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Ye S, Bagić A, He B. Disentanglement of Resting State Brain Networks for Localizing Epileptogenic Zone in Focal Epilepsy. Brain Topogr 2024; 37:152-168. [PMID: 38112884 PMCID: PMC10771380 DOI: 10.1007/s10548-023-01025-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 11/20/2023] [Indexed: 12/21/2023]
Abstract
The objective of this study is to extract pathological brain networks from interictal period of E/MEG recordings to localize epileptic foci for presurgical evaluation. We proposed here a resting state E/MEG analysis framework, to disentangle brain functional networks represented by neural oscillations. By using an Embedded Hidden Markov Model, we constructed a state space for resting state recordings consisting of brain states with different spatiotemporal patterns. Functional connectivity analysis along with graph theory was applied on the extracted brain states to quantify the network features of the extracted brain states, based on which the source location of pathological states is determined. The method is evaluated by computer simulations and our simulation results revealed the proposed framework can extract brain states with high accuracy regarding both spatial and temporal profiles. We further evaluated the framework as compared with intracranial EEG defined seizure onset zone in 10 patients with drug-resistant focal epilepsy who underwent MEG recordings and were seizure free after surgical resection. The real patient data analysis showed very good localization results using the extracted pathological brain states in 6/10 patients, with localization error of about 15 mm as compared to the seizure onset zone. We show that the pathological brain networks can be disentangled from the resting-state electromagnetic recording and could be identified based on the connectivity features. The framework can serve as a useful tool in extracting brain functional networks from noninvasive resting state electromagnetic recordings, and promises to offer an alternative to aid presurgical evaluation guiding intracranial EEG electrodes implantation.
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Affiliation(s)
- Shuai Ye
- Department of Biomedical Engineering, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA, 15213, USA
| | - Anto Bagić
- Department of Neurology, University of Pittsburgh Comprehensive Epilepsy Center (UPCEC), University of Pittsburgh Medical School, Pittsburgh, PA, USA
| | - Bin He
- Department of Biomedical Engineering, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA, 15213, USA.
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2
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Foldes ST, Chandrasekaran S, Camerone J, Lowe J, Ramdeo R, Ebersole J, Bouton CE. Case Study: Mapping Evoked Fields in Primary Motor and Sensory Areas via Magnetoencephalography in Tetraplegia. Front Neurol 2021; 12:739693. [PMID: 34630308 PMCID: PMC8497881 DOI: 10.3389/fneur.2021.739693] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 08/13/2021] [Indexed: 12/02/2022] Open
Abstract
Devices interfacing with the brain through implantation in cortical or subcortical structures have great potential for restoration and rehabilitation in patients with sensory or motor dysfunction. Typical implantation surgeries are planned based on maps of brain activity generated from intact function. However, mapping brain activity for planning implantation surgeries is challenging in the target population due to abnormal residual function and, increasingly often, existing MRI-incompatible implanted hardware. Here, we present methods and results for mapping impaired somatosensory and motor function in an individual with paralysis and an existing brain–computer interface (BCI) device. Magnetoencephalography (MEG) was used to directly map the neural activity evoked during transcutaneous electrical stimulation and attempted movement of the impaired hand. Evoked fields were found to align with the expected anatomy and somatotopic organization. This approach may be valuable for guiding implants in other applications, such as cortical stimulation for pain and to improve implant targeting to help reduce the craniotomy size.
