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Silva Alves A, Rigoni I, Mégevand P, Lagarde S, Picard F, Seeck M, Vulliémoz S, Roehri N. High-density electroencephalographic functional networks in genetic generalized epilepsy: Preserved whole-brain topology hides local reorganization. Epilepsia 2024; 65:961-973. [PMID: 38306118 DOI: 10.1111/epi.17903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 01/15/2024] [Accepted: 01/16/2024] [Indexed: 02/03/2024]
Abstract
OBJECTIVE Genetic generalized epilepsy (GGE) accounts for approximately 20% of adult epilepsy cases and is considered a disorder of large brain networks, involving both hemispheres. Most studies have not shown any difference in functional whole-brain network topology when compared to healthy controls. Our objective was to examine whether this preserved global network topology could hide local reorganizations that balance out at the global network level. METHODS We recorded high-density electroencephalograms from 20 patients and 20 controls, and reconstructed the activity of 118 regions. We computed functional connectivity in windows free of interictal epileptiform discharges in broad, delta, theta, alpha, and beta frequency bands, characterized the network topology, and used the Hub Disruption Index (HDI) to quantify the topological reorganization. We examined the generalizability of our results by reproducing a 25-electrode clinical system. RESULTS Our study did not reveal any significant change in whole-brain network topology among GGE patients. However, the HDI was significantly different between patients and controls in all frequency bands except alpha (p < .01, false discovery rate [FDR] corrected, d < -1), and accompanied by an increase in connectivity in the prefrontal regions and default mode network. This reorganization suggests that regions that are important in transferring the information in controls were less so in patients. Inversely, the crucial regions in patients are less so in controls. These findings were also found in delta and theta frequency bands when using 25 electrodes (p < .001, FDR corrected, d < -1). SIGNIFICANCE In GGE patients, the overall network topology is similar to that of healthy controls but presents a balanced local topological reorganization. This reorganization causes the prefrontal areas and default mode network to be more integrated and segregated, which may explain executive impairment associated with GGE. Additionally, the reorganization distinguishes patients from controls even when using 25 electrodes, suggesting its potential use as a diagnostic tool.
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Affiliation(s)
- André Silva Alves
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Isotta Rigoni
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Pierre Mégevand
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Stanislas Lagarde
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes, Marseille, France
| | - Fabienne Picard
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Margitta Seeck
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Serge Vulliémoz
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Nicolas Roehri
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
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Issabekov G, Matsumoto T, Hoshi H, Fukasawa K, Ichikawa S, Shigihara Y. Resting-state brain activity distinguishes patients with generalised epilepsy from others. Seizure 2024; 115:50-58. [PMID: 38183828 DOI: 10.1016/j.seizure.2024.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 12/14/2023] [Accepted: 01/01/2024] [Indexed: 01/08/2024] Open
Abstract
PURPOSE Epilepsy is a prevalent neurological disorder characterised by repetitive seizures. It is categorised into three types: generalised epilepsy (GE), focal epilepsy (FE), and combined generalised and focal epilepsy. Correctly subtyping the epilepsy is important to select appropriate treatments. The types are mainly determined (i.e., diagnosed) by their semiologies supported by clinical examinations, such as electroencephalography and magnetoencephalography (MEG). Although these examinations are traditionally based on visual inspections of interictal epileptic discharges (IEDs), which are not always visible, alternative analyses have been anticipated. We examined if resting-state brain activities can distinguish patients with GE, which would help us to diagnose the type of epilepsy. METHODS The 5 min resting-state brain activities acquired using MEG were obtained retrospectively from 15 patients with GE. The cortical source of the activities was estimated at each frequency band from delta to high-frequency oscillation (HFO). These estimated activities were compared with reference datasets from 133 healthy individuals and control data from 29 patients with FE. RESULTS Patients with GE showed larger theta in the occipital, alpha in the left temporal, HFO in the rostral deep regions, and smaller HFO in the caudal ventral regions. Their area under the curves of the receiver operating characteristic curves was around 0.8-0.9. The distinctive pattern was not found for data from FE. CONCLUSION Patients with GE show distinctive resting-state brain activity, which could be a potential biomarker and used complementarily to classical analysis based on the visual inspection of IEDs.
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Affiliation(s)
- Galymzhan Issabekov
- Precision Medicine Centre, Kumagaya General Hospital, Kumagaya 360-8567, Japan
| | - Takahiro Matsumoto
- Department of Neurosurgery, Kumagaya General Hospital, Kumagaya 360-8567, Japan
| | - Hideyuki Hoshi
- Precision Medicine Centre, Hokuto Hospital, Obihiro 080-0833, Japan
| | - Keisuke Fukasawa
- Clinical Laboratory, Kumagaya General Hospital, Kumagaya 360-8567, Japan
| | - Sayuri Ichikawa
- Clinical Laboratory, Kumagaya General Hospital, Kumagaya 360-8567, Japan
| | - Yoshihito Shigihara
- Precision Medicine Centre, Kumagaya General Hospital, Kumagaya 360-8567, Japan; Precision Medicine Centre, Hokuto Hospital, Obihiro 080-0833, Japan.
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van de Velden D, Stier C, Kotikalapudi R, Heide EC, Garnica-Agudelo D, Focke NK. Comparison of Resting-State EEG Network Analyses With and Without Parallel MRI in Genetic Generalized Epilepsy. Brain Topogr 2023; 36:750-765. [PMID: 37354244 PMCID: PMC10415462 DOI: 10.1007/s10548-023-00977-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 06/12/2023] [Indexed: 06/26/2023]
Abstract
Genetic generalized epilepsy (GGE) is conceptualized as a brain disorder involving distributed bilateral networks. To study these networks, simultaneous EEG-fMRI measurements can be used. However, inside-MRI EEG suffers from strong MR-related artifacts; it is not established whether EEG-based metrics in EEG-fMRI resting-state measurements are suitable for the analysis of group differences at source-level. We evaluated the impact of the inside-MR measurement condition on statistical group comparisons of EEG on source-level power and functional connectivity in patients with GGE versus healthy controls. We studied the cross-modal spatial relation of statistical group differences in seed-based FC derived from EEG and parallel fMRI. We found a significant increase in power and a frequency-specific change in functional connectivity for the inside MR-scanner compared to the outside MR-scanner condition. For power, we found reduced group difference between GGE and controls both in terms of statistical significance as well as effect size. Group differences for ImCoh remained similar both in terms of statistical significance as well as effect size. We found increased seed-based FC for GGE patients from the thalamus to the precuneus cortex region in fMRI, and in the theta band of simultaneous EEG. Our findings suggest that the analysis of EEG functional connectivity based on ImCoh is suitable for MR-EEG, and that relative group difference in a comparison of patients with GGE against controls are preserved. Spatial correspondence of seed-based FC group differences between the two modalities was found for the thalamus.
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Affiliation(s)
- Daniel van de Velden
- Clinic for Neurology, University Medical Center Göttingen, 37075, Göttingen, Germany.
| | - Christina Stier
- Clinic for Neurology, University Medical Center Göttingen, 37075, Göttingen, Germany
- Department of Neurology and Epileptology, Hertie Institute of Clinical Brain Research, University Medical Center Tübingen, University of Tübingen, 72076, Tübingen, Germany
| | - Raviteja Kotikalapudi
- Department of Neurology and Epileptology, Hertie Institute of Clinical Brain Research, University Medical Center Tübingen, University of Tübingen, 72076, Tübingen, Germany
- Clinic for Neurology, University Medical Center Essen/University Duisburg-Essen, 45147, Essen, Germany
| | - Ev-Christin Heide
- Clinic for Neurology, University Medical Center Göttingen, 37075, Göttingen, Germany
| | - David Garnica-Agudelo
- Clinic for Neurology, University Medical Center Göttingen, 37075, Göttingen, Germany
| | - Niels K Focke
- Clinic for Neurology, University Medical Center Göttingen, 37075, Göttingen, Germany.
- Department of Neurology and Epileptology, Hertie Institute of Clinical Brain Research, University Medical Center Tübingen, University of Tübingen, 72076, Tübingen, Germany.
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Stier C, Braun C, Focke NK. Adult lifespan trajectories of neuromagnetic signals and interrelations with cortical thickness. Neuroimage 2023; 278:120275. [PMID: 37451375 PMCID: PMC10443236 DOI: 10.1016/j.neuroimage.2023.120275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 07/03/2023] [Accepted: 07/11/2023] [Indexed: 07/18/2023] Open
Abstract
Oscillatory power and phase synchronization map neuronal dynamics and are commonly studied to differentiate the healthy and diseased brain. Yet, little is known about the course and spatial variability of these features from early adulthood into old age. Leveraging magnetoencephalography (MEG) resting-state data in a cross-sectional adult sample (n = 350), we probed lifespan differences (18-88 years) in connectivity and power and interaction effects with sex. Building upon recent attempts to link brain structure and function, we tested the spatial correspondence between age effects on cortical thickness and those on functional networks. We further probed a direct structure-function relationship at the level of the study sample. We found MEG frequency-specific patterns with age and divergence between sexes in low frequencies. Connectivity and power exhibited distinct linear trajectories or turning points at midlife that might reflect different physiological processes. In the delta and beta bands, these age effects corresponded to those on cortical thickness, pointing to co-variation between the modalities across the lifespan. Structure-function coupling was frequency-dependent and observed in unimodal or multimodal regions. Altogether, we provide a comprehensive overview of the topographic functional profile of adulthood that can form a basis for neurocognitive and clinical investigations. This study further sheds new light on how the brain's structural architecture relates to fast oscillatory activity.
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Affiliation(s)
- Christina Stier
- Clinic of Neurology, University Medical Center Göttingen, Göttingen, Germany; Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany.
| | - Christoph Braun
- MEG-Center, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany; CIMeC, Center for Mind/Brain Sciences, University of Trento, Rovereto, Italy
| | - Niels K Focke
- Clinic of Neurology, University Medical Center Göttingen, Göttingen, Germany
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5
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Barone V, Piastra MC, van Dijk JP, Visser GH, Debeij-van Hall MHJA, van Putten MJAM. Neurophysiological signatures reflect differences in visual attention during absence seizures. Clin Neurophysiol 2023; 152:34-42. [PMID: 37269771 DOI: 10.1016/j.clinph.2023.05.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 05/12/2023] [Accepted: 05/16/2023] [Indexed: 06/05/2023]
Abstract
OBJECTIVE Absences affect visual attention and eye movements variably. Here, we explore whether the dissimilarity of these symptoms during absences is reflected in differences in electroencephalographic (EEG) features, functional connectivity, and activation of the frontal eye field. METHODS Pediatric patients with absences performed a computerized choice reaction time task, with simultaneous recording of EEG and eye-tracking. We quantified visual attention and eye movements with reaction times, response correctness, and EEG features. Finally, we studied brain networks involved in the generation and propagation of seizures. RESULTS Ten pediatric patients had absences during the measurement. Five patients had preserved eye movements (preserved group) and five patients showed disrupted eye movements (unpreserved group) during seizures. Source reconstruction showed a stronger involvement of the right frontal eye field during absences in the unpreserved group than in the preserved group (dipole fraction 1.02% and 0.34%, respectively, p < 0.05). Graph analysis revealed different connection fractions of specific channels. CONCLUSIONS The impairment of visual attention varies among patients with absences and is associated with differences in EEG features, network activation, and involvement of the right frontal eye field. SIGNIFICANCE Assessing the visual attention of patients with absences can be usefully employed in clinical practice for tailored advice to the individual patient.
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Affiliation(s)
- Valentina Barone
- Clinical Neurophysiology (CNPH), TechMed Centre, University of Twente, Enschede, the Netherlands.
| | - Maria Carla Piastra
- Clinical Neurophysiology (CNPH), TechMed Centre, University of Twente, Enschede, the Netherlands.
| | - Johannes P van Dijk
- Academic Center for Epileptology Kempenhaeghe, Heeze, the Netherlands; Eindhoven University of Technology, Eindhoven, the Netherlands.
| | - Gerhard H Visser
- Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede, the Netherlands.
| | | | - Michel J A M van Putten
- Clinical Neurophysiology (CNPH), TechMed Centre, University of Twente, Enschede, the Netherlands; Department of Clinical Neurophysiology, Medisch Spectrum Twente, Enschede, the Netherlands.
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Wang Y, Li Y, Sun F, Xu Y, Xu F, Wang S, Wang X. Altered neuromagnetic activity in default mode network in childhood absence epilepsy. Front Neurosci 2023; 17:1133064. [PMID: 37008207 PMCID: PMC10060817 DOI: 10.3389/fnins.2023.1133064] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 02/27/2023] [Indexed: 03/18/2023] Open
Abstract
PurposeThe electrophysiological characterization of resting state oscillatory functional connectivity within the default mode network (DMN) during interictal periods in childhood absence epilepsy (CAE) remains unclear. Using magnetoencephalographic (MEG) recordings, this study investigated how the connectivity within the DMN was altered in CAE.MethodsUsing a cross-sectional design, we analyzed MEG data from 33 children newly diagnosed with CAE and 26 controls matched for age and sex. The spectral power and functional connectivity of the DMN were estimated using minimum norm estimation combined with the Welch technique and corrected amplitude envelope correlation.ResultsDefault mode network showed stronger activation in the delta band during the ictal period, however, the relative spectral power in other bands was significantly lower than that in the interictal period (pcorrected < 0.05 for DMN regions, except bilateral medial frontal cortex, left medial temporal lobe, left posterior cingulate cortex in the theta band, and the bilateral precuneus in the alpha band). It should be noted that the significant power peak in the alpha band was lost compared with the interictal data. Compared with controls, the interictal relative spectral power of DMN regions (except bilateral precuneus) in CAE patients was significantly increased in the delta band (pcorrected < 0.01), whereas the values of all DMN regions in the beta-gamma 2 band were significantly decreased (pcorrected < 0.01). In the higher frequency band (alpha-gamma1), especially in the beta and gamma1 band, the ictal node strength of DMN regions except the left precuneus was significantly higher than that in the interictal periods (pcorrected < 0.01), and the node strength of the right inferior parietal lobe increased most significantly in the beta band (Ictal: 3.8712 vs. Interictal: 0.7503, pcorrected < 0.01). Compared with the controls, the interictal node strength of DMN increased in all frequency bands, especially the right medial frontal cortex in the beta band (Controls: 0.1510 vs. Interictal: 3.527, pcorrected < 0.01). Comparing relative node strength between groups, the right precuneus in CAE children decreased significantly (β: Controls: 0.1009 vs. Interictal: 0.0475; γ 1: Controls:0.1149 vs. Interictal:0.0587, pcorrected < 0.01) such that it was no longer the central hub.ConclusionThese findings indicated DMN abnormalities in CAE patients, even in interictal periods without interictal epileptic discharges. Abnormal functional connectivity in CAE may reflect abnormal anatomo-functional architectural integration in DMN, as a result of cognitive mental impairment and unconsciousness during absence seizure. Future studies are needed to examine if the altered functional connectivity can be used as a biomarker for treatment responses, cognitive dysfunction, and prognosis in CAE patients.
