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de Borman A, Vespa S, Absil PA, El Tahry R. Estimation of seizure onset zone from ictal scalp EEG using independent component analysis in extratemporal lobe epilepsy. J Neural Eng 2022; 19. [PMID: 35172295 DOI: 10.1088/1741-2552/ac55ad] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 02/16/2022] [Indexed: 11/12/2022]
Abstract
OBJECTIVE The purpose of this study is to localize the seizure onset zone of patients suffering from drug-resistant epilepsy. During the last two decades, multiple studies proposed the use of Independent Component Analysis (ICA) to analyze ictal electroencephalogram (EEG) recordings. This study aims at evaluating ICA potential with quantitative measurements. In particular, we address the challenging step where the components extracted by ICA of an ictal nature must be selected. APPROACH We considered a cohort of 10 patients suffering from extratemporal lobe epilepsy who were rendered seizure-free after surgery. Different sets of pre-processing parameters were compared and component features were explored to help distinguish ictal components from others. Quantitative measurements were implemented to determine whether some of the components returned by ICA were located within the resection zone and thus likely to be ictal. Finally, an assistance to the component selection was proposed based on the implemented features. MAIN RESULTS For every seizure, at least one component returned by ICA was localized within the resection zone, with the optimal pre-processing parameters. Three features were found to distinguish components localized within the resection zone: the dispersion of their active brain sources, the ictal rhythm power and the contribution to the EEG variance. Using the implemented component selection assistance based on the features, the probability that the first proposed component yields an accurate estimation reaches 51.43% (without assistance: 24.74%). The accuracy reaches 80% when considering the best result within the first five components. SIGNIFICANCE This study confirms the utility of ICA for ictal EEG analysis in extratemporal lobe epilepsy, and suggests relevant features to analyze the components returned by ICA. A component selection assistance is proposed to guide clinicians in their choice for ictal components.
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Affiliation(s)
- Aurélie de Borman
- ICTEAM, Université catholique de Louvain, Avenue Georges Lemaitre 4, Louvain-la-Neuve, 1348, BELGIUM
| | - Simone Vespa
- Institute of Neuroscience (IoNS), Université catholique de Louvain, Avenue Mounier 53 bte B1.53.02, Louvain-la-Neuve, 1348, BELGIUM
| | - Pierre-Antoine Absil
- ICTEAM, Université catholique de Louvain, Avenue Georges Lemaître 4 bte L4.05.01, Louvain-la-Neuve, 1348, BELGIUM
| | - Riëm El Tahry
- Institute of Neuroscience (IoNS), Université catholique de Louvain, Avenue Mounier 53 bte B1.53.02, Louvain-la-Neuve, 1348, BELGIUM
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van Mierlo P, Vorderwülbecke BJ, Staljanssens W, Seeck M, Vulliémoz S. Ictal EEG source localization in focal epilepsy: Review and future perspectives. Clin Neurophysiol 2020; 131:2600-2616. [PMID: 32927216 DOI: 10.1016/j.clinph.2020.08.001] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 07/12/2020] [Accepted: 08/04/2020] [Indexed: 11/25/2022]
Abstract
Electroencephalographic (EEG) source imaging localizes the generators of neural activity in the brain. During presurgical epilepsy evaluation, EEG source imaging of interictal epileptiform discharges is an established tool to estimate the irritative zone. However, the origin of interictal activity can be partly or fully discordant with the origin of seizures. Therefore, source imaging based on ictal EEG data to determine the seizure onset zone can provide precious clinical information. In this descriptive review, we address the importance of localizing the seizure onset zone based on noninvasive EEG recordings as a complementary analysis that might reduce the burden of the presurgical evaluation. We identify three major challenges (low signal-to-noise ratio of the ictal EEG data, spread of ictal activity in the brain, and validation of the developed methods) and discuss practical solutions. We provide an extensive overview of the existing clinical studies to illustrate the potential clinical utility of EEG-based localization of the seizure onset zone. Finally, we conclude with future perspectives and the needs for translating ictal EEG source imaging into clinical practice.
