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Rampp S, Müller-Voggel N, Hamer H, Doerfler A, Brandner S, Buchfelder M. Interictal Electrical Source Imaging. J Clin Neurophysiol 2024; 41:19-26. [PMID: 38181384 DOI: 10.1097/wnp.0000000000001012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2024] Open
Abstract
SUMMARY Interictal electrical source imaging (ESI) determines the neuronal generators of epileptic activity in EEG occurring outside of seizures. It uses computational models to take anatomic and neuronal characteristics of the individual patient into account. The presented article provides an overview of application and clinical value of interictal ESI in patients with pharmacoresistant focal epilepsies undergoing evaluation for surgery. Neurophysiological constraints of interictal data are discussed and technical considerations are summarized. Typical indications are covered as well as issues of integration into clinical routine. Finally, an outlook on novel markers of epilepsy for interictal source analysis is presented. Interictal ESI provides diagnostic performance on par with other established methods, such as MRI, PET, or SPECT. Although its accuracy benefits from high-density recordings, it provides valuable information already when applied to EEG with only a limited number of electrodes with complete coverage. Novel oscillatory markers and the integration of frequency coupling and connectivity may further improve accuracy and efficiency.
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Affiliation(s)
- Stefan Rampp
- Department of Neurosurgery, University Hospital Erlangen, Germany
- Department of Neurosurgery, University Hospital Halle (Saale), Germany
| | | | - Hajo Hamer
- Epilepsy Center, Department of Neurology, University Hospital Erlangen, Germany; and
| | - Arnd Doerfler
- Department of Neuroradiology, University Hospital Erlangen, Germany
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2
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Rampp S, Kaltenhäuser M, Müller-Voggel N, Doerfler A, Kasper BS, Hamer HM, Brandner S, Buchfelder M. MEG Node Degree for Focus Localization: Comparison with Invasive EEG. Biomedicines 2023; 11:biomedicines11020438. [PMID: 36830974 PMCID: PMC9953213 DOI: 10.3390/biomedicines11020438] [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: 01/10/2023] [Revised: 01/23/2023] [Accepted: 01/30/2023] [Indexed: 02/05/2023] Open
Abstract
Epilepsy surgery is a viable therapy option for patients with pharmacoresistant focal epilepsies. A prerequisite for postoperative seizure freedom is the localization of the epileptogenic zone, e.g., using electro- and magnetoencephalography (EEG/MEG). Evidence shows that resting state MEG contains subtle alterations, which may add information to the workup of epilepsy surgery. Here, we investigate node degree (ND), a graph-theoretical parameter of functional connectivity, in relation to the seizure onset zone (SOZ) determined by invasive EEG (iEEG) in a consecutive series of 50 adult patients. Resting state data were subjected to whole brain, all-to-all connectivity analysis using the imaginary part of coherence. Graphs were described using parcellated ND. SOZ localization was investigated on a lobar and sublobar level. On a lobar level, all frequency bands except alpha showed significantly higher maximal ND (mND) values inside the SOZ compared to outside (ratios 1.11-1.20, alpha 1.02). Area-under-the-curve (AUC) was 0.67-0.78 for all expected alpha (0.44, ns). On a sublobar level, mND inside the SOZ was higher for all frequency bands (1.13-1.38, AUC 0.58-0.78) except gamma (1.02). MEG ND is significantly related to SOZ in delta, theta and beta bands. ND may provide new localization tools for presurgical evaluation of epilepsy surgery.