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Kumar A, Lyzhko E, Hamid L, Srivastav A, Stephani U, Japaridze N. Neuronal networks underlying ictal and subclinical discharges in childhood absence epilepsy. J Neurol 2023; 270:1402-1415. [PMID: 36370186 PMCID: PMC9971098 DOI: 10.1007/s00415-022-11462-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 10/25/2022] [Accepted: 10/26/2022] [Indexed: 11/13/2022]
Abstract
Childhood absence epilepsy (CAE), involves 3 Hz generalized spikes and waves discharges (GSWDs) on the electroencephalogram (EEG), associated with ictal discharges (seizures) with clinical symptoms and impairment of consciousness and subclinical discharges without any objective clinical symptoms or impairment of consciousness. This study aims to comparatively characterize neuronal networks underlying absence seizures and subclinical discharges, using source localization and functional connectivity (FC), to better understand the pathophysiological mechanism of these discharges. Routine EEG data from 12 CAE patients, consisting of 45 ictal and 42 subclinical discharges were selected. Source localization was performed using the exact low-resolution electromagnetic tomography (eLORETA) algorithm, followed by FC based on the imaginary part of coherency. FC based on the thalamus as the seed of interest showed significant differences between ictal and subclinical GSWDs (p < 0.05). For delta (1-3 Hz) and alpha bands (8-12 Hz), the thalamus displayed stronger connectivity towards other brain regions for ictal GSWDs as compared to subclinical GSWDs. For delta band, the thalamus was strongly connected to the posterior cingulate cortex (PCC), precuneus, angular gyrus, supramarginal gyrus, parietal superior, and occipital mid-region for ictal GSWDs. The strong connections of the thalamus with other brain regions that are important for consciousness, and with components of the default mode network (DMN) suggest the severe impairment of consciousness in ictal GSWDs. However, for subclinical discharges, weaker connectivity between the thalamus and these brain regions may suggest the prevention of impairment of consciousness. This may benefit future therapeutic targets and improve the management of CAE patients.
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Affiliation(s)
- Ami Kumar
- Department of Neuropediatrics, Children's Hospital, University Medical Center Schleswig-Holstein, University of Kiel, Kiel, Germany. .,Faculty of Mathematics and Natural Sciences, University of Kiel, Kiel, Germany. .,Department of Neurology, Columbia University Irving Medical Center, New York, USA.
| | - Ekaterina Lyzhko
- Department of Neuropediatrics, Children’s Hospital, University Medical Center Schleswig-Holstein, University of Kiel, Kiel, Germany
| | - Laith Hamid
- Institute of Medical Psychology and Medical Sociology, University of Kiel, Kiel, Germany ,Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Anand Srivastav
- Faculty of Mathematics and Natural Sciences, University of Kiel, Kiel, Germany
| | - Ulrich Stephani
- Department of Neuropediatrics, Children’s Hospital, University Medical Center Schleswig-Holstein, University of Kiel, Kiel, Germany
| | - Natia Japaridze
- Department of Neuropediatrics, Children’s Hospital, University Medical Center Schleswig-Holstein, University of Kiel, Kiel, Germany
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Koo GE, Jeong HT, Youn YC, Han SH. Is Functional Connectivity after a First Unprovoked Seizure Different Based on Subsequent Seizures and Future Diagnosis of Epilepsy? J Epilepsy Res 2022; 12:62-67. [PMID: 36685746 PMCID: PMC9830024 DOI: 10.14581/jer.22011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Revised: 12/06/2022] [Accepted: 12/14/2022] [Indexed: 01/09/2023] Open
Abstract
Background and Purpose There are no highly sensitive biomarkers for epilepsy to date. Recently, promising results regarding functional connectivity analysis have been obtained, which may improve epilepsy diagnosis even in the absence of visible abnormality in electroencephalography. We aimed to investigate the differences in functional connectivity after a first unprovoked seizure between patients diagnosed with epilepsy within 1 year due to subsequent seizures and those who were not. Methods We compared quantitative electroencephalography power spectra and functional connectivity between 12 patients who were diagnosed with epilepsy (two or more unprovoked seizures) within 1 year and 17 controls (those not diagnosed within 1 year) using iSyncBrain® (iMediSync Inc., Suwon, Korea; https://isyncbrain.com/). In the source-level analysis, the current distribution across the brain was assessed using the standardized low-resolution brain electromagnetic tomography technique, to compare relative power values in 68 regions of interest and connectivity (the imaginary part of coherency) between regions of interest. Results In the epilepsy group, quantitative electroencephalography showed lower alpha2 band power in left frontal, central, superior temporal, and parietal regions and higher beta2 power in both frontal, central, temporal, occipital, and left parietal regions compared with the control group. Additionally, epilepsy patients had significantly lower connectivity in alpha2 and beta2 bands than the controls. Conclusions Patients experiencing their first unprovoked seizure presented different brain function according to whether they have subsequent seizures and future epilepsy. Our results propose the potential clinical ability to diagnose epilepsy after the first unprovoked seizure in the absence of interictal epileptiform discharges.
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Affiliation(s)
- Ga Eun Koo
- Department of Neurology, Chung-Ang University College of Medicine, Seoul, Korea
| | - Ho Tae Jeong
- Department of Neurology, Chung-Ang University College of Medicine, Seoul, Korea
| | - Young Chul Youn
- Department of Neurology, Chung-Ang University College of Medicine, Seoul, Korea
| | - Su-Hyun Han
- Department of Neurology, Chung-Ang University College of Medicine, Seoul, Korea
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Aung T, Tenney JR, Bagić AI. Contributions of Magnetoencephalography to Understanding Mechanisms of Generalized Epilepsies: Blurring the Boundary Between Focal and Generalized Epilepsies? Front Neurol 2022; 13:831546. [PMID: 35572923 PMCID: PMC9092024 DOI: 10.3389/fneur.2022.831546] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 03/08/2022] [Indexed: 12/31/2022] Open
Abstract
According to the latest operational 2017 ILAE classification of epileptic seizures, the generalized epileptic seizure is still conceptualized as "originating at some point within and rapidly engaging, bilaterally distributed networks." In contrast, the focal epileptic seizure is defined as "originating within networks limited to one hemisphere." Hence, one of the main concepts of "generalized" and "focal" epilepsy comes from EEG descriptions before the era of source localization, and a presumed simultaneous bilateral onset and bi-synchrony of epileptiform discharges remains a hallmark for generalized seizures. Current literature on the pathophysiology of generalized epilepsy supports the concept of a cortical epileptogenic focus triggering rapidly generalized epileptic discharges involving intact corticothalamic and corticocortical networks, known as the cortical focus theory. Likewise, focal epilepsy with rich connectivity can give rise to generalized spike and wave discharges resulting from widespread bilateral synchronization. Therefore, making this key distinction between generalized and focal epilepsy may be challenging in some cases, and for the first time, a combined generalized and focal epilepsy is categorized in the 2017 ILAE classification. Nevertheless, treatment options, such as the choice of antiseizure medications or surgical treatment, are the reason behind the importance of accurate epilepsy classification. Over the past several decades, plentiful scientific research on the pathophysiology of generalized epilepsy has been conducted using non-invasive neuroimaging and postprocessing of the electromagnetic neural signal by measuring the spatiotemporal and interhemispheric latency of bi-synchronous or generalized epileptiform discharges as well as network analysis to identify diagnostic and prognostic biomarkers for accurate diagnosis of the two major types of epilepsy. Among all the advanced techniques, magnetoencephalography (MEG) and multiple other methods provide excellent temporal and spatial resolution, inherently suited to analyzing and visualizing the propagation of generalized EEG activities. This article aims to provide a comprehensive literature review of recent innovations in MEG methodology using source localization and network analysis techniques that contributed to the literature of idiopathic generalized epilepsy in terms of pathophysiology and clinical prognosis, thus further blurring the boundary between focal and generalized epilepsy.
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Affiliation(s)
- Thandar Aung
- Department of Neurology, University of Pittsburgh Comprehensive Epilepsy Center (UPCEC), University of Pittsburgh Medical Center (UPMC), Pittsburgh, PA, United States
| | - Jeffrey R. Tenney
- Division of Neurology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States
| | - Anto I. Bagić
- Department of Neurology, University of Pittsburgh Comprehensive Epilepsy Center (UPCEC), University of Pittsburgh Medical Center (UPMC), Pittsburgh, PA, United States
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Stier C, Loose M, Kotikalapudi R, Elshahabi A, Li Hegner Y, Marquetand J, Braun C, Lerche H, Focke NK. Combined electrophysiological and morphological phenotypes in patients with genetic generalized epilepsy and their healthy siblings. Epilepsia 2022; 63:1643-1657. [PMID: 35416282 DOI: 10.1111/epi.17258] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 04/11/2022] [Accepted: 04/11/2022] [Indexed: 11/27/2022]
Abstract
OBJECTIVE Genetic generalized epilepsy is characterized by aberrant neuronal dynamics and subtle structural alterations. We evaluated whether a combination of magnetic and electrical neuronal signals and cortical thickness would provide complementary information about network pathology in GGE. We also investigated if these imaging phenotypes were present in healthy siblings of the patients to test for genetic influence. METHODS In this cross-sectional study, we analyzed five minutes of resting-state data acquired using electroencephalography (EEG) and magnetoencephalography (MEG) in patients, their siblings, and controls, matched for age and sex. We computed source-reconstructed power and connectivity in six frequency bands (1-40 Hz) and cortical thickness (derived from magnetic resonance imaging (MRI)). Group differences were assessed using permutation analysis of linear models for each modality separately and jointly for all modalities using a non-parametric combination. RESULTS Patients with GGE (n = 23) had higher power than controls (n = 35) in all frequencies, with a more posterior focus in MEG than EEG. Connectivity was also increased, particularly in frontotemporal and central regions in theta (strongest in EEG) and low beta frequencies (strongest in MEG), which was eminent in the joint EEG/MEG analysis. EEG showed weaker connectivity differences in higher frequencies, possibly related to drug effects. The inclusion of cortical thickness reinforced group differences in connectivity and power. Siblings (n = 18) had functional and structural patterns intermediate between those of patients and controls. SIGNIFICANCE EEG detected increased connectivity and power in GGE similar to MEG, but with different spectral sensitivity, highlighting the importance of theta and beta oscillations. Cortical thickness reductions in GGE corresponded to functional imaging patterns. Our multimodal approach extends the understanding of the resting-state in GGE and points to genetic underpinnings of the imaging markers studied, providing new insights into the causes and consequences of epilepsy.
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Affiliation(s)
- Christina Stier
- Clinic of Neurology, University Medical Center Göttingen, Göttingen, Germany.,Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Markus Loose
- Clinic of Neurology, University Medical Center Göttingen, Göttingen, Germany
| | - Raviteja Kotikalapudi
- Clinic of Neurology, University Medical Center Göttingen, Göttingen, Germany.,Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.,Institute of Psychology, University of Bern, Bern, Switzerland
| | - Adham Elshahabi
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.,Department of Neurology, University Hospital Zurich, Zurich, Switzerland
| | - Yiwen Li Hegner
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Justus Marquetand
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.,Department of Neural Dynamics and Magnetoencephalography, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Christoph Braun
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.,MEG-Center, University of Tübingen, Tübingen, Germany.,CIMeC, Center for Mind/Brain Sciences, University of Trento, Rovereto, Italy
| | - Holger Lerche
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Niels K Focke
- Clinic of Neurology, University Medical Center Göttingen, Göttingen, Germany.,Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
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11
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Genetic generalized epilepsies in adults - challenging assumptions and dogmas. Nat Rev Neurol 2022; 18:71-83. [PMID: 34837042 DOI: 10.1038/s41582-021-00583-9] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/19/2021] [Indexed: 01/16/2023]
Abstract
Genetic generalized epilepsy (GGE) syndromes start during childhood or adolescence, and four commonly persist into adulthood, making up 15-20% of all cases of epilepsy in adults. These four GGE syndromes are childhood absence epilepsy, juvenile absence epilepsy, juvenile myoclonic epilepsy and epilepsy with generalized tonic-clonic seizures alone. However, in ~20% of patients with GGE, characteristics of more than one syndrome are present. Novel insights into the genetic aetiology, comorbidities and prognosis of the GGE syndromes have emerged and challenge traditional concepts about these conditions. Evidence has shown that the mode of inheritance in GGE is mostly polygenic. Neuropsychological and imaging studies indicate similar abnormalities in unaffected relatives of patients with GGE, supporting the concept that underlying alterations in bilateral frontothalamocortical networks are genetically determined. Contrary to popular belief, first-line anti-seizure medication often fails to provide seizure freedom in combination with good tolerability. Nevertheless, long-term follow-up studies have shown that with advancing age, many patients can discontinue their anti-seizure medication without seizure relapses. Several outcome predictors have been identified, but prognosis across the syndromes is more homogeneous than previously assumed. Overall, overlap in pathophysiology, seizure types, treatment responses and outcomes support the idea that GGEs are not separate nosological entities but represent a neurobiological continuum.
