Abstract
Epilepsy is one of the most prevalent neurological diseases with a high morbidity. Accumulating evidence has shown that epilepsy is an archetypical neural network disorder. Here we developed a non-invasive cortical functional connectivity analysis based on magnetoencephalography (MEG) to assess commonalities and differences in the network phenotype in different epilepsy syndromes (non-lesional/cryptogenic focal and idiopathic/genetic generalized epilepsy). Thirty-seven epilepsy patients with normal structural brain anatomy underwent a 30-min resting state MEG measurement with eyes closed. We only analyzed interictal epochs without epileptiform discharges. The imaginary part of coherency was calculated as an indicator of cortical functional connectivity in five classical frequency bands. This connectivity measure was computed between all sources on individually reconstructed cortical surfaces that were surface-aligned to a common template. In comparison to healthy controls, both focal and generalized epilepsy patients showed widespread increased functional connectivity in several frequency bands, demonstrating the potential of elevated functional connectivity as a common pathophysiological hallmark in different epilepsy types. Furthermore, the comparison between focal and generalized epilepsies revealed increased network connectivity in bilateral mesio-frontal and motor regions specifically for the generalized epilepsy patients. Our study indicated that the surface-based normalization of MEG sources of individual brains enables the comparison of imaging findings across subjects and groups on a united platform, which leads to a straightforward and effective disclosure of pathological network characteristics in epilepsy. This approach may allow for the definition of more specific markers of different epilepsy syndromes, and increased MEG-based resting-state functional connectivity seems to be a common feature in MRI-negative epilepsy syndromes.
Similar content being viewed by others
References
Arzy S, Allali G, Brunet D et al (2010) Antiepileptic drugs modify power of high EEG frequencies and their neural generators. Eur J Neurol 17:1308–1312. https://doi.org/10.1111/j.1468-1331.2010.03018.x
Berg AT, Berkovic SF, Brodie MJ et al (2010) Revised terminology and concepts for organization of seizures and epilepsies: report of the ILAE Commission on Classification and Terminology, 2005–2009. Epilepsia 51:676–685. https://doi.org/10.1111/j.1528-1167.2010.02522.x
Bettus G, Wendling F, Guye M et al (2008) Enhanced EEG functional connectivity in mesial temporal lobe epilepsy. Epilepsy Res 81:58–68. https://doi.org/10.1016/j.eplepsyres.2008.04.020
Chavez M, Valencia M, Navarro V et al (2010) Functional modularity of background activities in normal and epileptic brain networks. Phys Rev Lett 104:118701. https://doi.org/10.1103/PhysRevLett.104.118701
Chen P-C, Castillo EM, Baumgartner J et al (2016) Identification of focal epileptogenic networks in generalized epilepsy using brain functional connectivity analysis of bilateral intracranial EEG signals. Brain Topogr. https://doi.org/10.1007/s10548-016-0493-3
Coito A, Genetti M, Pittau F et al (2016a) Altered directed functional connectivity in temporal lobe epilepsy in the absence of interictal spikes: a high density EEG study. Epilepsia 57:402–411. https://doi.org/10.1111/epi.13308
Coito A, Michel CM, van Mierlo P et al (2016b) Directed functional brain connectivity based on EEG source imaging: methodology and application to temporal lobe epilepsy. IEEE Trans Biomed Eng 63:2619–2628. https://doi.org/10.1109/TBME.2016.2619665
Dale AM, Fischl B, Sereno MI (1999) Cortical surface-based analysis. I. Segmentation and surface reconstruction. Neuroimage 9:179–194
Desikan RS, Ségonne F, Fischl B et al (2006) An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 31:968–980. https://doi.org/10.1016/j.neuroimage.2006.01.021
Elisevich K, Shukla N, Moran JE et al (2011) An assessment of MEG coherence imaging in the study of temporal lobe epilepsy. Epilepsia 52:1110–1119. https://doi.org/10.1111/j.1528-1167.2011.02990.x
Elshahabi A, Klamer S, Sahib AK et al (2015) Magnetoencephalography reveals a widespread increase in network connectivity in idiopathic/genetic generalized epilepsy. PLoS ONE 10:e0138119. https://doi.org/10.1371/journal.pone.0138119