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Affiliation(s)
- Stefan Rampp
- Department of Neurosurgery, University Hospital Erlangen, 91054 Erlangen, Germany
- Department of Neurosurgery, University Hospital Halle (Saale), 06120 Halle (Saale), Germany
- Correspondence: ; Tel.: +49-9131-85-46921; Fax: +49-9131-85-34476
| | - Martin Kaltenhäuser
- Department of Neurosurgery, University Hospital Erlangen, 91054 Erlangen, Germany
| | - Nadia Müller-Voggel
- Department of Neurosurgery, University Hospital Erlangen, 91054 Erlangen, Germany
| | - Arnd Doerfler
- Department of Neuroradiology, University Hospital Erlangen, 91054 Erlangen, Germany
| | - Burkhard S. Kasper
- Epilepsy Center, Department of Neurology, University Hospital Erlangen, 91054 Erlangen, Germany
| | - Hajo M. Hamer
- Epilepsy Center, Department of Neurology, University Hospital Erlangen, 91054 Erlangen, Germany
| | - Sebastian Brandner
- Department of Neurosurgery, University Hospital Erlangen, 91054 Erlangen, Germany
| | - Michael Buchfelder
- Department of Neurosurgery, University Hospital Erlangen, 91054 Erlangen, Germany
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3
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Wang R, Wang H, Shi L, Han C, Che Y. Epileptic Seizure Detection Using Geometric Features Extracted from SODP Shape of EEG Signals and AsyLnCPSO-GA. ENTROPY (BASEL, SWITZERLAND) 2022; 24:1540. [PMID: 36359630 PMCID: PMC9689850 DOI: 10.3390/e24111540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 10/21/2022] [Accepted: 10/24/2022] [Indexed: 06/16/2023]
Abstract
Epilepsy is a neurological disorder that is characterized by transient and unexpected electrical disturbance of the brain. Seizure detection by electroencephalogram (EEG) is associated with the primary interest of the evaluation and auxiliary diagnosis of epileptic patients. The aim of this study is to establish a hybrid model with improved particle swarm optimization (PSO) and a genetic algorithm (GA) to determine the optimal combination of features for epileptic seizure detection. First, the second-order difference plot (SODP) method was applied, and ten geometric features of epileptic EEG signals were derived in each frequency band (δ, θ, α and β), forming a high-dimensional feature vector. Secondly, an optimization algorithm, AsyLnCPSO-GA, combining a modified PSO with asynchronous learning factor (AsyLnCPSO) and the genetic algorithm (GA) was proposed for feature selection. Finally, the feature combinations were fed to a naïve Bayesian classifier for epileptic seizure and seizure-free identification. The method proposed in this paper achieved 95.35% classification accuracy with a tenfold cross-validation strategy when the interfrequency bands were crossed, serving as an effective method for epilepsy detection, which could help clinicians to expeditiously diagnose epilepsy based on SODP analysis and an optimization algorithm for feature selection.
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Affiliation(s)
- Ruofan Wang
- School of Information Technology Engineering, Tianjin University of Technology and Education, Tianjin 300222, China
| | - Haodong Wang
- School of Information Technology Engineering, Tianjin University of Technology and Education, Tianjin 300222, China
| | - Lianshuan Shi
- School of Information Technology Engineering, Tianjin University of Technology and Education, Tianjin 300222, China
| | - Chunxiao Han
- Tianjin Key Laboratory of Information Sensing & Intelligent Control, School of Automation and Electrical Engineering, Tianjin University of Technology and Education, Tianjin 300222, China
| | - Yanqiu Che
- Tianjin Key Laboratory of Information Sensing & Intelligent Control, School of Automation and Electrical Engineering, Tianjin University of Technology and Education, Tianjin 300222, China
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4
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Pernice R, Faes L, Feucht M, Benninger F, Mangione S, Schiecke K. Pairwise and higher-order measures of brain-heart interactions in children with temporal lobe epilepsy. J Neural Eng 2022; 19. [PMID: 35803218 DOI: 10.1088/1741-2552/ac7fba] [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: 03/28/2022] [Accepted: 07/08/2022] [Indexed: 11/11/2022]
Abstract
OBJECTIVE While it is well-known that epilepsy has a clear impact on the activity of both the central nervous system (CNS) and the autonomic nervous system (ANS), its role on the complex interplay between CNS and ANS has not been fully elucidated yet. In this work, pairwise and higher-order predictability measures based on the concepts of Granger causality (GC) and Partial Information Decomposition (PID) were applied on time series of electroencephalographic (EEG) brain wave amplitude and heart rate variability (HRV) in order to investigate directed brain-heart interactions associated with the occurrence of focal epilepsy. APPROACH HRV and the envelopes of δ and α EEG activity recorded from ipsilateral (ipsi-EEG) and contralateral (contra-EEG) scalp regions were analyzed in 18 children suffering from temporal lobe epilepsy monitored during pre-ictal, ictal and post-ictal periods. After linear parametric model identification, we compared pairwise GC measures computed between HRV and a single EEG component with PID measures quantifying the unique, redundant and synergistic information transferred from ipsi-EEG and contra-EEG to HRV. MAIN RESULTS The analysis of GC revealed a dominance of the information transfer from EEG to HRV and negligible transfer from HRV to EEG, suggesting that CNS activities drive the ANS modulation of the heart rhythm, but did not evidence clear differences between δ and α rhythms, ipsi-EEG and contra-EEG, or pre- and post-ictal periods. On the contrary, PID revealed that epileptic seizures induce a reorganization of the interactions from brain to heart, as the unique predictability of HRV originated from the ipsi-EEG for the δ waves and from the contra-EEG for the α waves in the pre-ictal phase, while these patterns were reversed after the seizure. SIGNIFICANCE These results highlight the importance of considering higher-order interactions elicited by PID for the study of the neuro-autonomic effects of focal epilepsy, and may have neurophysiological and clinical implications.