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12
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Qin K, Xu S, Han Y, Wang S, Yan J, Shao X. Research Progress of Collapse Response Mediator Proteins in Neurodegenerative Diseases. Dev Neurosci 2022; 44:429-437. [PMID: 35249012 DOI: 10.1159/000523875] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2021] [Accepted: 02/16/2022] [Indexed: 11/19/2022] Open
Abstract
Collapse response mediator proteins (CRMPs) are a family of cytoplasmic phosphorylated proteins, and the mechanism of action has always been the research focus of neurological diseases. Previous studies on the CRMPs family have revealed that CRMPs mediate the growth and development of neuronal cytoskeleton through different signaling pathways in the body. It plays an important role in neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and spinocerebellar ataxia, which has attracted the attention of researchers. This article reviews the recent literature on the biological characteristics and mechanisms of CRMPs in different neurodegenerative diseases.
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Affiliation(s)
- Kun Qin
- Department of Human Anatomy, Guilin Medical University, Guilin, China
| | - Shaoye Xu
- Scientific Experiment Center, Guilin Medical University, Guilin, China
| | - Yu Han
- Department of Human Anatomy, Guilin Medical University, Guilin, China
| | - Songhao Wang
- Department of Human Anatomy, Guilin Medical University, Guilin, China
| | - Jianguo Yan
- Department of Physiology, Guilin Medical University, Guilin, China
- Guangxi Key Laboratory of Brain and Cognitive Neuroscience, Guilin Medical University, Guilin, China
| | - Xiaoyun Shao
- Department of Human Anatomy, Guilin Medical University, Guilin, China
- Guangxi Key Laboratory of Brain and Cognitive Neuroscience, Guilin Medical University, Guilin, China
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13
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Jiang Y, Zhu M, Hu Y, Wang K. Altered Resting-State Electroencephalography Microstates in Idiopathic Generalized Epilepsy: A Prospective Case-Control Study. Front Neurol 2021; 12:710952. [PMID: 34880822 PMCID: PMC8645577 DOI: 10.3389/fneur.2021.710952] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Accepted: 11/01/2021] [Indexed: 11/20/2022] Open
Abstract
Objective: Idiopathic generalized epilepsy (IGE) involves aberrant organization and functioning of large-scale brain networks. This study aims to investigate whether the resting-state EEG microstate analysis could provide novel insights into the abnormal temporal and spatial properties of intrinsic brain activities in patients with IGE. Methods: Three groups of participants were chosen for this study (namely IGE-Seizure, IGE-Seizure Free, and Healthy Controls). EEG microstate analysis on the resting-state EEG datasets was conducted for all participants. The average duration (“Duration”), the average number of microstates per second (“Frequency”), as well as the percentage of total analysis time occupied in that state (“Coverage”) of the EEG microstate were compared among the three groups. Results: For microstate classes B and D, the differences in Duration, Frequency, and Coverage among the three groups were not statistically significant. Both Frequency and Coverage of microstate class A were statistically significantly larger in the IGE-Seizure group than in the other two groups. The Duration and Coverage of microstate class C were statistically significantly smaller in the IGE-Seizure group than those in the other two groups. Conclusions: The Microstate class A was regarded as a sensorimotor network and Microstate class C was mainly related to the salience network, this study indicated an altered sensorimotor and salience network in patients with IGE, especially in those who had experienced seizures in the past 2 years, while the visual and attention networks seemed to be intact. Significance: The temporal dynamics of resting-state networks were studied through EEG microstate analysis in patients with IGE, which is expected to generate indices that could be utilized in clinical researches of epilepsy.
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Affiliation(s)
- YuBao Jiang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - MingYu Zhu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Ying Hu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China.,Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China
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14
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Vogel S, Kaltenhäuser M, Kim C, Müller-Voggel N, Rössler K, Dörfler A, Schwab S, Hamer H, Buchfelder M, Rampp S. MEG Node Degree Differences in Patients with Focal Epilepsy vs. Controls-Influence of Experimental Conditions. Brain Sci 2021; 11:1590. [PMID: 34942895 PMCID: PMC8699109 DOI: 10.3390/brainsci11121590] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 11/25/2021] [Accepted: 11/27/2021] [Indexed: 11/16/2022] Open
Abstract
Drug-resistant epilepsy can be most limiting for patients, and surgery represents a viable therapy option. With the growing research on the human connectome and the evidence of epilepsy being a network disorder, connectivity analysis may be able to contribute to our understanding of epilepsy and may be potentially developed into clinical applications. In this magnetoencephalographic study, we determined the whole-brain node degree of connectivity levels in patients and controls. Resting-state activity was measured at five frequency bands in 15 healthy controls and 15 patients with focal epilepsy of different etiologies. The whole-brain all-to-all imaginary part of coherence in source space was then calculated. Node degree was determined and parcellated and was used for further statistical evaluation. In comparison to controls, we found a significantly higher overall node degree in patients with lesional and non-lesional epilepsy. Furthermore, we examined the conditions of high/reduced vigilance and open/closed eyes in controls, to analyze whether patient node degree levels can be achieved. We evaluated intraclass-correlation statistics (ICC) to evaluate the reproducibility. Connectivity and specifically node degree analysis could present new tools for one of the most common neurological diseases, with potential applications in epilepsy diagnostics.
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Affiliation(s)
- Stephan Vogel
- Department of Neurosurgery, University Hospital Erlangen, 91054 Erlangen, Germany; (M.K.); (C.K.); (N.M.-V.); (M.B.); (S.R.)
- Friedrich Alexander University Erlangen Nürnberg (FAU), 91054 Erlangen, Germany
| | - Martin Kaltenhäuser
- Department of Neurosurgery, University Hospital Erlangen, 91054 Erlangen, Germany; (M.K.); (C.K.); (N.M.-V.); (M.B.); (S.R.)
| | - Cora Kim
- Department of Neurosurgery, University Hospital Erlangen, 91054 Erlangen, Germany; (M.K.); (C.K.); (N.M.-V.); (M.B.); (S.R.)
| | - Nadia Müller-Voggel
- Department of Neurosurgery, University Hospital Erlangen, 91054 Erlangen, Germany; (M.K.); (C.K.); (N.M.-V.); (M.B.); (S.R.)
| | - Karl Rössler
- Department of Neurosurgery, Medical University Vienna, 1090 Vienna, Austria;
| | - Arnd Dörfler
- Department of Neuroradiology, University Hospital Erlangen, 91054 Erlangen, Germany;
| | - Stefan Schwab
- Department of Neurology, University Hospital Erlangen, 91054 Erlangen, Germany; (S.S.); (H.H.)
| | - Hajo Hamer
- Department of Neurology, University Hospital Erlangen, 91054 Erlangen, Germany; (S.S.); (H.H.)
| | - Michael Buchfelder
- Department of Neurosurgery, University Hospital Erlangen, 91054 Erlangen, Germany; (M.K.); (C.K.); (N.M.-V.); (M.B.); (S.R.)
| | - Stefan Rampp
- Department of Neurosurgery, University Hospital Erlangen, 91054 Erlangen, Germany; (M.K.); (C.K.); (N.M.-V.); (M.B.); (S.R.)
- Department of Neurosurgery, University Hospital Halle (Saale), 06120 Halle (Saale), Germany
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15
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Dharan AL, Bowden SC, Lai A, Peterson ADH, Cheung MWL, Woldman W, D'Souza WJ. Resting-state functional connectivity in the idiopathic generalized epilepsies: A systematic review and meta-analysis of EEG and MEG studies. Epilepsy Behav 2021; 124:108336. [PMID: 34607215 DOI: 10.1016/j.yebeh.2021.108336] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 09/09/2021] [Accepted: 09/12/2021] [Indexed: 11/20/2022]
Abstract
For idiopathic generalized epilepsies (IGE), brain network analysis is emerging as a biomarker for potential use in clinical care. To determine whether people with IGE show alterations in resting-state brain connectivity compared to healthy controls, and to quantify these differences, we conducted a systematic review and meta-analysis of EEG and magnetoencephalography (MEG) functional connectivity and network studies. The review was conducted according to PRISMA guidelines. Twenty-two studies were eligible for inclusion. Outcomes from individual studies supported hypotheses for interictal, resting-state brain connectivity alterations in IGE patients compared to healthy controls. In contrast, meta-analysis from six studies of common network metrics clustering coefficient, path length, mean degree and nodal strength showed no significant differences between IGE and control groups (effect sizes ranged from -0.151 -1.78). The null findings of the meta-analysis and the heterogeneity of the included studies highlights the importance of developing standardized, validated methodologies for future research. Network neuroscience has significant potential as both a diagnostic and prognostic biomarker in epilepsy, though individual variability in network dynamics needs to be better understood and accounted for.
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Affiliation(s)
- Anita L Dharan
- Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, VIC, Australia.
| | - Stephen C Bowden
- Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, VIC, Australia; Department of Clinical Neurosciences, St Vincent's Hospital Melbourne, Fitzroy, VIC, Australia
| | - Alan Lai
- Department of Medicine, St Vincent's Hospital, The University of Melbourne, Fitzroy, VIC, Australia
| | - Andre D H Peterson
- Department of Medicine, St Vincent's Hospital, The University of Melbourne, Fitzroy, VIC, Australia
| | - Mike W-L Cheung
- Department of Psychology, National University of Singapore, Singapore
| | - Wessel Woldman
- Centre for Systems Modelling and Quantitative Biomedicine, University of Birmingham, Edgbaston, United Kingdom
| | - Wendyl J D'Souza
- Department of Medicine, St Vincent's Hospital, The University of Melbourne, Fitzroy, VIC, Australia
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16
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Papadelis C, Perry MS. Localizing the Epileptogenic Zone with Novel Biomarkers. Semin Pediatr Neurol 2021; 39:100919. [PMID: 34620466 PMCID: PMC8501232 DOI: 10.1016/j.spen.2021.100919] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 08/09/2021] [Accepted: 08/11/2021] [Indexed: 01/01/2023]
Abstract
Several noninvasive methods, such as high-density EEG or magnetoencephalography, are currently used to delineate the epileptogenic zone (EZ) during the presurgical evaluation of patients with drug resistant epilepsy (DRE). Yet, none of these methods can reliably identify the EZ by their own. In most cases a multimodal approach is needed. Challenging cases often require the implantation of intracranial electrodes, either through stereo-taxic EEG or electro-corticography. Recently, a growing body of literature introduces novel biomarkers of epilepsy that can be used for analyzing both invasive as well as noninvasive electrophysiological data. Some of these biomarkers are able to delineate the EZ with high precision, augment the presurgical evaluation, and predict the surgical outcome of patients with DRE undergoing surgery. However, the use of these epilepsy biomarkers in clinical practice is limited. Here, we summarize and discuss the latest technological advances in the presurgical neurophysiological evaluation of children with DRE with emphasis on electric and magnetic source imaging, high frequency oscillations, and functional connectivity.
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Affiliation(s)
- Christos Papadelis
- Jane and John Justin Neurosciences Center, Cook Children's Health Care System, Fort Worth, TX; School of Medicine, Texas Christian University and University of North Texas Health Science Center, Fort Worth, TX; Department of Bioengineering, University of Texas at Arlington, Arlington, TX; Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA.
| | - M Scott Perry
- Jane and John Justin Neurosciences Center, Cook Children’s Health Care System, Fort Worth, TX, USA
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17
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Pegg EJ, McKavanagh A, Bracewell RM, Chen Y, Das K, Denby C, Kreilkamp BAK, Laiou P, Marson A, Mohanraj R, Taylor JR, Keller SS. Functional network topology in drug resistant and well-controlled idiopathic generalized epilepsy: a resting state functional MRI study. Brain Commun 2021; 3:fcab196. [PMID: 34514400 PMCID: PMC8417840 DOI: 10.1093/braincomms/fcab196] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/18/2021] [Indexed: 11/23/2022] Open
Abstract
Despite an increasing number of drug treatment options for people with idiopathic generalized epilepsy (IGE), drug resistance remains a significant issue and the mechanisms underlying it remain poorly understood. Previous studies have largely focused on potential cellular or genetic explanations for drug resistance. However, epilepsy is understood to be a network disorder and there is a growing body of literature suggesting altered topology of large-scale resting networks in people with epilepsy compared with controls. We hypothesize that network alterations may also play a role in seizure control. The aim of this study was to compare resting state functional network structure between well-controlled IGE (WC-IGE), drug resistant IGE (DR-IGE) and healthy controls. Thirty-three participants with IGE (10 with WC-IGE and 23 with DR-IGE) and 34 controls were included. Resting state functional MRI networks were constructed using the Functional Connectivity Toolbox (CONN). Global graph theoretic network measures of average node strength (an equivalent measure to mean degree in a network that is fully connected), node strength distribution variance, characteristic path length, average clustering coefficient, small-world index and average betweenness centrality were computed. Graphs were constructed separately for positively weighted connections and for absolute values. Individual nodal values of strength and betweenness centrality were also measured and ‘hub nodes’ were compared between groups. Outcome measures were assessed across the three groups and between both groups with IGE and controls. The IGE group as a whole had a higher average node strength, characteristic path length and average betweenness centrality. There were no clear differences between groups according to seizure control. Outcome metrics were sensitive to whether negatively correlated connections were included in network construction. There were no clear differences in the location of ‘hub nodes’ between groups. The results suggest that, irrespective of seizure control, IGE interictal network topology is more regular and has a higher global connectivity compared to controls, with no alteration in hub node locations. These alterations may produce a resting state network that is more vulnerable to transitioning to the seizure state. It is possible that the lack of apparent influence of seizure control on network topology is limited by challenges in classifying drug response. It is also demonstrated that network topological features are influenced by the sign of connectivity weights and therefore future methodological work is warranted to account for anticorrelations in graph theoretic studies.
