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Hssain-Khalladi S, Giron A, Huneau C, Gitton C, Schwartz D, George N, Le Van Quyen M, Marrelec G, Marchand-Pauvert V. Further characterisation of late somatosensory evoked potentials using electroencephalogram and magnetoencephalogram source imaging. Eur J Neurosci 2024; 60:3772-3794. [PMID: 38726801 DOI: 10.1111/ejn.16379] [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: 12/21/2021] [Revised: 09/27/2023] [Accepted: 04/18/2024] [Indexed: 07/06/2024]
Abstract
Beside the well-documented involvement of secondary somatosensory area, the cortical network underlying late somatosensory evoked potentials (P60/N60 and P100/N100) is still unknown. Electroencephalogram and magnetoencephalogram source imaging were performed to further investigate the origin of the brain cortical areas involved in late somatosensory evoked potentials, using sensory inputs of different strengths and by testing the correlation between cortical sources. Simultaneous high-density electroencephalograms and magnetoencephalograms were performed in 19 participants, and electrical stimulation was applied to the median nerve (wrist level) at intensity between 1.5 and 9 times the perceptual threshold. Source imaging was undertaken to map the stimulus-induced brain cortical activity according to each individual brain magnetic resonance imaging, during three windows of analysis covering early and late somatosensory evoked potentials. Results for P60/N60 and P100/N100 were compared with those for P20/N20 (early response). According to literature, maximal activity during P20/N20 was found in central sulcus contralateral to stimulation site. During P60/N60 and P100/N100, activity was observed in contralateral primary sensorimotor area, secondary somatosensory area (on both hemispheres) and premotor and multisensory associative cortices. Late responses exhibited similar characteristics but different from P20/N20, and no significant correlation was found between early and late generated activities. Specific clusters of cortical activities were activated with specific input/output relationships underlying early and late somatosensory evoked potentials. Cortical networks, partly common to and distinct from early somatosensory responses, contribute to late responses, all participating in the complex somatosensory brain processing.
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Affiliation(s)
- Sahar Hssain-Khalladi
- Sorbonne Université, Inserm, CNRS, Laboratoire d'Imagerie Biomédicale, LIB, Paris, France
- Sorbonne Université, Laboratoire d'Excellence SMART, Paris, France
| | - Alain Giron
- Sorbonne Université, Inserm, CNRS, Laboratoire d'Imagerie Biomédicale, LIB, Paris, France
| | - Clément Huneau
- Université de Nantes, CNRS, Laboratoire des Sciences du Numérique de Nantes, LS2N, Nantes, France
| | - Christophe Gitton
- Sorbonne Université, Inserm, CNRS, Institut du Cerveau, ICM, Paris, France
| | - Denis Schwartz
- Sorbonne Université, Inserm, CNRS, Institut du Cerveau, ICM, Paris, France
| | - Nathalie George
- Sorbonne Université, Inserm, CNRS, Institut du Cerveau, ICM, Paris, France
| | - Michel Le Van Quyen
- Sorbonne Université, Inserm, CNRS, Laboratoire d'Imagerie Biomédicale, LIB, Paris, France
| | - Guillaume Marrelec
- Sorbonne Université, Inserm, CNRS, Laboratoire d'Imagerie Biomédicale, LIB, Paris, France
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Buschermöhle Y, Höltershinken MB, Erdbrügger T, Radecke JO, Sprenger A, Schneider TR, Lencer R, Gross J, Wolters CH. Comparing the performance of beamformer algorithms in estimating orientations of neural sources. iScience 2024; 27:109150. [PMID: 38420593 PMCID: PMC10901088 DOI: 10.1016/j.isci.2024.109150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 11/12/2023] [Accepted: 02/01/2024] [Indexed: 03/02/2024] Open
Abstract
The efficacy of transcranial electric stimulation (tES) to effectively modulate neuronal activity depends critically on the spatial orientation of the targeted neuronal population. Therefore, precise estimation of target orientation is of utmost importance. Different beamforming algorithms provide orientation estimates; however, a systematic analysis of their performance is still lacking. For fixed brain locations, EEG and MEG data from sources with randomized orientations were simulated. The orientation was then estimated (1) with an EEG and (2) with a combined EEG-MEG approach. Three commonly used beamformer algorithms were evaluated with respect to their abilities to estimate the correct orientation: Unit-Gain (UG), Unit-Noise-Gain (UNG), and Array-Gain (AG) beamformer. Performance depends on the signal-to-noise ratios for the modalities and on the chosen beamformer. Overall, the UNG and AG beamformers appear as the most reliable. With increasing noise, the UG estimate converges to a vector determined by the leadfield, thus leading to insufficient orientation estimates.
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Affiliation(s)
- Yvonne Buschermöhle
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, 48149 Münster, Germany
- Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, 48149 Münster, Germany
| | - Malte B Höltershinken
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, 48149 Münster, Germany
- Institute for Analysis and Numerics, University of Münster, 48149 Münster, Germany
| | - Tim Erdbrügger
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, 48149 Münster, Germany
- Institute for Analysis and Numerics, University of Münster, 48149 Münster, Germany
| | - Jan-Ole Radecke
- Department of Psychiatry and Psychotherapy, University of Lübeck, 23562 Lübeck, Germany
- Center of Brain, Behavior and Metabolism, University of Lübeck, 23562 Lübeck, Germany
| | - Andreas Sprenger
- Center of Brain, Behavior and Metabolism, University of Lübeck, 23562 Lübeck, Germany
- Department of Neurology, University of Lübeck, 23562 Lübeck, Germany
- Institute of Psychology II, University of Lübeck, 23562 Lübeck, Germany
| | - Till R Schneider
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany
| | - Rebekka Lencer
- Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, 48149 Münster, Germany
- Department of Psychiatry and Psychotherapy, University of Lübeck, 23562 Lübeck, Germany
- Center of Brain, Behavior and Metabolism, University of Lübeck, 23562 Lübeck, Germany
- Institute of Translational Psychiatry, University of Münster, 48149 Münster, Germany
| | - Joachim Gross
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, 48149 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, 48149 Münster, Germany
- Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, 48149 Münster, Germany
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Vorwerk J, Wolters CH, Baumgarten D. Global sensitivity of EEG source analysis to tissue conductivity uncertainties. Front Hum Neurosci 2024; 18:1335212. [PMID: 38532791 PMCID: PMC10963400 DOI: 10.3389/fnhum.2024.1335212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 01/22/2024] [Indexed: 03/28/2024] Open
Abstract
Introduction To reliably solve the EEG inverse problem, accurate EEG forward solutions based on a detailed, individual volume conductor model of the head are essential. A crucial-but often neglected-aspect in generating a volume conductor model is the choice of the tissue conductivities, as these may vary from subject to subject. In this study, we investigate the sensitivity of EEG forward and inverse solutions to tissue conductivity uncertainties for sources distributed over the whole cortex surface. Methods We employ a detailed five-compartment head model distinguishing skin, skull, cerebrospinal fluid, gray matter, and white matter, where we consider uncertainties of skin, skull, gray matter, and white matter conductivities. We use the finite element method (FEM) to calculate EEG forward solutions and goal function scans (GFS) as inverse approach. To be able to generate the large number of EEG forward solutions, we employ generalized polynomial chaos (gPC) expansions. Results For sources up to a depth of 4 cm, we find the strongest influence on the signal topography of EEG forward solutions for the skull conductivity and a notable effect for the skin conductivity. For even deeper sources, e.g., located deep in the longitudinal fissure, we find an increasing influence of the white matter conductivity. The conductivity variations translate to varying source localizations particularly for quasi-tangential sources on sulcal walls, whereas source localizations of quasi-radial sources on the top of gyri are less affected. We find a strong correlation between skull conductivity and the variation of source localizations and especially the depth of the reconstructed source for quasi-tangential sources. We furthermore find a clear but weaker correlation between depth of the reconstructed source and the skin conductivity. Discussion Our results clearly show the influence of tissue conductivity uncertainties on EEG source analysis. We find a particularly strong influence of skull and skin conductivity uncertainties.
