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Chericoni A, Ricci L, Ntolkeras G, Billardello R, Stone SSD, Madsen JR, Papadelis C, Grant PE, Pearl PL, Taffoni F, Rotenberg A, Tamilia E. Sleep Spindle Generation Before and After Epilepsy Surgery: A Source Imaging Study in Children with Drug-Resistant Epilepsy. Brain Topogr 2024; 37:88-101. [PMID: 37737957 DOI: 10.1007/s10548-023-01007-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 09/09/2023] [Indexed: 09/23/2023]
Abstract
INTRODUCTION Literature lacks studies investigating the cortical generation of sleep spindles in drug-resistant epilepsy (DRE) and how they evolve after resection of the epileptogenic zone (EZ). Here, we examined sleep EEGs of children with focal DRE who became seizure-free after focal epilepsy surgery, and aimed to investigate the changes in the spindle generation before and after the surgery using low-density scalp EEG and electrical source imaging (ESI). METHODS We analyzed N2-sleep EEGs from 19 children with DRE before and after surgery. We identified slow (8-12 Hz) and fast spindles (13-16 Hz), computed their spectral features and cortical generators through ESI and computed their distance from the EZ and irritative zone (IZ). We performed two-way ANOVA testing the effect of spindle type (slow vs. fast) and surgical phase (pre-surgery vs. post-surgery) on each feature. RESULTS Power, frequency and cortical activation of slow spindles increased after surgery (p < 0.005), while this was not seen for fast spindles. Before surgery, the cortical generators of slow spindles were closer to the EZ (57.3 vs. 66.2 mm, p = 0.007) and IZ (41.3 vs. 55.5 mm, p = 0.02) than fast spindle generators. CONCLUSIONS Our data indicate alterations in the EEG slow spindles after resective epilepsy surgery. Fast spindle generation on the contrary did not change after surgery. Although the study is limited by its retrospective nature, lack of healthy controls, and reduced cortical spatial sampling, our findings suggest a spatial relationship between the slow spindles and the epileptogenic generators.
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Affiliation(s)
- Assia Chericoni
- Fetal Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Lorenzo Ricci
- Department of Medicine and Surgery, Research Unit of Neurology, Neurobiology, Neurophysiology, University Campus Bio-Medico di Roma, Rome, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico di Roma, Via Alvaro del Portillo, 200, 00128, Rome, Italy
| | - Georgios Ntolkeras
- Fetal Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Roberto Billardello
- Fetal Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Advanced Robotics and Human-Centred Technologies - CREO Lab, Campus Bio-Medico di Roma, Rome, Italy
| | - Scellig S D Stone
- Department of Neurosurgery, Boston Children's Hospital, Harvard Medical School, Boston, USA
| | - Joseph R Madsen
- Department of Neurosurgery, Boston Children's Hospital, Harvard Medical School, Boston, USA
| | - Christos Papadelis
- Jane and John Justin Neurosciences Center, Cook children's Health Care System, Boston, TX, USA
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX, USA
| | - P Ellen Grant
- Fetal Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Phillip L Pearl
- Division of Epilepsy and Clinical Neurophysiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Fabrizio Taffoni
- Advanced Robotics and Human-Centred Technologies - CREO Lab, Campus Bio-Medico di Roma, Rome, Italy
| | - Alexander Rotenberg
- Division of Epilepsy and Clinical Neurophysiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Eleonora Tamilia
- Fetal Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
- Division of Epilepsy and Clinical Neurophysiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
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Ricci L, Matarrese M, Peters JM, Tamilia E, Madsen JR, Pearl PL, Papadelis C. Virtual implantation using conventional scalp EEG delineates seizure onset and predicts surgical outcome in children with epilepsy. Clin Neurophysiol 2022; 139:49-57. [PMID: 35526353 PMCID: PMC10026594 DOI: 10.1016/j.clinph.2022.04.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2022] [Revised: 04/04/2022] [Accepted: 04/08/2022] [Indexed: 11/16/2022]
Abstract
OBJECTIVE Delineation of the seizure onset zone (SOZ) is required in children with drug resistant epilepsy (DRE) undergoing neurosurgery. Intracranial EEG (icEEG) serves as gold standard but has limitations. Here, we examine the utility of virtual implantation with electrical source imaging (ESI) on ictal scalp EEG for mapping the SOZ and predict surgical outcome. METHODS We retrospectively analyzed EEG data from 35 children with DRE who underwent surgery and dichotomized into seizure-free (SF) and non-seizure-free (NSF). We estimated virtual sensors (VSs) at brain locations that matched icEEG implantation and compared ictal patterns at VSs vs icEEG. We calculated the agreement between VSs SOZ and clinically defined SOZ and built receiver operating characteristic (ROC) curves to test whether it predicted outcome. RESULTS Twenty-one patients were SF after surgery. Moderate agreement between virtual and icEEG patterns was observed (kappa = 0.45, p < 0.001). Virtual SOZ agreement with clinically defined SOZ was higher in SF vs NSF patients (66.6% vs 41.6%, p = 0.01). Anatomical concordance of virtual SOZ with clinically defined SOZ predicted outcome (AUC = 0.73; 95% CI: 0.57-0.89; sensitivity = 66.7%; specificity = 78.6%; accuracy = 71.4%). CONCLUSIONS Virtual implantation on ictal scalp EEG can approximate the SOZ and predict outcome. SIGNIFICANCE SOZ mapping with VSs may contribute to tailoring icEEG implantation and predict outcome.