Engel J, Thompson PM, Stern JM et al (2013) Connectomics and epilepsy. Curr Opin Neurol 26:186–194. https://doi.org/10.1097/WCO.0b013e32835ee5b8
Englot DJ, Hinkley LB, Kort NS et al (2015) Global and regional functional connectivity maps of neural oscillations in focal epilepsy. Brain 138:2249–2262. https://doi.org/10.1093/brain/awv130
Englot DJ, Konrad PE, Morgan VL (2016) Regional and global connectivity disturbances in focal epilepsy, related neurocognitive sequelae, and potential mechanistic underpinnings. Epilepsia. https://doi.org/10.1111/epi.13510
Fischl B, Sereno MI, Dale AM (1999) Cortical surface-based analysis. II: inflation, flattening, and a surface-based coordinate system. Neuroimage 9:195–207
Fischl B, van der Kouwe A, Destrieux C et al (2004) Automatically parcellating the human cerebral cortex. Cereb Cortex 14:11–22
Gross J, Kujala J, Hamalainen M et al (2001) Dynamic imaging of coherent sources: studying neural interactions in the human brain. Proc Natl Acad Sci USA 98:694–699
Hamandi K, Routley BC, Koelewijn L, Singh KD (2016) Non-invasive brain mapping in epilepsy: applications from magnetoencephalography. J Neurosci Methods 260:283–291. https://doi.org/10.1016/j.jneumeth.2015.11.012
Horstmann M-T, Bialonski S, Noennig N et al (2010) State dependent properties of epileptic brain networks: comparative graph-theoretical analyses of simultaneously recorded EEG and MEG. Clin Neurophysiol 121:172–185. https://doi.org/10.1016/j.clinph.2009.10.013
Hsiao F-J, Yu H-Y, Chen W-T et al (2015) Increased intrinsic connectivity of the default mode network in temporal lobe epilepsy: evidence from resting-state MEG recordings. PLoS ONE 10:e0128787. https://doi.org/10.1371/journal.pone.0128787
Jeong W, Jin S-H, Kim M et al (2014) Abnormal functional brain network in epilepsy patients with focal cortical dysplasia. Epilepsy Res 108:1618–1626. https://doi.org/10.1016/j.eplepsyres.2014.09.006
Jin S-H, Jeong W, Chung CK (2015) Focal cortical dysplasia alters electrophysiological cortical hubs in the resting-state. Clin Neurophysiol 126:1482–1492. https://doi.org/10.1016/j.clinph.2014.10.010
Kramer MA, Cash SS (2012) Epilepsy as a disorder of cortical network organization. Neuroscientist 18:360–372. https://doi.org/10.1177/1073858411422754
Litt B, Echauz J (2002) Prediction of epileptic seizures. Lancet Neurol 1:22–30
Maris E, Oostenveld R (2007) Nonparametric statistical testing of EEG- and MEG-data. J Neurosci Methods 164:177–190
Nazem-Zadeh M-R, Bowyer SM, Moran JE et al (2016) MEG coherence and DTI connectivity in mTLE. Brain Topogr 29:598–622. https://doi.org/10.1007/s10548-016-0488-0
Niso G, Carrasco S, Gudín M et al (2015) What graph theory actually tells us about resting state interictal MEG epileptic activity. Neuroimage Clin 8:503–515. https://doi.org/10.1016/j.nicl.2015.05.008
Nolte G (2003) The magnetic lead field theorem in the quasi-static approximation and its use for magnetoencephalography forward calculation in realistic volume conductors. Phys Med Biol 48:3637–3652
Nolte G, Bai O, Wheaton L et al (2004) Identifying true brain interaction from EEG data using the imaginary part of coherency. Clin Neurophysiol 115:2292–2307. https://doi.org/10.1016/j.clinph.2004.04.029
Onnela J-P, Saramäki J, Kertész J, Kaski K (2005) Intensity and coherence of motifs in weighted complex networks. Phys Rev E 71:65103. https://doi.org/10.1103/PhysRevE.71.065103
Oostenveld R, Fries P, Maris E et al (2010) FieldTrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data, FieldTrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Comput Intell Neurosci 2011:e156869. https://doi.org/10.1155/2011/156869
Penfield W, Jasper H (1954) Epilepsy and the functional anatomy of the human brain. Little, Brown, Boston
Pitkänen A, Löscher W, Vezzani A et al (2016) Advances in the development of biomarkers for epilepsy. Lancet Neurol 15:843–856. https://doi.org/10.1016/S1474-4422(16)00112-5
Rubinov M, Sporns O (2010) Complex network measures of brain connectivity: uses and interpretations. Neuroimage 52:1059–1069. https://doi.org/10.1016/j.neuroimage.2009.10.003
Saad ZS, Reynolds RC (2012) SUMA. Neuroimage 62:768–773. https://doi.org/10.1016/j.neuroimage.2011.09.016
Scheffer IE, Berkovic S, Capovilla G et al (2017) ILAE classification of the epilepsies: position paper of the ILAE Commission for Classification and Terminology. Epilepsia 58:512–521. https://doi.org/10.1111/epi.13709