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Affiliation(s)
- Pieter van Mierlo
- Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium.
| | - Bernd J Vorderwülbecke
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland; Department of Neurology, Epilepsy-Center Berlin-Brandenburg, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany.
| | - Willeke Staljanssens
- Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium
| | - Margitta Seeck
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland.
| | - Serge Vulliémoz
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland.
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Habib MA, Ibrahim F, Mohktar MS, Kamaruzzaman SB, Lim KS. Recursive independent component analysis (ICA)-decomposition of ictal EEG to select the best ictal component for EEG source imaging. Clin Neurophysiol 2020; 131:642-654. [DOI: 10.1016/j.clinph.2019.11.058] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2018] [Revised: 11/25/2019] [Accepted: 11/30/2019] [Indexed: 11/28/2022]
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Baroumand AG, van Mierlo P, Strobbe G, Pinborg LH, Fabricius M, Rubboli G, Leffers AM, Uldall P, Jespersen B, Brennum J, Henriksen OM, Beniczky S. Automated EEG source imaging: A retrospective, blinded clinical validation study. Clin Neurophysiol 2018; 129:2403-2410. [DOI: 10.1016/j.clinph.2018.09.015] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2018] [Revised: 08/21/2018] [Accepted: 09/15/2018] [Indexed: 11/16/2022]
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Kuo CC, Tucker DM, Luu P, Jenson K, Tsai JJ, Ojemann JG, Holmes MD. EEG source imaging of epileptic activity at seizure onset. Epilepsy Res 2018; 146:160-171. [DOI: 10.1016/j.eplepsyres.2018.07.006] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Revised: 07/06/2018] [Accepted: 07/16/2018] [Indexed: 01/16/2023]
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Abstract
Brain activity and connectivity are distributed in the three-dimensional space and evolve in time. It is important to image brain dynamics with high spatial and temporal resolution. Electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive measurements associated with complex neural activations and interactions that encode brain functions. Electrophysiological source imaging estimates the underlying brain electrical sources from EEG and MEG measurements. It offers increasingly improved spatial resolution and intrinsically high temporal resolution for imaging large-scale brain activity and connectivity on a wide range of timescales. Integration of electrophysiological source imaging and functional magnetic resonance imaging could further enhance spatiotemporal resolution and specificity to an extent that is not attainable with either technique alone. We review methodological developments in electrophysiological source imaging over the past three decades and envision its future advancement into a powerful functional neuroimaging technology for basic and clinical neuroscience applications.
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Affiliation(s)
- Bin He
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA;
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - Abbas Sohrabpour
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - Emery Brown
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Zhongming Liu
- Weldon School of Biomedical Engineering, School of Electrical and Computer Engineering, and Purdue Institute of Integrative Neuroscience, Purdue University, West Lafayette, Indiana 47906, USA
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Haor D, Shavit R, Shapiro M, Geva AB. Back-Projection Cortical Potential Imaging: Theory and Results. IEEE TRANSACTIONS ON MEDICAL IMAGING 2017; 36:1583-1595. [PMID: 28362583 DOI: 10.1109/tmi.2017.2679756] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Electroencephalography (EEG) is the single brain monitoring technique that is non-invasive, portable, passive, exhibits high-temporal resolution, and gives a directmeasurement of the scalp electrical potential. Amajor disadvantage of the EEG is its low-spatial resolution, which is the result of the low-conductive skull that "smears" the currents coming from within the brain. Recording brain activity with both high temporal and spatial resolution is crucial for the localization of confined brain activations and the study of brainmechanismfunctionality, whichis then followed by diagnosis of brain-related diseases. In this paper, a new cortical potential imaging (CPI) method is presented. The new method gives an estimation of the electrical activity on the cortex surface and thus removes the "smearing effect" caused by the skull. The scalp potentials are back-projected CPI (BP-CPI) onto the cortex surface by building a well-posed problem to the Laplace equation that is solved by means of the finite elements method on a realistic head model. A unique solution to the CPI problem is obtained by introducing a cortical normal current estimation technique. The technique is based on the same mechanism used in the well-known surface Laplacian calculation, followed by a scalp-cortex back-projection routine. The BP-CPI passed four stages of validation, including validation on spherical and realistic head models, probabilistic analysis (Monte Carlo simulation), and noise sensitivity tests. In addition, the BP-CPI was compared with the minimum norm estimate CPI approach and found superior for multi-source cortical potential distributions with very good estimation results (CC >0.97) on a realistic head model in the regions of interest, for two representative cases. The BP-CPI can be easily incorporated in different monitoring tools and help researchers by maintaining an accurate estimation for the cortical potential of ongoing or event-related potentials in order to have better neurological inferences from the EEG.