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Affiliation(s)
- Lorenzo Ricci
- Unit of Neurology, Neurophysiology, Neurobiology, Department of Medicine, University Campus Bio-Medico of Rome, Rome, Italy
| | - Margherita Matarrese
- Unit of Non-Linear Physics and Mathematical Modelling, Engineering Department, University Campus Bio-Medico of Rome, Rome, Italy; Jane and John Justin Neurosciences Center, Cook Children's Health Care System, Fort Worth, TX, USA; Department of Bioengineering, University of Texas at Arlington, Arlington, TX, USA
| | - Jurriaan M Peters
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Eleonora Tamilia
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Joseph R Madsen
- Division of Epilepsy Surgery, Department of Neurosurgery, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Phillip L Pearl
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Christos Papadelis
- Jane and John Justin Neurosciences Center, Cook Children's Health Care System, Fort Worth, TX, USA; Department of Bioengineering, University of Texas at Arlington, Arlington, TX, USA; School of Medicine, Texas Christian University, Fort Worth, TX, USA.
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Spencer ER, Chinappen D, Emerton BC, Morgan AK, Hämäläinen MS, Manoach DS, Eden UT, Kramer MA, Chu CJ. Source EEG reveals that Rolandic epilepsy is a regional epileptic encephalopathy. Neuroimage Clin 2022; 33:102956. [PMID: 35151039 PMCID: PMC8844714 DOI: 10.1016/j.nicl.2022.102956] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 01/10/2022] [Accepted: 02/03/2022] [Indexed: 01/15/2023]
Abstract
Children with RE have fewer spindles but they have typical time–frequency features. Spindle deficits extend to multiple cortical regions in Rolandic epilepsy. Cognitive deficits are predicted by spindle rate in Rolandic epilepsy. Regional spindle rate predicts motor deficits better than Rolandic spindle deficit. Spindle features in RE identify a regional thalamocortical epileptic encephalopathy.
Rolandic epilepsy is the most common form of epileptic encephalopathy, characterized by sleep-potentiated inferior Rolandic epileptiform spikes, seizures, and cognitive deficits in school-age children that spontaneously resolve by adolescence. We recently identified a paucity of sleep spindles, physiological thalamocortical rhythms associated with sleep-dependent learning, in the Rolandic cortex during the active phase of this disease. Because spindles are generated in the thalamus and amplified through regional thalamocortical circuits, we hypothesized that: 1) deficits in spindle rate would involve but extend beyond the inferior Rolandic cortex in active epilepsy and 2) regional spindle deficits would better predict cognitive function than inferior Rolandic spindle deficits alone. To test these hypotheses, we obtained high-resolution MRI, high-density EEG recordings, and focused neuropsychological assessments in children with Rolandic epilepsy during active (n = 8, age 9–14.7 years, 3F) and resolved (seizure free for > 1 year, n = 10, age 10.3–16.7 years, 1F) stages of disease and age-matched controls (n = 8, age 8.9–14.5 years, 5F). Using a validated spindle detector applied to estimates of electrical source activity in 31 cortical regions, including the inferior Rolandic cortex, during stages 2 and 3 of non-rapid eye movement sleep, we compared spindle rates in each cortical region across groups. Among detected spindles, we compared spindle features (power, duration, coherence, bilateral synchrony) between groups. We then used regression models to examine the relationship between spindle rate and cognitive function (fine motor dexterity, phonological processing, attention, and intelligence, and a global measure of all functions). We found that spindle rate was reduced in the inferior Rolandic cortices in active but not resolved disease (active P = 0.007; resolved P = 0.2) compared to controls. Spindles in this region were less synchronous between hemispheres in the active group (P = 0.005; resolved P = 0.1) compared to controls; but there were no differences in spindle power, duration, or coherence between groups. Compared to controls, spindle rate in the active group was also reduced in the prefrontal, insular, superior temporal, and posterior parietal regions (i.e., “regional spindle rate”, P < 0.039 for all). Independent of group, regional spindle rate positively correlated with fine motor dexterity (P < 1e-3), attention (P = 0.02), intelligence (P = 0.04), and global cognitive performance (P < 1e-4). Compared to the inferior Rolandic spindle rate alone, models including regional spindle rate trended to improve prediction of global cognitive performance (P = 0.052), and markedly improved prediction of fine motor dexterity (P = 0.006). These results identify a spindle disruption in Rolandic epilepsy that extends beyond the epileptic cortex and a potential mechanistic explanation for the broad cognitive deficits that can be observed in this epileptic encephalopathy.
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Affiliation(s)
- Elizabeth R Spencer
- Graduate Program in Neuroscience, Boston University, Boston, MA 02215; Department of Neurology, Massachusetts General Hospital, Boston, MA 02114
| | - Dhinakaran Chinappen
- Graduate Program in Neuroscience, Boston University, Boston, MA 02215; Department of Neurology, Massachusetts General Hospital, Boston, MA 02114
| | - Britt C Emerton
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114
| | - Amy K Morgan
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114
| | - Matti S Hämäläinen
- Harvard Medical School, Boston, MA 02115; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA 02129; Massachusetts General Hospital, Department of Radiology, Boston, MA 02114
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114; Harvard Medical School, Boston, MA 02115; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA 02129
| | - Uri T Eden
- Department of Mathematics and Statistics, Boston University, Boston, MA 02215; Center for Systems Neuroscience, Boston University, Boston, MA 02215
| | - Mark A Kramer
- Department of Mathematics and Statistics, Boston University, Boston, MA 02215; Center for Systems Neuroscience, Boston University, Boston, MA 02215
| | - Catherine J Chu
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114; Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114.