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Affiliation(s)
- Stephen T Foldes
- Department of Neurology, Barrow Neurological Institute, Phoenix, AZ, United States
| | - Santosh Chandrasekaran
- Neural Bypass and Brain-Computer Interface Laboratory, Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research at Northwell Health, New York, NY, United States
| | - Joseph Camerone
- MEG Center, Overlook Medical Center, Atlantic Health, Summit, NJ, United States
| | - James Lowe
- MEG Center, Overlook Medical Center, Atlantic Health, Summit, NJ, United States
| | - Richard Ramdeo
- Neural Bypass and Brain-Computer Interface Laboratory, Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research at Northwell Health, New York, NY, United States
| | - John Ebersole
- MEG Center, Overlook Medical Center, Atlantic Health, Summit, NJ, United States
| | - Chad E Bouton
- Neural Bypass and Brain-Computer Interface Laboratory, Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research at Northwell Health, New York, NY, United States.,Department of Molecular Medicine, Hofstra-Northwell Medical School, New York, NY, United States
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3
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Pellegrino G, Xu M, Alkuwaiti A, Porras-Bettancourt M, Abbas G, Lina JM, Grova C, Kobayashi E. Effects of Independent Component Analysis on Magnetoencephalography Source Localization in Pre-surgical Frontal Lobe Epilepsy Patients. Front Neurol 2020; 11:479. [PMID: 32582009 PMCID: PMC7280485 DOI: 10.3389/fneur.2020.00479] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Accepted: 05/01/2020] [Indexed: 01/18/2023] Open
Abstract
Objective: Magnetoencephalography source imaging (MSI) of interictal epileptiform discharges (IED) is a useful presurgical tool in the evaluation of drug-resistant frontal lobe epilepsy (FLE) patients. Yet, failures in MSI can arise related to artifacts and to interference of background activity. Independent component analysis (ICA) is a popular denoising procedure but its clinical application remains challenging, as the selection of multiple independent components (IC) is controversial, operator dependent, and time consuming. We evaluated whether selecting only one IC of interest based on its similarity with the average IED field improves MSI in FLE. Methods: MSI was performed with the equivalent current dipole (ECD) technique and two distributed magnetic source imaging (dMSI) approaches: minimum norm estimate (MNE) and coherent Maximum Entropy on the Mean (cMEM). MSI accuracy was evaluated under three conditions: (1) ICA of continuous data (Cont_ICA), (2) ICA at the time of IED (IED_ICA), and (3) without ICA (No_ICA). Localization performance was quantitatively measured as actual distance of the source maximum in relation to the focus (Dmin), and spatial dispersion (SD) for dMSI. Results: After ICA, ECD Dmin did not change significantly (p > 0.200). For both dMSI techniques, ICA application worsened the source localization accuracy. We observed a worsening of both MNE Dmin (p < 0.05, consistently) and MNE SD (p < 0.001, consistently) for both ICA approaches. A similar behaviour was observed for cMEM, for which, however, Cont_ICA seemed less detrimental. Conclusion: We demonstrated that a simplified ICA approach selecting one IC of interest in combination with distributed magnetic source imaging can be detrimental. More complex approaches may provide better results but would be rather difficult to apply in real-world clinical setting. In a broader perspective, caution should be taken in applying ICA for source localization of interictal activity. To ensure optimal and useful results, effort should focus on acquiring good quality data, minimizing artifacts, and determining optimal candidacy for MEG, rather than counting on data cleaning techniques.
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Affiliation(s)
- Giovanni Pellegrino
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Min Xu
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, QC, Canada.,Department of Geriatrics, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Abdulla Alkuwaiti
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Manuel Porras-Bettancourt
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Ghada Abbas
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Jean-Marc Lina
- Multimodal Functional Imaging Laboratory, Biomedical Engineering Department, McGill University, Montreal, QC, Canada.,Département de Génie Électrique, École de Technologie Supérieure, Montreal, QC, Canada.,Centre de Recherches Mathematiques, Univeristé de Montréal, Montreal, QC, Canada
| | - Christophe Grova
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, QC, Canada.,Multimodal Functional Imaging Laboratory, Biomedical Engineering Department, McGill University, Montreal, QC, Canada.,Département de Génie Électrique, École de Technologie Supérieure, Montreal, QC, Canada.,Physics Department and PERFORM Centre, Concordia University, Montreal, QC, Canada
| | - Eliane Kobayashi
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
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4
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Pellegrino G, Hedrich T, Porras-Bettancourt M, Lina JM, Aydin Ü, Hall J, Grova C, Kobayashi E. Accuracy and spatial properties of distributed magnetic source imaging techniques in the investigation of focal epilepsy patients. Hum Brain Mapp 2020; 41:3019-3033. [PMID: 32386115 PMCID: PMC7336148 DOI: 10.1002/hbm.24994] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Revised: 02/18/2020] [Accepted: 03/11/2020] [Indexed: 02/03/2023] Open
Abstract
Source localization of interictal epileptiform discharges (IEDs) is clinically useful in the presurgical workup of epilepsy patients. We aimed to compare the performance of four different distributed magnetic source imaging (dMSI) approaches: Minimum norm estimate (MNE), dynamic statistical parametric mapping (dSPM), standardized low-resolution electromagnetic tomography (sLORETA), and coherent maximum entropy on the mean (cMEM). We also evaluated whether a simple average of maps obtained from multiple inverse solutions (Ave) can improve localization accuracy. We analyzed dMSI of 206 IEDs derived from magnetoencephalography recordings in 28 focal epilepsy patients who had a well-defined focus determined through intracranial EEG (iEEG), epileptogenic MRI lesions or surgical resection. dMSI accuracy and spatial properties were quantitatively estimated as: (a) distance from the epilepsy focus, (b) reproducibility, (c) spatial dispersion (SD), (d) map extension, and (e) effect of thresholding on map properties. Clinical performance was excellent for all methods (median distance from the focus MNE = 2.4 mm; sLORETA = 3.5 mm; cMEM = 3.5 mm; dSPM = 6.8 mm, Ave = 0 mm). Ave showed the lowest distance between the map maximum and epilepsy focus (Dmin lower than cMEM, MNE, and dSPM, p = .021, p = .008, p < .001, respectively). cMEM showed the best spatial features, with lowest SD outside the focus (SD lower than all other methods, p < .001 consistently) and high contrast between the generator and surrounding regions. The average map Ave provided the best localization accuracy, whereas cMEM exhibited the lowest amount of spurious distant activity. dMSI techniques have the potential to significantly improve identification of iEEG targets and to guide surgical planning, especially when multiple methods are combined.
