Literature DB >> 27334988

Comparison of Brain Networks During Interictal Oscillations and Spikes on Magnetoencephalography and Intracerebral EEG.

Nawel Jmail1,2, Martine Gavaret1,3, F Bartolomei1,3, P Chauvel1,3, Jean-Michel Badier1, Christian-G Bénar4.   

Abstract

Electromagnetic source localization in electroencephalography (EEG) and magnetoencephalography (MEG) allows finding the generators of transient interictal epileptiform discharges ('interictal spikes'). In intracerebral EEG (iEEG), oscillatory activity (above 30 Hz) has also been shown to be a marker of neuronal dysfunction. Still, the difference between networks involved in transient and oscillatory activities remains largely unknown. Our goal was thus to extract and compare the networks involved in interictal oscillations and spikes, and to compare the non-invasive results to those obtained directly within the brain. In five patients with both MEG and iEEG recordings, we computed correlation graphs across regions, for (1) interictal spikes and (2) epileptic oscillations around 30 Hz. We show that the corresponding networks can involve a widespread set of regions (average of 10 per patient), with only partial overlap (38 % of the total number of regions in MEG, 50 % in iEEG). The non-invasive results were concordant with intracerebral recordings (79 % for the spikes and 50 % for the oscillations). We compared our interictal results to iEEG ictal data. The regions labeled as seizure onset zone (SOZ) belonged to interictal networks in a large proportion of cases: 75 % (resp. 58 %) for spikes and 58 % (resp. 33 %) for oscillations in iEEG (resp. MEG). A subset of SOZ regions were detected by one type of discharges but not the other (25 % for spikes and 8 % for oscillations). Our study suggests that spike and oscillatory activities involve overlapping but distinct networks, and are complementary for presurgical mapping.

Entities:  

Keywords:  Connectivity; Epilepsy; Intracerebral EEG; MEG; Oscillations; Spikes

Mesh:

Year:  2016        PMID: 27334988     DOI: 10.1007/s10548-016-0501-7

Source DB:  PubMed          Journal:  Brain Topogr        ISSN: 0896-0267            Impact factor:   3.020


  5 in total

1.  Electrophysiological Brain Connectivity: Theory and Implementation.

Authors:  Bin He; Laura Astolfi; Pedro A Valdes-Sosa; Daniele Marinazzo; Satu Palva; Christian G Benar; Christoph M Michel; Thomas Koenig
Journal:  IEEE Trans Biomed Eng       Date:  2019-05-07       Impact factor: 4.538

2.  Integration of stationary wavelet transform on a dynamic partial reconfiguration for recognition of pre-ictal gamma oscillations.

Authors:  N Jmail; M Zaghdoud; A Hadriche; T Frikha; C Ben Amar; C Bénar
Journal:  Heliyon       Date:  2018-03-01

3.  Assessment of Effective Network Connectivity among MEG None Contaminated Epileptic Transitory Events.

Authors:  Abir Hadriche; Ichrak Behy; Amal Necibi; Abdennaceur Kachouri; Chokri Ben Amar; Nawel Jmail
Journal:  Comput Math Methods Med       Date:  2021-12-28       Impact factor: 2.238

4.  Dynamic analysis on simultaneous iEEG-MEG data via hidden Markov model.

Authors:  Siqi Zhang; Chunyan Cao; Andrew Quinn; Umesh Vivekananda; Shikun Zhan; Wei Liu; Bomin Sun; Mark Woolrich; Qing Lu; Vladimir Litvak
Journal:  Neuroimage       Date:  2021-03-01       Impact factor: 6.556

Review 5.  Presurgical Evaluation of Epilepsy Using Resting-State MEG Functional Connectivity.

Authors:  Na Xu; Wei Shan; Jing Qi; Jianping Wu; Qun Wang
Journal:  Front Hum Neurosci       Date:  2021-07-02       Impact factor: 3.169

  5 in total

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