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Sohrabpour A, Worrell G. Identifying epileptic source location and extent: an iterative sparse electromagnetic source imaging algorithm. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2017; 2016:109-112. [PMID: 28268292 DOI: 10.1109/embc.2016.7590652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
In this paper we have introduced a novel electromagnetic source imaging (ESI) technique and demonstrated its validity and excellent performance in imaging the location and extent of underlying epileptic sources in patients suffering from focal epilepsy. The proposed algorithm employs ideas from sparse signal processing literature and convex optimization theories to improve source imaging results obtained from scalp-recorded electroencephalogram (EEG). EEG source imaging results generally use subjective methods to determine the extent of the underlying brain activity. The proposed technique provides significant improvement in dealing with such shortcomings and eliminates the need for thresholding. The results of our computer simulations and clinical validation study demonstrate the excellent performance of the proposed algorithm and suggest it may become a useful tool for objectively determining the location and extent of focal epileptic activity in a noninvasive fashion.
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Sohrabpour A, Ye S, Worrell GA, Zhang W, He B. Noninvasive Electromagnetic Source Imaging and Granger Causality Analysis: An Electrophysiological Connectome (eConnectome) Approach. IEEE Trans Biomed Eng 2016; 63:2474-2487. [PMID: 27740473 PMCID: PMC5152676 DOI: 10.1109/tbme.2016.2616474] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
OBJECTIVE Combined source-imaging techniques and directional connectivity analysis can provide useful information about the underlying brain networks in a noninvasive fashion. Source-imaging techniques have been used successfully to either determine the source of activity or to extract source time-courses for Granger causality analysis, previously. In this work, we utilize source-imaging algorithms to both find the network nodes [regions of interest (ROI)] and then extract the activation time series for further Granger causality analysis. The aim of this work is to find network nodes objectively from noninvasive electromagnetic signals, extract activation time-courses, and apply Granger analysis on the extracted series to study brain networks under realistic conditions. METHODS Source-imaging methods are used to identify network nodes and extract time-courses and then Granger causality analysis is applied to delineate the directional functional connectivity of underlying brain networks. Computer simulations studies where the underlying network (nodes and connectivity pattern) is known were performed; additionally, this approach has been evaluated in partial epilepsy patients to study epilepsy networks from interictal and ictal signals recorded by EEG and/or Magnetoencephalography (MEG). RESULTS Localization errors of network nodes are less than 5 mm and normalized connectivity errors of ∼20% in estimating underlying brain networks in simulation studies. Additionally, two focal epilepsy patients were studied and the identified nodes driving the epileptic network were concordant with clinical findings from intracranial recordings or surgical resection. CONCLUSION Our study indicates that combined source-imaging algorithms with Granger causality analysis can identify underlying networks precisely (both in terms of network nodes location and internodal connectivity). SIGNIFICANCE The combined source imaging and Granger analysis technique is an effective tool for studying normal or pathological brain conditions.
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Affiliation(s)
- Abbas Sohrabpour
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455 USA
| | - Shuai Ye
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455 USA
| | | | - Wenbo Zhang
- Minnesota Epilepsy Group, United Hospital, MN 55102 USA and also with the Department of Neurology, University of Minnesota, Minneapolis, 55455 USA
| | - Bin He
- Department of Biomedical Engineering, and the Institute for Engineering in Medicine, University of Minnesota, Minneapolis, MN 55455 USA
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Sohrabpour A, Lu Y, Worrell G, He B. Imaging brain source extent from EEG/MEG by means of an iteratively reweighted edge sparsity minimization (IRES) strategy. Neuroimage 2016; 142:27-42. [PMID: 27241482 PMCID: PMC5124544 DOI: 10.1016/j.neuroimage.2016.05.064] [Citation(s) in RCA: 51] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2015] [Revised: 05/09/2016] [Accepted: 05/26/2016] [Indexed: 11/23/2022] Open
Abstract
Estimating extended brain sources using EEG/MEG source imaging techniques is challenging. EEG and MEG have excellent temporal resolution at millisecond scale but their spatial resolution is limited due to the volume conduction effect. We have exploited sparse signal processing techniques in this study to impose sparsity on the underlying source and its transformation in other domains (mathematical domains, like spatial gradient). Using an iterative reweighting strategy to penalize locations that are less likely to contain any source, it is shown that the proposed iteratively reweighted edge sparsity minimization (IRES) strategy can provide reasonable information regarding the location and extent of the underlying sources. This approach is unique in the sense that it estimates extended sources without the need of subjectively thresholding the solution. The performance of IRES was evaluated in a series of computer simulations. Different parameters such as source location and signal-to-noise ratio were varied and the estimated results were compared to the targets using metrics such as localization error (LE), area under curve (AUC) and overlap between the estimated and simulated sources. It is shown that IRES provides extended solutions which not only localize the source but also provide estimation for the source extent. The performance of IRES was further tested in epileptic patients undergoing intracranial EEG (iEEG) recording for pre-surgical evaluation. IRES was applied to scalp EEGs during interictal spikes, and results were compared with iEEG and surgical resection outcome in the patients. The pilot clinical study results are promising and demonstrate a good concordance between noninvasive IRES source estimation with iEEG and surgical resection outcomes in the same patients. The proposed algorithm, i.e. IRES, estimates extended source solutions from scalp electromagnetic signals which provide relatively accurate information about the location and extent of the underlying source.
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Affiliation(s)
- Abbas Sohrabpour
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - Yunfeng Lu
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | | | - Bin He
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA; Institute for Engineering in Medicine, University of Minnesota, Minneapolis, MN, USA.
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Habib MA, Ibrahim F, Mohktar MS, Kamaruzzaman SB, Rahmat K, Lim KS. Ictal EEG Source Imaging for Presurgical Evaluation of Refractory Focal Epilepsy. World Neurosurg 2015; 88:576-585. [PMID: 26548833 DOI: 10.1016/j.wneu.2015.10.096] [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: 06/15/2015] [Revised: 10/25/2015] [Accepted: 10/26/2015] [Indexed: 11/25/2022]
Abstract
BACKGROUND Electroencephalography source imaging (ESI) is a promising tool for localizing the cortical sources of both ictal and interictal epileptic activities. Many studies have shown the clinical usefulness of interictal ESI, but very few have investigated the utility of ictal ESI. The aim of this article is to examine the clinical usefulness of ictal ESI for epileptic focus localization in patients with refractory focal epilepsy, especially extratemporal lobe epilepsy. METHODS Both ictal and interictal ESI were performed by the use of patient-specific realistic forward models and 3 different linear distributed inverse models. Lateralization as well as concordance between ESI-estimated focuses and single-photon emission computed tomography (SPECT) focuses were assessed. RESULTS All the ESI focuses (both ictal and interictal) were found lateralized to the same hemisphere as ictal SPECT focuses. Lateralization results also were in agreement with the lesion sides as visualized on magnetic resonance imaging. Ictal ESI results, obtained from the best-performing inverse model, were fully concordant with the same cortical lobe as SPECT focuses, whereas the corresponding concordance rate is 87.50% in case of interictal ESI. CONCLUSIONS Our findings show that ictal ESI gives fully lateralized and highly concordant results with ictal SPECT and may provide a cost-effective substitute for ictal SPECT.
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Affiliation(s)
- Mohammad Ashfak Habib
- Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia; Centre for Innovation in Medical Engineering (CIME), Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia; Department of Computer Science & Engineering, Chittagong University of Engineering & Technology, Chittagong, Bangladesh
| | - Fatimah Ibrahim
- Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia; Centre for Innovation in Medical Engineering (CIME), Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia.
| | - Mas S Mohktar
- Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia; Centre for Innovation in Medical Engineering (CIME), Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia
| | - Shahrul Bahyah Kamaruzzaman
- Centre for Innovation in Medical Engineering (CIME), Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia; Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Kartini Rahmat
- Department of Biomedical Imaging, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Kheng Seang Lim
- Centre for Innovation in Medical Engineering (CIME), Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia; Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
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Thalamocortical relationship in epileptic patients with generalized spike and wave discharges--A multimodal neuroimaging study. NEUROIMAGE-CLINICAL 2015; 9:117-27. [PMID: 26448912 PMCID: PMC4552814 DOI: 10.1016/j.nicl.2015.07.014] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/29/2015] [Revised: 05/30/2015] [Accepted: 07/05/2015] [Indexed: 01/01/2023]
Abstract
Unlike focal or partial epilepsy, which has a confined range of influence, idiopathic generalized epilepsy (IGE) often affects the whole or a larger portion of the brain without obvious, known cause. It is important to understand the underlying network which generates epileptic activity and through which epileptic activity propagates. The aim of the present study was to investigate the thalamocortical relationship using non-invasive imaging modalities in a group of IGE patients. We specifically investigated the roles of the mediodorsal nuclei in the thalami and the medial frontal cortex in generating and spreading IGE activities. We hypothesized that the connectivity between these two structures is key in understanding the generation and propagation of epileptic activity in brains affected by IGE. Using three imaging techniques of EEG, fMRI and EEG-informed fMRI, we identified important players in generation and propagation of generalized spike-and-wave discharges (GSWDs). EEG-informed fMRI suggested multiple regions including the medial frontal area near to the anterior cingulate cortex, mediodorsal nuclei of the thalamus, caudate nucleus among others that related to the GSWDs. The subsequent seed-based fMRI analysis revealed a reciprocal cortical and bi-thalamic functional connection. Through EEG-based Granger Causality analysis using (DTF) and adaptive DTF, within the reciprocal thalamocortical circuitry, thalamus seems to serve as a stronger source in driving cortical activity from initiation to the propagation of a GSWD. Such connectivity change starts before the GSWDs and continues till the end of the slow wave discharge. Thalamus, especially the mediodorsal nuclei, may serve as potential targets for deep brain stimulation to provide more effective treatment options for patients with drug-resistant generalized epilepsy.
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Hamid L, Sarabi M, Japaridze N, Wiegand G, Heute U, Stephani U, Galka A, Siniatchkin M. The performance of the spatiotemporal Kalman filter and LORETA in seizure onset localization. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2015; 2015:2741-2744. [PMID: 26736859 DOI: 10.1109/embc.2015.7318959] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
The assumption of spatial-smoothness is often used to solve the bioelectric inverse problem during electroencephalographic (EEG) source imaging, e.g., in low resolution electromagnetic tomography (LORETA). Since the EEG data show a temporal structure, the combination of the temporal-smoothness and the spatial-smoothness constraints may improve the solution of the EEG inverse problem. This study investigates the performance of the spatiotemporal Kalman filter (STKF) method, which is based on spatial and temporal smoothness, in the localization of a focal seizure's onset and compares its results to those of LORETA. The main finding of the study was that the STKF with an autoregressive model of order two significantly outperformed LORETA in the accuracy and consistency of the localization, provided that the source space consists of a whole-brain volumetric grid. In the future, these promising results will be confirmed using data from more patients and performing statistical analyses on the results. Furthermore, the effects of the temporal smoothness constraint will be studied using different types of focal seizures.
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He B, Sohrabpour A. Imaging epileptogenic brain using high density EEG source imaging and MRI. Clin Neurophysiol 2015; 127:5-7. [PMID: 26051752 DOI: 10.1016/j.clinph.2015.04.074] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2015] [Revised: 04/30/2015] [Accepted: 04/30/2015] [Indexed: 10/23/2022]
Affiliation(s)
- Bin He
- Department of Biomedical Engineering, University of Minnesota, 312 Church Street, SE, Minneapolis, MN 55455, USA.
| | - Abbas Sohrabpour
- Department of Biomedical Engineering, University of Minnesota, 312 Church Street, SE, Minneapolis, MN 55455, USA
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Sohrabpour A, Lu Y, Kankirawatana P, Blount J, Kim H, He B. Effect of EEG electrode number on epileptic source localization in pediatric patients. Clin Neurophysiol 2015; 126:472-80. [PMID: 25088733 PMCID: PMC4289666 DOI: 10.1016/j.clinph.2014.05.038] [Citation(s) in RCA: 83] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2014] [Revised: 05/14/2014] [Accepted: 05/19/2014] [Indexed: 11/18/2022]
Abstract
OBJECTIVE To investigate the relationship between EEG source localization and the number of scalp EEG recording channels. METHODS 128 EEG channel recordings of 5 pediatric patients with medically intractable partial epilepsy were used to perform source localization of interictal spikes. The results were compared with surgical resection and intracranial recordings. Various electrode configurations were tested and a series of computer simulations based on a realistic head boundary element model were also performed in order to further validate the clinical findings. RESULTS The improvement seen in source localization substantially decreases as the number of electrodes increases. This finding was evaluated using the surgical resection, intracranial recordings and computer simulation. It was also shown in the simulation that increasing the electrode numbers could remedy the localization error of deep sources. A plateauing effect was seen in deep and superficial sources with further increasing the electrode number. CONCLUSION The source localization is improved when electrode numbers increase, but the absolute improvement in accuracy decreases with increasing electrode number. SIGNIFICANCE Increasing the electrode number helps decrease localization error and thus can more ably assist the physician to better plan for surgical procedures.
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Affiliation(s)
- Abbas Sohrabpour
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - Yunfeng Lu
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - Pongkiat Kankirawatana
- Division of Pediatric Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jeffrey Blount
- Division of Neurosurgery, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Hyunmi Kim
- Division of Pediatric Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Bin He
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA; Institute for Engineering in Medicine, University of Minnesota, Minneapolis, MN, USA.
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Localization Accuracy of Distributed Inverse Solutions for Electric and Magnetic Source Imaging of Interictal Epileptic Discharges in Patients with Focal Epilepsy. Brain Topogr 2015; 29:162-81. [DOI: 10.1007/s10548-014-0423-1] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2014] [Accepted: 12/24/2014] [Indexed: 10/24/2022]
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Xu H, Lu Y, Zhu S, He B. Assessing dynamic spectral causality by lagged adaptive directed transfer function and instantaneous effect factor. IEEE Trans Biomed Eng 2014; 61:1979-88. [PMID: 24956616 PMCID: PMC4068271 DOI: 10.1109/tbme.2014.2311034] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
It is of significance to assess the dynamic spectral causality among physiological signals. Several practical estimators adapted from spectral Granger causality have been exploited to track dynamic causality based on the framework of time-varying multivariate autoregressive (tvMVAR) models. The nonzero covariance of the model's residuals has been used to describe the instantaneous effect phenomenon in some causality estimators. However, for the situations with Gaussian residuals in some autoregressive models, it is challenging to distinguish the directed instantaneous causality if the sufficient prior information about the "causal ordering" is missing. Here, we propose a new algorithm to assess the time-varying causal ordering of tvMVAR model under the assumption that the signals follow the same acyclic causal ordering for all time lags and to estimate the instantaneous effect factor (IEF) value in order to track the dynamic directed instantaneous connectivity. The time-lagged adaptive directed transfer function (ADTF) is also estimated to assess the lagged causality after removing the instantaneous effect. In this study, we first investigated the performance of the causal-ordering estimation algorithm and the accuracy of IEF value. Then, we presented the results of IEF and time-lagged ADTF method by comparing with the conventional ADTF method through simulations of various propagation models. Statistical analysis results suggest that the new algorithm could accurately estimate the causal ordering and give a good estimation of the IEF values in the Gaussian residual conditions. Meanwhile, the time-lagged ADTF approach is also more accurate in estimating the time-lagged dynamic interactions in a complex nervous system after extracting the instantaneous effect. In addition to the simulation studies, we applied the proposed method to estimate the dynamic spectral causality on real visual evoked potential (VEP) data in a human subject. Its usefulness in time-variant spectral causality assessment was demonstrated through the mutual causality investigation of brain activity during the VEP experiments.
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Affiliation(s)
- Haojie Xu
- College of Electrical Engineering, Zhejiang University, Hangzhou, China
| | - Yunfeng Lu
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455 USA
| | - Shanan Zhu
- College of Electrical Engineering, Zhejiang University, Hangzhou, China
| | - Bin He
- Department of Biomedical Engineering and Institute for Engineering in Medicine, University of Minnesota, Minneapolis, MN 55455 USA
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Lu Y, Worrell GA, Zhang HC, Yang L, Brinkmann B, Nelson C, He B. Noninvasive imaging of the high frequency brain activity in focal epilepsy patients. IEEE Trans Biomed Eng 2014; 61:1660-7. [PMID: 24845275 PMCID: PMC4123538 DOI: 10.1109/tbme.2013.2297332] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
High-frequency (HF) activity represents a potential biomarker of the epileptogenic zone in epilepsy patients, the removal of which is considered to be crucial for seizure-free surgical outcome. We proposed a high frequency source imaging (HFSI) approach to noninvasively image the brain sources of the scalp-recorded HF EEG activity. Both computer simulation and clinical patient data analysis were performed to investigate the feasibility of using the HFSI approach to image the sources of HF activity from noninvasive scalp EEG recordings. The HF activity was identified from high-density scalp recordings after high-pass filtering the EEG data and the EEG segments with HF activity were concatenated together to form repetitive HF activity. Independent component analysis was utilized to extract the components corresponding to the HF activity. Noninvasive EEG source imaging using realistic geometric boundary element head modeling was then applied to image the sources of the pathological HF brain activity. Five medically intractable focal epilepsy patients were studied and the estimated sources were found to be concordant with the surgical resection or intracranial recordings of the patients. The present study demonstrates, for the first time, that source imaging from the scalp HF activity could help to localize the seizure onset zone and provide a novel noninvasive way of studying the epileptic brain in humans. This study also indicates the potential application of studying HF activity in the presurgical planning of medically intractable epilepsy patients.
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Affiliation(s)
- Yunfeng Lu
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455 USA
| | | | - Huishi Clara Zhang
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455 USA
| | - Lin Yang
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455 USA
| | | | - Cindy Nelson
- Department of Neurology, Mayo Clinic, Rochester, MN 55901 USA
| | - Bin He
- Department of Biomedical Engineering and the Institute for Engineering in Medicine, University of Minnesota, Minneapolis, MN 55455 USA ()
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Sohrabpour A, Lu Y, Kankirawatana P, He B. Electroencephalography Electrode Configuration and Source Imaging1. J Med Device 2014. [DOI: 10.1115/1.4027019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Affiliation(s)
- Abbas Sohrabpour
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455
| | - Yunfeng Lu
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455
| | - Pongkiat Kankirawatana
- Division of Pediatric Neurology, University of Alabama at Birmingham, Birmingham, AL 35233
| | - Bin He
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455
- Institute of Engineering in Medicine, University of Minnesota, Minneapolis, MN 55455
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Zhang CH, Lu Y, Brinkmann B, Welker K, Worrell G, He B. Lateralization and localization of epilepsy related hemodynamic foci using presurgical fMRI. Clin Neurophysiol 2014; 126:27-38. [PMID: 24856460 DOI: 10.1016/j.clinph.2014.04.011] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2014] [Revised: 03/09/2014] [Accepted: 04/16/2014] [Indexed: 12/01/2022]
Abstract
OBJECTIVE The aim was to develop a method for the purpose of localizing epilepsy related hemodynamic foci for patients suffering intractable focal epilepsy using task-free fMRI alone. METHODS We studied three groups of subjects: patients with intractable focal epilepsy, healthy volunteers performing motor tasks, and healthy volunteers in resting state. We performed spatial independent component analysis (ICA) on the fMRI alone data and developed a set of IC selection criteria to identify epilepsy related ICs. The method was then tested in the two healthy groups. RESULTS In seven out of the nine surgery patients, identified ICs were concordant with surgical resection. Our results were also consistent with presurgical evaluation of the remaining one patient without surgery and may explain why she was not suitable for resection treatment. In the motor task study of ten healthy subjects, our method revealed components with concordant spatial and temporal features as expected from the unilateral motor tasks. In the resting state study of seven healthy subjects, the method successfully rejected all components in four out of seven subjects as non-epilepsy related components. CONCLUSION These results suggest the lateralization and localization value of fMRI alone in presurgical evaluation for patients with intractable unilateral focal epilepsy. SIGNIFICANCE The proposed method is noninvasive in nature and easy to implement. It has the potential to be incorporated in current presurgical workup for treating intractable focal epilepsy patients.
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Affiliation(s)
| | - Yunfeng Lu
- Department of Biomedical Engineering, University of Minnesota, USA
| | - Benjamin Brinkmann
- Department of Neurology, Mayo Clinic, USA; Mayo Systems Electrophysiology Laboratory, Mayo Clinic, USA
| | | | - Gregory Worrell
- Department of Neurology, Mayo Clinic, USA; Mayo Systems Electrophysiology Laboratory, Mayo Clinic, USA
| | - Bin He
- Department of Biomedical Engineering, University of Minnesota, USA; Institute for Engineering in Medicine, University of Minnesota, USA.
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Beniczky S, Lantz G, Rosenzweig I, Åkeson P, Pedersen B, Pinborg LH, Ziebell M, Jespersen B, Fuglsang-Frederiksen A. Source localization of rhythmic ictal EEG activity: a study of diagnostic accuracy following STARD criteria. Epilepsia 2013; 54:1743-52. [PMID: 23944234 DOI: 10.1111/epi.12339] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/09/2013] [Indexed: 11/28/2022]
Abstract
PURPOSE Although precise identification of the seizure-onset zone is an essential element of presurgical evaluation, source localization of ictal electroencephalography (EEG) signals has received little attention. The aim of our study was to estimate the accuracy of source localization of rhythmic ictal EEG activity using a distributed source model. METHODS Source localization of rhythmic ictal scalp EEG activity was performed in 42 consecutive cases fulfilling inclusion criteria. The study was designed according to recommendations for studies on diagnostic accuracy (STARD). The initial ictal EEG signals were selected using a standardized method, based on frequency analysis and voltage distribution of the ictal activity. A distributed source model-local autoregressive average (LAURA)-was used for the source localization. Sensitivity, specificity, and measurement of agreement (kappa) were determined based on the reference standard-the consensus conclusion of the multidisciplinary epilepsy surgery team. Predictive values were calculated from the surgical outcome of the operated patients. To estimate the clinical value of the ictal source analysis, we compared the likelihood ratios of concordant and discordant results. Source localization was performed blinded to the clinical data, and before the surgical decision. KEY FINDINGS Reference standard was available for 33 patients. The ictal source localization had a sensitivity of 70% and a specificity of 76%. The mean measurement of agreement (kappa) was 0.61, corresponding to substantial agreement (95% confidence interval (CI) 0.38-0.84). Twenty patients underwent resective surgery. The positive predictive value (PPV) for seizure freedom was 92% and the negative predictive value (NPV) was 43%. The likelihood ratio was nine times higher for the concordant results, as compared with the discordant ones. SIGNIFICANCE Source localization of rhythmic ictal activity using a distributed source model (LAURA) for the ictal EEG signals selected with a standardized method is feasible in clinical practice and has a good diagnostic accuracy. Our findings encourage clinical neurophysiologists assessing ictal EEGs to include this method in their armamentarium.
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Affiliation(s)
- Sándor Beniczky
- Department of Clinical Neurophysiology, Danish Epilepsy Center, Dianalund, Denmark; Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark
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