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Affiliation(s)
- Giovanni Pellegrino
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.,IRCCS Fondazione San Camillo Hospital, Venice, Italy.,Department of Multimodal Functional Imaging Lab, Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - Tanguy Hedrich
- Department of Multimodal Functional Imaging Lab, Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - Manuel Porras-Bettancourt
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Jean-Marc Lina
- Departement de Genie Electrique, Ecole de Technologie Superieure, Montreal, Quebec, Canada.,Centre de Recherches Mathematiques, Montréal, Quebec, Canada
| | - Ümit Aydin
- Physics Department and PERFORM Centre, Concordia University, Montreal, Quebec, Canada
| | - Jeffery Hall
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Christophe Grova
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.,Department of Multimodal Functional Imaging Lab, Biomedical Engineering, McGill University, Montreal, Quebec, Canada.,Centre de Recherches Mathematiques, Montréal, Quebec, Canada.,Physics Department and PERFORM Centre, Concordia University, Montreal, Quebec, Canada
| | - Eliane Kobayashi
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
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Chang WS, Nakajima M, Ochi A, Widjaja E, Rutka JT, Yau I, Baba S, Otsubo H. Detection of epileptogenic focus using advanced dynamic statistical parametric mapping with magnetoencephalography in a patient with MRI-negative focal cortical dysplasia type IIB. J Neurosurg Pediatr 2019; 25:78-82. [PMID: 31604322 DOI: 10.3171/2019.7.peds1948] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2019] [Accepted: 07/16/2019] [Indexed: 11/06/2022]
Abstract
Advanced dynamic statistical parametric mapping (AdSPM) with magnetoencephalography (MEG) was used to identify MRI-negative epileptogenic lesions in this report. A 15-year-old girl had MRI-negative and pharmacology-resistant focal-onset epilepsy. She experienced two types of seizures. Type I consisted of her arousal from sleep, staring, and a forced head-turning movement to the left, followed by secondary generalization. Type II began with an aura of dizziness followed by staring and postictal headache with fatigue. Scalp video-electroencephalography (EEG) captured two type I seizures originating from the right frontocentral region. MEG showed scattered dipoles over the right frontal region. AdSPM identified the spike source at the bottom of the right inferior frontal sulcus. Intracranial video-EEG captured one type I seizure, which originated from the depth electrode at the bottom of the sulcus and correlated with the AdSPM spike source. Accordingly, the patient underwent resection of the middle and inferior frontal gyri, including the AdSPM-identified spike source. Histopathological examination revealed that the patient had focal cortical dysplasia type IIB. To date, the patient has been seizure free for 2 years while receiving topiramate treatment. This is the first preliminary report to identify MRI-negative epilepsy using AdSPM. Further investigation of AdSPM would be valuable for cases of MRI-negative focal epilepsy.
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Affiliation(s)
- Won Seok Chang
- 1Division of Neurology, Hospital for Sick Children, Toronto, Ontario, Canada
- 2Department of Neurosurgery, Brain Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea; and
| | - Midori Nakajima
- 1Division of Neurology, Hospital for Sick Children, Toronto, Ontario, Canada
| | - Ayako Ochi
- 1Division of Neurology, Hospital for Sick Children, Toronto, Ontario, Canada
| | | | - James T Rutka
- 4Division of Neurosurgery, Hospital for Sick Children, Toronto, Ontario, Canada
| | - Ivanna Yau
- 1Division of Neurology, Hospital for Sick Children, Toronto, Ontario, Canada
| | - Shiro Baba
- 1Division of Neurology, Hospital for Sick Children, Toronto, Ontario, Canada
| | - Hiroshi Otsubo
- 1Division of Neurology, Hospital for Sick Children, Toronto, Ontario, Canada
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Tomlinson SB, Wong JN, Conrad EC, Kennedy BC, Marsh ED. Reproducibility of interictal spike propagation in children with refractory epilepsy. Epilepsia 2019; 60:898-910. [PMID: 31006860 PMCID: PMC6488404 DOI: 10.1111/epi.14720] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2019] [Revised: 02/11/2019] [Accepted: 03/13/2019] [Indexed: 01/03/2023]
Abstract
OBJECTIVE Interictal spikes are a characteristic feature of invasive electroencephalography (EEG) recordings in children with refractory epilepsy. Spikes frequently co-occur across multiple brain regions with discernable latencies, suggesting that spikes can propagate through distributed neural networks. The purpose of this study was to examine the long-term reproducibility of spike propagation patterns over hours to days of interictal recording. METHODS Twelve children (mean age 13.1 years) were retrospectively studied. A mean ± standard deviation (SD) of 47.2 ± 40.1 hours of interictal EEG recordings were examined per patient (range 17.5-166.5 hours). Interictal recordings were divided into 30-minute segments. Networks were extracted based on the frequency of spike coactivation between pairs of electrodes. For each 30-minute segment, electrodes were assigned a "Degree Preference (DP)" based on the tendency to appear upstream or downstream within propagation sequences. The consistency of DPs across segments ("DP-Stability") was quantified using the Spearman rank correlation. RESULTS Regions exhibited highly stable preferences to appear upstream, intermediate, or downstream in spike propagation sequences. Across networks, the mean ± SD DP-Stability was 0.88 ± 0.07, indicating that propagation patterns observed in 30-minute segments were representative of the patterns observed in the full interictal window. At the group level, regions involved in seizure generation appeared more upstream in spike propagation sequences. SIGNIFICANCE Interictal spike propagation is a highly reproducible output of epileptic networks. These findings shed new light on the spatiotemporal dynamics that may constrain the network mechanisms of refractory epilepsy.