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Iachim E, Vespa S, Baroumand AG, Danthine V, Vrielynck P, de Tourtchaninoff M, Fierain A, Ribeiro Vaz JG, Raftopoulos C, Ferrao Santos S, van Mierlo P, El Tahry R. Automated electrical source imaging with scalp EEG to define the insular irritative zone: Comparison with simultaneous intracranial EEG. Clin Neurophysiol 2021; 132:2965-2978. [PMID: 34715421 DOI: 10.1016/j.clinph.2021.09.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 08/13/2021] [Accepted: 09/16/2021] [Indexed: 11/30/2022]
Abstract
OBJECTIVE To evaluate the accuracy of automatedinterictallow-density electrical source imaging (LD-ESI) to define the insular irritative zone (IZ) by comparing the simultaneous interictal ESI localization with the SEEG interictal activity. METHODS Long-term simultaneous scalp electroencephalography (EEG) and stereo-EEG (SEEG) with at least one depth electrode exploring the operculo-insular region(s) were analyzed. Automated interictal ESI was performed on the scalp EEG using standardized low-resolution brain electromagnetic tomography (sLORETA) and individual head models. A two-step analysis was performed: i) sublobar concordance betweencluster-based ESI localization and SEEG-based IZ; ii) time-locked ESI-/SEEG analysis. Diagnostic accuracy values were calculated using SEEG as reference standard. Subgroup analysis wascarried out, based onthe involvement of insular contacts in the seizure onset and patterns of insular interictal activity. RESULTS Thirty patients were included in the study. ESI showed an overall accuracy of 53% (C.I. 29-76%). Sensitivity and specificity were calculated as 53% (C.I. 29-76%), 55% (C.I. 23-83%) respectively. Higher accuracy was found in patients with frequent and dominant interictal insular spikes. CONCLUSIONS LD-ESI defines with good accuracy the insular implication in the IZ, which is not possible with classical interictalscalpEEG interpretation. SIGNIFICANCE Automated LD-ESI may be a valuable additional tool to characterize the epileptogenic zone in epilepsies with suspected insular involvement.
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Affiliation(s)
- Evelina Iachim
- Carol Davila University of Medicine and Pharmacy, Bucharest, Romania; Centre for Refractory Epilepsy, Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Simone Vespa
- Institute of Neuroscience (IoNS), Université Catholique de Louvain, Brussels, Belgium.
| | - Amir G Baroumand
- Medical Image and Signal Processing Group (MEDISIP), Department of Electronics and Information Systems, Ghent University, Ghent, Belgium; Epilog NV, Ghent, Belgium
| | - Venethia Danthine
- Institute of Neuroscience (IoNS), Université Catholique de Louvain, Brussels, Belgium
| | - Pascal Vrielynck
- Epileptology and Clinical Neurophysiology, Centre Neurologique William Lennox, Ottignies, Belgium
| | - Marianne de Tourtchaninoff
- Centre for Refractory Epilepsy, Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Alexane Fierain
- Epileptology and Clinical Neurophysiology, Centre Neurologique William Lennox, Ottignies, Belgium
| | - Jose Geraldo Ribeiro Vaz
- Centre for Refractory Epilepsy, Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | | | - Susana Ferrao Santos
- Institute of Neuroscience (IoNS), Université Catholique de Louvain, Brussels, Belgium; Centre for Refractory Epilepsy, Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Pieter van Mierlo
- Medical Image and Signal Processing Group (MEDISIP), Department of Electronics and Information Systems, Ghent University, Ghent, Belgium; Epilog NV, Ghent, Belgium
| | - Riëm El Tahry
- Institute of Neuroscience (IoNS), Université Catholique de Louvain, Brussels, Belgium; Centre for Refractory Epilepsy, Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
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Duma GM, Danieli A, Vettorel A, Antoniazzi L, Mento G, Bonanni P. Investigation of dynamic functional connectivity of the source reconstructed epileptiform discharges in focal epilepsy: A graph theory approach. Epilepsy Res 2021; 176:106745. [PMID: 34428725 DOI: 10.1016/j.eplepsyres.2021.106745] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 07/26/2021] [Accepted: 08/17/2021] [Indexed: 11/18/2022]
Abstract
OBJECTIVE The aim of the present study is to investigate with noninvasive methods the modulation of dynamic functional connectivity during interictal epileptiform discharge (IED). METHOD We reconstructed the cortical source of the EEG recorded IED of 17 patients with focal epilepsy. We then computed dynamic connectivity using the time resolved phase locking value (PLV). We derived graph theory indices (i.e. degree, strength, local efficiency, clustering coefficient and global efficiency). Finally, we selected the atlas node with the maximum activation as the IED cortical source investigating the graph indices dynamics in theta, alpha, beta and gamma frequency bands. RESULTS We observed IED-locked modulations of the graph indexes depending on the frequency bands. We detected a modulation of the strength, clustering coefficient, local and global efficiency both in theta and in alpha bands, which also displayed modulations of the degree index. In the beta band only the global efficiency was modulated by the IED, while no effects were detected in the gamma band. Finally, we found a correlation between alpha and theta local efficiency, as well as alpha global efficiency, and the epilepsy duration. SIGNIFICANCE Our findings suggest that the neural synchronization is not limited to the IED cortical source, but implies a phase synchronization across multiple brain areas. We hypothesize that the aberrant electrical activity originating from the IED locus is spread amongst the other network nodes throughout the low frequency bands (i.e. theta and alpha). Moreover, IED-dependent increase in the global efficiency indicates that the IED interfere with the whole network functioning. We finally discussed possible application of this methodology for future investigation.