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Affiliation(s)
- Johannes Vorwerk
- Institute of Electrical and Biomedical Engineering, UMIT TIROL—Private University for Health Sciences and Health Technology, Hall in Tirol, Austria
| | - 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
| | - Daniel Baumgarten
- Institute of Electrical and Biomedical Engineering, UMIT TIROL—Private University for Health Sciences and Health Technology, Hall in Tirol, Austria
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Ji Z, Song RR, Swan AR, Angeles Quinto A, Lee RR, Huang M. Magnetoencephalography Language Mapping Using Auditory Memory Retrieval and Silent Repeating Task. J Clin Neurophysiol 2024; 41:148-154. [PMID: 35512180 PMCID: PMC9633581 DOI: 10.1097/wnp.0000000000000947] [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] [Indexed: 11/26/2022] Open
Abstract
PURPOSE The study aims to (1) examine the spatiotemporal map of magnetoencephalography-evoked responses during an Auditory Memory Retrieval and Silent Repeating (AMRSR) task, and determine the hemispheric dominance for language, and (2) evaluate the accuracy of the AMRSR task in Wernicke and Broca area localization. METHODS In 30 patients with brain tumors and/or epilepsies, the AMRSR task was used to evoke magnetoencephalography responses. We applied Fast VEctor-based Spatial-Temporal Analyses with minimum L1-norm source imaging method to the magnetoencephalography responses for localizing the brain areas evoked by the AMRSR task. RESULTS The Fast-VEctor-based Spatial-Temporal Analysis found consistent activation in the posterior superior temporal gyrus around 300 to 500 ms, and another activation in the frontal cortex (pars opercularis and/or pars triangularis) around 600 to 900 ms, which were localized to the Wernicke area (BA 22) and Broca area (BA 44 and BA 45), respectively. The language-dominant hemispheric laterization elicited by the AMRSR task was comparable with the result from an Auditory Dichotic task result given to the same patient, with the exception that AMRSR is more sensitive on bilateral language laterization cases on finding the Wernicke and Broca areas. CONCLUSIONS For all patients who successfully finished the AMRSR task, Fast-VEctor-based Spatial-Temporal Analysis could establish accurate and robust localizations of Broca and Wernicke area and determine hemispheric dominance. For subjects with normal auditory functionality, the AMRSR paradigm evaluation showed significant promise in providing reliable assessments of cerebral language dominance and language network localization.
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Affiliation(s)
- Zhengwei Ji
- Radiology Department, University of California, San Diego, California, U.S.A
| | - Ryan R. Song
- Department of Molecular and Cell Biology, University of California, Berkeley, California, U.S.A.; and
| | - Ashley Robb Swan
- Radiology Department, University of California, San Diego, California, U.S.A
| | | | - Roland R. Lee
- Radiology Department, University of California, San Diego, California, U.S.A
- Radiology Service, San Diego VA Healthcare System, San Diego, California, U.S.A
| | - Mingxiong Huang
- Radiology Department, University of California, San Diego, California, U.S.A
- Radiology Service, San Diego VA Healthcare System, San Diego, California, U.S.A
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5
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Huang MX, Harrington DL, Angeles-Quinto A, Ji Z, Robb-Swan A, Huang CW, Shen Q, Hansen H, Baumgartner J, Hernandez-Lucas J, Nichols S, Jacobus J, Song T, Lerman I, Bazhenov M, Krishnan GP, Baker DG, Rao R, Lee RR. EMG-projected MEG high-resolution source imaging of human motor execution: Brain-muscle coupling above movement frequencies. IMAGING NEUROSCIENCE (CAMBRIDGE, MASS.) 2024; 2:1-20. [PMID: 39290632 PMCID: PMC11403128 DOI: 10.1162/imag_a_00056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 11/29/2023] [Accepted: 11/30/2023] [Indexed: 09/19/2024]
Abstract
Magnetoencephalography (MEG) is a non-invasive functional imaging technique for pre-surgical mapping. However, movement-related MEG functional mapping of primary motor cortex (M1) has been challenging in presurgical patients with brain lesions and sensorimotor dysfunction due to the large numbers of trials needed to obtain adequate signal to noise. Moreover, it is not fully understood how effective the brain communication is with the muscles at frequencies above the movement frequency and its harmonics. We developed a novel Electromyography (EMG)-projected MEG source imaging technique for localizing early-stage (-100 to 0 ms) M1 activity during ~l min recordings of left and right self-paced finger movements (~1 Hz). High-resolution MEG source images were obtained by projecting M1 activity towards the skin EMG signal without trial averaging. We studied delta (1-4 Hz), theta (4-7 Hz), alpha (8-12 Hz), beta (15-30 Hz), gamma (30-90 Hz), and upper-gamma (60-90 Hz) bands in 13 healthy participants (26 datasets) and three presurgical patients with sensorimotor dysfunction. In healthy participants, EMG-projected MEG accurately localized M1 with high accuracy in delta (100.0%), theta (100.0%), and beta (76.9%) bands, but not alpha (34.6%) or gamma/upper-gamma (0.0%) bands. Except for delta, all other frequency bands were above the movement frequency and its harmonics. In three presurgical patients, M1 activity in the affected hemisphere was also accurately localized, despite highly irregular EMG movement patterns in one patient. Altogether, our EMG-projected MEG imaging approach is highly accurate and feasible for M1 mapping in presurgical patients. The results also provide insight into movement-related brain-muscle coupling above the movement frequency and its harmonics.