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Affiliation(s)
- Riccardo Pernice
- Department of Engineering, University of Palermo, Viale delle Scienze, Bldg. 9, Palermo, 90128, ITALY
| | - Luca Faes
- Department of Engineering, University of Palermo, Viale delle Scienze, Bldg. 9, Palermo, 90128, ITALY
| | - Martha Feucht
- Epilepsy Monitoring Unit, Department of Child and Adolenscent Neuropsychiatry, University Hospital Vienna, Währinger Gürtel 18-20, Vienna, 1090, AUSTRIA
| | - Franz Benninger
- Department of Child and Adolescent Medicine, University Hospital Vienna, Währinger Gürtel 18-20, Vienna, 1090, AUSTRIA
| | - Stefano Mangione
- Department of Engineering, University of Palermo, Viale delle Scienze, Bldg. 9, Palermo, Sicilia, 90128, ITALY
| | - Karin Schiecke
- Institute of Medical Statistics, Computer Sciences and Documentation, Jena University Hospital, Friedrich Schiller University Jena, Bachstraße 18, Jena, 07743, GERMANY
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5
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Nair KP, Salaka RJ, Srikumar BN, Kutty BM, Rao BSS. Enriched environment rescues impaired sleep-wake architecture and abnormal neural dynamics in chronic epileptic rats. Neuroscience 2022; 495:97-114. [DOI: 10.1016/j.neuroscience.2022.05.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2021] [Revised: 05/12/2022] [Accepted: 05/19/2022] [Indexed: 11/16/2022]
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6
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Prediction of seizure outcome following temporal lobectomy: a magnetoencephalography-based graph theory approach". Seizure 2022; 97:73-81. [DOI: 10.1016/j.seizure.2022.03.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 03/12/2022] [Accepted: 03/15/2022] [Indexed: 11/22/2022] Open
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7
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Houtman SJ, Lammertse HCA, van Berkel AA, Balagura G, Gardella E, Ramautar JR, Reale C, Møller RS, Zara F, Striano P, Misra-Isrie M, van Haelst MM, Engelen M, van Zuijen TL, Mansvelder HD, Verhage M, Bruining H, Linkenkaer-Hansen K. STXBP1 Syndrome Is Characterized by Inhibition-Dominated Dynamics of Resting-State EEG. Front Physiol 2022; 12:775172. [PMID: 35002760 PMCID: PMC8733612 DOI: 10.3389/fphys.2021.775172] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 11/23/2021] [Indexed: 11/19/2022] Open
Abstract
STXBP1 syndrome is a rare neurodevelopmental disorder caused by heterozygous variants in the STXBP1 gene and is characterized by psychomotor delay, early-onset developmental delay, and epileptic encephalopathy. Pathogenic STXBP1 variants are thought to alter excitation-inhibition (E/I) balance at the synaptic level, which could impact neuronal network dynamics; however, this has not been investigated yet. Here, we present the first EEG study of patients with STXBP1 syndrome to quantify the impact of the synaptic E/I dysregulation on ongoing brain activity. We used high-frequency-resolution analyses of classical and recently developed methods known to be sensitive to E/I balance. EEG was recorded during eyes-open rest in children with STXBP1 syndrome (n = 14) and age-matched typically developing children (n = 50). Brain-wide abnormalities were observed in each of the four resting-state measures assessed here: (i) slowing of activity and increased low-frequency power in the range 1.75–4.63 Hz, (ii) increased long-range temporal correlations in the 11–18 Hz range, (iii) a decrease of our recently introduced measure of functional E/I ratio in a similar frequency range (12–24 Hz), and (iv) a larger exponent of the 1/f-like aperiodic component of the power spectrum. Overall, these findings indicate that large-scale brain activity in STXBP1 syndrome exhibits inhibition-dominated dynamics, which may be compensatory to counteract local circuitry imbalances expected to shift E/I balance toward excitation, as observed in preclinical models. We argue that quantitative EEG investigations in STXBP1 and other neurodevelopmental disorders are a crucial step to understand large-scale functional consequences of synaptic E/I perturbations.