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Affiliation(s)
- Gian Marco Duma
- Department of General Psychology, University of Padova, Italy; Epilepsy and Clinical Neurophysiology Unit, Scientific Institute, IRCCS "E. Medea", Conegliano, TV, Italy.
| | - Alberto Danieli
- Epilepsy and Clinical Neurophysiology Unit, Scientific Institute, IRCCS "E. Medea", Conegliano, TV, Italy
| | - Airis Vettorel
- Epilepsy and Clinical Neurophysiology Unit, Scientific Institute, IRCCS "E. Medea", Conegliano, TV, Italy
| | - Lisa Antoniazzi
- Epilepsy and Clinical Neurophysiology Unit, Scientific Institute, IRCCS "E. Medea", Conegliano, TV, Italy
| | - Giovanni Mento
- Department of General Psychology, University of Padova, Italy; Padova Neuroscience Center (PNC), University of Padova, Italy
| | - Paolo Bonanni
- Epilepsy and Clinical Neurophysiology Unit, Scientific Institute, IRCCS "E. Medea", Conegliano, TV, Italy
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Avigdor T, Abdallah C, von Ellenrieder N, Hedrich T, Rubino A, Lo Russo G, Bernhardt B, Nobili L, Grova C, Frauscher B. Fast oscillations >40 Hz localize the epileptogenic zone: An electrical source imaging study using high-density electroencephalography. Clin Neurophysiol 2021; 132:568-80. [PMID: 33450578 DOI: 10.1016/j.clinph.2020.11.031] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 10/04/2020] [Accepted: 11/06/2020] [Indexed: 01/25/2023]
Abstract
OBJECTIVE Fast Oscillations (FO) >40 Hz are a promising biomarker of the epileptogenic zone (EZ). Evidence using scalp electroencephalography (EEG) remains scarce. We assessed if electrical source imaging of FO using 256-channel high-density EEG (HD-EEG) is useful for EZ identification. METHODS We analyzed HD-EEG recordings of 10 focal drug-resistant epilepsy patients with seizure-free postsurgical outcome. We marked FO candidate events at the time of epileptic spikes and verified them by screening for an isolated peak in the time-frequency plot. We performed electrical source imaging of spikes and FO within the Maximum Entropy of the Mean framework. Source localization maps were validated against the surgical cavity. RESULTS We identified FO in five out of 10 patients who had a superficial or intermediate deep generator. The maximum of the FO maps was localized inside the cavity in all patients (100%). Analysis with a reduced electrode coverage using the 10-10 and 10-20 system showed a decreased localization accuracy of 60% and 40% respectively. CONCLUSIONS FO recorded with HD-EEG localize the EZ. HD-EEG is better suited to detect and localize FO than conventional EEG approaches. SIGNIFICANCE This study acts as proof-of-concept that FO localization using 256-channel HD-EEG is a viable marker of the EZ.
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Urriola J, Bollmann S, Tremayne F, Burianová H, Marstaller L, Reutens D. Functional connectivity of the irritative zone identified by electrical source imaging, and EEG-correlated fMRI analyses. Neuroimage Clin 2020; 28:102440. [PMID: 33002859 PMCID: PMC7527619 DOI: 10.1016/j.nicl.2020.102440] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 09/02/2020] [Accepted: 09/15/2020] [Indexed: 11/06/2022]
Abstract
The irritative zone differs on Electrical Source Imaging (ESI) and EEG-fMRI. Findings differ in functional connectivity and show low temporal correlation. ESI and EEG-fMRI reveal distinct aspects of the irritative zone. The differences may reflect differences in temporal resolution of the techniques.
Objective The irritative zone - the area generating epileptic spikes - can be studied non-invasively during the interictal period using Electrical Source Imaging (ESI) and simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI). Although the techniques yield results which may overlap spatially, differences in spatial localization of the irritative zone within the same patient are consistently observed. To investigate this discrepancy, we used Blood Oxygenation Level Dependent (BOLD) functional connectivity measures to examine the underlying relationship between ESI and EEG-fMRI findings. Methods Fifteen patients (age 20–54), who underwent presurgical epilepsy investigation, were scanned using a single-session resting-state EEG-fMRI protocol. Structural MRI was used to obtain the electrode localisation of a high-density 64-channel EEG cap. Electrical generators of interictal epileptiform discharges were obtained using a distributed local autoregressive average (LAURA) algorithm as implemented in Cartool EEG software. BOLD activations were obtained using both spike-related and voltage-map EEG-fMRI analysis. The global maxima of each method were used to investigate the temporal relationship of BOLD time courses and to assess the spatial similarity using the Dice similarity index between functional connectivity maps. Results ESI, voltage-map and spike-related EEG-fMRI methods identified peaks in 15 (100%), 13 (67%) and 8 (53%) of the 15 patients, respectively. For all methods, maxima were localised within the same lobe, but differed in sub-lobar localisation, with a median distance of 22.8 mm between the highest peak for each method. The functional connectivity analysis showed that the temporal correlation between maxima only explained 38% of the variance between the time course of the BOLD response at the maxima. The mean Dice similarity index between seed-voxel functional connectivity maps showed poor spatial agreement. Significance Non-invasive methods for the localisation of the irritative zone have distinct spatial and temporal sensitivity to different aspects of the local cortical network involved in the generation of interictal epileptiform discharges.