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Affiliation(s)
- Ming-Xiong Huang
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, United States
- Department of Radiology, University of California, San Diego, CA, United States
- Department of Electrical and Computer Engineering, University of California, San Diego, CA, United States
| | - Deborah L Harrington
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, United States
- Department of Radiology, University of California, San Diego, CA, United States
| | | | - Zhengwei Ji
- Department of Radiology, University of California, San Diego, CA, United States
| | - Ashley Robb-Swan
- Department of Radiology, University of California, San Diego, CA, United States
| | - Charles W Huang
- Department of Bioengineering, Stanford University, Stanford, CA, United States
| | - Qian Shen
- Department of Radiology, University of California, San Diego, CA, United States
| | - Hayden Hansen
- Department of Radiology, University of California, San Diego, CA, United States
| | - Jared Baumgartner
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, United States
| | - Jaqueline Hernandez-Lucas
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, United States
| | - Sharon Nichols
- Department of Neurosciences, University of California, San Diego, CA, United States
| | - Joanna Jacobus
- Department of Psychiatry, University of California, San Diego, CA, United States
| | - Tao Song
- Department of Radiology, University of California, San Diego, CA, United States
| | - Imanuel Lerman
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, United States
| | - Maksim Bazhenov
- Department of Medicine, University of California, San Diego, CA, United States
| | - Giri P Krishnan
- Department of Medicine, University of California, San Diego, CA, United States
| | - Dewleen G Baker
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, United States
- Department of Psychiatry, University of California, San Diego, CA, United States
- VA Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, United States
| | - Ramesh Rao
- Department of Electrical and Computer Engineering, University of California, San Diego, CA, United States
| | - Roland R Lee
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, United States
- Department of Radiology, University of California, San Diego, CA, United States
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Pellegrini F, Delorme A, Nikulin V, Haufe S. Identifying good practices for detecting inter-regional linear functional connectivity from EEG. Neuroimage 2023; 277:120218. [PMID: 37307866 PMCID: PMC10374983 DOI: 10.1016/j.neuroimage.2023.120218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 05/12/2023] [Accepted: 06/02/2023] [Indexed: 06/14/2023] Open
Abstract
Aggregating voxel-level statistical dependencies between multivariate time series is an important intermediate step when characterising functional connectivity (FC) between larger brain regions. However, there are numerous ways in which voxel-level data can be aggregated into inter-regional FC, and the advantages of each of these approaches are currently unclear. In this study we generate ground-truth data and compare the performances of various pipelines that estimate directed and undirected linear phase-to-phase FC between regions. We test the ability of several existing and novel FC analysis pipelines to identify the true regions within which connectivity was simulated. We test various inverse modelling algorithms, strategies to aggregate time series within regions, and connectivity metrics. Furthermore, we investigate the influence of the number of interactions, the signal-to-noise ratio, the noise mix, the interaction time delay, and the number of active sources per region on the ability of detecting phase-to-phase FC. Throughout all simulated scenarios, lowest performance is obtained with pipelines involving the absolute value of coherency. Further, the combination of dynamic imaging of coherent sources (DICS) beamforming with directed FC metrics that aggregate information across multiple frequencies leads to unsatisfactory results. Pipelines that show promising results with our simulated pseudo-EEG data involve the following steps: (1) Source projection using the linearly-constrained minimum variance (LCMV) beamformer. (2) Principal component analysis (PCA) using the same fixed number of components within every region. (3) Calculation of the multivariate interaction measure (MIM) for every region pair to assess undirected phase-to-phase FC, or calculation of time-reversed Granger Causality (TRGC) to assess directed phase-to-phase FC. We formulate recommendations based on these results that may increase the validity of future experimental connectivity studies. We further introduce the free ROIconnect plugin for the EEGLAB toolbox that includes the recommended methods and pipelines that are presented here. We show an exemplary application of the best performing pipeline to the analysis of EEG data recorded during motor imagery.
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Affiliation(s)
- Franziska Pellegrini
- Charité-Universitätsmedizin Berlin, Charitéplatz 1, Berlin, 10117, Germany; Bernstein Center for Computational Neuroscience, Philippstraße 13, Berlin, 10117, Germany.
| | - Arnaud Delorme
- Swartz Center for Computational Neuroscience, 9500 Gilman Dr., La Jolla, California, 92903-0559, United States
| | - Vadim Nikulin
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences Leipzig, Stephanstraße 1a, Leipzig, 04103, Germany
| | - Stefan Haufe
- Charité-Universitätsmedizin Berlin, Charitéplatz 1, Berlin, 10117, Germany; Bernstein Center for Computational Neuroscience, Philippstraße 13, Berlin, 10117, Germany; Technische Universität Berlin, Straße des 17. Juni 135, Berlin, 10623, Germany; Physikalisch-Technische Bundesanstalt Braunschweig und Berlin, Abbestraße 2-12, Berlin, 10587, Germany
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7
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Huang MX, Harrington DL, Angeles-Quinto A, Ji Z, Robb-Swan A, Huang CW, Shen Q, Hansen H, Baumgartner J, Hernandez-Lucas J, Nichols S, Jacobus J, Song T, Lerman I, Bazhenov M, Krishnan GP, Baker DG, Rao R, Lee RR. EMG-projected MEG High-Resolution Source Imaging of Human Motor Execution: Brain-Muscle Coupling above Movement Frequencies. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.23.23291825. [PMID: 37425691 PMCID: PMC10327237 DOI: 10.1101/2023.06.23.23291825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Magnetoencephalography (MEG) is a non-invasive functional imaging technique for pre-surgical mapping. However, movement-related MEG functional mapping of primary motor cortex (M1) has been challenging in presurgical patients with brain lesions and sensorimotor dysfunction due to the large numbers of trails needed to obtain adequate signal to noise. Moreover, it is not fully understood how effective the brain communication is with the muscles at frequencies above the movement frequency and its harmonics. We developed a novel Electromyography (EMG)-projected MEG source imaging technique for localizing M1 during ~1 minute recordings of left and right self-paced finger movements (~1 Hz). High-resolution MEG source images were obtained by projecting M1 activity towards the skin EMG signal without trial averaging. We studied delta (1-4 Hz), theta (4-7 Hz), alpha (8-12 Hz), beta (15-30 Hz), and gamma (30-90 Hz) bands in 13 healthy participants (26 datasets) and two presurgical patients with sensorimotor dysfunction. In healthy participants, EMG-projected MEG accurately localized M1 with high accuracy in delta (100.0%), theta (100.0%), and beta (76.9%) bands, but not alpha (34.6%) and gamma (0.0%) bands. Except for delta, all other frequency bands were above the movement frequency and its harmonics. In both presurgical patients, M1 activity in the affected hemisphere was also accurately localized, despite highly irregular EMG movement patterns in one patient. Altogether, our EMG-projected MEG imaging approach is highly accurate and feasible for M1 mapping in presurgical patients. The results also provide insight into movement related brain-muscle coupling above the movement frequency and its harmonics.