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Affiliation(s)
- Samuel B. Tomlinson
- Division of Neurosurgery, Children’s Hospital of Philadelphia, Philadelphia, PA
- School of Medicine and Dentistry, University of Rochester Medical Center, Rochester, NY
| | - Jeremy N. Wong
- Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA
| | - Erin C. Conrad
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA
| | - Benjamin C. Kennedy
- Division of Neurosurgery, Children’s Hospital of Philadelphia, Philadelphia, PA
| | - Eric D. Marsh
- Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA
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7
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Ishizaki T, Maesawa S, Nakatsubo D, Yamamoto H, Shibata M, Kato S, Yoshida M, Natsume J, Hoshiyama M, Wakabayashi T. Anatomo-electro-clinical correlations of hypermotor seizures with amygdala enlargement: Hippocampal seizure origin identified using stereoelectroencephalography. EPILEPSY & BEHAVIOR CASE REPORTS 2018; 11:10-13. [PMID: 30591881 PMCID: PMC6305660 DOI: 10.1016/j.ebcr.2018.09.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/07/2018] [Revised: 09/23/2018] [Accepted: 09/26/2018] [Indexed: 12/02/2022]
Abstract
A drug-resistant epilepsy case showed hypermotor seizures and amygdala enlargement. Seizure onset zone was the hippocampus, not amygdala, as revealed by SEEG. The enlarged amygdala pathology was classified as FCD type I. Selective amygdalohippocampectomy led to good outcomes.
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Key Words
- AE, amygdala enlargement
- AEC, anatomo-electro-clinical correlation
- EEG, electroencephalography/electroencephalogram
- FCD, focal cortical dysplasia
- FLE, frontal lobe epilepsy
- HS, hippocampal sclerosis
- MEG, magnetoencephalography
- MTLE, mesial temporal lobe epilepsy
- SEEG, stereoelectroencephalography
- TLE, temporal lobe epilepsy
- VEEG, video-EEG
- iEEG, intracranial EEG
- sLORETA, standardized low-resolution brain electromagnetic tomography analysis
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Affiliation(s)
- Tomotaka Ishizaki
- Department of Neurosurgery, Nagoya University Graduate School of Medicine, 65 Tsurumai, Showa, Nagoya, Aichi 466-8550, Japan
| | - Satoshi Maesawa
- Department of Neurosurgery, Nagoya University Graduate School of Medicine, 65 Tsurumai, Showa, Nagoya, Aichi 466-8550, Japan.,Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan
| | - Daisuke Nakatsubo
- Department of Neurosurgery, Nagoya University Graduate School of Medicine, 65 Tsurumai, Showa, Nagoya, Aichi 466-8550, Japan.,Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan
| | - Hiroyuki Yamamoto
- Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan.,Department of Pediatrics, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Masashi Shibata
- Department of Neurosurgery, Nagoya University Graduate School of Medicine, 65 Tsurumai, Showa, Nagoya, Aichi 466-8550, Japan
| | - Sachiko Kato
- Department of Neurosurgery, Nagoya University Graduate School of Medicine, 65 Tsurumai, Showa, Nagoya, Aichi 466-8550, Japan
| | - Mari Yoshida
- Department of Neuropathology, Institute for Medical Science of Aging, Aichi Medical University, Aichi-gun, 1-1 Yazakokarimata, Nagakute, Aichi 480-1195, Japan
| | - Jun Natsume
- Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan.,Department of Pediatrics, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Minoru Hoshiyama
- Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan
| | - Toshihiko Wakabayashi
- Department of Neurosurgery, Nagoya University Graduate School of Medicine, 65 Tsurumai, Showa, Nagoya, Aichi 466-8550, Japan
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Magnetoencephalographic Mapping of Epileptic Spike Population Using Distributed Source Analysis: Comparison With Intracranial Electroencephalographic Spikes. J Clin Neurophysiol 2018; 35:339-345. [PMID: 29746391 DOI: 10.1097/wnp.0000000000000476] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
INTRODUCTION This study evaluates magnetoencephalographic (MEG) spike population as compared with intracranial electroencephalographic (IEEG) spikes using a quantitative method based on distributed source analysis. METHODS We retrospectively studied eight patients with medically intractable epilepsy who had an MEG and subsequent IEEG monitoring. Fifty MEG spikes were analyzed in each patient using minimum norm estimate. For individual spikes, each vertex in the source space was considered activated when its source amplitude at the peak latency was higher than a threshold, which was set at 50% of the maximum amplitude over all vertices. We mapped the total count of activation at each vertex. We also analyzed 50 IEEG spikes in the same manner over the intracranial electrodes and created the activation count map. The location of the electrodes was obtained in the MEG source space by coregistering postimplantation computed tomography to MRI. We estimated the MEG- and IEEG-active regions associated with the spike populations using the vertices/electrodes with a count over 25. RESULTS The activation count maps of MEG spikes demonstrated the localization associated with the spike population by variable count values at each vertex. The MEG-active region overlapped with 65 to 85% of the IEEG-active region in our patient group. CONCLUSIONS Mapping the MEG spike population is valid for demonstrating the trend of spikes clustering in patients with epilepsy. In addition, comparison of MEG and IEEG spikes quantitatively may be informative for understanding their relationship.