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Affiliation(s)
- Javier Urriola
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia
| | - Steffen Bollmann
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia; ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Australia
| | - Fred Tremayne
- Department of Neurology, Royal Brisbane and Women's Hospital, Australia
| | - Hana Burianová
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia; Department of Psychology, Bournemouth University, Bournemouth, United Kingdom
| | - Lars Marstaller
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia; Department of Psychology, Bournemouth University, Bournemouth, United Kingdom
| | - David Reutens
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia; ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Australia.
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Abdallah C, Maillard LG, Rikir E, Jonas J, Thiriaux A, Gavaret M, Bartolomei F, Colnat-Coulbois S, Vignal JP, Koessler L. Localizing value of electrical source imaging: Frontal lobe, malformations of cortical development and negative MRI related epilepsies are the best candidates. Neuroimage Clin 2017; 16:319-329. [PMID: 28856095 PMCID: PMC5565782 DOI: 10.1016/j.nicl.2017.08.009] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Revised: 07/24/2017] [Accepted: 08/07/2017] [Indexed: 11/29/2022]
Abstract
OBJECTIVE We aimed to prospectively assess the anatomical concordance of electric source localizations of interictal discharges with the epileptogenic zone (EZ) estimated by stereo-electroencephalography (SEEG) according to different subgroups: the type of epilepsy, the presence of a structural MRI lesion, the aetiology and the depth of the EZ. METHODS In a prospective multicentric observational study, we enrolled 85 consecutive patients undergoing pre-surgical SEEG investigation for focal drug-resistant epilepsy. Electric source imaging (ESI) was performed before SEEG. Source localizations were obtained from dipolar and distributed source methods. Anatomical concordance between ESI and EZ was defined according to 36 predefined sublobar regions. ESI was interpreted blinded to- and subsequently compared with SEEG estimated EZ. RESULTS 74 patients were finally analyzed. 38 patients had temporal and 36 extra-temporal lobe epilepsy. MRI was positive in 52. 41 patients had malformation of cortical development (MCD), 33 had another or an unknown aetiology. EZ was medial in 27, lateral in 13, and medio-lateral in 34. In the overall cohort, ESI completely or partly localized the EZ in 85%: full concordance in 13 cases and partial concordance in 50 cases. The rate of ESI full concordance with EZ was significantly higher in (i) frontal lobe epilepsy (46%; p = 0.05), (ii) cases of negative MRI (36%; p = 0.01) and (iii) MCD (27%; p = 0.03). The rate of ESI full concordance with EZ was not statistically different according to the depth of the EZ. SIGNIFICANCE We prospectively demonstrated that ESI more accurately estimated the EZ in subgroups of patients who are often the most difficult cases in epilepsy surgery: frontal lobe epilepsy, negative MRI and the presence of MCD.
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Affiliation(s)
- Chifaou Abdallah
- Neurology Department, University Hospital of Nancy, Nancy, France
| | - Louis G Maillard
- Neurology Department, University Hospital of Nancy, Nancy, France.,CRAN, UMR 7039, Lorraine University, Vandœuvre-les-Nancy Cedex, France.,CNRS, CRAN, UMR 7039, Vandœuvre-les-Nancy Cedex, France.,Medical Faculty, Lorraine University, Nancy, France
| | - Estelle Rikir
- Neurology Department, University Hospital of Sart-Tilman, Liege, Belgium.,Medical Faculty, Liege University, Liege, Belgium
| | - Jacques Jonas
- Neurology Department, University Hospital of Nancy, Nancy, France.,CRAN, UMR 7039, Lorraine University, Vandœuvre-les-Nancy Cedex, France.,CNRS, CRAN, UMR 7039, Vandœuvre-les-Nancy Cedex, France
| | - Anne Thiriaux
- Neurology department, University Hospital of Reims, Reims, France
| | - Martine Gavaret
- Clinical Neurophysiology Department, AP-HM, University Hospital la Timone, Marseille, France.,INSERM UMR 1106, Institut de Neurosciences des Systemes, Marseille, France.,Medical Faculty, Aix-Marseille University, Marseille, France
| | - Fabrice Bartolomei
- Clinical Neurophysiology Department, AP-HM, University Hospital la Timone, Marseille, France.,INSERM UMR 1106, Institut de Neurosciences des Systemes, Marseille, France.,Medical Faculty, Aix-Marseille University, Marseille, France
| | - Sophie Colnat-Coulbois
- Medical Faculty, Lorraine University, Nancy, France.,Neurosurgery Department, University Hospital of Nancy, Nancy, France
| | - Jean-Pierre Vignal
- Neurology Department, University Hospital of Nancy, Nancy, France.,CRAN, UMR 7039, Lorraine University, Vandœuvre-les-Nancy Cedex, France.,CNRS, CRAN, UMR 7039, Vandœuvre-les-Nancy Cedex, France
| | - Laurent Koessler
- Neurology Department, University Hospital of Nancy, Nancy, France.,CRAN, UMR 7039, Lorraine University, Vandœuvre-les-Nancy Cedex, France.,CNRS, CRAN, UMR 7039, Vandœuvre-les-Nancy Cedex, France
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9
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Cam SL, Ranta R, Caune V, Korats G, Koessler L, Maillard L, Louis-Dorr V. SEEG dipole source localization based on an empirical Bayesian approach taking into account forward model uncertainties. Neuroimage 2017; 153:1-15. [PMID: 28323161 DOI: 10.1016/j.neuroimage.2017.03.030] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2016] [Revised: 01/18/2017] [Accepted: 03/14/2017] [Indexed: 11/24/2022] Open