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Affiliation(s)
- Ming-Xiong Huang
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiology, University of California, San Diego, CA, USA
- Department of Electrical and Computer Engineering, University of California, San Diego, CA, USA
| | - Deborah L. Harrington
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiology, University of California, San Diego, CA, USA
| | | | - Zhengwei Ji
- Department of Radiology, University of California, San Diego, CA, USA
| | - Ashley Robb-Swan
- Department of Radiology, University of California, San Diego, CA, USA
| | - Charles W. Huang
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Qian Shen
- Department of Radiology, University of California, San Diego, CA, USA
| | - Hayden Hansen
- Department of Radiology, University of California, San Diego, CA, USA
| | - Jared Baumgartner
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
| | | | - Sharon Nichols
- Department of Neurosciences, University of California, San Diego, CA, USA
| | - Joanna Jacobus
- Department of Psychiatry, University of California, San Diego, CA, USA
| | - Tao Song
- Department of Radiology, University of California, San Diego, CA, USA
| | - Imanuel Lerman
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
| | - Maksim Bazhenov
- Department of Medicine, University of California, San Diego, CA, USA
| | - Giri P Krishnan
- Department of Medicine, University of California, San Diego, CA, USA
| | - Dewleen G. Baker
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California, San Diego, CA, USA
- VA Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
| | - Ramesh Rao
- Department of Electrical and Computer Engineering, University of California, San Diego, CA, USA
| | - Roland R. Lee
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiology, University of California, San Diego, CA, USA
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Huang MX, Angeles-Quinto A, Robb-Swan A, De-la-Garza BG, Huang CW, Cheng CK, Hesselink JR, Bigler ED, Wilde EA, Vaida F, Troyer EA, Max JE. Assessing Pediatric Mild Traumatic Brain Injury and Its Recovery Using Resting-State Magnetoencephalography Source Magnitude Imaging and Machine Learning. J Neurotrauma 2023; 40:1112-1129. [PMID: 36884305 PMCID: PMC10259613 DOI: 10.1089/neu.2022.0220] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/09/2023] Open
Abstract
The objectives of this machine-learning (ML) resting-state magnetoencephalography (rs-MEG) study involving children with mild traumatic brain injury (mTBI) and orthopedic injury (OI) controls were to define a neural injury signature of mTBI and to delineate the pattern(s) of neural injury that determine behavioral recovery. Children ages 8-15 years with mTBI (n = 59) and OI (n = 39) from consecutive admissions to an emergency department were studied prospectively for parent-rated post-concussion symptoms (PCS) at: 1) baseline (average of 3 weeks post-injury) to measure pre-injury symptoms and also concurrent symptoms; and 2) at 3-months post-injury. rs-MEG was conducted at the baseline assessment. The ML algorithm predicted cases of mTBI versus OI with sensitivity of 95.5 ± 1.6% and specificity of 90.2 ± 2.7% at 3-weeks post-injury for the combined delta-gamma frequencies. The sensitivity and specificity were significantly better (p < 0.0001) for the combined delta-gamma frequencies compared with the delta-only and gamma-only frequencies. There were also spatial differences in rs-MEG activity between mTBI and OI groups in both delta and gamma bands in frontal and temporal lobe, as well as more widespread differences in the brain. The ML algorithm accounted for 84.5% of the variance in predicting recovery measured by PCS changes between 3 weeks and 3 months post-injury in the mTBI group, and this was significantly lower (p < 10-4) in the OI group (65.6%). Frontal lobe pole (higher) gamma activity was significantly (p < 0.001) associated with (worse) PCS recovery exclusively in the mTBI group. These findings demonstrate a neural injury signature of pediatric mTBI and patterns of mTBI-induced neural injury related to behavioral recovery.
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Affiliation(s)
- Ming-Xiong Huang
- Department of Radiology, University of California, San Diego, California, USA
- Radiology and Research Services, VA San Diego Healthcare System, San Diego, California, USA
| | - Annemarie Angeles-Quinto
- Department of Radiology, University of California, San Diego, California, USA
- Radiology and Research Services, VA San Diego Healthcare System, San Diego, California, USA
| | - Ashley Robb-Swan
- Department of Radiology, University of California, San Diego, California, USA
- Radiology and Research Services, VA San Diego Healthcare System, San Diego, California, USA
| | | | - Charles W. Huang
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Chung-Kuan Cheng
- Department of Computer Science and Engineering, University of California, San Diego, California, USA
| | - John R. Hesselink
- Department of Radiology, University of California, San Diego, California, USA
| | - Erin D. Bigler
- Department of Neurology, University of Utah, Salt Lake City, Utah, USA
| | | | - Florin Vaida
- Herbert Wertheim School of Public Health, Division of Biostatistics and Bioinformatics, University of California, San Diego, California, USA
| | - Emily A. Troyer
- Department of Psychiatry, University of California, San Diego, California, USA
| | - Jeffrey E. Max
- Department of Psychiatry, University of California, San Diego, California, USA
- Department of Psychiatry, Rady Children's Hospital, San Diego, California, USA
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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: 8] [Impact Index Per Article: 8.0] [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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10
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Edgar JC, Berman JI, Liu S, Chen YH, Huang M, Brodkin ES, Roberts TPL, Bloy L. Two mechanisms facilitate regional independence between brain regions based on an examination of alpha-band activity in healthy control adult males. Int J Psychophysiol 2022; 178:51-59. [PMID: 35718287 PMCID: PMC10155819 DOI: 10.1016/j.ijpsycho.2022.06.007] [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: 10/14/2021] [Revised: 04/26/2022] [Accepted: 06/10/2022] [Indexed: 11/29/2022]
Abstract
BACKGROUND At rest, 8 to 12 Hz alpha rhythms are the dominant rhythm in the brain, with a common peak alpha frequency (PAF = the frequency at which alpha generators show maximum power) observed across brain regions. Although a common PAF across brain regions should result in high between-region connectivity, especially connectivity measures assessing the phase-similarity between alpha generators, high inter-regional alpha connectivity has not been observed. The present study was conducted as an initial step toward identifying mechanisms that allow brain regions to maintain functional independence in the presence of a common PAF. METHODS MEG data were obtained from 16 healthy control male adults (mean age = 24 years; range 21 to 30 years). A task requiring participants to alternate between a 10 s eyes-closed condition and a 5 s eyes-open condition was used to drive parietal-occipital alpha generators, with the 10 s eyes-closed condition eliciting large-amplitude alpha activity and thus providing alpha measures with good signal-to-noise ratio for source localization. Alpha source-space measures were obtained using Vector-based Spatial-Temporal Analysis using L1-minimum-norm. In each participant, the four strongest parietal-occipital alpha generators were identified. Connectivity between sources was assessed via a measure of phase-based connectivity called inter-site phase clustering (ISPC). RESULTS Intra-class correlations (ICC) showed very high similarity in the average PAF (=computed using all eyes-closed data) between the four alpha sources (ICC single measure = 0.88, p < 0.001). Despite a common average PAF, across participants, significant ISPC was often observed no more than that expected by chance. Examination of the alpha time course data indicated that low ISPC was often due to instantaneous changes in alpha phase (phase slips). ISPC analyses removing data with phase slips indicated that low ISPC was also due to slight continuous changes in the alpha frequency, with frequency drift more likely in non-significant than significant ISPC trials. CONCLUSIONS The present exploratory effort suggested two processes underlying the lack of observed inter-regional alpha phase coherence that may help maintain regional functional independence even in the presence of a common PAF. In particular, although the alpha generators were observed to oscillate at the same rate on average, across time each alpha generator oscillated a little slower or faster, and about every one and a half seconds an alpha generator abruptly lost the beat. Because of this, functional independence among alpha generators (and thus brain regions) was the rule rather than the exception. Studies replicating these processes that allow brain regions to maintain functional independence, using different source localization methods and in different conditions (e.g., a true resting state), are warranted. IMPACT STATEMENT Using source localization to measure parietal-occipital alpha generator activity, two properties that limit between-region alpha functional connectivity are proposed. In particular, a model of alpha generator activity is offered where via transient phase slips occurring approximately every 1.5 s, as well as slight non-stationarity in the alpha frequency, brain regions retain a common alpha frequency while also maintaining regional identity and presumably functionality. Findings also suggest novel markers for use in studies examining changes in alpha activity across maturation as well as in studies examining alpha activity in patient populations where alpha abnormalities have been reported.