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Affiliation(s)
- Emily J Pegg
- Department of Neurology, Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, Salford, UK.,Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Andrea McKavanagh
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | | | - Yachin Chen
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Kumar Das
- The Walton Centre NHS Foundation Trust, Liverpool, UK
| | | | - Barbara A K Kreilkamp
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.,Department of Neurology, University Medical Center Göttingen, Göttingen, Germany
| | - Petroula Laiou
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Anthony Marson
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Rajiv Mohanraj
- Department of Neurology, Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, Salford, UK.,Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Jason R Taylor
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.,Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK
| | - Simon S Keller
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
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18
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Hirosawa T, An KM, Soma D, Shiota Y, Sano M, Kameya M, Hino S, Naito N, Tanaka S, Yaoi K, Iwasaki S, Yoshimura Y, Kikuchi M. Epileptiform discharges relate to altered functional brain networks in autism spectrum disorders. Brain Commun 2021; 3:fcab184. [PMID: 34541529 PMCID: PMC8440646 DOI: 10.1093/braincomms/fcab184] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 05/23/2021] [Accepted: 06/22/2021] [Indexed: 11/13/2022] Open
Abstract
Many individuals with autism spectrum disorders have comorbid epilepsy. Even in the absence of observable seizures, interictal epileptiform discharges are common in individuals with autism spectrum disorders. However, how these interictal epileptiform discharges are related to autistic symptomatology remains unclear. This study used magnetoencephalography to investigate the relation between interictal epileptiform discharges and altered functional brain networks in children with autism spectrum disorders. Instead of particularly addressing individual brain regions, we specifically examine network properties. For this case-control study, we analysed 70 children with autism spectrum disorders (52 boys, 18 girls, 38-92 months old) and 19 typically developing children (16 boys, 3 girls, 48-88 months old). After assessing the participants' social reciprocity using the Social Responsiveness Scale, we constructed graphs of functional brain networks from frequency band separated task-free magnetoencephalography recordings. Nodes corresponded to Desikan-Killiany atlas-based 68 brain regions. Edges corresponded to phase lag index values between pairs of brain regions. To elucidate the effects of the existence of interictal epileptiform discharges on graph metrics, we matched each of three pairs from three groups (typically developing children, children with autism spectrum disorders who had interictal epileptiform discharges and those who did not) in terms of age and sex. We used a coarsened exact matching algorithm and applied adjusted regression analysis. We also investigated the relation between social reciprocity and the graph metric. Results show that, in children with autism spectrum disorders, the average clustering coefficient in the theta band was significantly higher in children who had interictal epileptiform discharges. Moreover, children with autism spectrum disorders who had no interictal epileptiform discharges had a significantly lower average clustering coefficient in the theta band than typically developing children had. However, the difference between typically developing children and children with autism spectrum disorder who had interictal epileptiform discharges was not significant. Furthermore, the higher average clustering coefficient in the theta band corresponded to severe autistic symptoms in children with autism spectrum disorder who had interictal epileptiform discharges. However, the association was not significant in children with autism spectrum disorders who had no interictal epileptiform discharge. In conclusion, results demonstrate that alteration of functional brain networks in children with autism spectrum disorders depends on the existence of interictal epileptiform discharges. Interictal epileptiform discharges might 'normalize' the deviation of altered brain networks in autism spectrum disorders, increasing the clustering coefficient. However, when the effect exceeds tolerance, it actually exacerbates autistic symptoms.
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Affiliation(s)
- Tetsu Hirosawa
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa 920-0934, Japan
- Research Center for Child Mental Development, Kanazawa University, Kanazawa 920-8641, Japan
- Division of Socio-Cognitive-Neuroscience, Department of Child Development United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Kanazawa 920-8640, Japan
| | - Kyung-min An
- Research Center for Child Mental Development, Kanazawa University, Kanazawa 920-8641, Japan
- Division of Socio-Cognitive-Neuroscience, Department of Child Development United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Kanazawa 920-8640, Japan
| | - Daiki Soma
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa 920-0934, Japan
| | - Yuka Shiota
- Research Center for Child Mental Development, Kanazawa University, Kanazawa 920-8641, Japan
- Division of Socio-Cognitive-Neuroscience, Department of Child Development United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Kanazawa 920-8640, Japan
| | - Masuhiko Sano
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa 920-0934, Japan
| | - Masafumi Kameya
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa 920-0934, Japan
| | - Shoryoku Hino
- Department of Neuropsychiatry, Ishikawa Prefectural Takamatsu Hospital, Ishikawa 929-1214, Japan
| | - Nobushige Naito
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa 920-0934, Japan
| | - Sanae Tanaka
- Research Center for Child Mental Development, Kanazawa University, Kanazawa 920-8641, Japan
- Division of Socio-Cognitive-Neuroscience, Department of Child Development United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Kanazawa 920-8640, Japan
| | - Ken Yaoi
- Research Center for Child Mental Development, Kanazawa University, Kanazawa 920-8641, Japan
- Division of Socio-Cognitive-Neuroscience, Department of Child Development United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Kanazawa 920-8640, Japan
| | - Sumie Iwasaki
- Research Center for Child Mental Development, Kanazawa University, Kanazawa 920-8641, Japan
| | - Yuko Yoshimura
- Research Center for Child Mental Development, Kanazawa University, Kanazawa 920-8641, Japan
- Division of Socio-Cognitive-Neuroscience, Department of Child Development United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Kanazawa 920-8640, Japan
- Faculty of Education, Institute of Human and Social Sciences, Kanazawa University, Kanazawa 920-1164, Japan
| | - Mitsuru Kikuchi
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa 920-0934, Japan
- Research Center for Child Mental Development, Kanazawa University, Kanazawa 920-8641, Japan
- Division of Socio-Cognitive-Neuroscience, Department of Child Development United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Kanazawa 920-8640, Japan
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19
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Xu N, Shan W, Qi J, Wu J, Wang Q. Presurgical Evaluation of Epilepsy Using Resting-State MEG Functional Connectivity. Front Hum Neurosci 2021; 15:649074. [PMID: 34276321 PMCID: PMC8283278 DOI: 10.3389/fnhum.2021.649074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2021] [Accepted: 06/07/2021] [Indexed: 11/21/2022] Open
Abstract
Epilepsy is caused by abnormal electrical discharges (clinically identified by electrophysiological recording) in a specific part of the brain [originating in only one part of the brain, namely, the epileptogenic zone (EZ)]. Epilepsy is now defined as an archetypical hyperexcited neural network disorder. It can be investigated through the network analysis of interictal discharges, ictal discharges, and resting-state functional connectivity. Currently, there is an increasing interest in embedding resting-state connectivity analysis into the preoperative evaluation of epilepsy. Among the various neuroimaging technologies employed to achieve brain functional networks, magnetoencephalography (MEG) with the excellent temporal resolution is an ideal tool for estimating the resting-state connectivity between brain regions, which can reveal network abnormalities in epilepsy. What value does MEG resting-state functional connectivity offer for epileptic presurgical evaluation? Regarding this topic, this paper introduced the origin of MEG and the workflow of constructing source-space functional connectivity based on MEG signals. Resting-state functional connectivity abnormalities correlate with epileptogenic networks, which are defined by the brain regions involved in the production and propagation of epileptic activities. This paper reviewed the evidence of altered epileptic connectivity based on low- or high-frequency oscillations (HFOs) and the evidence of the advantage of using simultaneous MEG and intracranial electroencephalography (iEEG) recordings. More importantly, this review highlighted that MEG-based resting-state functional connectivity has the potential to predict postsurgical outcomes. In conclusion, resting-state MEG functional connectivity has made a substantial progress toward serving as a candidate biomarker included in epileptic presurgical evaluations.
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Affiliation(s)
- Na Xu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Wei Shan
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jing Qi
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jianping Wu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Qun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
- Beijing Institute of Brain Disorders, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Neuromodulation, Beijing, China
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20
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Stier C, Elshahabi A, Li Hegner Y, Kotikalapudi R, Marquetand J, Braun C, Lerche H, Focke NK. Heritability of Magnetoencephalography Phenotypes Among Patients With Genetic Generalized Epilepsy and Their Siblings. Neurology 2021; 97:e166-e177. [PMID: 34045271 PMCID: PMC8279565 DOI: 10.1212/wnl.0000000000012144] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Accepted: 04/07/2021] [Indexed: 11/15/2022] Open
Abstract
Objective To assess whether neuronal signals in patients with genetic generalized epilepsy (GGE) are heritable, we examined magnetoencephalography resting-state recordings in patients and their healthy siblings. Methods In a prospective, cross-sectional design, we investigated source-reconstructed power and functional connectivity in patients, siblings, and controls. We analyzed 5 minutes of cleaned and awake data without epileptiform discharges in 6 frequency bands (1–40 Hz). We further calculated intraclass correlations to estimate heritability for the imaging patterns within families. Results Compared with controls (n = 45), patients with GGE (n = 25) showed widespread increased functional connectivity (θ to γ frequency bands) and power (δ to γ frequency bands) across the spectrum. Siblings (n = 18) fell between the levels of patients and controls. Heritability of the imaging metrics was observed in regions where patients strongly differed from controls, mainly in β frequencies, but also for δ and θ power. Network connectivity in GGE was heritable in frontal, central, and inferior parietal brain areas and power in central, temporo-parietal, and subcortical structures. Presence of generalized spike-wave activity during recordings and medication were associated with the network patterns, whereas other clinical factors such as age at onset, disease duration, or seizure control were not. Conclusion Metrics of brain oscillations are well suited to characterize GGE and likely relate to genetic factors rather than the active disease or treatment. High power and connectivity levels co-segregated in patients with GGE and healthy siblings, predominantly in the β band, representing an endophenotype of GGE.
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Affiliation(s)
- Christina Stier
- From the Clinic of Clinical Neurophysiology (C.S., R.K., N.K.F.), University Medical Center Göttingen; Department of Neurology and Epileptology, Hertie Institute of Clinical Brain Research (C.S., A.E., Y.L.H., R.K., J.M., H.L., N.K.F., C.B.), and MEG Center (C.B.), University of Tübingen, Germany; Department of Neurology (A.E.), University Hospital Zurich; Institute of Psychology (R.K.), University of Bern, Switzerland; and CIMeC (C.B.), Center for Mind/Brain Sciences, University of Trento, Italy
| | - Adham Elshahabi
- From the Clinic of Clinical Neurophysiology (C.S., R.K., N.K.F.), University Medical Center Göttingen; Department of Neurology and Epileptology, Hertie Institute of Clinical Brain Research (C.S., A.E., Y.L.H., R.K., J.M., H.L., N.K.F., C.B.), and MEG Center (C.B.), University of Tübingen, Germany; Department of Neurology (A.E.), University Hospital Zurich; Institute of Psychology (R.K.), University of Bern, Switzerland; and CIMeC (C.B.), Center for Mind/Brain Sciences, University of Trento, Italy
| | - Yiwen Li Hegner
- From the Clinic of Clinical Neurophysiology (C.S., R.K., N.K.F.), University Medical Center Göttingen; Department of Neurology and Epileptology, Hertie Institute of Clinical Brain Research (C.S., A.E., Y.L.H., R.K., J.M., H.L., N.K.F., C.B.), and MEG Center (C.B.), University of Tübingen, Germany; Department of Neurology (A.E.), University Hospital Zurich; Institute of Psychology (R.K.), University of Bern, Switzerland; and CIMeC (C.B.), Center for Mind/Brain Sciences, University of Trento, Italy
| | - Raviteja Kotikalapudi
- From the Clinic of Clinical Neurophysiology (C.S., R.K., N.K.F.), University Medical Center Göttingen; Department of Neurology and Epileptology, Hertie Institute of Clinical Brain Research (C.S., A.E., Y.L.H., R.K., J.M., H.L., N.K.F., C.B.), and MEG Center (C.B.), University of Tübingen, Germany; Department of Neurology (A.E.), University Hospital Zurich; Institute of Psychology (R.K.), University of Bern, Switzerland; and CIMeC (C.B.), Center for Mind/Brain Sciences, University of Trento, Italy
| | - Justus Marquetand
- From the Clinic of Clinical Neurophysiology (C.S., R.K., N.K.F.), University Medical Center Göttingen; Department of Neurology and Epileptology, Hertie Institute of Clinical Brain Research (C.S., A.E., Y.L.H., R.K., J.M., H.L., N.K.F., C.B.), and MEG Center (C.B.), University of Tübingen, Germany; Department of Neurology (A.E.), University Hospital Zurich; Institute of Psychology (R.K.), University of Bern, Switzerland; and CIMeC (C.B.), Center for Mind/Brain Sciences, University of Trento, Italy
| | - Christoph Braun
- From the Clinic of Clinical Neurophysiology (C.S., R.K., N.K.F.), University Medical Center Göttingen; Department of Neurology and Epileptology, Hertie Institute of Clinical Brain Research (C.S., A.E., Y.L.H., R.K., J.M., H.L., N.K.F., C.B.), and MEG Center (C.B.), University of Tübingen, Germany; Department of Neurology (A.E.), University Hospital Zurich; Institute of Psychology (R.K.), University of Bern, Switzerland; and CIMeC (C.B.), Center for Mind/Brain Sciences, University of Trento, Italy
| | - Holger Lerche
- From the Clinic of Clinical Neurophysiology (C.S., R.K., N.K.F.), University Medical Center Göttingen; Department of Neurology and Epileptology, Hertie Institute of Clinical Brain Research (C.S., A.E., Y.L.H., R.K., J.M., H.L., N.K.F., C.B.), and MEG Center (C.B.), University of Tübingen, Germany; Department of Neurology (A.E.), University Hospital Zurich; Institute of Psychology (R.K.), University of Bern, Switzerland; and CIMeC (C.B.), Center for Mind/Brain Sciences, University of Trento, Italy
| | - Niels K Focke
- From the Clinic of Clinical Neurophysiology (C.S., R.K., N.K.F.), University Medical Center Göttingen; Department of Neurology and Epileptology, Hertie Institute of Clinical Brain Research (C.S., A.E., Y.L.H., R.K., J.M., H.L., N.K.F., C.B.), and MEG Center (C.B.), University of Tübingen, Germany; Department of Neurology (A.E.), University Hospital Zurich; Institute of Psychology (R.K.), University of Bern, Switzerland; and CIMeC (C.B.), Center for Mind/Brain Sciences, University of Trento, Italy.