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Affiliation(s)
- Simon J Houtman
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, (CNCR), Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands
| | - Hanna C A Lammertse
- Department of Functional Genomics, Center for Neurogenomics and Cognitive Research, (CNCR), Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands.,Department of Human Genetics, Amsterdam UMC, Amsterdam, Netherlands
| | - Annemiek A van Berkel
- Department of Functional Genomics, Center for Neurogenomics and Cognitive Research, (CNCR), Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands.,Department of Human Genetics, Amsterdam UMC, Amsterdam, Netherlands
| | - Ganna Balagura
- Department of Functional Genomics, Center for Neurogenomics and Cognitive Research, (CNCR), Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands.,IRCCS Istituto Giannina Gaslini, Genova, Italy.,Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
| | - Elena Gardella
- Department of Epilepsy Genetics and Personalized Treatment, Danish Epilepsy Centre, Dianalund, Denmark.,Department of Regional Health Research, University of Southern Denmark, Odense, Denmark.,Member of the ERN EpiCARE
| | - Jennifer R Ramautar
- Child and Adolescent Psychiatry and Psychosocial Care, Emma Children's Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Chiara Reale
- Department of Epilepsy Genetics and Personalized Treatment, Danish Epilepsy Centre, Dianalund, Denmark.,Department of Clinical and Experimental Medicine, Epilepsy Center, University Hospital of Messina, Messina, Italy
| | - Rikke S Møller
- Department of Epilepsy Genetics and Personalized Treatment, Danish Epilepsy Centre, Dianalund, Denmark.,Department of Regional Health Research, University of Southern Denmark, Odense, Denmark.,Member of the ERN EpiCARE
| | - Federico Zara
- IRCCS Istituto Giannina Gaslini, Genova, Italy.,Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
| | - Pasquale Striano
- IRCCS Istituto Giannina Gaslini, Genova, Italy.,Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
| | - Mala Misra-Isrie
- Department of Human Genetics, Amsterdam UMC, Amsterdam, Netherlands
| | | | - Marc Engelen
- Department of Pediatric Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Titia L van Zuijen
- Research Institute of Child Development and Education, University of Amsterdam, Amsterdam, Netherlands
| | - Huibert D Mansvelder
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, (CNCR), Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands
| | - Matthijs Verhage
- Department of Functional Genomics, Center for Neurogenomics and Cognitive Research, (CNCR), Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands.,Department of Human Genetics, Amsterdam UMC, Amsterdam, Netherlands
| | - Hilgo Bruining
- Child and Adolescent Psychiatry and Psychosocial Care, Emma Children's Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,N=You Neurodevelopmental Precision Center, Amsterdam Neuroscience, Amsterdam Reproduction and Development, Amsterdam UMC, Amsterdam, Netherlands.,Levvel, Center for Child and Adolescent Psychiatry, Amsterdam, Netherlands
| | - Klaus Linkenkaer-Hansen
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, (CNCR), Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands
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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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9
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van Heumen S, Moreau JT, Simard-Tremblay E, Albrecht S, Dudley RWR, Baillet S. Case Report: Aperiodic Fluctuations of Neural Activity in the Ictal MEG of a Child With Drug-Resistant Fronto-Temporal Epilepsy. Front Hum Neurosci 2021; 15:646426. [PMID: 33746727 PMCID: PMC7969518 DOI: 10.3389/fnhum.2021.646426] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2020] [Accepted: 02/12/2021] [Indexed: 11/24/2022] Open
Abstract
Successful surgical treatment of patients with focal drug-resistant epilepsy remains challenging, especially in cases for which it is difficult to define the area of cortex from which seizures originate, the seizure onset zone (SOZ). Various diagnostic methods are needed to select surgical candidates and determine the extent of resection. Interictal magnetoencephalography (MEG) with source imaging has proven to be useful for presurgical evaluation, but the use of ictal MEG data remains limited. The purpose of the present study was to determine whether pre-ictal variations of spectral properties of neural activity from ictal MEG recordings are predictive of SOZ location.We performed a 4 h overnight MEG recording in an 8-year-old child with drug-resistant focal epilepsy of suspected right fronto-temporal origin and captured one ~45-s seizure. The patient underwent a right temporal resection from the anterior temporal neocortex and amygdala to the mid-posterior temporal neocortex, sparing the hippocampus proper. She remains seizure-free 21 months postoperatively. The histopathological assessment confirmed frank focal cortical dysplasia (FCD) type IIa in the MEG-defined SOZ, which was based on source imaging of averaged ictal spikes at seizure onset. We investigated temporal changes (inter-ictal, pre-ictal, and ictal periods) together with spatial differences (SOZ vs. control regions) in spectral parameters of background brain activity, namely the aperiodic broadband offset and slope, and assessed how they confounded the interpretation of apparent variations of signal power in typical electrophysiological bands. Our data show that the SOZ was associated with a higher aperiodic offset and exponent during the seizure compared to control regions. Both parameters increased in all regions from 2 min before the seizure onwards. Regions anatomically closer to the SOZ also expressed higher values compared to contralateral regions, potentially indicating ictal spread. We also show that narrow-band power changes were caused by these fluctuations in the aperiodic component of ongoing brain activity. Our results indicate that the broadband aperiodic component of ongoing brain activity cannot be reduced to background noise of no physiological interest, and rather may be indicative of the neuropathophysiology of the SOZ. We believe these findings will inspire future studies of ictal MEG cases and confirm their significance.