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Affiliation(s)
| | | | - Song Liu
- The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Yu-Han Chen
- The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Mingxiong Huang
- The University of California San Diego, Department of Radiology, San Diego, CA, USA; San Diego VA Healthcare System, Department of Radiology, San Diego, CA, USA
| | - Edward S Brodkin
- Department of Psychiatry, Center for Neurobiology and Behavior, Perelman School of Medicine at the University of Pennsylvania, Translational Research Laboratory, Philadelphia, PA, USA
| | | | - Luke Bloy
- The Children's Hospital of Philadelphia, Philadelphia, PA, USA
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11
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Zahran S, Mahmoudzadeh M, Wallois F, Betrouni N, Derambure P, Le Prado M, Palacios-Laloy A, Labyt E. Performance Analysis of Optically Pumped 4He Magnetometers vs. Conventional SQUIDs: From Adult to Infant Head Models. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22083093. [PMID: 35459077 PMCID: PMC9024855 DOI: 10.3390/s22083093] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 03/30/2022] [Accepted: 04/08/2022] [Indexed: 05/27/2023]
Abstract
Optically pumped magnetometers (OPMs) are new, room-temperature alternatives to superconducting quantum interference devices (SQUIDs) for measuring the brain's magnetic fields. The most used OPM in MagnetoEncephaloGraphy (MEG) are based on alkali atoms operating in the spin-exchange relaxation-free (SERF) regime. These sensors do not require cooling but have to be heated. Another kind of OPM, based on the parametric resonance of 4He atoms are operated at room temperature, suppressing the heat dissipation issue. They also have an advantageous bandwidth and dynamic range more suitable for MEG recordings. We quantitatively assessed the improvement (relative to a SQUID magnetometers array) in recording the magnetic field with a wearable 4He OPM-MEG system through data simulations. The OPM array and magnetoencephalography forward models were based on anatomical MRI data from an adult, a nine-year-old child, and 10 infants aged between one month and two years. Our simulations showed that a 4He OPMs array offers markedly better spatial specificity than a SQUID magnetometers array in various key performance areas (e.g., signal power, information content, and spatial resolution). Our results are also discussed regarding previous simulation results obtained for alkali OPM.
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Affiliation(s)
- Saeed Zahran
- INSERM, U1105, GRAMFC, Université de Picardie Jules Verne, CHU Sud, 80000 Amiens, France; (S.Z.); (M.M.); (F.W.)
| | - Mahdi Mahmoudzadeh
- INSERM, U1105, GRAMFC, Université de Picardie Jules Verne, CHU Sud, 80000 Amiens, France; (S.Z.); (M.M.); (F.W.)
| | - Fabrice Wallois
- INSERM, U1105, GRAMFC, Université de Picardie Jules Verne, CHU Sud, 80000 Amiens, France; (S.Z.); (M.M.); (F.W.)
| | - Nacim Betrouni
- INSERM, U1172, CHU de Lille, Université de Lille, Degenerative & Vascular Cognitive Disorders, 59000 Lille, France; (N.B.); (P.D.)
| | - Philippe Derambure
- INSERM, U1172, CHU de Lille, Université de Lille, Degenerative & Vascular Cognitive Disorders, 59000 Lille, France; (N.B.); (P.D.)
| | - Matthieu Le Prado
- Laboratoire d’Electronique et de Technologies de l’Information, CEA, 38054 Grenoble, France; (M.L.P.); (A.P.-L.)
- Mag4health, 9 Avenue Paul Verlaine, 38000 Grenoble, France
| | - Agustin Palacios-Laloy
- Laboratoire d’Electronique et de Technologies de l’Information, CEA, 38054 Grenoble, France; (M.L.P.); (A.P.-L.)
| | - Etienne Labyt
- Laboratoire d’Electronique et de Technologies de l’Information, CEA, 38054 Grenoble, France; (M.L.P.); (A.P.-L.)
- CEA Tech Hauts de France, 59000 Lille, France
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12
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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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13
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Individually optimized multi-channel tDCS for targeting somatosensory cortex. Clin Neurophysiol 2021; 134:9-26. [PMID: 34923283 DOI: 10.1016/j.clinph.2021.10.016] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 09/19/2021] [Accepted: 10/13/2021] [Indexed: 01/07/2023]
Abstract
OBJECTIVE Transcranial direct current stimulation (tDCS) is a non-invasive neuro-modulation technique that delivers current through the scalp by a pair of patch electrodes (2-Patch). This study proposes a new multi-channel tDCS (mc-tDCS) optimization method, the distributed constrained maximum intensity (D-CMI) approach. For targeting the P20/N20 somatosensory source at Brodmann area 3b, an integrated combined magnetoencephalography (MEG) and electroencephalography (EEG) source analysis is used with individualized skull conductivity calibrated realistic head modeling. METHODS Simulated electric fields (EF) for our new D-CMI method and the already known maximum intensity (MI), alternating direction method of multipliers (ADMM) and 2-Patch methods were produced and compared for the individualized P20/N20 somatosensory target for 10 subjects. RESULTS D-CMI and MI showed highest intensities parallel to the P20/N20 target compared to ADMM and 2-Patch, with ADMM achieving highest focality. D-CMI showed a slight reduction in intensity compared to MI while reducing side effects and skin level sensations by current distribution over multiple stimulation electrodes. CONCLUSION Individualized D-CMI montages are preferred for our follow up somatosensory experiment to provide a good balance between high current intensities at the target and reduced side effects and skin sensations. SIGNIFICANCE An integrated combined MEG and EEG source analysis with D-CMI montages for mc-tDCS stimulation potentially can improve control, reproducibility and reduce sensitivity differences between sham and real stimulations.
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14
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Ensemble multi-modal brain source localization using theory of evidence. Biomed Signal Process Control 2021. [DOI: 10.1016/j.bspc.2021.102668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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15
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Huang MX, Huang CW, Harrington DL, Nichols S, Robb-Swan A, Angeles-Quinto A, Le L, Rimmele C, Drake A, Song T, Huang JW, Clifford R, Ji Z, Cheng CK, Lerman I, Yurgil KA, Lee RR, Baker DG. Marked Increases in Resting-State MEG Gamma-Band Activity in Combat-Related Mild Traumatic Brain Injury. Cereb Cortex 2021; 30:283-295. [PMID: 31041986 DOI: 10.1093/cercor/bhz087] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2019] [Revised: 03/29/2019] [Accepted: 04/01/2019] [Indexed: 01/08/2023] Open
Abstract
Combat-related mild traumatic brain injury (mTBI) is a leading cause of sustained impairments in military service members and veterans. Recent animal studies show that GABA-ergic parvalbumin-positive interneurons are susceptible to brain injury, with damage causing abnormal increases in spontaneous gamma-band (30-80 Hz) activity. We investigated spontaneous gamma activity in individuals with mTBI using high-resolution resting-state magnetoencephalography source imaging. Participants included 25 symptomatic individuals with chronic combat-related blast mTBI and 35 healthy controls with similar combat experiences. Compared with controls, gamma activity was markedly elevated in mTBI participants throughout frontal, parietal, temporal, and occipital cortices, whereas gamma activity was reduced in ventromedial prefrontal cortex. Across groups, greater gamma activity correlated with poorer performances on tests of executive functioning and visuospatial processing. Many neurocognitive associations, however, were partly driven by the higher incidence of mTBI participants with both higher gamma activity and poorer cognition, suggesting that expansive upregulation of gamma has negative repercussions for cognition particularly in mTBI. This is the first human study to demonstrate abnormal resting-state gamma activity in mTBI. These novel findings suggest the possibility that abnormal gamma activities may be a proxy for GABA-ergic interneuron dysfunction and a promising neuroimaging marker of insidious mild head injuries.