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21
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Hatlestad-Hall C, Bruña R, Syvertsen MR, Erichsen A, Andersson V, Vecchio F, Miraglia F, Rossini PM, Renvall H, Taubøll E, Maestú F, Haraldsen IH. Source-level EEG and graph theory reveal widespread functional network alterations in focal epilepsy. Clin Neurophysiol 2021; 132:1663-1676. [PMID: 34044189 DOI: 10.1016/j.clinph.2021.04.008] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 03/19/2021] [Accepted: 04/20/2021] [Indexed: 01/15/2023]
Abstract
OBJECTIVE The hypersynchronous neuronal activity associated with epilepsy causes widespread functional network disruptions extending beyond the epileptogenic zone. This altered network topology is considered a mediator for non-seizure symptoms, such as cognitive impairment. The aim of this study was to investigate functional network alterations in focal epilepsy patients with good seizure control and high quality of life. METHODS We compared twenty-two focal epilepsy patients and sixteen healthy controls on graph metrics derived from functional connectivity of source-level resting-state EEG. Graph metrics were calculated over a range of network densities in five frequency bands. RESULTS We observed a significantly increased small world index in patients relative to controls. On the local level, two left-hemisphere regions displayed a shift towards greater alpha band "hubness". The findings were not mediated by age, sex or education, nor by age of epilepsy onset, duration or focus lateralisation. CONCLUSIONS Widespread functional network alterations are evident in focal epilepsy, even in a cohort characterised by successful anti-seizure medication therapy and high quality of life. These findings might support the position that functional network analysis could hold clinical relevance for epilepsy. SIGNIFICANCE Focal epilepsy is accompanied by global and local functional network aberrancies which might be implied in the sustenance of non-seizure symptoms.
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Affiliation(s)
| | - Ricardo Bruña
- Center for Biomedical Technology, Technical University of Madrid, Pozuelo de Alarcón, Spain; Department of Experimental Psychology, Complutense University of Madrid, Pozuelo de Alarcón, Spain; Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain.
| | - Marte Roa Syvertsen
- Department of Neurology, Drammen Hospital, Vestre Viken Health Care Trust, Drammen, Norway.
| | - Aksel Erichsen
- Department of Neurology, Oslo University Hospital, Oslo, Norway; Department of Nuclear Medicine, Oslo University Hospital, Oslo, Norway.
| | | | - Fabrizio Vecchio
- Brain Connectivity Laboratory, Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele Pisana, Rome, Italy.
| | - Francesca Miraglia
- Brain Connectivity Laboratory, Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele Pisana, Rome, Italy.
| | - Paolo M Rossini
- Brain Connectivity Laboratory, Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele Pisana, Rome, Italy.
| | - Hanna Renvall
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland; BioMag Laboratory, HUS Diagnostic Center, Helsinki University Hospital, University of Helsinki and Aalto University School of Science, Helsinki, Finland.
| | - Erik Taubøll
- Department of Neurology, Oslo University Hospital, Oslo, Norway; Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway.
| | - Fernando Maestú
- Center for Biomedical Technology, Technical University of Madrid, Pozuelo de Alarcón, Spain; Department of Experimental Psychology, Complutense University of Madrid, Pozuelo de Alarcón, Spain; Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain.
| | - Ira H Haraldsen
- Department of Neurology, Oslo University Hospital, Oslo, Norway.
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22
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Tanoue Y, Uda T, Hoshi H, Shigihara Y, Kawashima T, Nakajo K, Tsuyuguchi N, Goto T. Specific Oscillatory Power Changes and Their Efficacy for Determining Laterality in Mesial Temporal Lobe Epilepsy: A Magnetoencephalographic Study. Front Neurol 2021; 12:617291. [PMID: 33633670 PMCID: PMC7900569 DOI: 10.3389/fneur.2021.617291] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Accepted: 01/21/2021] [Indexed: 01/22/2023] Open
Abstract
Appropriate determination of the epileptic focus and its laterality are important for the diagnosis of mesial temporal lobe epilepsy (MTLE). The aims of this study are to establish a specific oscillatory distribution and laterality of the oscillatory power in unilateral MTLE with frequency analysis of magnetoencephalography (MEG), and to confirm their potential to carry significant information for determining lateralization of the epileptic focus. Thirty-five patients with MTLE [left (LtMTLE), 16; right (RtMTLE), 19] and 102 healthy control volunteers (CTR) were enrolled. Cortical oscillatory powers were compared among the groups by contrasting the source images using a one-way ANOVA model for each frequency band. Further, to compare the lateralization of regional oscillatory powers between LtMTLEs and RtMTLEs, the laterality index (LI) was calculated for four brain regions (frontal, temporal, parietal, and occipital) in each frequency band, which were compared between patient groups (LtMTLE, RtMTLE, and CTR), and used for machine learning prediction of the groups with support vector machine (SVM) with linear kernel function. Significant oscillatory power differences between MTLE and CTR were found in certain areas. In the theta to high-frequency oscillation bands, there were marked increases in the parietal lobe, especially on the left side, in LtMTLE. In the theta, alpha, and high-gamma bands, there were marked increases in the parietal lobe, especially on the right side in RtMTLE. Compared with CTR, LIs were significantly higher in 24/28 regions in LtMTLE, but lower in 4/28 regions and higher in 10/28 regions in RtMTLE. LI at the temporal lobe in the theta band was significantly higher in LtMTLE and significantly lower in RtMTLE. Comparing LtMTLE and RtMTLE, there were significant LI differences in most regions and frequencies (21/28 regions). In all frequency bands, there were significant differences between LtMTLE and RtMTLE in the temporal and parietal lobes. The leave-one-out cross-validation of the linear-SVM showed the classification accuracy to be over 91%, where the model had high specificity over 96% and mild sensitivity ~68–75%. Using MEG frequency analysis, the characteristics of the oscillatory power distribution in the MTLE were demonstrated. Compared with CTR, LIs shifted to the side of the epileptic focus in the temporal lobe in the theta band. The machine learning approach also confirmed that LIs have significant predictive ability in the lateralization of the epileptic focus. These results provide useful additional information for determining the laterality of the focus.
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Affiliation(s)
- Yuta Tanoue
- Department of Neurosurgery, Graduate School of Medicine, Osaka City University, Osaka, Japan
| | - Takehiro Uda
- Department of Neurosurgery, Graduate School of Medicine, Osaka City University, Osaka, Japan
| | - Hideyuki Hoshi
- Precision Medicine Centre, Hokuto Hospital, Obihiro City, Japan
| | - Yoshihito Shigihara
- Precision Medicine Centre, Hokuto Hospital, Obihiro City, Japan.,Precision Medicine Centre, Kumagaya General Hospital, Kumagaya, Japan
| | - Toshiyuki Kawashima
- Department of Neurosurgery, Graduate School of Medicine, Osaka City University, Osaka, Japan
| | - Kosuke Nakajo
- Department of Neurosurgery, Graduate School of Medicine, Osaka City University, Osaka, Japan
| | - Naohiro Tsuyuguchi
- Department of Neurosurgery, Graduate School of Medicine, Osaka City University, Osaka, Japan.,Department of Neurosurgery, Faculty of Medicine, Kindai University, Osaka, Japan
| | - Takeo Goto
- Department of Neurosurgery, Graduate School of Medicine, Osaka City University, Osaka, Japan
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23
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Pegg EJ, Taylor JR, Laiou P, Richardson M, Mohanraj R. Interictal electroencephalographic functional network topology in drug-resistant and well-controlled idiopathic generalized epilepsy. Epilepsia 2021; 62:492-503. [PMID: 33501642 DOI: 10.1111/epi.16811] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 12/20/2020] [Accepted: 12/22/2020] [Indexed: 01/17/2023]
Abstract
OBJECTIVE The study aim was to compare interictal encephalographic (EEG) functional network topology between people with well-controlled idiopathic generalized epilepsy (WC-IGE) and drug-resistant IGE (DR-IGE). METHODS Nineteen participants with WC-IGE, 18 with DR-IGE, and 20 controls underwent a resting state, 64-channel EEG. An artifact-free epoch was bandpass filtered into the frequency range of high and low extended alpha. Weighted functional connectivity matrices were calculated. Mean degree, degree distribution variance, characteristic path length (L), clustering coefficient, small world index (SWI), and betweenness centrality were measured. A Kruskal-Wallis H-test assessed effects across groups. Where significant differences were found, Bonferroni-corrected Mann-Whitney pairwise comparisons were calculated. RESULTS In the low alpha band (6-9 Hz), there was a significant difference in L at the three-group level (p < .0001). This was lower in controls than both WC-IGE and DR-IGE (p < .0001 for both), with no difference in L between WC-IGE and DR-IGE. Mean degree (p = .031), degree distribution variance (p = .032), and SWI (p = .023) differed across the three groups in the high alpha band (10-12 Hz). Mean degree and degree distribution variance were lower in WC-IGE than controls (p = .029 for both), and SWI was higher in WC-IGE compared with controls (p = .038), with no differences in other pairwise comparisons. SIGNIFICANCE IGE network topology is more regular in the low alpha frequency band, potentially reflecting a more vulnerable structure. WC-IGE network topology is different from controls in the high alpha band. This may reflect drug-induced network changes that have stabilized the WC-IGE network by rendering it less likely to synchronize. These results are of potential importance in advancing the understanding of mechanisms of epilepsy drug resistance and as a possible basis for a biomarker of DR-IGE.
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Affiliation(s)
- Emily J Pegg
- Department of Neurology, Manchester Centre for Clinical Neurosciences, Salford, UK.,Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine, and Health, School of Biological Sciences, University of Manchester, Manchester, UK
| | - Jason R Taylor
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine, and Health, School of Biological Sciences, University of Manchester, Manchester, UK.,Manchester Academic Health Sciences Centre, Manchester, UK
| | - Petroula Laiou
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Mark Richardson
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Rajiv Mohanraj
- Department of Neurology, Manchester Centre for Clinical Neurosciences, Salford, UK.,Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine, and Health, School of Biological Sciences, University of Manchester, Manchester, UK
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24
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Bou Assi E, Zerouali Y, Robert M, Lesage F, Pouliot P, Nguyen DK. Large-Scale Desynchronization During Interictal Epileptic Discharges Recorded With Intracranial EEG. Front Neurol 2020; 11:529460. [PMID: 33424733 PMCID: PMC7785800 DOI: 10.3389/fneur.2020.529460] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Accepted: 11/27/2020] [Indexed: 11/13/2022] Open
Abstract
It is increasingly recognized that deep understanding of epileptic seizures requires both localizing and characterizing the functional network of the region where they are initiated, i. e., the epileptic focus. Previous investigations of the epileptogenic focus' functional connectivity have yielded contrasting results, reporting both pathological increases and decreases during resting periods and seizures. In this study, we shifted paradigm to investigate the time course of connectivity in relation to interictal epileptiform discharges. We recruited 35 epileptic patients undergoing intracranial EEG (iEEG) investigation as part of their presurgical evaluation. For each patient, 50 interictal epileptic discharges (IEDs) were marked and iEEG signals were epoched around those markers. Signals were narrow-band filtered and time resolved phase-locking values were computed to track the dynamics of functional connectivity during IEDs. Results show that IEDs are associated with a transient decrease in global functional connectivity, time-locked to the peak of the discharge and specific to the high range of the gamma frequency band. Disruption of the long-range connectivity between the epileptic focus and other brain areas might be an important process for the generation of epileptic activity. Transient desynchronization could be a potential biomarker of the epileptogenic focus since 1) the functional connectivity involving the focus decreases significantly more than the connectivity outside the focus and 2) patients with good surgical outcome appear to have a significantly more disconnected focus than patients with bad outcomes.
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Affiliation(s)
- Elie Bou Assi
- University of Montreal Hospital Research Center (CRCHUM), University of Montreal, Montreal, QC, Canada.,Department of Neuroscience, University of Montreal, Montreal, QC, Canada
| | - Younes Zerouali
- University of Montreal Hospital Research Center (CRCHUM), University of Montreal, Montreal, QC, Canada.,Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Manon Robert
- University of Montreal Hospital Research Center (CRCHUM), University of Montreal, Montreal, QC, Canada
| | - Frederic Lesage
- Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada.,Montreal Heart Institute, Montreal, QC, Canada
| | - Philippe Pouliot
- Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada.,Montreal Heart Institute, Montreal, QC, Canada
| | - Dang K Nguyen
- University of Montreal Hospital Research Center (CRCHUM), University of Montreal, Montreal, QC, Canada.,Department of Neuroscience, University of Montreal, Montreal, QC, Canada
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25
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Pegg EJ, Taylor JR, Mohanraj R. Spectral power of interictal EEG in the diagnosis and prognosis of idiopathic generalized epilepsies. Epilepsy Behav 2020; 112:107427. [PMID: 32949965 DOI: 10.1016/j.yebeh.2020.107427] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 08/09/2020] [Accepted: 08/11/2020] [Indexed: 12/19/2022]
Abstract
INTRODUCTION Idiopathic generalized epilepsies (IGE) are characterized by generalized interictal epileptiform discharges (IEDs) on a normal background electroencephalography (EEG). However, the yield of IEDs can be low. Approximately 20% of patients with IGE fail to achieve seizure control with antiepileptic drug (AED) treatment. Currently, there are no reliable prognostic markers for early identification of drug-resistant epilepsy (DRE). We examined spectral power of the interictal EEG in patients with IGE and healthy controls, to identify potential diagnostic and prognostic biomarkers of IGE. METHODS A 64-channel EEG was recorded under standard conditions in patients with well-controlled IGE (WC-IGE, n = 19), drug-resistant IGE (DR-IGE, n = 18), and age-matched controls (n = 20). After preprocessing, fast Fourier transform was performed to obtain 1D frequency spectra for each EEG channel. The 1D spectra (averaged over channels) and 2D topographic maps (averaged over canonical frequency bands) were computed for each participant. Power spectra in the 3 cohorts were compared using one-way analysis of variance (ANOVA), and power spectra images were compared using T-contrast tests. A post hoc analysis compared peak alpha power between the groups. RESULTS Compared with controls, participants with IGE had higher interictal EEG spectral power in the delta band in the midline central region, in the theta band in the midline, in the beta band over the left hemisphere, and in the gamma band over right hemisphere and left central regions. There were no differences in spectral power between cohorts with WC-IGE and DR-IGE. Peak alpha power was lower in WC-IGE and DR-IGE than controls. CONCLUSIONS Electroencephalography spectral power analysis could form part of a clinically useful diagnostic biomarker for IGE; however, it did not correlate with response to AED in this study.
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Affiliation(s)
- Emily J Pegg
- Department of Neurology, Manchester Centre for Clinical Neurosciences, United Kingdom; Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, United Kingdom
| | - Jason R Taylor
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, United Kingdom; Manchester Academic Health Sciences Centre, United Kingdom
| | - Rajiv Mohanraj
- Department of Neurology, Manchester Centre for Clinical Neurosciences, United Kingdom; Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, United Kingdom.
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26
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Pegg EJ, Taylor JR, Keller SS, Mohanraj R. Interictal structural and functional connectivity in idiopathic generalized epilepsy: A systematic review of graph theoretical studies. Epilepsy Behav 2020; 106:107013. [PMID: 32193094 DOI: 10.1016/j.yebeh.2020.107013] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2019] [Revised: 02/22/2020] [Accepted: 02/28/2020] [Indexed: 12/18/2022]
Abstract
The evaluation of the role of anomalous neuronal networks in epilepsy using a graph theoretical approach is of growing research interest. There is currently no consensus on optimal methods for performing network analysis, and it is possible that variations in study methodology account for diverging findings. This review focuses on global functional and structural interictal network characteristics in people with idiopathic generalized epilepsy (IGE) with the aim of appraising the methodological approaches used and assessing for meaningful consensus. Thirteen studies were included in the review. Data were heterogenous and not suitable for meta-analysis. Overall, there is a suggestion that the cerebral neuronal networks of people with IGE have different global structural and functional characteristics to people without epilepsy. However, the nature of the aberrations is inconsistent with some studies demonstrating a more regular network configuration in IGE, and some, a more random topology. There is greater consistency when different data modalities and connectivity subtypes are compared separately, with a tendency towards increased small-worldness of networks in functional electroencephalography/magnetoencephalography (EEG/MEG) studies and decreased small-worldness of networks in structural studies. Prominent variation in study design at all stages is likely to have contributed to differences in study outcomes. Despite increasing literature surrounding neuronal network analysis, systematic methodological studies are lacking. Absence of consensus in this area significantly limits comparison of results from different studies, and the ability to draw firm conclusions about network characteristics in IGE.
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Affiliation(s)
- Emily J Pegg
- Department of Neurology, Manchester Centre for Clinical Neurosciences, United Kingdom; Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, United Kingdom.
| | - Jason R Taylor
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, United Kingdom; Manchester Academic Health Sciences Centre, United Kingdom
| | - Simon S Keller
- Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, United Kingdom; The Walton Centre NHS Foundation Trust, Liverpool, United Kingdom
| | - Rajiv Mohanraj
- Department of Neurology, Manchester Centre for Clinical Neurosciences, United Kingdom; Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, United Kingdom
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27
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Routley B, Shaw A, Muthukumaraswamy SD, Singh KD, Hamandi K. Juvenile myoclonic epilepsy shows increased posterior theta, and reduced sensorimotor beta resting connectivity. Epilepsy Res 2020; 163:106324. [PMID: 32335503 PMCID: PMC7684644 DOI: 10.1016/j.eplepsyres.2020.106324] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 03/06/2020] [Accepted: 03/26/2020] [Indexed: 12/16/2022]
Abstract
We investigated whole brain source space connectivity in JME using across standard MEG frequency bands. Connectivity was increased in posterior theta and alpha bands in JME, and decreased in sensorimotor beta band. Our findings highlight altered interactions between posterior networks of arousal and attention and the motor system in JME.
Background Widespread structural and functional brain network changes have been shown in Juvenile Myoclonic Epilepsy (JME) despite normal clinical neuroimaging. We sought to better define these changes using magnetoencephalography (MEG) and source space connectivity analysis for optimal neurophysiological and anatomical localisation. Methods We consecutively recruited 26 patients with JME who underwent resting state MEG recording, along with 26 age-and-sex matched controls. Whole brain connectivity was determined through correlation of Automated Anatomical Labelling (AAL) atlas source space MEG timeseries in conventional frequency bands of interest delta (1−4 Hz), theta (4−8 Hz), alpha (8−13 Hz), beta (13−30 Hz) and gamma (40−60 Hz). We used a Linearly Constrained Minimum Variance (LCMV) beamformer to extract voxel wise time series of ‘virtual sensors’ for the desired frequency bands, followed by connectivity analysis using correlation between frequency- and node-specific power fluctuations, for the voxel maxima in each AAL atlas label, correcting for noise, potentially spurious connections and multiple comparisons. Results We found increased connectivity in the theta band in posterior brain regions, surviving statistical correction for multiple comparisons (corrected p < 0.05), and decreased connectivity in the beta band in sensorimotor cortex, between right pre- and post- central gyrus (p < 0.05) in JME compared to controls. Conclusions Altered resting-state MEG connectivity in JME comprised increased connectivity in posterior theta – the frequency band associated with long range connections affecting attention and arousal - and decreased beta-band sensorimotor connectivity. These findings likely relate to altered regulation of the sensorimotor network and seizure prone states in JME.
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Affiliation(s)
- Bethany Routley
- Cardiff University Brain Research Imaging, School of Psychology, Cardiff University, United Kingdom
| | - Alexander Shaw
- Cardiff University Brain Research Imaging, School of Psychology, Cardiff University, United Kingdom
| | - Suresh D Muthukumaraswamy
- School of Pharmacy, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Krish D Singh
- Cardiff University Brain Research Imaging, School of Psychology, Cardiff University, United Kingdom
| | - Khalid Hamandi
- Cardiff University Brain Research Imaging, School of Psychology, Cardiff University, United Kingdom; The Wales Epilepsy Unit, Department of Neurology, University Hospital of Wales, Cardiff, United Kingdom.
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28
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Krzemiński D, Masuda N, Hamandi K, Singh KD, Routley B, Zhang J. Energy landscape of resting magnetoencephalography reveals fronto-parietal network impairments in epilepsy. Netw Neurosci 2020; 4:374-396. [PMID: 32537532 PMCID: PMC7286306 DOI: 10.1162/netn_a_00125] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Accepted: 01/07/2020] [Indexed: 12/13/2022] Open
Abstract
Juvenile myoclonic epilepsy (JME) is a form of idiopathic generalized epilepsy. It is yet unclear to what extent JME leads to abnormal network activation patterns. Here, we characterized statistical regularities in magnetoencephalograph (MEG) resting-state networks and their differences between JME patients and controls by combining a pairwise maximum entropy model (pMEM) and novel energy landscape analyses for MEG. First, we fitted the pMEM to the MEG oscillatory power in the front-oparietal network (FPN) and other resting-state networks, which provided a good estimation of the occurrence probability of network states. Then, we used energy values derived from the pMEM to depict an energy landscape, with a higher energy state corresponding to a lower occurrence probability. JME patients showed fewer local energy minima than controls and had elevated energy values for the FPN within the theta, beta, and gamma bands. Furthermore, simulations of the fitted pMEM showed that the proportion of time the FPN was occupied within the basins of energy minima was shortened in JME patients. These network alterations were highlighted by significant classification of individual participants employing energy values as multivariate features. Our findings suggested that JME patients had altered multistability in selective functional networks and frequency bands in the fronto-parietal cortices.
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Affiliation(s)
- Dominik Krzemiński
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, United Kingdom
| | - Naoki Masuda
- Department of Engineering Mathematics, University of Bristol, United Kingdom
| | - Khalid Hamandi
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, United Kingdom
| | - Krish D Singh
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, United Kingdom
| | - Bethany Routley
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, United Kingdom
| | - Jiaxiang Zhang
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, United Kingdom
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29
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Wang Z, Larivière S, Xu Q, Vos de Wael R, Hong SJ, Wang Z, Xu Y, Zhu B, Bernasconi N, Bernasconi A, Zhang B, Zhang Z, Bernhardt BC. Community-informed connectomics of the thalamocortical system in generalized epilepsy. Neurology 2019; 93:e1112-e1122. [PMID: 31405905 DOI: 10.1212/wnl.0000000000008096] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2018] [Accepted: 04/30/2019] [Indexed: 12/22/2022] Open
Abstract
OBJECTIVE To study the intrinsic organization of the thalamocortical circuitry in patients with generalized epilepsy with tonic-clonic seizures (GTCS) via resting-state fMRI (rs-fMRI) connectome analysis and to evaluate its relation to drug response. METHODS In a prospectively followed-up sample of 41 patients and 27 healthy controls, we obtained rs-fMRI and structural MRI. After 1 year of follow-up, 27 patients were classified as seizure-free and 14 as drug-resistant. We examined connectivity within and between resting-state communities in cortical and thalamic subregions. In addition to comparing patients to controls, we examined associations with seizure control. We assessed reproducibility in an independent cohort of 21 patients. RESULTS Compared to controls, patients showed a more constrained network embedding of the thalamus, while frontocentral neocortical regions expressed increased functional diversity. Findings remained significant after regressing out thalamic volume and cortical thickness, suggesting independence from structural alterations. We observed more marked network imbalances in drug-resistant compared to seizure-free patients. Findings were similar in the reproducibility dataset. CONCLUSIONS Our findings suggest a pathoconnectomic mechanism of generalized epilepsy centered on diverging changes in cortical and thalamic connectivity. More restricted thalamic connectivity could reflect the tendency to engage in recursive thalamocortical loops, which may contribute to hyperexcitability. Conversely, increased connectional diversity of frontocentral networks may relay abnormal activity to an extended bilateral territory. Network imbalances were observed shortly after diagnosis and related to future drug response, suggesting clinical utility.
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Affiliation(s)
- Zhengge Wang
- From the Departments of Radiology (Z.W., B.Z., B.Z.) and Neurology (Z.W., Y.X.), Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, China; Multimodal Imaging and Connectome Analysis Laboratory (Z.W., S.L., R.V.d.W., S.-J.H., B.C.B.) and Neuroimaging of Epilepsy Laboratory (S.-J.H., N.B., A.B.), McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Quebec, Canada; and Department of Medical Imaging (Q.X., Z.Z.), Jinling Hospital, Nanjing University School of Medicine, China
| | - Sara Larivière
- From the Departments of Radiology (Z.W., B.Z., B.Z.) and Neurology (Z.W., Y.X.), Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, China; Multimodal Imaging and Connectome Analysis Laboratory (Z.W., S.L., R.V.d.W., S.-J.H., B.C.B.) and Neuroimaging of Epilepsy Laboratory (S.-J.H., N.B., A.B.), McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Quebec, Canada; and Department of Medical Imaging (Q.X., Z.Z.), Jinling Hospital, Nanjing University School of Medicine, China
| | - Qiang Xu
- From the Departments of Radiology (Z.W., B.Z., B.Z.) and Neurology (Z.W., Y.X.), Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, China; Multimodal Imaging and Connectome Analysis Laboratory (Z.W., S.L., R.V.d.W., S.-J.H., B.C.B.) and Neuroimaging of Epilepsy Laboratory (S.-J.H., N.B., A.B.), McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Quebec, Canada; and Department of Medical Imaging (Q.X., Z.Z.), Jinling Hospital, Nanjing University School of Medicine, China
| | - Reinder Vos de Wael
- From the Departments of Radiology (Z.W., B.Z., B.Z.) and Neurology (Z.W., Y.X.), Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, China; Multimodal Imaging and Connectome Analysis Laboratory (Z.W., S.L., R.V.d.W., S.-J.H., B.C.B.) and Neuroimaging of Epilepsy Laboratory (S.-J.H., N.B., A.B.), McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Quebec, Canada; and Department of Medical Imaging (Q.X., Z.Z.), Jinling Hospital, Nanjing University School of Medicine, China
| | - Seok-Jun Hong
- From the Departments of Radiology (Z.W., B.Z., B.Z.) and Neurology (Z.W., Y.X.), Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, China; Multimodal Imaging and Connectome Analysis Laboratory (Z.W., S.L., R.V.d.W., S.-J.H., B.C.B.) and Neuroimaging of Epilepsy Laboratory (S.-J.H., N.B., A.B.), McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Quebec, Canada; and Department of Medical Imaging (Q.X., Z.Z.), Jinling Hospital, Nanjing University School of Medicine, China
| | - Zhongyuan Wang
- From the Departments of Radiology (Z.W., B.Z., B.Z.) and Neurology (Z.W., Y.X.), Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, China; Multimodal Imaging and Connectome Analysis Laboratory (Z.W., S.L., R.V.d.W., S.-J.H., B.C.B.) and Neuroimaging of Epilepsy Laboratory (S.-J.H., N.B., A.B.), McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Quebec, Canada; and Department of Medical Imaging (Q.X., Z.Z.), Jinling Hospital, Nanjing University School of Medicine, China
| | - Yun Xu
- From the Departments of Radiology (Z.W., B.Z., B.Z.) and Neurology (Z.W., Y.X.), Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, China; Multimodal Imaging and Connectome Analysis Laboratory (Z.W., S.L., R.V.d.W., S.-J.H., B.C.B.) and Neuroimaging of Epilepsy Laboratory (S.-J.H., N.B., A.B.), McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Quebec, Canada; and Department of Medical Imaging (Q.X., Z.Z.), Jinling Hospital, Nanjing University School of Medicine, China
| | - Bin Zhu
- From the Departments of Radiology (Z.W., B.Z., B.Z.) and Neurology (Z.W., Y.X.), Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, China; Multimodal Imaging and Connectome Analysis Laboratory (Z.W., S.L., R.V.d.W., S.-J.H., B.C.B.) and Neuroimaging of Epilepsy Laboratory (S.-J.H., N.B., A.B.), McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Quebec, Canada; and Department of Medical Imaging (Q.X., Z.Z.), Jinling Hospital, Nanjing University School of Medicine, China
| | - Neda Bernasconi
- From the Departments of Radiology (Z.W., B.Z., B.Z.) and Neurology (Z.W., Y.X.), Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, China; Multimodal Imaging and Connectome Analysis Laboratory (Z.W., S.L., R.V.d.W., S.-J.H., B.C.B.) and Neuroimaging of Epilepsy Laboratory (S.-J.H., N.B., A.B.), McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Quebec, Canada; and Department of Medical Imaging (Q.X., Z.Z.), Jinling Hospital, Nanjing University School of Medicine, China
| | - Andrea Bernasconi
- From the Departments of Radiology (Z.W., B.Z., B.Z.) and Neurology (Z.W., Y.X.), Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, China; Multimodal Imaging and Connectome Analysis Laboratory (Z.W., S.L., R.V.d.W., S.-J.H., B.C.B.) and Neuroimaging of Epilepsy Laboratory (S.-J.H., N.B., A.B.), McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Quebec, Canada; and Department of Medical Imaging (Q.X., Z.Z.), Jinling Hospital, Nanjing University School of Medicine, China
| | - Bing Zhang
- From the Departments of Radiology (Z.W., B.Z., B.Z.) and Neurology (Z.W., Y.X.), Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, China; Multimodal Imaging and Connectome Analysis Laboratory (Z.W., S.L., R.V.d.W., S.-J.H., B.C.B.) and Neuroimaging of Epilepsy Laboratory (S.-J.H., N.B., A.B.), McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Quebec, Canada; and Department of Medical Imaging (Q.X., Z.Z.), Jinling Hospital, Nanjing University School of Medicine, China
| | - Zhiqiang Zhang
- From the Departments of Radiology (Z.W., B.Z., B.Z.) and Neurology (Z.W., Y.X.), Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, China; Multimodal Imaging and Connectome Analysis Laboratory (Z.W., S.L., R.V.d.W., S.-J.H., B.C.B.) and Neuroimaging of Epilepsy Laboratory (S.-J.H., N.B., A.B.), McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Quebec, Canada; and Department of Medical Imaging (Q.X., Z.Z.), Jinling Hospital, Nanjing University School of Medicine, China
| | - Boris C Bernhardt
- From the Departments of Radiology (Z.W., B.Z., B.Z.) and Neurology (Z.W., Y.X.), Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, China; Multimodal Imaging and Connectome Analysis Laboratory (Z.W., S.L., R.V.d.W., S.-J.H., B.C.B.) and Neuroimaging of Epilepsy Laboratory (S.-J.H., N.B., A.B.), McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Quebec, Canada; and Department of Medical Imaging (Q.X., Z.Z.), Jinling Hospital, Nanjing University School of Medicine, China.
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30
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van Mierlo P, Höller Y, Focke NK, Vulliemoz S. Network Perspectives on Epilepsy Using EEG/MEG Source Connectivity. Front Neurol 2019; 10:721. [PMID: 31379703 PMCID: PMC6651209 DOI: 10.3389/fneur.2019.00721] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Accepted: 06/18/2019] [Indexed: 12/17/2022] Open
Abstract
The evolution of EEG/MEG source connectivity is both, a promising, and controversial advance in the characterization of epileptic brain activity. In this narrative review we elucidate the potential of this technology to provide an intuitive view of the epileptic network at its origin, the different brain regions involved in the epilepsy, without the limitation of electrodes at the scalp level. Several studies have confirmed the added value of using source connectivity to localize the seizure onset zone and irritative zone or to quantify the propagation of epileptic activity over time. It has been shown in pilot studies that source connectivity has the potential to obtain prognostic correlates, to assist in the diagnosis of the epilepsy type even in the absence of visually noticeable epileptic activity in the EEG/MEG, and to predict treatment outcome. Nevertheless, prospective validation studies in large and heterogeneous patient cohorts are still lacking and are needed to bring these techniques into clinical use. Moreover, the methodological approach is challenging, with several poorly examined parameters that most likely impact the resulting network patterns. These fundamental challenges affect all potential applications of EEG/MEG source connectivity analysis, be it in a resting, spiking, or ictal state, and also its application to cognitive activation of the eloquent area in presurgical evaluation. However, such method can allow unique insights into physiological and pathological brain functions and have great potential in (clinical) neuroscience.
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Affiliation(s)
- Pieter van Mierlo
- Medical Image and Signal Processing Group, Ghent University, Ghent, Belgium
| | - Yvonne Höller
- Faculty of Psychology, University of Akureyri, Akureyri, Iceland
| | - Niels K Focke
- Clinical Neurophysiology, University Medicine Göttingen, Göttingen, Germany
| | - Serge Vulliemoz
- EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland
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31
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Abstract
Epilepsy is a chronic neurological condition, following some trigger, transforming a normal brain to one that produces recurrent unprovoked seizures. In the search for the mechanisms that best explain the epileptogenic process, there is a growing body of evidence suggesting that the epilepsies are network level disorders. In this review, we briefly describe the concept of neuronal networks and highlight 2 methods used to analyse such networks. The first method, graph theory, is used to describe general characteristics of a network to facilitate comparison between normal and abnormal networks. The second, dynamic causal modelling, is useful in the analysis of the pathways of seizure spread. We concluded that the end results of the epileptogenic process are best understood as abnormalities of neuronal circuitry and not simply as molecular or cellular abnormalities. The network approach promises to generate new understanding and more targeted treatment of epilepsy.
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Affiliation(s)
- Aminu T Abdullahi
- Department of Psychiatry, Aminu Kano Teaching Hospital, Kano, Nigeria
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32
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Marquetand J, Vannoni S, Carboni M, Li Hegner Y, Stier C, Braun C, Focke NK. Reliability of Magnetoencephalography and High-Density Electroencephalography Resting-State Functional Connectivity Metrics. Brain Connect 2019; 9:539-553. [PMID: 31115272 DOI: 10.1089/brain.2019.0662] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Resting-state connectivity, for example, based on magnetoencephalography (MEG) or electroencephalography (EEG), is a widely used method for characterizing brain networks and a promising imaging biomarker. However, there is no established standard as to which method, modality, and analysis variant is preferable and there is only limited knowledge on the reproducibility, an important prerequisite for clinical application. We conducted an MEG-/high-density (hd)-EEG-study on 22 young healthy adults, who were measured twice in a scan/rescan design after 7 ± 2 days. Reliability of resting-state (15 min, eyes-closed) connectivity in source space was calculated via intraclass correlation coefficient (ICC) in classical frequency bands (delta-gamma). We investigated the reliability of two commonly used connectivity metrics, namely the imaginary part of coherency and the weighted phase-lag index and the influence of frequency band, vigilance, and the number of trials. We found a strong increase of reliability with more trials and relatively mild effects of vigilance. Reliability was excellent in the alpha band for MEG, as well as hd-EEG (ICC >0.85); in the theta band, reliability was good for MEG and poor for EEG. Other frequency bands showed lower reliability, with delta band being the worst. Furthermore, we investigated the spatial reliability of resting-state connectivity in a vertex-based approach, which reached fair to good reliability (ICC up to 0.67) with 5 min of data. Our results indicate that excellent reliability of global connectivity is achievable in alpha band, and vertex-based connectivity was still fair to good. Moreover, electrophysiological resting-state studies could benefit from more data than used previously. MEG and hd-EEG were similar in their overall performance but showed frequency band-specific differences.
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Affiliation(s)
- Justus Marquetand
- Department of Epileptology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Silvia Vannoni
- Department of Epileptology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.,MEG-Center, University of Tübingen, Tübingen, Germany.,Section of Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neurosciences (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Margherita Carboni
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland.,Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
| | - Yiwen Li Hegner
- Department of Epileptology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.,MEG-Center, University of Tübingen, Tübingen, Germany
| | - Christina Stier
- Department of Epileptology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.,Clinical Neurophysiology, Georg-August University Göttingen, Göttingen, Germany
| | | | - Niels K Focke
- Department of Epileptology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.,Clinical Neurophysiology, Georg-August University Göttingen, Göttingen, Germany
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33
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Ogren JA, Tripathi R, Macey PM, Kumar R, Stern JM, Eliashiv DS, Allen LA, Diehl B, Engel J, Rani MRS, Lhatoo SD, Harper RM. Regional cortical thickness changes accompanying generalized tonic-clonic seizures. Neuroimage Clin 2018; 20:205-215. [PMID: 30094170 PMCID: PMC6073085 DOI: 10.1016/j.nicl.2018.07.015] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2018] [Revised: 06/27/2018] [Accepted: 07/15/2018] [Indexed: 12/12/2022]
Abstract
Objective Generalized tonic-clonic seizures are accompanied by cardiovascular and respiratory sequelae that threaten survival. The frequency of these seizures is a major risk factor for sudden unexpected death in epilepsy (SUDEP), a leading cause of untimely death in epilepsy. The circumstances accompanying such fatal events suggest a cardiovascular or respiratory failure induced by unknown neural processes rather than an inherent cardiac or lung deficiency. Certain cortical regions, especially the insular, cingulate, and orbitofrontal cortices, are key structures that integrate sensory input and influence diencephalic and brainstem regions regulating blood pressure, cardiac rhythm, and respiration; output from those cortical regions compromised by epilepsy-associated injury may lead to cardiorespiratory dysregulation. The aim here was to assess changes in cortical integrity, reflected as cortical thickness, relative to healthy controls. Cortical alterations in areas that influence cardiorespiratory action could contribute to SUDEP mechanisms. Methods High-resolution T1-weighted images were collected with a 3.0-Tesla MRI scanner from 53 patients with generalized tonic-clonic seizures (Mean age ± SD: 37.1 ± 12.6 years, 22 male) at Case Western Reserve University, University College London, and the University of California at Los Angeles. Control data included 530 healthy individuals (37.1 ± 12.6 years; 220 male) from UCLA and two open access databases (OASIS and IXI). Cortical thickness group differences were assessed at all non-cerebellar brain surface locations (P < 0.05 corrected). Results Increased cortical thickness appeared in post-central gyri, insula, and subgenual, anterior, posterior, and isthmus cingulate cortices. Post-central gyri increases were greater in females, while males showed more extensive cingulate increases. Frontal and temporal cortex, lateral orbitofrontal, frontal pole, and lateral parietal and occipital cortices showed thinning. The extents of thickness changes were sex- and hemisphere-dependent, with only males exhibiting right-sided and posterior cingulate thickening, while females showed only left lateral orbitofrontal thinning. Regional cortical thickness showed modest correlations with seizure frequency, but not epilepsy duration. Significance Cortical thickening and thinning occur in patients with generalized tonic-clonic seizures, in cardiovascular and somatosensory areas, with extent of changes sex- and hemisphere-dependent. The data show injury in key autonomic and respiratory cortical areas, which may contribute to dysfunctional cardiorespiratory patterns during seizures, as well as to longer-term SUDEP risk.
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Affiliation(s)
- Jennifer A Ogren
- Department of Neurobiology, David Geffen School of Medicine at UCLA, University of California at Los Angeles, Los Angeles, CA, USA
| | - Raghav Tripathi
- Department of Neurobiology, David Geffen School of Medicine at UCLA, University of California at Los Angeles, Los Angeles, CA, USA; Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Paul M Macey
- UCLA School of Nursing, University of California at Los Angeles, Los Angeles, CA, USA; Brain Research Institute, University of California at Los Angeles, Los Angeles, CA, USA
| | - Rajesh Kumar
- Brain Research Institute, University of California at Los Angeles, Los Angeles, CA, USA; Department of Anesthesiology, David Geffen School of Medicine at UCLA, University of California at Los Angeles, Los Angeles, CA, USA; Department of Radiological Sciences, David Geffen School of Medicine at UCLA, University of California at Los Angeles, Los Angeles, CA, USA
| | - John M Stern
- Department of Neurology, David Geffen School of Medicine at UCLA, University of California at Los Angeles, Los Angeles, CA, USA
| | - Dawn S Eliashiv
- Department of Neurology, David Geffen School of Medicine at UCLA, University of California at Los Angeles, Los Angeles, CA, USA
| | - Luke A Allen
- Institute of Neurology, University College London, London, United Kingdom
| | - Beate Diehl
- Institute of Neurology, University College London, London, United Kingdom
| | - Jerome Engel
- Department of Neurobiology, David Geffen School of Medicine at UCLA, University of California at Los Angeles, Los Angeles, CA, USA; Brain Research Institute, University of California at Los Angeles, Los Angeles, CA, USA; Department of Neurology, David Geffen School of Medicine at UCLA, University of California at Los Angeles, Los Angeles, CA, USA; Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, University of California at Los Angeles, Los Angeles, CA, USA
| | | | | | - Ronald M Harper
- Department of Neurobiology, David Geffen School of Medicine at UCLA, University of California at Los Angeles, Los Angeles, CA, USA; Brain Research Institute, University of California at Los Angeles, Los Angeles, CA, USA.
