalography (MEG) long-range RS functional connectivity patterns in patients with drug-resistant focal epilepsy. MEG recorded prior to surgery from seven seizure-free (Engel Ia) and five non seizure-free (Engel III or IV) patients were analyzed (minimum 2-years post-surgical follow-up). MEG segments without any detectable epileptic activity were source localized using wavelet-based Maximum Entropy on the Mean method. Amplitude envelope correlation in the theta (4-8 Hz), alpha (8-13 Hz), and beta (13-26 Hz) bands were used for assessing connectivity.

MAIN RESULTS: For seizure-free patients, we found an isolated epileptic network characterized by weaker connections between the brain region where interictal epileptic discharges (IED) are generated and the rest of the cortex, when compared to connectivity between the corresponding contralateral homologous region and the rest of the cortex. Contrarily, non seizure-free patients exhibited a widespread RS epileptic network characterized by stronger connectivity between the IED generator and the rest of the cortex, in comparison to the contralateral region and the cortex. Differences between the two seizure outcome groups concerned mainly distant long-range connections and were found in the alpha band.

SIGNIFICANCE: Importantly, these connectivity patterns suggest specific mechanisms describing the underlying organization of the epileptic network and were detectable at the individual patient level, supporting the prospect use of MEG connectivity patterns in epilepsy to predict post-surgical seizure outcome.

PMID: 32191632 [PubMed - as supplied by publisher]