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Pellegrino G, Hedrich T, Chowdhury RA, Hall JA, Dubeau F, Lina JM, Kobayashi E, Grova C. Clinical yield of magnetoencephalography distributed source imaging in epilepsy: A comparison with equivalent current dipole method. Hum Brain Mapp 2017; 39:218-231. [PMID: 29024165 DOI: 10.1002/hbm.23837] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2017] [Revised: 08/25/2017] [Accepted: 09/25/2017] [Indexed: 01/03/2023] Open
Abstract
OBJECTIVE Source localization of interictal epileptic discharges (IEDs) is clinically useful in the presurgical workup of epilepsy patients. It is usually obtained by equivalent current dipole (ECD) which localizes a point source and is the only inverse solution approved by clinical guidelines. In contrast, magnetic source imaging using distributed methods (dMSI) provides maps of the location and the extent of the generators, but its yield has not been clinically validated. We systematically compared ECD versus dMSI performed using coherent Maximum Entropy on the Mean (cMEM), a method sensitive to the spatial extent of the generators. METHODS 340 source localizations of IEDs derived from 49 focal epilepsy patients with foci well-defined through intracranial EEG, MRI lesions, and surgery were analyzed. The comparison was based on the assessment of the sublobar concordance with the focus and of the distance between the source and the focus. RESULTS dMSI sublobar concordance was significantly higher than ECD (81% vs 69%, P < 0.001), especially for extratemporal lobe sources (dMSI = 84%; ECD = 67%, P < 0.001) and for seizure free patients (dMSI = 83%; ECD = 70%, P < 0.001). The median distance from the focus was 4.88 mm for ECD and 3.44 mm for dMSI (P < 0.001). ECD dipoles were often wrongly localized in deep brain regions. CONCLUSIONS dMSI using cMEM exhibited better accuracy. dMSI also offered the advantage of recovering more realistic maps of the generator, which could be exploited for neuronavigation aimed at targeting invasive EEG and surgical resection. Therefore, dMSI may be preferred to ECD in clinical practice. Hum Brain Mapp 39:218-231, 2018. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Giovanni Pellegrino
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montreal, Quebec, Canada.,Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.,IRCCS Fondazione San Camillo Hospital, Venice, Italy
| | - Tanguy Hedrich
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montreal, Quebec, Canada
| | - Rasheda Arman Chowdhury
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montreal, Quebec, Canada
| | - Jeffery A Hall
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Francois Dubeau
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Jean-Marc Lina
- Departement de Génie Electrique, Ecole de Technologie Supérieure, Montreal, Quebec, Canada.,Centre De Recherches En Mathématiques, Montreal, Quebec, Canada.,Centre D'études Avancées En Médecine Du Sommeil, Centre De Recherche De L'hôpital Sacré-Coeur De Montréal, Montreal, Quebec, Canada
| | - Eliane Kobayashi
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Christophe Grova
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montreal, Quebec, Canada.,Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.,Centre De Recherches En Mathématiques, Montreal, Quebec, Canada.,Physics Department and PERFORM Centre, Concordia University, Montreal, Quebec, Canada
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10
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Exploring the Epileptic Brain Network Using Time-Variant Effective Connectivity and Graph Theory. IEEE J Biomed Health Inform 2017; 21:1411-1421. [DOI: 10.1109/jbhi.2016.2607802] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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11
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Tomlinson SB, Bermudez C, Conley C, Brown MW, Porter BE, Marsh ED. Spatiotemporal Mapping of Interictal Spike Propagation: A Novel Methodology Applied to Pediatric Intracranial EEG Recordings. Front Neurol 2016; 7:229. [PMID: 28066315 PMCID: PMC5165024 DOI: 10.3389/fneur.2016.00229] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2016] [Accepted: 11/30/2016] [Indexed: 12/19/2022] Open