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Affiliation(s)
- Ming-Xiong Huang
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Radiology, University of California, San Diego, CA, USA
| | - Charles W Huang
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Deborah L Harrington
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Radiology, University of California, San Diego, CA, USA
| | - Sharon Nichols
- Department of Neuroscience, University of California, San Diego, CA, USA
| | - Ashley Robb-Swan
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Radiology, University of California, San Diego, CA, USA
| | - Annemarie Angeles-Quinto
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Radiology, University of California, San Diego, CA, USA
| | - Lu Le
- ASPIRE Center, VASDHS Residential Rehabilitation Treatment Program, San Diego, CA, USA
| | - Carl Rimmele
- ASPIRE Center, VASDHS Residential Rehabilitation Treatment Program, San Diego, CA, USA
| | - Angela Drake
- Cedar Sinai Medical Group Chronic Pain Program, Beverly Hills, CA, USA
| | - Tao Song
- Department of Radiology, University of California, San Diego, CA, USA
| | - Jeffrey W Huang
- Department of Computer Science, Columbia University, New York, NY, USA
| | - Royce Clifford
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Psychiatry, University of California, San Diego, CA, USA.,VA Center of Excellence for Stress and Mental Health, San Diego, CA, USA
| | - Zhengwei Ji
- Department of Radiology, University of California, San Diego, CA, USA
| | - Chung-Kuan Cheng
- Department of Computer Science and Engineering, University of California, San Diego, CA, USA
| | - Imanuel Lerman
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
| | - Kate A Yurgil
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,VA Center of Excellence for Stress and Mental Health, San Diego, CA, USA.,Department of Psychological Sciences, Loyola University, New Orleans, LA, USA
| | - Roland R Lee
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Radiology, University of California, San Diego, CA, USA
| | - Dewleen G Baker
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Psychiatry, University of California, San Diego, CA, USA.,VA Center of Excellence for Stress and Mental Health, San Diego, CA, USA
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16
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Hämäläinen M, Huang M, Bowyer SM. Magnetoencephalography Signal Processing, Forward Modeling, Magnetoencephalography Inverse Source Imaging, and Coherence Analysis. Neuroimaging Clin N Am 2021; 30:125-143. [PMID: 32336402 DOI: 10.1016/j.nic.2020.02.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Magnetoencephalography (MEG) is a noninvasive functional imaging technique for the brain. MEG directly measures the magnetic signal due to neuronal activation in gray matter with high spatial localization accuracy. The first part of this article covers the overall concepts of MEG and the forward and inverse modeling techniques. It is followed by examples of analyzing evoked and resting-state MEG signals using a high-resolution MEG source imaging technique. Next, different techniques for connectivity and network analysis are reviewed with examples showing connectivity estimates from resting-state and epileptic activity.
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Affiliation(s)
- Matti Hämäläinen
- Department of Radiology, Athinoula A. Martinos Center, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA; Harvard Medical School, Boston, MA, USA
| | - Mingxiong Huang
- Department of Radiology, UCSD Radiology Imaging Lab, University of California, San Diego, 3510 Dunhill Street, San Diego, CA 92121, USA
| | - Susan M Bowyer
- Department of Neurology, MEG Lab, Henry Ford Hospital, 2799 West Grand Boulevard, CFP 079, Detroit, MI 48202, USA; Wayne State University School of Medicine, Detroit, MI, USA; Department of Physics, Oakland University, Rochester, MI, USA.
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17
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Piastra MC, Nüßing A, Vorwerk J, Clerc M, Engwer C, Wolters CH. A comprehensive study on electroencephalography and magnetoencephalography sensitivity to cortical and subcortical sources. Hum Brain Mapp 2021; 42:978-992. [PMID: 33156569 PMCID: PMC7856654 DOI: 10.1002/hbm.25272] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Revised: 10/19/2020] [Accepted: 10/21/2020] [Indexed: 12/31/2022] Open
Abstract
Signal-to-noise ratio (SNR) maps are a good way to visualize electroencephalography (EEG) and magnetoencephalography (MEG) sensitivity. SNR maps extend the knowledge about the modulation of EEG and MEG signals by source locations and orientations and can therefore help to better understand and interpret measured signals as well as source reconstruction results thereof. Our work has two main objectives. First, we investigated the accuracy and reliability of EEG and MEG finite element method (FEM)-based sensitivity maps for three different head models, namely an isotropic three and four-compartment and an anisotropic six-compartment head model. As a result, we found that ignoring the cerebrospinal fluid leads to an overestimation of EEG SNR values. Second, we examined and compared EEG and MEG SNR mappings for both cortical and subcortical sources and their modulation by source location and orientation. Our results for cortical sources show that EEG sensitivity is higher for radial and deep sources and MEG for tangential ones, which are the majority of sources. As to the subcortical sources, we found that deep sources with sufficient tangential source orientation are recordable by the MEG. Our work, which represents the first comprehensive study where cortical and subcortical sources are considered in highly detailed FEM-based EEG and MEG SNR mappings, sheds a new light on the sensitivity of EEG and MEG and might influence the decision of brain researchers or clinicians in their choice of the best modality for their experiment or diagnostics, respectively.
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Affiliation(s)
- Maria Carla Piastra
- Institute for Biomagnetism and BiosignalanalysisUniversity of MünsterMünsterGermany
- Institute for Computational and Applied MathematicsUniversity of MünsterMünsterGermany
- Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical CenterNijmegenThe Netherlands
| | - Andreas Nüßing
- Institute for Biomagnetism and BiosignalanalysisUniversity of MünsterMünsterGermany
- Institute for Computational and Applied MathematicsUniversity of MünsterMünsterGermany
| | - Johannes Vorwerk
- Institute of Electrical and Biomedical Engineering, University for Health SciencesMedical Informatics and TechnologyHall in TirolAustria
| | - Maureen Clerc
- Inria Sophia Antipolis‐MediterranéeBiotFrance
- Université Côte d'AzurNiceFrance
| | - Christian Engwer
- Institute for Computational and Applied MathematicsUniversity of MünsterMünsterGermany
- Cluster of Excellence EXC 1003, Cells in Motion, CiM, University of MünsterMünsterGermany
| | - Carsten H. Wolters
- Institute for Biomagnetism and BiosignalanalysisUniversity of MünsterMünsterGermany
- Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of MünsterMünsterGermany
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18
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Schrader S, Antonakakis M, Rampp S, Engwer C, Wolters CH. A novel method for calibrating head models to account for variability in conductivity and its evaluation in a sphere model. Phys Med Biol 2020; 65:245043. [PMID: 33113524 DOI: 10.1088/1361-6560/abc5aa] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
The accuracy in electroencephalography (EEG) and combined EEG and magnetoencephalography (MEG) source reconstructions as well as in optimized transcranial electric stimulation (TES) depends on the conductive properties assigned to the head model, and most importantly on individual skull conductivity. In this study, we present an automatic pipeline to calibrate head models with respect to skull conductivity based on the reconstruction of the P20/N20 response using somatosensory evoked potentials and fields. In order to validate in a well-controlled setup without interplay with numerical errors, we evaluate the accuracy of this algorithm in a 4-layer spherical head model using realistic noise levels as well as dipole sources at different eccentricities with strengths and orientations related to somatosensory experiments. Our results show that the reference skull conductivity can be reliably reconstructed for sources resembling the generator of the P20/N20 response. In case of erroneous assumptions on scalp conductivity, the resulting skull conductivity parameter counterbalances this effect, so that EEG source reconstructions using the fitted skull conductivity parameter result in lower errors than when using the standard value. We propose an automatized procedure to calibrate head models which only relies on non-invasive modalities that are available in a standard MEG laboratory, measures under in vivo conditions and in the low frequency range of interest. Calibrated head modeling can improve EEG and combined EEG/MEG source analysis as well as optimized TES.