Schindler KA, Bialonski S, Horstmann M-T et al (2008) Evolving functional network properties and synchronizability during human epileptic seizures. Chaos 18:33119. https://doi.org/10.1063/1.2966112
Schoffelen J-M, Gross J (2009) Source connectivity analysis with MEG and EEG. Hum Brain Mapp 30:1857–1865. https://doi.org/10.1002/hbm.20745
Stam CJ (2004) Functional connectivity patterns of human magnetoencephalographic recordings: a “small-world” network? Neurosci Lett 355:25–28
Tracy JI, Doucet GE (2015) Resting-state functional connectivity in epilepsy: growing relevance for clinical decision making. Curr Opin Neurol 28:158–165. https://doi.org/10.1097/WCO.0000000000000178
van Dellen E, Douw L, Hillebrand A et al (2012) MEG network differences between low- and high-grade glioma related to epilepsy and cognition. PLoS ONE 7:e50122. https://doi.org/10.1371/journal.pone.0050122
van Dellen E, Douw L, Hillebrand A et al (2014) Epilepsy surgery outcome and functional network alterations in longitudinal MEG: a minimum spanning tree analysis. Neuroimage 86:354–363. https://doi.org/10.1016/j.neuroimage.2013.10.010
van Diessen E, Diederen SJH, Braun KPJ et al (2013) Functional and structural brain networks in epilepsy: what have we learned? Epilepsia 54:1855–1865. https://doi.org/10.1111/epi.12350
van Diessen E, Zweiphenning WJEM., Jansen FE et al (2014) Brain network organization in focal epilepsy: a systematic review and meta-analysis. PLoS ONE 9:e114606. https://doi.org/10.1371/journal.pone.0114606
van Diessen E, Otte WM, Stam CJ et al (2016) Electroencephalography based functional networks in newly diagnosed childhood epilepsies. Clin Neurophysiol 127:2325–2332. https://doi.org/10.1016/j.clinph.2016.03.015
Vaughan DN, Rayner G, Tailby C, Jackson GD (2016) MRI-negative temporal lobe epilepsy: a network disorder of neocortical connectivity. Neurology 87:1934–1942. https://doi.org/10.1212/WNL.0000000000003289
Verhoeven T, Coito A, Plomp G et al (2018) Automated diagnosis of temporal lobe epilepsy in the absence of interictal spikes. NeuroImage: Clinical 17:10–15. https://doi.org/10.1016/j.nicl.2017.09.021
Weaver KE, Chaovalitwongse WA, Novotny EJ et al (2013) Local functional connectivity as a pre-surgical tool for seizure focus identification in non-lesion, focal epilepsy. Front Neurol 4:43. https://doi.org/10.3389/fneur.2013.00043
Wu T, Ge S, Zhang R et al (2014) Neuromagnetic coherence of epileptic activity: an MEG study. Seizure 23:417–423. https://doi.org/10.1016/j.seizure.2014.01.022
Zalesky A, Fornito A, Bullmore ET (2010) Network-based statistic: identifying differences in brain networks. NeuroImage 53:1197–1207. https://doi.org/10.1016/j.neuroimage.2010.06.041
Zhang Z, Liao W, Chen H et al (2011) Altered functional-structural coupling of large-scale brain networks in idiopathic generalized epilepsy. Brain 134:2912–2928. https://doi.org/10.1093/brain/awr223
Zhang CH, Sha Z, Mundahl J et al (2015) Thalamocortical relationship in epileptic patients with generalized spike and wave discharges—a multimodal neuroimaging study. Neuroimage Clin 9:117–127. https://doi.org/10.1016/j.nicl.2015.07.014
Acknowledgements
Author A.E. was funded by the Werner Reichardt Center for Integrative Neuroscience, Pool Project Number (2014-02), University of Tuebingen. Author N.K.F. was supported by DFG Grant FO-750 5/1. Part of this work was performed on the computational resource bwUniCluster funded by the Ministry of Science, Research and the Arts Baden-Württemberg and the Universities of the State of Baden-Württemberg, Germany, within the framework program bwHPC.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
N.K.F. has received speaker honoraria from Eisai, UCB and Bial and served in advisory boards for Eisai and Bial, none of which were directly related to the present work. The other authors have no conflict of interest to disclose.
Additional information
Handling Editor: Christoph M. Michel.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Li Hegner, Y., Marquetand, J., Elshahabi, A. et al. Increased Functional MEG Connectivity as a Hallmark of MRI-Negative Focal and Generalized Epilepsy. Brain Topogr 31, 863–874 (2018). https://doi.org/10.1007/s10548-018-0649-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10548-018-0649-4