Abstract
Synchronized cortical activity is implicated in both normative cognitive functioning and many neurologic disorders. For epilepsy patients with intractable seizures, irregular synchronization within the epileptogenic zone (EZ) is believed to provide the network substrate through which seizures initiate and propagate. Mapping the EZ prior to epilepsy surgery is critical for detecting seizure networks in order to achieve postsurgical seizure control. However, automated techniques for characterizing epileptic networks have yet to gain traction in the clinical setting. Recent advances in signal processing and spike detection have made it possible to examine the spatiotemporal propagation of interictal spike discharges across the epileptic cortex. In this study, we present a novel methodology for detecting, extracting, and visualizing spike propagation and demonstrate its potential utility as a biomarker for the EZ. Eighteen presurgical intracranial EEG recordings were obtained from pediatric patients ultimately experiencing favorable (i.e., seizure-free, n = 9) or unfavorable (i.e., seizure-persistent, n = 9) surgical outcomes. Novel algorithms were applied to extract multichannel spike discharges and visualize their spatiotemporal propagation. Quantitative analysis of spike propagation was performed using trajectory clustering and spatial autocorrelation techniques. Comparison of interictal propagation patterns revealed an increase in trajectory organization (i.e., spatial autocorrelation) among Sz-Free patients compared with Sz-Persist patients. The pathophysiological basis and clinical implications of these findings are considered.
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Affiliation(s)
- Samuel B Tomlinson
- Department of Pediatrics, Division of Child Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA; School of Medicine and Dentistry, University of Rochester Medical Center, Rochester, NY, USA
| | - Camilo Bermudez
- Department of Pediatrics, Division of Child Neurology, Children's Hospital of Philadelphia , Philadelphia, PA , USA
| | - Chiara Conley
- Department of Pediatrics, Division of Child Neurology, Children's Hospital of Philadelphia , Philadelphia, PA , USA
| | - Merritt W Brown
- Department of Pediatrics, Division of Child Neurology, Children's Hospital of Philadelphia , Philadelphia, PA , USA
| | - Brenda E Porter
- Department of Neurology and Neurological Science, Stanford School of Medicine , Palo Alto, CA , USA
| | - Eric D Marsh
- Department of Pediatrics, Division of Child Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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Wilson TW, Heinrichs-Graham E, Proskovec AL, McDermott TJ. Neuroimaging with magnetoencephalography: A dynamic view of brain pathophysiology. Transl Res 2016; 175:17-36. [PMID: 26874219 PMCID: PMC4959997 DOI: 10.1016/j.trsl.2016.01.007] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2015] [Revised: 01/15/2016] [Accepted: 01/18/2016] [Indexed: 01/12/2023]
Abstract
Magnetoencephalography (MEG) is a noninvasive, silent, and totally passive neurophysiological imaging method with excellent temporal resolution (∼1 ms) and good spatial precision (∼3-5 mm). In a typical experiment, MEG data are acquired as healthy controls or patients with neurologic or psychiatric disorders perform a specific cognitive task, or receive sensory stimulation. The resulting data are generally analyzed using standard electrophysiological methods, coupled with advanced image reconstruction algorithms. To date, the total number of MEG instruments and associated users is significantly smaller than comparable human neuroimaging techniques, although this is likely to change in the near future with advances in the technology. Despite this small base, MEG research has made a significant impact on several areas of translational neuroscience, largely through its unique capacity to quantify the oscillatory dynamics of activated brain circuits in humans. This review focuses on the clinical areas where MEG imaging has arguably had the greatest impact in regard to the identification of aberrant neural dynamics at the regional and network level, monitoring of disease progression, determining how efficacious pharmacologic and behavioral interventions modulate neural systems, and the development of neural markers of disease. Specifically, this review covers recent advances in understanding the abnormal neural oscillatory dynamics that underlie Parkinson's disease, autism spectrum disorders, human immunodeficiency virus (HIV)-associated neurocognitive disorders, cerebral palsy, attention-deficit hyperactivity disorder, cognitive aging, and post-traumatic stress disorder. MEG imaging has had a major impact on how clinical neuroscientists understand the brain basis of these disorders, and its translational influence is rapidly expanding with new discoveries and applications emerging continuously.