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Affiliation(s)
- S Schrader
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
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19
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Antonakakis M, Schrader S, Aydin Ü, Khan A, Gross J, Zervakis M, Rampp S, Wolters CH. Inter-Subject Variability of Skull Conductivity and Thickness in Calibrated Realistic Head Models. Neuroimage 2020; 223:117353. [DOI: 10.1016/j.neuroimage.2020.117353] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 08/19/2020] [Accepted: 09/05/2020] [Indexed: 01/11/2023] Open
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20
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Zheng L, Sheng J, Cen Z, Teng P, Wang J, Wang Q, Lee RR, Luan G, Huang M, Gao JH. Enhanced Fast-VESTAL for Magnetoencephalography Source Imaging: From Theory to Clinical Application in Epilepsy. IEEE Trans Biomed Eng 2020; 68:793-806. [PMID: 32790623 DOI: 10.1109/tbme.2020.3016468] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
A novel magnetoencephalography source imaging approach called Fast Vector-based Spatio-Temporal Analysis (Fast-VESTAL) has been successfully applied in creating source images from evoked and resting-state data from both healthy subjects and individuals with neurological and/or psychiatric disorders, but its reconstructed source images may show false-positive activations, especially under low signal-to-noise ratio conditions. Here, to effectively reduce false-positive artifacts, we introduced an enhanced Fast-VESTAL (eFast-VESTAL) approach that adopts generalized second-order cone programming. We compared the spatiotemporal characteristics of the eFast-VESTAL approach to those of the popular distributed source approaches (e.g., the minimum L2-norm/ mixed-norm methods) using computer simulations and auditory experiments. More importantly, we applied eFast-VESTAL to the presurgical evaluation of epilepsy. Our results demonstrated that eFast-VESTAL exhibited a lower dipole localization error and/or a higher correlation coefficient (CC) between the estimated source time series and ground truth under various conditions of source waveforms. Experimentally, eFast-VESTAL displayed more focal activation maps and a higher CC between the raw and predicted sensor data in response to auditory stimulation. Notably, eFast-VESTAL was the most accurate method for noninvasively detecting the epileptic zones determined using more invasive stereo-electroencephalography in the comparison.
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Huang MX, Nichols S, Robb-Swan A, Angeles-Quinto A, Harrington DL, Drake A, Huang CW, Song T, Diwakar M, Risbrough VB, Matthews S, Clifford R, Cheng CK, Huang JW, Sinha A, Yurgil KA, Ji Z, Lerman I, Lee RR, Baker DG. MEG Working Memory N-Back Task Reveals Functional Deficits in Combat-Related Mild Traumatic Brain Injury. Cereb Cortex 2020; 29:1953-1968. [PMID: 29668852 DOI: 10.1093/cercor/bhy075] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2017] [Revised: 03/11/2018] [Accepted: 03/13/2018] [Indexed: 12/24/2022] Open
Abstract
Combat-related mild traumatic brain injury (mTBI) is a leading cause of sustained cognitive impairment in military service members and Veterans. However, the mechanism of persistent cognitive deficits including working memory (WM) dysfunction is not fully understood in mTBI. Few studies of WM deficits in mTBI have taken advantage of the temporal and frequency resolution afforded by electromagnetic measurements. Using magnetoencephalography (MEG) and an N-back WM task, we investigated functional abnormalities in combat-related mTBI. Study participants included 25 symptomatic active-duty service members or Veterans with combat-related mTBI and 20 healthy controls with similar combat experiences. MEG source-magnitude images were obtained for alpha (8-12 Hz), beta (15-30 Hz), gamma (30-90 Hz), and low-frequency (1-7 Hz) bands. Compared with healthy combat controls, mTBI participants showed increased MEG signals across frequency bands in frontal pole (FP), ventromedial prefrontal cortex, orbitofrontal cortex (OFC), and anterior dorsolateral prefrontal cortex (dlPFC), but decreased MEG signals in anterior cingulate cortex. Hyperactivations in FP, OFC, and anterior dlPFC were associated with slower reaction times. MEG activations in lateral FP also negatively correlated with performance on tests of letter sequencing, verbal fluency, and digit symbol coding. The profound hyperactivations from FP suggest that FP is particularly vulnerable to combat-related mTBI.
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Affiliation(s)
- Ming-Xiong Huang
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Radiology, University of California, San Diego, CA, USA
| | - Sharon Nichols
- Department of Neuroscience, University of California, San Diego, CA, USA
| | - Ashley Robb-Swan
- Department of Radiology, University of California, San Diego, CA, USA
| | | | - Deborah L Harrington
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Radiology, University of California, San Diego, CA, USA
| | - Angela Drake
- Cedar Sinai Medical Group Chronic Pain Program, Beverly Hills, CA, USA
| | - Charles W Huang
- Department of Bioengineering, University of California, San Diego, CA, USA
| | - Tao Song
- Department of Radiology, University of California, San Diego, CA, USA
| | - Mithun Diwakar
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Victoria B Risbrough
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Psychiatry, University of California, San Diego, CA, USA.,VA Center of Excellence for Stress and Mental Health, San Diego, CA, USA
| | - Scott Matthews
- ASPIRE Center, VASDHS Residential Rehabilitation Treatment Program, San Diego, CA, USA
| | - Royce Clifford
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Psychiatry, University of California, San Diego, CA, USA.,VA Center of Excellence for Stress and Mental Health, San Diego, CA, USA
| | - Chung-Kuan Cheng
- Department of Computer Science and Engineering, University of California, San Diego, CA, USA
| | | | - Anusha Sinha
- California Institute of Technology, Pasadena, CA, USA
| | - Kate A Yurgil
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,VA Center of Excellence for Stress and Mental Health, San Diego, CA, USA.,Loyola University New Orleans, LA, USA
| | - Zhengwei Ji
- Department of Radiology, University of California, San Diego, CA, USA
| | - Imanuel Lerman
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
| | - Roland R Lee
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Radiology, University of California, San Diego, CA, USA
| | - Dewleen G Baker
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Psychiatry, University of California, San Diego, CA, USA.,VA Center of Excellence for Stress and Mental Health, San Diego, CA, USA
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22
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Huang MX, Robb Swan A, Angeles Quinto A, Huang JW, De-la-Garza BG, Huang CW, Hesselink JR, Bigler ED, Wilde EA, Max JE. Resting-State Magnetoencephalography Source Imaging Pilot Study in Children with Mild Traumatic Brain Injury. J Neurotrauma 2019; 37:994-1001. [PMID: 31724480 DOI: 10.1089/neu.2019.6417] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Mild traumatic brain injury (mTBI) accounts for the vast majority of all pediatric TBI. An important minority of children who have suffered an mTBI have enduring cognitive and emotional symptoms. However, the mechanisms of chronic symptoms in children with pediatric mTBI are not fully understood. This is in part due to the limited sensitivity of conventional neuroimaging technologies. The present study examined resting-state magnetoencephalography (rs-MEG) source images in 12 children who had mTBI and 12 age-matched control children. The rs-MEG exams were performed in children with mTBI 6 months after injury when they reported no clinically significant post-injury psychiatric changes and few if any somatic sensorimotor symptoms but did report cognitive symptoms. MEG source magnitude images were obtained for different frequency bands in alpha (8-12 Hz), beta (15-30 Hz), gamma (30-90 Hz), and low-frequency (1-7 Hz) bands. In contrast to the control participants, rs-MEG source imaging in the children with mTBI showed: 1) hyperactivity from the bilateral insular cortices in alpha, beta, and low-frequency bands, from the left amygdala in alpha band, and from the left precuneus in beta band; 2) hypoactivity from the bilateral dorsolateral prefrontal cortices (dlPFC) in alpha and beta bands, from the ventromedial prefrontal cortex (vmPFC) in beta band, from the ventrolateral prefrontal cortex (vlPFC) in gamma band, from the anterior cingulate cortex (ACC) in alpha band, and from the right precuneus in alpha band. The present study showed that MEG source imaging technique revealed abnormalities in the resting-state electromagnetic signals from the children with mTBI.