Abstract
Electromagnetic brain source localization consists in the inversion of a forward model based on a limited number of potential measurements. A wide range of methods has been developed to regularize this severely ill-posed problem and to reduce the solution space, imposing spatial smoothness, anatomical constraint or sparsity of the activated source map. This last criteria, based on physiological assumptions stating that in some particular events (e.g., epileptic spikes, evoked potential) few focal area of the brain are simultaneously actives, has gained more and more interest. Bayesian approaches have the ability to provide sparse solutions under adequate parametrization, and bring a convenient framework for the introduction of priors in the form of probabilistic density functions. However the quality of the forward model is rarely questioned while this parameter has undoubtedly a great influence on the solution. Its construction suffers from numerous approximation and uncertainties, even when using realistic numerical models. In addition, it often encodes a coarse sampling of the continuous solution space due to the computational burden its inversion implies. In this work we propose an empirical Bayesian approach to take into account the uncertainties of the forward model by allowing constrained variations around a prior physical model, in the particular context of SEEG measurements. We demonstrate on simulations that the method enhance the accuracy of the source time-course estimation as well as the sparsity of the resulting source map. Results on real signals prove the applicability of the method in real contexts.
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Affiliation(s)
- S Le Cam
- Université de Lorraine, CRAN, UMR 7039, 54500 Vandœuvre-lès-Nancy, France; CNRS, CRAN, UMR, 7039, France.
| | - R Ranta
- Université de Lorraine, CRAN, UMR 7039, 54500 Vandœuvre-lès-Nancy, France; CNRS, CRAN, UMR, 7039, France
| | - V Caune
- Université de Lorraine, CRAN, UMR 7039, 54500 Vandœuvre-lès-Nancy, France; CNRS, CRAN, UMR, 7039, France
| | - G Korats
- Université de Lorraine, CRAN, UMR 7039, 54500 Vandœuvre-lès-Nancy, France; CNRS, CRAN, UMR, 7039, France; Ventspils University College, 101 Inzenieruiela, LV-3601 Ventspils, Latvia
| | - L Koessler
- Université de Lorraine, CRAN, UMR 7039, 54500 Vandœuvre-lès-Nancy, France; CNRS, CRAN, UMR, 7039, France
| | - L Maillard
- Université de Lorraine, CRAN, UMR 7039, 54500 Vandœuvre-lès-Nancy, France; CNRS, CRAN, UMR, 7039, France; CHU Nancy, Neurology Department, 54000 Nancy, France
| | - V Louis-Dorr
- Université de Lorraine, CRAN, UMR 7039, 54500 Vandœuvre-lès-Nancy, France; CNRS, CRAN, UMR, 7039, France
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10
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Coito A, Plomp G, Genetti M, Abela E, Wiest R, Seeck M, Michel CM, Vulliemoz S. Dynamic directed interictal connectivity in left and right temporal lobe epilepsy. Epilepsia 2015; 56:207-17. [PMID: 25599821 DOI: 10.1111/epi.12904] [Citation(s) in RCA: 98] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/25/2014] [Indexed: 11/27/2022]
Abstract
OBJECTIVE There is increasing evidence that epileptic activity involves widespread brain networks rather than single sources and that these networks contribute to interictal brain dysfunction. We investigated the fast-varying behavior of epileptic networks during interictal spikes in right and left temporal lobe epilepsy (RTLE and LTLE) at a whole-brain scale using directed connectivity. METHODS In 16 patients, 8 with LTLE and 8 with RTLE, we estimated the electrical source activity in 82 cortical regions of interest (ROIs) using high-density electroencephalography (EEG), individual head models, and a distributed linear inverse solution. A multivariate, time-varying, and frequency-resolved Granger-causal modeling (weighted Partial Directed Coherence) was applied to the source signal of all ROIs. A nonparametric statistical test assessed differences between spike and baseline epochs. Connectivity results between RTLE and LTLE were compared between RTLE and LTLE and with neuropsychological impairments. RESULTS Ipsilateral anterior temporal structures were identified as key drivers for both groups, concordant with the epileptogenic zone estimated invasively. We observed an increase in outflow from the key driver already before the spike. There were also important temporal and extratemporal ipsilateral drivers in both conditions, and contralateral only in RTLE. A different network pattern between LTLE and RTLE was found: in RTLE there was a much more prominent ipsilateral to contralateral pattern than in LTLE. Half of the RTLE patients but none of the LTLE patients had neuropsychological deficits consistent with contralateral temporal lobe dysfunction, suggesting a relationship between connectivity changes and cognitive deficits. SIGNIFICANCE The different patterns of time-varying connectivity in LTLE and RTLE suggest that they are not symmetrical entities, in line with our neuropsychological results. The highest outflow region was concordant with invasive validation of the epileptogenic zone. This enhanced characterization of dynamic connectivity patterns could better explain cognitive deficits and help the management of epilepsy surgery candidates.