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Affiliation(s)
- Saskia van Heumen
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Jeremy T. Moreau
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
- Department of Pediatric Surgery, Division of Neurosurgery, Montreal Children’s Hospital, Montreal, QC, Canada
- Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Elisabeth Simard-Tremblay
- Department of Pediatrics, Division of Pediatric Neurology, Montreal Children’s Hospital, McGill University, Montreal, QC, Canada
| | - Steffen Albrecht
- Department of Pathology, Montreal Children’s Hospital, McGill University, Montreal, QC, Canada
| | - Roy WR. Dudley
- Department of Pediatric Surgery, Division of Neurosurgery, Montreal Children’s Hospital, Montreal, QC, Canada
| | - Sylvain Baillet
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
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10
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Rampp S, Rössler K, Hamer H, Illek M, Buchfelder M, Doerfler A, Pieper T, Hartlieb T, Kudernatsch M, Koelble K, Peixoto-Santos JE, Blümcke I, Coras R. Dysmorphic neurons as cellular source for phase-amplitude coupling in Focal Cortical Dysplasia Type II. Clin Neurophysiol 2021; 132:782-792. [PMID: 33571886 DOI: 10.1016/j.clinph.2021.01.004] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 01/04/2021] [Accepted: 01/11/2021] [Indexed: 02/07/2023]
Abstract
OBJECTIVE Reliable localization of the epileptogenic zone is necessary for successful epilepsy surgery. Neurophysiological biomarkers include ictal onsets and interictal spikes. Furthermore, the epileptic network shows oscillations with potential localization value and pathomechanistic implications. The cellular origin of such markers in invasive EEG in vivo remains to be clarified. METHODS In the presented pilot study, surgical brain samples and invasive EEG recordings of seven patients with surgically treated Focal Cortical Dysplasia (FCD) type II were coregistered using a novel protocol. Dysmorphic neurons and balloon cells were immunohistochemically quantified. Evaluated markers included seizure onset, spikes, and oscillatory activity in delta, theta, gamma and ripple frequency bands, as well as sample entropy and phase-amplitude coupling between delta, theta, alpha and beta phase and gamma amplitude. RESULTS Correlations between histopathology and neurophysiology provided evidence for a contribution of dysmorphic neurons to interictal spikes, fast gamma activity and ripples. Furthermore, seizure onset and phase-amplitude coupling in areas with dysmorphic neurons suggests preserved connectivity is related to seizure initiation. Balloon cells showed no association. CONCLUSIONS Phase-amplitude coupling, spikes, fast gamma and ripples are related to the density of dysmorphic neurons and localize the seizure onset zone. SIGNIFICANCE The results of our pilot study provide a new powerful tool to address the cellular source of abnormal neurophysiology signals to leverage current and novel biomarkers for the localization of epileptic activity in the human brain.
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Affiliation(s)
- Stefan Rampp
- Department of Neurosurgery, University Hospital Erlangen, Germany; Department of Neurosurgery, University Hospital Halle, Germany.
| | - Karl Rössler
- Department of Neurosurgery, University Hospital Erlangen, Germany; Department of Neurosurgery, University Hospital Vienna, Austria
| | - Hajo Hamer
- Epilepsy Center, Department of Neurology, University Hospital Erlangen, Germany
| | - Margit Illek
- Department of Neurosurgery, University Hospital Erlangen, Germany
| | | | - Arnd Doerfler
- Department of Neuroradiology, University Hospital Erlangen, Germany
| | - Tom Pieper
- Hospital for Neuropediatrics and Neurological Rehabilitation, Epilepsy Center for Children and Adolescents, Schön Klinik Vogtareuth, Germany
| | - Till Hartlieb
- Hospital for Neuropediatrics and Neurological Rehabilitation, Epilepsy Center for Children and Adolescents, Schön Klinik Vogtareuth, Germany
| | - Manfred Kudernatsch
- Epilepsy Center and Department of Neurosurgery, Schön Klinik Vogtareuth, Germany; Research Institute, Rehabilitation, Transition, Palliation, PMU Salzburg, Salzburg, Austria
| | - Konrad Koelble
- Department of Neuropathology, University Hospital Erlangen, Germany
| | - Jose Eduardo Peixoto-Santos
- Department of Neuropathology, University Hospital Erlangen, Germany; Department of Neurology and Neurosurgery, Paulista School of Medicine, UNIFESP, Brazil
| | - Ingmar Blümcke
- Department of Neuropathology, University Hospital Erlangen, Germany
| | - Roland Coras
- Department of Neuropathology, University Hospital Erlangen, Germany
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11
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Rampp S, Kakisaka Y, Shibata S, Wu X, Rössler K, Buchfelder M, Burgess RC. Normal Variants in Magnetoencephalography. J Clin Neurophysiol 2020; 37:518-536. [PMID: 33165225 DOI: 10.1097/wnp.0000000000000484] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
Normal variants, although not occurring frequently, may appear similar to epileptic activity. Misinterpretation may lead to false diagnoses. In the context of presurgical evaluation, normal variants may lead to mislocalizations with severe impact on the viability and success of surgical therapy. While the different variants are well known in EEG, little has been published in regard to their appearance in magnetoencephalography. Furthermore, there are some magnetoencephalography normal variants that have no counterparts in EEG. This article reviews benign epileptiform variants and provides examples in EEG and magnetoencephalography. In addition, the potential of oscillatory configurations in different frequency bands to appear as epileptic activity is discussed.
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Affiliation(s)
- Stefan Rampp
- Department of Neurosurgery, University Hospital, Erlangen, Germany.,Department of Neurosurgery, University Hospital, Halle (Saale), Germany
| | - Yosuke Kakisaka
- Department of Epileptology, Tohoku University School of Medicine, Sendai, Japan
| | - Sumiya Shibata
- Department of Neurosurgery and Human Brain Research Center, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Xingtong Wu
- Department of Neurosurgery, University Hospital, Erlangen, Germany.,Department of Neurology, West China Hospital, Sichuan University, Sichuan, China; and
| | - Karl Rössler
- Department of Neurosurgery, University Hospital, Erlangen, Germany
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Tseng HT, Hsiao YT, Yi PL, Chang FC. Deep Brain Stimulation Increases Seizure Threshold by Altering REM Sleep and Delta Powers During NREM Sleep. Front Neurol 2020; 11:752. [PMID: 32903424 PMCID: PMC7434934 DOI: 10.3389/fneur.2020.00752] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2019] [Accepted: 06/18/2020] [Indexed: 12/02/2022] Open
Abstract
We previously demonstrated that seizure occurrences at different zeitgeber times alter sleep and circadian rhythm differently. On the other hand, the synchronized delta wave of electroencephalogram (EEG) during non-rapid eye movement (NREM) sleep facilitates seizure, while the desynchronized EEG of rapid eye movement (REM) sleep suppresses it. We also elucidated that unilateral deep brain stimulation (DBS) of the anterior nucleus of thalamus (ANT) suppresses seizure recurrence. In the present study, we intraperitoneally injected pentylenetetrazol (PTZ, 40 mg/kg) for 14 consecutive days (PTZ kindling) to induce spontaneous seizure in rats, and a 30-min (delivered 10 min before each PTZ injection) or a 3-h DBS of unilateral ANT (delivered 1 h before each PTZ injection) was applied to suppress seizure. The frequency of DBS stimulation was 200 Hz and the electrical current consisted of biphasic square pulses with 50-μA intensity, 100-μs pulse width, and 4.1-ms stimulation interval. Our results found that PTZ-induced spontaneous seizure did not cause a significant change in the quantity of NREM sleep but suppressed the amount of REM sleep. Unilateral ANT DBS prolonged the onset latency of ictal seizure, decreased the spontaneous seizure duration, and increased the survival rate but did not change the amplitude of epileptiform EEGs during ictal period. Unilateral ANT DBS did not significantly alter NREM sleep but increased the amount of REM sleep. An analysis of the spectrograms of fast Fourier transform indicated that the intensities of all frequencies were enhanced during the PTZ-induced ictal period and the subsequent spontaneous seizure. Thirty minutes of unilateral ANT DBS suppressed the augmentation of low-frequency (<10 Hz) intensities during the spontaneous seizure induced by PTZ kindling. We further found that consecutive injections of PTZ progressively increased the enhancement of the delta powers during NREM sleep, whereas unilateral ANT DBS inhibited this progressive enhancement. It was also noticed that 30 min of ANT DBS exhibited a better efficacy in epilepsy suppression than 3 h of ANT DBS. These results elucidated that unilateral ANT DBS enhanced the seizure threshold by increasing the amount of REM sleep and decreasing the progressive enhancement of delta power during NREM sleep to suppress spontaneous seizure recurrences in PTZ kindling-induced epileptic rats.