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Affiliation(s)
- Ming-Xiong Huang
- Department of Radiology, University of California, San Diego, California.,Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California
| | - Ashley Robb Swan
- Department of Radiology, University of California, San Diego, California.,Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California
| | - Annemarie Angeles Quinto
- Department of Radiology, University of California, San Diego, California.,Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California
| | - Jeffrey W Huang
- Department of Computer Sciences, Columbia University, New York, New York
| | | | - Charles W Huang
- Department of Bioengineering, Stanford University, Stanford, California
| | - John R Hesselink
- Department of Radiology, University of California, San Diego, California
| | - Erin D Bigler
- Department of Neurology, University of Utah, Salt Lake City, Utah
| | | | - Jeffrey E Max
- Department of Psychiatry, University of California, San Diego, California.,Department of Psychiatry, Rady Children's Hospital, San Diego, California
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23
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Plummer C, Vogrin SJ, Woods WP, Murphy MA, Cook MJ, Liley DTJ. Interictal and ictal source localization for epilepsy surgery using high-density EEG with MEG: a prospective long-term study. Brain 2019; 142:932-951. [PMID: 30805596 PMCID: PMC6459284 DOI: 10.1093/brain/awz015] [Citation(s) in RCA: 81] [Impact Index Per Article: 16.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2018] [Revised: 10/07/2018] [Accepted: 12/05/2018] [Indexed: 11/17/2022] Open
Abstract
Drug-resistant focal epilepsy is a major clinical problem and surgery is under-used. Better non-invasive techniques for epileptogenic zone localization are needed when MRI shows no lesion or an extensive lesion. The problem is interictal and ictal localization before propagation from the epileptogenic zone. High-density EEG (HDEEG) and magnetoencephalography (MEG) offer millisecond-order temporal resolution to address this but co-acquisition is challenging, ictal MEG studies are rare, long-term prospective studies are lacking, and fundamental questions remain. Should HDEEG-MEG discharges be assessed independently [electroencephalographic source localization (ESL), magnetoencephalographic source localization (MSL)] or combined (EMSL) for source localization? Which phase of the discharge best characterizes the epileptogenic zone (defined by intracranial EEG and surgical resection relative to outcome)? Does this differ for interictal and ictal discharges? Does MEG detect mesial temporal lobe discharges? Thirteen patients (10 non-lesional, three extensive-lesional) underwent synchronized HDEEG-MEG (72–94 channel EEG, 306-sensor MEG). Source localization (standardized low-resolution tomographic analysis with MRI patient-individualized boundary-element method) was applied to averaged interictal epileptiform discharges (IED) and ictal discharges at three phases: ‘early-phase’ (first latency 90% explained variance), ‘mid-phase’ (first of 50% rising-phase, 50% mean global field power), ‘late-phase’ (negative peak). ‘Earliest-solution’ was the first of the three early-phase solutions (ESL, MSL, EMSL). Prospective follow-up was 3–21 (median 12) months before surgery, 14–39 (median 21) months after surgery. IEDs (n = 1474) were recorded, seen in: HDEEG only, 626 (42%); MEG only, 232 (16%); and both 616 (42%). Thirty-three seizures were captured, seen in: HDEEG only, seven (21%); MEG only, one (3%); and both 25 (76%). Intracranial EEG was done in nine patients. Engel scores were I (9/13, 69%), II (2/13,15%), and III (2/13). MEG detected baso-mesial temporal lobe epileptogenic zone sources. Epileptogenic zone OR [odds ratio(s)] were significantly higher for earliest-solution versus early-phase IED-surgical resection and earliest-solution versus all mid-phase and late-phase solutions. ESL outperformed EMSL for ictal-surgical resection [OR 3.54, 95% confidence interval (CI) 1.09–11.55, P = 0.036]. MSL outperformed EMSL for IED-intracranial EEG (OR 4.67, 95% CI 1.19–18.34, P = 0.027). ESL outperformed MSL for ictal-surgical resection (OR 3.73, 95% CI 1.16–12.03, P = 0.028) but was outperformed by MSL for IED-intracranial EEG (OR 0.18, 95% CI 0.05–0.73, P = 0.017). Thus, (i) HDEEG and MEG source solutions more accurately localize the epileptogenic zone at the earliest resolvable phase of interictal and ictal discharges, not mid-phase (as is common practice) or late peak-phase (when signal-to-noise ratios are maximal); (ii) from empirical observation of the differential timing of HDEEG and MEG discharges and based on the superiority of ESL plus MSL over either modality alone and over EMSL, concurrent HDEEG-MEG signals should be assessed independently, not combined; (iii) baso-mesial temporal lobe sources are detectable by MEG; and (iv) MEG is not ‘more accurate’ than HDEEG—emphasis is best placed on the earliest signal (whether HDEEG or MEG) amenable to source localization. Our findings challenge current practice and our reliance on invasive monitoring in these patients.
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Affiliation(s)
- Chris Plummer
- Department of Neurology, St Vincent's Hospital, Fitzroy, Australia.,School of Health Sciences, Swinburne University of Technology, Hawthorn, Australia.,Department of Medicine, University of Melbourne, Parkville, Australia
| | - Simon J Vogrin
- Department of Neurology, St Vincent's Hospital, Fitzroy, Australia.,School of Health Sciences, Swinburne University of Technology, Hawthorn, Australia.,Department of Medicine, University of Melbourne, Parkville, Australia
| | - William P Woods
- School of Health Sciences, Swinburne University of Technology, Hawthorn, Australia
| | - Michael A Murphy
- Department of Neurology, St Vincent's Hospital, Fitzroy, Australia.,Department of Medicine, University of Melbourne, Parkville, Australia
| | - Mark J Cook
- