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Medani T, Garcia-Prieto J, Tadel F, Antonakakis M, Erdbrügger T, Höltershinken M, Mead W, Schrader S, Joshi A, Engwer C, Wolters CH, Mosher JC, Leahy RM. Brainstorm-DUNEuro: An integrated and user-friendly Finite Element Method for modeling electromagnetic brain activity. Neuroimage 2023; 267:119851. [PMID: 36599389 PMCID: PMC9904282 DOI: 10.1016/j.neuroimage.2022.119851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2022] [Revised: 11/28/2022] [Accepted: 12/31/2022] [Indexed: 01/02/2023] Open
Abstract
Human brain activity generates scalp potentials (electroencephalography - EEG), intracranial potentials (iEEG), and external magnetic fields (magnetoencephalography - MEG). These electrophysiology (e-phys) signals can often be measured simultaneously for research and clinical applications. The forward problem involves modeling these signals at their sensors for a given equivalent current dipole configuration within the brain. While earlier researchers modeled the head as a simple set of isotropic spheres, today's magnetic resonance imaging (MRI) data allow for a detailed anatomic description of brain structures and anisotropic characterization of tissue conductivities. We present a complete pipeline, integrated into the Brainstorm software, that allows users to automatically generate an individual and accurate head model based on the subject's MRI and calculate the electromagnetic forward solution using the finite element method (FEM). The head model generation is performed by integrating the latest tools for MRI segmentation and FEM mesh generation. The final head model comprises the five main compartments: white-matter, gray-matter, CSF, skull, and scalp. The anisotropic brain conductivity model is based on the effective medium approach (EMA), which estimates anisotropic conductivity tensors from diffusion-weighted imaging (DWI) data. The FEM electromagnetic forward solution is obtained through the DUNEuro library, integrated into Brainstorm, and accessible with either a user-friendly graphical interface or scripting. With tutorials and example data sets available in an open-source format on the Brainstorm website, this integrated pipeline provides access to advanced FEM tools for electromagnetic modeling to a broader neuroscience community.
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Affiliation(s)
- Takfarinas Medani
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90089, United States.
| | - Juan Garcia-Prieto
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, United States; Harvard Medical School, Boston, Massachusetts, United States.
| | - Francois Tadel
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90089, United States
| | - Marios Antonakakis
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany; School of Electrical and Computer Engineering, Technical University of Crete, Greece
| | - Tim Erdbrügger
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
| | - Malte Höltershinken
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
| | - Wayne Mead
- Department of Neurology, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Sophie Schrader
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany; Department of Applied Mathematics, University of Münster, Germany
| | - Anand Joshi
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90089, United States
| | - Christian Engwer
- Department of Applied Mathematics, University of Münster, Germany
| | - Carsten H Wolters
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany; Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, Münster, Germany
| | - John C Mosher
- Department of Neurology, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Richard M Leahy
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90089, United States
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Khan A, Antonakakis M, Suntrup-Krueger S, Lencer R, Nitsche MA, Paulus W, Groß J, Wolters CH. Can individually targeted and optimized multi-channel tDCS outperform standard bipolar tDCS in stimulating the primary somatosensory cortex? Brain Stimul 2023; 16:1-16. [PMID: 36526154 DOI: 10.1016/j.brs.2022.12.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 11/22/2022] [Accepted: 12/12/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Transcranial direct current stimulation (tDCS) has emerged as a non-invasive neuro-modulation technique. Most studies show that anodal tDCS increases cortical excitability, however, with variable outcomes. Previously, we have shown in computer simulations that our multi-channel tDCS (mc-tDCS) approach, the distributed constrained maximum intensity (D-CMI) method can potentially lead to better controlled tDCS results due to the improved directionality of the injected current at the target side for individually optimized D-CMI montages. OBJECTIVE In this study, we test the application of the D-CMI approach in an experimental study to stimulate the somatosensory P20/N20 target source in Brodmann area 3b and compare it with standard bipolar tDCS and sham conditions. METHODS We applied anodal D-CMI, the standard bipolar and D-CMI based Sham tDCS for 10 min to target the 20 ms post-stimulus somatosensory P20/N20 target brain source in Brodmann area 3b reconstructed using combined magnetoencephalography (MEG) and electroencephalography (EEG) source analysis in realistic head models with calibrated skull conductivity in a group-study with 13 subjects. Finger-stimulated somatosensory evoked fields (SEF) were recorded and the component at 20 ms post-stimulus (M20) was analyzed before and after the application of the three tDCS conditions in order to read out the stimulation effect on Brodmann area 3b. RESULTS Analysis of the finger stimulated SEF M20 peak before (baseline) and after tDCS shows a significant increase in source amplitude in Brodmann area 3b for D-CMI (6-16 min after tDCS), while no significant effects are found for standard bipolar (6-16 min after tDCS) and sham (6-16 min after tDCS) stimulation conditions. For the later time courses (16-26 and 27-37 min post-stimulation), we found a significant decrease in M20 peak source amplitude for standard bipolar and sham tDCS, while there was no effect for D-CMI. CONCLUSION Our results indicate that targeted and optimized, and thereby highly individualized, mc-tDCS can outperform standard bipolar stimulation and lead to better control over stimulation outcomes with, however, a considerable amount of additional work compared to standard bipolar tDCS.
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Affiliation(s)
- Asad Khan
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany.
| | - Marios Antonakakis
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
| | | | - Rebekka Lencer
- Institute for Translational Psychiatry, University of Münster, Münster, Germany; Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany
| | - Michael A Nitsche
- Leibniz Research Centre for Working Environment and Human Factors at TU Dortmund, Dortmund, Germany
| | - Walter Paulus
- Department of Neurology, Ludwig Maximilians University, München, Germany; Department of Clinical Neurophysiology, University Medical Center, Georg-August University, Göttingen, Germany
| | - Joachim Groß
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany; Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, 48149 Münster, Germany
| | - Carsten H Wolters
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany; Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, 48149 Münster, Germany
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Beumer S, Boon P, Klooster DCW, van Ee R, Carrette E, Paulides MM, Mestrom RMC. Personalized tDCS for Focal Epilepsy—A Narrative Review: A Data-Driven Workflow Based on Imaging and EEG Data. Brain Sci 2022; 12:brainsci12050610. [PMID: 35624997 PMCID: PMC9139054 DOI: 10.3390/brainsci12050610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 05/03/2022] [Accepted: 05/05/2022] [Indexed: 02/01/2023] Open
Abstract
Conventional transcranial electric stimulation(tES) using standard anatomical positions for the electrodes and standard stimulation currents is frequently not sufficiently selective in targeting and reaching specific brain locations, leading to suboptimal application of electric fields. Recent advancements in in vivo electric field characterization may enable clinical researchers to derive better relationships between the electric field strength and the clinical results. Subject-specific electric field simulations could lead to improved electrode placement and more efficient treatments. Through this narrative review, we present a processing workflow to personalize tES for focal epilepsy, for which there is a clear cortical target to stimulate. The workflow utilizes clinical imaging and electroencephalography data and enables us to relate the simulated fields to clinical outcomes. We review and analyze the relevant literature for the processing steps in the workflow, which are the following: tissue segmentation, source localization, and stimulation optimization. In addition, we identify shortcomings and ongoing trends with regard to, for example, segmentation quality and tissue conductivity measurements. The presented processing steps result in personalized tES based on metrics like focality and field strength, which allow for correlation with clinical outcomes.
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Affiliation(s)
- Steven Beumer
- Department of Electrical Engineering, University of Technology Eindhoven, P.O. Box 513, 5600 MB Eindhoven, The Netherlands; (P.B.); (D.C.W.K.); (E.C.); (M.M.P.); (R.M.C.M.)