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Affiliation(s)
- Ana Coito
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
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11
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Chu CJ, Tanaka N, Diaz J, Edlow BL, Wu O, Hämäläinen M, Stufflebeam S, Cash SS, Kramer MA. EEG functional connectivity is partially predicted by underlying white matter connectivity. Neuroimage 2014; 108:23-33. [PMID: 25534110 DOI: 10.1016/j.neuroimage.2014.12.033] [Citation(s) in RCA: 72] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2014] [Revised: 12/09/2014] [Accepted: 12/11/2014] [Indexed: 01/15/2023] Open
Abstract
Over the past decade, networks have become a leading model to illustrate both the anatomical relationships (structural networks) and the coupling of dynamic physiology (functional networks) linking separate brain regions. The relationship between these two levels of description remains incompletely understood and an area of intense research interest. In particular, it is unclear how cortical currents relate to underlying brain structural architecture. In addition, although theory suggests that brain communication is highly frequency dependent, how structural connections influence overlying functional connectivity in different frequency bands has not been previously explored. Here we relate functional networks inferred from statistical associations between source imaging of EEG activity and underlying cortico-cortical structural brain connectivity determined by probabilistic white matter tractography. We evaluate spontaneous fluctuating cortical brain activity over a long time scale (minutes) and relate inferred functional networks to underlying structural connectivity for broadband signals, as well as in seven distinct frequency bands. We find that cortical networks derived from source EEG estimates partially reflect both direct and indirect underlying white matter connectivity in all frequency bands evaluated. In addition, we find that when structural support is absent, functional connectivity is significantly reduced for high frequency bands compared to low frequency bands. The association between cortical currents and underlying white matter connectivity highlights the obligatory interdependence of functional and structural networks in the human brain. The increased dependence on structural support for the coupling of higher frequency brain rhythms provides new evidence for how underlying anatomy directly shapes emergent brain dynamics at fast time scales.
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Affiliation(s)
- C J Chu
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
| | - N Tanaka
- Harvard Medical School, Boston, MA, USA; MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - J Diaz
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - B L Edlow
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - O Wu
- Harvard Medical School, Boston, MA, USA; MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - M Hämäläinen
- Harvard Medical School, Boston, MA, USA; MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - S Stufflebeam
- Harvard Medical School, Boston, MA, USA; MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - S S Cash
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - M A Kramer
- Department of Mathematics and Statistics, Boston University, Boston, MA, USA
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12
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Birot G, Spinelli L, Vulliémoz S, Mégevand P, Brunet D, Seeck M, Michel CM. Head model and electrical source imaging: a study of 38 epileptic patients. Neuroimage Clin 2014; 5:77-83. [PMID: 25003030 PMCID: PMC4081973 DOI: 10.1016/j.nicl.2014.06.005] [Citation(s) in RCA: 73] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/17/2014] [Revised: 05/28/2014] [Accepted: 06/06/2014] [Indexed: 11/18/2022]
Abstract
Electrical source imaging (ESI) aims at reconstructing the electrical brain activity from scalp EEG. When applied to interictal epileptiform discharges (IEDs), this technique is of great use for identifying the irritative zone in focal epilepsies. Inaccuracies in the modeling of electro-magnetic field propagation in the head (forward model) may strongly influence ESI and lead to mislocalization of IED generators. However, a systematic study on the influence of the selected head model on the localization precision of IED in a large number of patients with known focus localization has not yet been performed. We here present such a performance evaluation of different head models in a dataset of 38 epileptic patients who have undergone high-density scalp EEG, intracranial EEG and, for the majority, subsequent surgery. We compared ESI accuracy resulting from three head models: a Locally Spherical Model with Anatomical Constraints (LSMAC), a Boundary Element Model (BEM) and a Finite Element Model (FEM). All of them were computed from the individual MRI of the patient and ESI was performed on averaged IED. We found that all head models provided very similar source locations. In patients having a positive post-operative outcome, at least 74% of the source maxima were within the resection. The median distance from the source maximum to the nearest intracranial electrode showing IED was 13.2, 15.6 and 15.6 mm for LSMAC, BEM and FEM, respectively. The study demonstrates that in clinical applications, the use of highly sophisticated and difficult to implement head models is not a crucial factor for an accurate ESI.
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Affiliation(s)
- Gwénael Birot
- Department of Fundamental and Clinical Neurosciences, University of Geneva, Rue Michel Servet 1, 1211 Genève, Switzerland
- Corresponding author. Tel.: + 41 22 372 82 94; fax: + 41 22 372 83 40.