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Li Hegner Y, Marquetand J, Elshahabi A, Klamer S, Lerche H, Braun C, Focke NK. Increased Functional MEG Connectivity as a Hallmark of MRI-Negative Focal and Generalized Epilepsy. Brain Topogr 2018; 31:863-874. [PMID: 29766384 DOI: 10.1007/s10548-018-0649-4] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2018] [Accepted: 05/08/2018] [Indexed: 01/13/2023]
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.
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Affiliation(s)
- Yiwen Li Hegner
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Hope-Seyler-Straße 3, 72076, Tübingen, Germany.
| | - Justus Marquetand
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Hope-Seyler-Straße 3, 72076, Tübingen, Germany
| | - Adham Elshahabi
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Hope-Seyler-Straße 3, 72076, Tübingen, Germany.,Werner Reichardt Centre for Integrative Neuroscience, Tübingen, Germany
| | - Silke Klamer
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Hope-Seyler-Straße 3, 72076, Tübingen, Germany
| | - Holger Lerche
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Hope-Seyler-Straße 3, 72076, Tübingen, Germany.,Werner Reichardt Centre for Integrative Neuroscience, Tübingen, Germany
| | - Christoph Braun
- Werner Reichardt Centre for Integrative Neuroscience, Tübingen, Germany.,MEG Center, University of Tübingen, Tübingen, Germany.,CIMeC, Center for Mind/Brain Sciences, University of Trento, Trento, Italy
| | - Niels K Focke
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Hope-Seyler-Straße 3, 72076, Tübingen, Germany.,Werner Reichardt Centre for Integrative Neuroscience, Tübingen, Germany.,Clinical Neurophysiology, University of Göttingen, Göttingen, Germany
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35
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Koirala GR, Lee D, Eom S, Kim NY, Kim HD. Altered brain functional connectivity induced by physical exercise may improve neuropsychological functions in patients with benign epilepsy. Epilepsy Behav 2017; 76:126-132. [PMID: 28919388 DOI: 10.1016/j.yebeh.2017.06.021] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2017] [Revised: 05/17/2017] [Accepted: 06/17/2017] [Indexed: 10/18/2022]
Abstract
OBJECTIVE The objective of this study was to elucidate alteration in functional connectivity (FC) in patients with benign epilepsy with centrotemporal spikes (BECTS) as induced by physical exercise therapy and their correlation to the neuropsychological (NP) functions. METHODS We analyzed 115 artifact- and spike-free 2-second epochs extracted from resting state EEG recordings before and after 5weeks of physical exercise in eight patients with BECTS. The exact Low Resolution Electromagnetic Tomography (eLORETA) was used for source reconstruction. We evaluated the cortical current source density (CSD) power across five different frequency bands (delta, theta, alpha, beta, and gamma). Altered FC between 34 regions of interests (ROIs) was then examined using lagged phase synchronization (LPS) method. We further investigated the correlation between the altered FC measures and the changes in NP test scores. RESULTS We observed changes in CSD power following the exercise for all frequency bands and statistically significant increases in the right temporal region for the alpha band. There were a number of altered FC between the cortical ROIs in all frequency bands of interest. Furthermore, significant correlations were observed between FC measures and NP test scores at theta and alpha bands. CONCLUSION The increased localization power at alpha band may be an indication of the positive impact of exercise in patients with BECTS. Frequency band-specific alterations in FC among cortical regions were associated with the modulation of cognitive and NP functions. The significant correlation between FC and NP tests suggests that physical exercise may mitigate the severity of BECTS, thereby enhancing NP function.
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Affiliation(s)
- Gyan Raj Koirala
- Radio Frequency Integrated Circuits Lab, Kwangwoon University, Department of Electronic Engineering, Seoul, Republic of Korea
| | - Dongpyo Lee
- Epilepsy Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Soyong Eom
- Epilepsy Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Nam-Young Kim
- Radio Frequency Integrated Circuits Lab, Kwangwoon University, Department of Electronic Engineering, Seoul, Republic of Korea.
| | - Heung Dong Kim
- Epilepsy Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea; Division of Pediatric Neurology, Severance Children's Hospital, Yonsei University, Seoul, Republic of Korea; Department of Pediatrics, Yonsei University College of Medicine, Seoul, Republic of Korea.
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Kajal DS, Braun C, Mellinger J, Sacchet MD, Ruiz S, Fetz E, Birbaumer N, Sitaram R. Learned control of inter-hemispheric connectivity: Effects on bimanual motor performance. Hum Brain Mapp 2017; 38:4353-4369. [PMID: 28580720 DOI: 10.1002/hbm.23663] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2016] [Revised: 05/12/2017] [Accepted: 05/15/2017] [Indexed: 11/11/2022] Open
Abstract
Bimanual movements involve the interactions between both primary motor cortices. These interactions are assumed to involve phase-locked oscillatory brain activity referred to as inter-hemispheric functional coupling. So far, inter-hemispheric functional coupling has been investigated as a function of motor performance. These studies report mostly a negative correlation between the performance in motor tasks and the strength of functional coupling. However, correlation might not reflect a causal relationship. To overcome this limitation, we opted for an alternative approach by manipulating the strength of inter-hemispheric functional coupling and assessing bimanual motor performance as a dependent variable. We hypothesize that an increase/decrease of functional coupling deteriorates/facilitates motor performance in an out-of-phase bimanual finger-tapping task. Healthy individuals were trained to volitionally regulate functional coupling in an operant conditioning paradigm using real-time magnetoencephalography neurofeedback. During operant conditioning, two discriminative stimuli were associated with upregulation and downregulation of functional coupling. Effects of training were assessed by comparing motor performance prior to (pre-test) and after the training (post-test). Participants receiving contingent feedback learned to upregulate and downregulate functional coupling. Comparing motor performance, as indexed by the ratio of tapping speed for upregulation versus downregulation trials, no change was found in the control group between pre- and post-test. In contrast, the group receiving contingent feedback evidenced a significant decrease of the ratio implicating lower tapping speed with stronger functional coupling. Results point toward a causal role of inter-hemispheric functional coupling for the performance in bimanual tasks. Hum Brain Mapp 38:4353-4369, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Diljit Singh Kajal
- Institute of Medical Psychology and Behavioral Neurobiology, Tübingen, 72076, Germany.,MEG-Center, University of Tübingen, Tübingen, 72076, Germany.,GTC, Graduate Training Center of Neuroscience, University of Tübingen, Tübingen, 72074, Germany.,CIN, Werner Reichardt Centre for Integrative Neuroscience, University of Tübingen, Tübingen, 72076, Germany
| | - Christoph Braun
- MEG-Center, University of Tübingen, Tübingen, 72076, Germany.,CIN, Werner Reichardt Centre for Integrative Neuroscience, University of Tübingen, Tübingen, 72076, Germany.,CIMeC, Center for Mind/Brain Sciences, University of Trento, Rovereto, 38068, Italy.,Department of Psychology and Cognitive Science, University of Trento, Rovereto, 38068, Italy
| | - Jürgen Mellinger
- Max Planck Institute for Intelligent Systems (Department of Empirical Inference), Spemannstr. 41, Tübingen, 72076, Germany
| | - Matthew D Sacchet
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, 94305-5717, USA
| | - Sergio Ruiz
- Institute of Medical Psychology and Behavioral Neurobiology, Tübingen, 72076, Germany.,Departamento de Psiquiatría, Escuela de Medicina, Centro Interdisciplinario de Neurociencias, Pontificia Universidad Catolica de Chile, Santiago, Chile.,Laboratory for Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Eberhard Fetz
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, 98195-7290, USA
| | - Niels Birbaumer
- Institute of Medical Psychology and Behavioral Neurobiology, Tübingen, 72076, Germany.,Wyss Center for Bio and Neuroengineering, Geneva, 1202, Switzerland.,Ospedale San Camillo IRCCS, Venezia, 30126, Italy
| | - Ranganatha Sitaram
- Departamento de Psiquiatría, Escuela de Medicina, Centro Interdisciplinario de Neurociencias, Pontificia Universidad Catolica de Chile, Santiago, Chile.,Laboratory for Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica de Chile, Santiago, Chile.,Institute for Biological and Medical Engineering, Schools of Engineering, Biology and Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
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Qu J, Lu SH, Lu ZL, Xu P, Xiang DX, Qu Q. Pharmacogenetic and case-control study on potassium channel related gene variants and genetic generalized epilepsy. Medicine (Baltimore) 2017; 96:e7321. [PMID: 28658141 PMCID: PMC5500063 DOI: 10.1097/md.0000000000007321] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
Potassium channels are the targets of antiepileptic drugs (AEDs), which play important roles in the etiology of epilepsy. KCNA1 and KCNA2 encode mammalian Kv1.1 and Kv1.2 channels, which are essential roles in the initiation and shaping of action potentials. KCNV2 encodes Kv8.2, which is a regional overlap with Kv2 subunits as functional heterotetramers. In our study, we aim to investigate whether variants of KCNA1, KCNA2, and KCNV2 genes influence susceptibility to genetic generalized epilepsies (GGEs) and the efficacy of AEDs. Seven hundred sixty-seven subjects (284 healthy controls, 279 drug-responsive, and 204 drug-resistant GGE patients) were enrolled in our study. Eight variants of KCNA1, KCNA2, and KCNV2 were assessed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry method. Results showed that there were no statistically significant correlations between the 8 variants of KCNA1, KCNA2, and KCNV2 and the risk/drug resistance of GGEs. In conclusion, our study suggests that KCNA1, KCNA2, and KCNV2 variants may not be involved in the risk/drug resistance of GGEs. Further multicenter, multiethnic, and large sample size pharmacogenetic and case-control studies are warranted to confirm our negative results.
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Affiliation(s)
- Jian Qu
- Department of Pharmacy, the Second Xiangya Hospital, Central South University, Institute of Clinical Pharmacy
| | - Shao-Hua Lu
- Department of Neurosurgery, the Third Xiangya Hospital
| | - Zhi-Li Lu
- Department of Pathology, the Affiliated Cancer Hospital of Xiangya School of Medicine
| | - Ping Xu
- Department of Pharmacy, the Second Xiangya Hospital, Central South University, Institute of Clinical Pharmacy
| | - Da-Xiong Xiang
- Department of Pharmacy, the Second Xiangya Hospital, Central South University, Institute of Clinical Pharmacy
| | - Qiang Qu
- Department of Pharmacy, Xiangya Hospital, Central South University, Changsha, P. R. China
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Pang EW, Snead III OC. From Structure to Circuits: The Contribution of MEG Connectivity Studies to Functional Neurosurgery. Front Neuroanat 2016; 10:67. [PMID: 27445705 PMCID: PMC4914570 DOI: 10.3389/fnana.2016.00067] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2016] [Accepted: 06/07/2016] [Indexed: 11/14/2022] Open
Abstract
New advances in structural neuroimaging have revealed the intricate and extensive connections within the brain, data which have informed a number of ambitious projects such as the mapping of the human connectome. Elucidation of the structural connections of the brain, at both the macro and micro levels, promises new perspectives on brain structure and function that could translate into improved outcomes in functional neurosurgery. The understanding of neuronal structural connectivity afforded by these data now offers a vista on the brain, in both healthy and diseased states, that could not be seen with traditional neuroimaging. Concurrent with these developments in structural imaging, a complementary modality called magnetoencephalography (MEG) has been garnering great attention because it too holds promise for being able to shed light on the intricacies of functional brain connectivity. MEG is based upon the elemental principle of physics that an electrical current generates a magnetic field. Hence, MEG uses highly sensitive biomagnetometers to measure extracranial magnetic fields produced by intracellular neuronal currents. Put simply then, MEG is a measure of neurophysiological activity, which captures the magnetic fields generated by synchronized intraneuronal electrical activity. As such, MEG recordings offer exquisite resolution in the time and oscillatory domain and, as well, when co-registered with magnetic resonance imaging (MRI), offer excellent resolution in the spatial domain. Recent advances in MEG computational and graph theoretical methods have led to studies of connectivity in the time-frequency domain. As such, MEG can elucidate a neurophysiological-based functional circuitry that may enhance what is seen with MRI connectivity studies. In particular, MEG may offer additional insight not possible by MRI when used to study complex eloquent function, where the precise timing and coordination of brain areas is critical. This article will review the traditional use of MEG for functional neurosurgery, describe recent advances in MEG connectivity analyses, and consider the additional benefits that could be gained with the inclusion of MEG connectivity studies. Since MEG has been most widely applied to the study of epilepsy, we will frame this article within the context of epilepsy surgery and functional neurosurgery for epilepsy.
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Affiliation(s)
- Elizabeth W. Pang
- Division of Neurology, Hospital for Sick ChildrenToronto, ON, Canada
- Neurosciences and Mental Health, SickKids Research InstituteToronto, ON, Canada
- Department of Paediatrics, Faculty of Medicine, University of TorontoToronto, ON, Canada
| | - O. C. Snead III
- Division of Neurology, Hospital for Sick ChildrenToronto, ON, Canada
- Neurosciences and Mental Health, SickKids Research InstituteToronto, ON, Canada
- Department of Paediatrics, Faculty of Medicine, University of TorontoToronto, ON, Canada
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