- Correspondence:
| | - Paul Boon
- Department of Electrical Engineering, University of Technology Eindhoven, P.O. Box 513, 5600 MB Eindhoven, The Netherlands; (P.B.); (D.C.W.K.); (E.C.); (M.M.P.); (R.M.C.M.)
- Department of Neurology, Ghent University Hospital, Corneel Heymanslaan 10, 9000 Ghent, Belgium
| | - Debby C. W. Klooster
- Department of Electrical Engineering, University of Technology Eindhoven, P.O. Box 513, 5600 MB Eindhoven, The Netherlands; (P.B.); (D.C.W.K.); (E.C.); (M.M.P.); (R.M.C.M.)
- Department of Neurology, Ghent University Hospital, Corneel Heymanslaan 10, 9000 Ghent, Belgium
| | - Raymond van Ee
- Philips Research Eindhoven, High Tech Campus 34, 5656 AE Eindhoven, The Netherlands;
| | - Evelien Carrette
- Department of Electrical Engineering, University of Technology Eindhoven, P.O. Box 513, 5600 MB Eindhoven, The Netherlands; (P.B.); (D.C.W.K.); (E.C.); (M.M.P.); (R.M.C.M.)
- Department of Neurology, Ghent University Hospital, Corneel Heymanslaan 10, 9000 Ghent, Belgium
| | - Maarten M. Paulides
- Department of Electrical Engineering, University of Technology Eindhoven, P.O. Box 513, 5600 MB Eindhoven, The Netherlands; (P.B.); (D.C.W.K.); (E.C.); (M.M.P.); (R.M.C.M.)
- Department of Radiation Oncology, Erasmus Medical Center Cancer Institute, Burgemeester Oudlaan 50, 3062 PA Rotterdam, The Netherlands
| | - Rob M. C. Mestrom
- Department of Electrical Engineering, University of Technology Eindhoven, P.O. Box 513, 5600 MB Eindhoven, The Netherlands; (P.B.); (D.C.W.K.); (E.C.); (M.M.P.); (R.M.C.M.)
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Validating EEG, MEG and Combined MEG and EEG Beamforming for an Estimation of the Epileptogenic Zone in Focal Cortical Dysplasia. Brain Sci 2022; 12:brainsci12010114. [PMID: 35053857 PMCID: PMC8796031 DOI: 10.3390/brainsci12010114] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 01/04/2022] [Accepted: 01/06/2022] [Indexed: 02/04/2023] Open
Abstract
MEG and EEG source analysis is frequently used for the presurgical evaluation of pharmacoresistant epilepsy patients. The source localization of the epileptogenic zone depends, among other aspects, on the selected inverse and forward approaches and their respective parameter choices. In this validation study, we compare the standard dipole scanning method with two beamformer approaches for the inverse problem, and we investigate the influence of the covariance estimation method and the strength of regularization on the localization performance for EEG, MEG, and combined EEG and MEG. For forward modelling, we investigate the difference between calibrated six-compartment and standard three-compartment head modelling. In a retrospective study, two patients with focal epilepsy due to focal cortical dysplasia type IIb and seizure freedom following lesionectomy or radiofrequency-guided thermocoagulation (RFTC) used the distance of the localization of interictal epileptic spikes to the resection cavity resp. RFTC lesion as reference for good localization. We found that beamformer localization can be sensitive to the choice of the regularization parameter, which has to be individually optimized. Estimation of the covariance matrix with averaged spike data yielded more robust results across the modalities. MEG was the dominant modality and provided a good localization in one case, while it was EEG for the other. When combining the modalities, the good results of the dominant modality were mostly not spoiled by the weaker modality. For appropriate regularization parameter choices, the beamformer localized better than the standard dipole scan. Compared to the importance of an appropriate regularization, the sensitivity of the localization to the head modelling was smaller, due to similar skull conductivity modelling and the fixed source space without orientation constraint.
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