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Affiliation(s)
- Tony W Wilson
- Department of Pharmacology and Experimental Neuroscience, University of Nebraska Medical Center (UNMC), Omaha, Neb; Center for Magnetoencephalography, UNMC, Omaha, Neb; Department of Neurological Sciences, UNMC, Omaha, Neb.
| | - Elizabeth Heinrichs-Graham
- Department of Pharmacology and Experimental Neuroscience, University of Nebraska Medical Center (UNMC), Omaha, Neb; Center for Magnetoencephalography, UNMC, Omaha, Neb
| | - Amy L Proskovec
- Center for Magnetoencephalography, UNMC, Omaha, Neb; Department of Psychology, University of Nebraska - Omaha, Neb
| | - Timothy J McDermott
- Department of Pharmacology and Experimental Neuroscience, University of Nebraska Medical Center (UNMC), Omaha, Neb; Center for Magnetoencephalography, UNMC, Omaha, Neb
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Hamandi K, Routley BC, Koelewijn L, Singh KD. Non-invasive brain mapping in epilepsy: Applications from magnetoencephalography. J Neurosci Methods 2015; 260:283-91. [PMID: 26642968 DOI: 10.1016/j.jneumeth.2015.11.012] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2015] [Revised: 11/17/2015] [Accepted: 11/18/2015] [Indexed: 01/11/2023]
Abstract
BACKGROUND Non-invasive in vivo neurophysiological recordings with EEG/MEG are key to the diagnosis, classification, and further understanding of epilepsy. Historically the emphasis of these recordings has been the localisation of the putative sources of epileptic discharges. More recent developments see new techniques studying oscillatory dynamics, connectivity and network properties. NEW METHOD New analysis strategies for whole head MEG include the development of spatial filters or beamformers for source localisation, time-frequency analysis for cortical dynamics and graph theory applications for connectivity. RESULTS The idea of epilepsy as a network disorder is not new, and new applications of structural and functional brain imaging show differences in cortical and subcortical networks in patients with epilepsy compared to controls. Concepts of 'focal' and 'generalised' are challenged by evidence of focal onsets in generalised epileptic discharges, and widespread network changes in focal epilepsy. Spectral analyses can show differences in induced cortical response profiles, particularly in photosensitive epilepsy. COMPARISON WITH EXISTING METHOD This review focuses on the application of MEG in the study of epilepsy, starting with a brief historical perspective, followed by novel applications of source localisation, time-frequency and connectivity analyses. CONCLUSION Novel MEG analyses approaches show altered cortical dynamics and widespread network alterations in focal and generalised epilepsies, and identification of regional network abnormalities may have a role in epilepsy surgery evaluation.
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Affiliation(s)
- Khalid Hamandi
- The Alan Richens Welsh Epilepsy Centre, University Hospital of Wales, Cardiff CF5 6LR, United Kingdom.
| | - Bethany C Routley
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff CF10 3AT, United Kingdom
| | - Loes Koelewijn
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff CF10 3AT, United Kingdom
| | - Krish D Singh
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff CF10 3AT, United Kingdom
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Shen HM, Lee KM, Hu L, Foong S, Fu X. Effects of reconstructed magnetic field from sparse noisy boundary measurements on localization of active neural source. Med Biol Eng Comput 2015; 54:177-89. [PMID: 26358243 DOI: 10.1007/s11517-015-1381-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2014] [Accepted: 08/22/2015] [Indexed: 10/23/2022]
Abstract
Localization of active neural source (ANS) from measurements on head surface is vital in magnetoencephalography. As neuron-generated magnetic fields are extremely weak, significant uncertainties caused by stochastic measurement interference complicate its localization. This paper presents a novel computational method based on reconstructed magnetic field from sparse noisy measurements for enhanced ANS localization by suppressing effects of unrelated noise. In this approach, the magnetic flux density (MFD) in the nearby current-free space outside the head is reconstructed from measurements through formulating the infinite series solution of the Laplace's equation, where boundary condition (BC) integrals over the entire measurements provide "smooth" reconstructed MFD with the decrease in unrelated noise. Using a gradient-based method, reconstructed MFDs with good fidelity are selected for enhanced ANS localization. The reconstruction model, spatial interpolation of BC, parametric equivalent current dipole-based inverse estimation algorithm using reconstruction, and gradient-based selection are detailed and validated. The influences of various source depths and measurement signal-to-noise ratio levels on the estimated ANS location are analyzed numerically and compared with a traditional method (where measurements are directly used), and it was demonstrated that gradient-selected high-fidelity reconstructed data can effectively improve the accuracy of ANS localization.
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Affiliation(s)
- Hui-min Shen
- State Key Laboratory of Fluid Power Transmission and Control, Zhejiang University, Hangzhou, China
| | - Kok-Meng Lee
- Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, USA. .,State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China.
| | - Liang Hu
- State Key Laboratory of Fluid Power Transmission and Control, Zhejiang University, Hangzhou, China.
| | - Shaohui Foong
- Engineering Product Development Pillar, Singapore University of Technology and Design, Singapore, Singapore
| | - Xin Fu
- State Key Laboratory of Fluid Power Transmission and Control, Zhejiang University, Hangzhou, China
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MEG-EEG Information Fusion and Electromagnetic Source Imaging: From Theory to Clinical Application in Epilepsy. Brain Topogr 2015; 28:785-812. [PMID: 26016950 PMCID: PMC4600479 DOI: 10.1007/s10548-015-0437-3] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2014] [Accepted: 05/04/2015] [Indexed: 11/26/2022]
Abstract
The purpose of this study is to develop and quantitatively assess whether fusion of EEG and MEG (MEEG) data within the maximum entropy on the mean (MEM) framework increases the spatial accuracy of source localization, by yielding better recovery of the spatial extent and propagation pathway of the underlying generators of inter-ictal epileptic discharges (IEDs). The key element in this study is the integration of the complementary information from EEG and MEG data within the MEM framework. MEEG was compared with EEG and MEG when localizing single transient IEDs. The fusion approach was evaluated using realistic simulation models involving one or two spatially extended sources mimicking propagation patterns of IEDs. We also assessed the impact of the number of EEG electrodes required for an efficient EEG–MEG fusion. MEM was compared with minimum norm estimate, dynamic statistical parametric mapping, and standardized low-resolution electromagnetic tomography. The fusion approach was finally assessed on real epileptic data recorded from two patients showing IEDs simultaneously in EEG and MEG. Overall the localization of MEEG data using MEM provided better recovery of the source spatial extent, more sensitivity to the source depth and more accurate detection of the onset and propagation of IEDs than EEG or MEG alone. MEM was more accurate than the other methods. MEEG proved more robust than EEG and MEG for single IED localization in low signal-to-noise ratio conditions. We also showed that only few EEG electrodes are required to bring additional relevant information to MEG during MEM fusion.
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Bagić A. Look back to leap forward: The emerging new role of magnetoencephalography (MEG) in nonlesional epilepsy. Clin Neurophysiol 2015; 127:60-66. [PMID: 26055337 DOI: 10.1016/j.clinph.2015.05.009] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2014] [Revised: 05/02/2015] [Accepted: 05/08/2015] [Indexed: 11/25/2022]
Abstract
This review considers accumulating evidence for a new role of MEG/MSI in increasing the diagnostic yield of supposedly negative MRIs, and suggests changes in the use of MEG/MSI in presurgical epilepsy evaluations. Specific alterations in practice protocols for both the MEG practitioner (i.e. physician magnetoencephalographer) and MEG user (i.e. referring physician) are proposed that should further enhance the overall value of MEG/MSI. Although advances in MEG analysis methods will likely become increasingly assisted by computers, interpretive competency and prudent clinical judgment remain irreplaceable.
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Affiliation(s)
- Anto Bagić
- University of Pittsburgh Comprehensive Epilepsy Center (UPCEC), UPMC MEG Epilepsy Program, Department of Neurology, University of Pittsburgh Medical School, Suite 811, Kaufmann Medical Building, 3471 Fifth Ave, Pittsburgh, PA 15213, USA.
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Papadelis C, Grant PE, Okada Y, Preissl H. Editorial on emerging neuroimaging tools for studying normal and abnormal human brain development. Front Hum Neurosci 2015; 9:127. [PMID: 25814947 PMCID: PMC4356076 DOI: 10.3389/fnhum.2015.00127] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2015] [Accepted: 02/23/2015] [Indexed: 12/05/2022] Open
Affiliation(s)
- Christos Papadelis
- BabyMEG/EEG facility, Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital Boston, MA, USA ; Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School Boston, MA, USA
| | - P Ellen Grant
- BabyMEG/EEG facility, Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital Boston, MA, USA ; Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School Boston, MA, USA ; Department of Radiology, Boston Children's Hospital, Harvard Medical School Boston, MA, USA
| | - Yoshio Okada
- BabyMEG/EEG facility, Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital Boston, MA, USA ; Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School Boston, MA, USA
| | - Hubert Preissl
- fMEG Center, Institute for Medical Psychology and Behavioural Neurobiology, University of Tuebingen Tuebingen, Germany ; Department of Obstetrics and Gynecology, University of Arkansas for Medical Sciences Little Rock, AR, USA
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