| | - Laurent Spinelli
- EEG and Epilepsy Unit, Department of Neurology, University Hospital of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Genève, Switzerland
| | - Serge Vulliémoz
- EEG and Epilepsy Unit, Department of Neurology, University Hospital of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Genève, Switzerland
| | - Pierre Mégevand
- EEG and Epilepsy Unit, Department of Neurology, University Hospital of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Genève, Switzerland
- Department of Neurosurgery, Hofstra North Shore-LIJ School of Medicine, Feinstein Institute for Medical Research, Manhasset, NY 11030, USA
| | - Denis Brunet
- Department of Fundamental and Clinical Neurosciences, University of Geneva, Rue Michel Servet 1, 1211 Genève, Switzerland
| | - Margitta Seeck
- EEG and Epilepsy Unit, Department of Neurology, University Hospital of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Genève, Switzerland
| | - Christoph M. Michel
- Department of Fundamental and Clinical Neurosciences, University of Geneva, Rue Michel Servet 1, 1211 Genève, Switzerland
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13
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Caune V, Ranta R, Le Cam S, Hofmanis J, Maillard L, Koessler L, Louis-Dorr V. Evaluating dipolar source localization feasibility from intracerebral SEEG recordings. Neuroimage 2014; 98:118-33. [PMID: 24795155 DOI: 10.1016/j.neuroimage.2014.04.058] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2013] [Revised: 03/26/2014] [Accepted: 04/22/2014] [Indexed: 11/23/2022] Open
Abstract
Stereo-electroencephalography (SEEG) is considered as the golden standard for exploring targeted structures during pre-surgical evaluation in drug-resistant partial epilepsy. The depth electrodes, inserted in the brain, consist of several collinear measuring contacts (sensors). Clinical routine analysis of SEEG signals is performed on bipolar montage, providing a focal view of the explored structures, thus eliminating activities of distant sources that propagate through the brain volume. We propose in this paper to exploit the common reference SEEG signals. In this case, the volume propagation information is preserved and electrical source localization (ESL) approaches can be proposed. Current ESL approaches used to localize and estimate the activity of the neural generators are mainly based on surface EEG/MEG signals, but very few studies exist on real SEEG recordings, and the case of equivalent current dipole source localization has not been explored yet in this context. In this study, we investigate the influence of volume conduction model, spatial configuration of SEEG sensors and level of noise on the ESL accuracy, using a realistic simulation setup. Localizations on real SEEG signals recorded during intracerebral electrical stimulations (ICS, known sources) as well as on epileptic interictal spikes are carried out. Our results show that, under certain conditions, a straightforward approach based on an equivalent current dipole model for the source and on simple analytical volume conduction models yields sufficiently precise solutions (below 10mm) of the localization problem. Thus, electrical source imaging using SEEG signals is a promising tool for distant brain source investigation and might be used as a complement to routine visual interpretations.
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Avanzini P, Vaudano AE, Vignoli A, Ruggieri A, Benuzzi F, Darra F, Mastrangelo M, Dalla Bernardina B, Nichelli PF, Canevini MP, Meletti S. Low frequency mu-like activity characterizes cortical rhythms in epilepsy due to ring chromosome 20. Clin Neurophysiol 2013; 125:239-49. [PMID: 23968845 DOI: 10.1016/j.clinph.2013.07.009] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2013] [Revised: 05/22/2013] [Accepted: 07/24/2013] [Indexed: 12/22/2022]
Abstract
OBJECTIVES To evaluate the spectral and spatial features of the cortical rhythms in patients affected by ring chromosome 20 - [r(20)]-syndrome. METHODS Twelve patients with [r(20)] syndrome were studied. As controls we enrolled 12 patients with idiopathic generalized epilepsy (IGE) and 12 healthy volunteers (HV). Blind source separation, spectral analyses and source reconstruction were applied in all cases in order to identify reliable spatio-temporal patterns of cortical activity. RESULTS A theta-delta EEG rhythm was identified in [r(20)] patients, with spectral peak ranging between 3 and 7Hz and whose generators mapped over the sensory-motor cortices. A second peak laying at a frequency about double with respect to the first one was present in 6 cases. Analogue methodological approach in HV and IGE groups failed to show similar findings. CONCLUSIONS EEG of [r(20)] patients reveals the existence of a highly reproducible EEG pattern arising from the sensory-motor system. SIGNIFICANCE The recognition of this peculiar EEG pattern could help the diagnostic work-up. Additionally, our findings supports the existence of a parallelism between this EEG trait and the physiological "mu" rhythm which is generate by the sensory-motor system. Such link suggests a sensory-motor system dysfunction in [r(20)] patients.
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Affiliation(s)
- Pietro Avanzini
- Department of Biomedical Sciences, Metabolism and Neuroscience, University of Modena and Reggio Emilia, NOCSE Hospital, Modena, Italy; Department di Neuroscience, University of Parma, Parma, Italy
| | - Anna Elisabetta Vaudano
- Department of Biomedical Sciences, Metabolism and Neuroscience, University of Modena and Reggio Emilia, NOCSE Hospital, Modena, Italy
| | - Aglaia Vignoli
- Epilepsy Centre, San Paolo Hospital, Health Science Department, University of Milano, Italy
| | - Andrea Ruggieri
- Department of Biomedical Sciences, Metabolism and Neuroscience, University of Modena and Reggio Emilia, NOCSE Hospital, Modena, Italy
| | - Francesca Benuzzi
- Department of Biomedical Sciences, Metabolism and Neuroscience, University of Modena and Reggio Emilia, NOCSE Hospital, Modena, Italy
| | - Francesca Darra
- Department of Life and Reproduction Sciences, University of Verona, Verona, Italy
| | | | | | - Paolo Frigio Nichelli
- Department of Biomedical Sciences, Metabolism and Neuroscience, University of Modena and Reggio Emilia, NOCSE Hospital, Modena, Italy
| | - Maria Paola Canevini
- Epilepsy Centre, San Paolo Hospital, Health Science Department, University of Milano, Italy; Department of Medicine, Surgery and Dentistry, Faculty of Medicine and Surgery, University of Milano, Milano, Italy
| | - Stefano Meletti
- Department of Biomedical Sciences, Metabolism and Neuroscience, University of Modena and Reggio Emilia, NOCSE Hospital, Modena, Italy.
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