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Affiliation(s)
- Hsin-Tzu Tseng
- Department of Veterinary Medicine, School of Veterinary Medicine, National Taiwan University, Taipei, Taiwan
| | - Yi-Tse Hsiao
- Department of Veterinary Medicine, School of Veterinary Medicine, National Taiwan University, Taipei, Taiwan
| | - Pei-Lu Yi
- Department of Sport Management, College of Tourism, Leisure and Sports, Aletheia University, Taipei, Taiwan
| | - Fang-Chia Chang
- Department of Veterinary Medicine, School of Veterinary Medicine, National Taiwan University, Taipei, Taiwan
- Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan
- Graduate Institute of Acupuncture Science, College of Chinese Medicine, China Medical University, Taichung City, Taiwan
- Department of Medicine, College of Medicine, China Medical University, Taichung City, Taiwan
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Baldini S, Coito A, Korff CM, Garibotto V, Ndenghera M, Spinelli L, Bartoli A, Momjian S, Schaller K, Seeck M, Pittau F, Vulliemoz S. Localizing non-epileptiform abnormal brain function in children using high density EEG: Electric Source Imaging of focal slowing. Epilepsy Res 2019; 159:106245. [PMID: 31846783 DOI: 10.1016/j.eplepsyres.2019.106245] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2019] [Revised: 11/01/2019] [Accepted: 11/22/2019] [Indexed: 11/18/2022]
Abstract
BACKGROUND Electric Source Imaging (ESI) of interictal epileptiform discharges (IED) is increasingly validated for localizing epileptic activity. In children, IED can be absent or multifocal even in cases of a focal epileptogenic zone and additional electrophysiological markers are needed. Here, we investigated ESI of pathological focal slowing (FS) recorded on EEG as a new localizing marker in children with drug-resistant epilepsy. METHODS We selected 15 children (median: 12; range: 4-18yrs), with high-density EEG (hdEEG), presurgical evaluation and surgical resection. One patient had a non-lesional MRI. ESI of patient-specific focal slow activity was performed (distributed linear inverse solution and individual head model). The maximal average power in the band of interest was considered as the source of focal slowing (ESI-FS). The Euclidian distance between ESI-FS and the resection (5 mm margin) was compared to the localization of maximal ESI of interictal epileptiform discharges (ESI-IED), interictal FDG-PET and ictal SPECT/SISCOM. RESULTS In 9/15 patients (60%), ESI of focal slowing (ESI-FS) was inside or ≤5 mm from resection margins. The remaining 6/15 cases had distances ≤15 mm. In 9/15 patients with interictal spikes, the ESI-IED was concordant with the resection. 6/15 patients with concordant ESI-FS showed also interictal concordant ESI of IED; in 3/15 patients, ESI-FS but not ESI-IED was concordant with the resection. In 10/15 patients, ESI-FS was concordant with MRI lesion and for ESI-IED this concordance was on 8/15 patients. Maximal hypometabolism and SISCOM were concordant with the resection for 7/15 and 7/12, respectively. CONCLUSION These findings suggest that "non-epileptiform" EEG activity, such as focal slowing, could be a complementary useful marker to localize the epileptogenic zone. ESI-FS may notably be applied in young patients without focal interictal spikes or multifocal spikes. This potential new marker of brain dysfunction has potential applications to other neurological disorders associated with slow EEG activity.
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Affiliation(s)
- Sara Baldini
- Neurology Clinic, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland; Clinical Unit of Neurology, Department of Medical Sciences, University Hospital and Health Services of Trieste, University of Trieste, Trieste, Italy
| | - Ana Coito
- Neurology Clinic, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland; Department of Neurology Cantonal Hospital Aarau, Aarau, Switzerland
| | - Christian M Korff
- Pediatric Neurology Unit, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Valentina Garibotto
- Nuclear Medicine and Molecular Imaging, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Martin Ndenghera
- Neurology Clinic, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Laurent Spinelli
- Neurology Clinic, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Andrea Bartoli
- Neurosurgery Clinic, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Shahan Momjian
- Neurosurgery Clinic, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Karl Schaller
- Neurosurgery Clinic, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Margittta Seeck
- Neurology Clinic, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Francesca Pittau
- Neurology Clinic, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Serge Vulliemoz
- Neurology Clinic, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland.
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The Neuropeptide Galanin Is Required for Homeostatic Rebound Sleep following Increased Neuronal Activity. Neuron 2019; 104:370-384.e5. [PMID: 31537465 DOI: 10.1016/j.neuron.2019.08.010] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2018] [Revised: 06/04/2019] [Accepted: 08/03/2019] [Indexed: 01/19/2023]
Abstract
Sleep pressure increases during wake and dissipates during sleep, but the molecules and neurons that measure homeostatic sleep pressure remain poorly understood. We present a pharmacological assay in larval zebrafish that generates short-term increases in wakefulness followed by sustained rebound sleep after washout. The intensity of global neuronal activity during drug-induced wakefulness predicted the amount of subsequent rebound sleep. Whole-brain mapping with the neuronal activity marker phosphorylated extracellular signal-regulated kinase (pERK) identified preoptic Galanin (Galn)-expressing neurons as selectively active during rebound sleep, and the relative induction of galn transcripts was predictive of total rebound sleep time. Galn is required for sleep homeostasis, as galn mutants almost completely lacked rebound sleep following both pharmacologically induced neuronal activity and physical sleep deprivation. These results suggest that Galn plays a key role in responding to sleep pressure signals derived from neuronal activity and functions as an output arm of the vertebrate sleep homeostat.
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Nissen IA, Stam CJ, van Straaten ECW, Wottschel V, Reijneveld JC, Baayen JC, de Witt Hamer PC, Idema S, Velis DN, Hillebrand A. Localization of the Epileptogenic Zone Using Interictal MEG and Machine Learning in a Large Cohort of Drug-Resistant Epilepsy Patients. Front Neurol 2018; 9:647. [PMID: 30131762 PMCID: PMC6090046 DOI: 10.3389/fneur.2018.00647] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2018] [Accepted: 07/18/2018] [Indexed: 01/01/2023] Open
Abstract
Objective: Epilepsy surgery results in seizure freedom in the majority of drug-resistant patients. To improve surgery outcome we studied whether MEG metrics combined with machine learning can improve localization of the epileptogenic zone, thereby enhancing the chance of seizure freedom. Methods: Presurgical interictal MEG recordings of 94 patients (64 seizure-free >1y post-surgery) were analyzed to extract four metrics in source space: delta power, low-to-high-frequency power ratio, functional connectivity (phase lag index), and minimum spanning tree betweenness centrality. At the group level, we estimated the overlap of the resection area with the five highest values for each metric and determined whether this overlap differed between surgery outcomes. At the individual level, those metrics were used in machine learning classifiers (linear support vector machine (SVM) and random forest) to distinguish between resection and non-resection areas and between surgery outcome groups. Results: The highest values, for all metrics, overlapped with the resection area in more than half of the patients, but the overlap did not differ between surgery outcome groups. The classifiers distinguished the resection areas from non-resection areas with 59.94% accuracy (95% confidence interval: 59.67–60.22%) for SVM and 60.34% (59.98–60.71%) for random forest, but could not differentiate seizure-free from not seizure-free patients [43.77% accuracy (42.08–45.45%) for SVM and 49.03% (47.25–50.82%) for random forest]. Significance: All four metrics localized the resection area but did not distinguish between surgery outcome groups, demonstrating that metrics derived from interictal MEG correspond to expert consensus based on several presurgical evaluation modalities, but do not yet localize the epileptogenic zone. Metrics should be improved such that they correspond to the resection area in seizure-free patients but not in patients with persistent seizures. It is important to test such localization strategies at an individual level, for example by using machine learning or individualized models, since surgery is individually tailored.
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Affiliation(s)
- Ida A Nissen
- Department of Clinical Neurophysiology and MEG Center, VU University Medical Center, Amsterdam, Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and MEG Center, VU University Medical Center, Amsterdam, Netherlands
| | - Elisabeth C W van Straaten
- Department of Clinical Neurophysiology and MEG Center, VU University Medical Center, Amsterdam, Netherlands
| | - Viktor Wottschel
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, Netherlands
| | - Jaap C Reijneveld
- Brain Tumor Center Amsterdam & Department of Neurology, VU University Medical Center, Amsterdam, Netherlands
| | - Johannes C Baayen
- Neurosurgical Center Amsterdam, VU University Medical Center, Amsterdam, Netherlands
| | - Philip C de Witt Hamer
- Brain Tumor Center Amsterdam & Department of Neurology, VU University Medical Center, Amsterdam, Netherlands.,Neurosurgical Center Amsterdam, VU University Medical Center, Amsterdam, Netherlands
| | - Sander Idema
- Neurosurgical Center Amsterdam, VU University Medical Center, Amsterdam, Netherlands
| | - Demetrios N Velis
- Department of Clinical Neurophysiology and MEG Center, VU University Medical Center, Amsterdam, Netherlands.,Neurosurgical Center Amsterdam, VU University Medical Center, Amsterdam, Netherlands
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and MEG Center, VU University Medical Center, Amsterdam, Netherlands
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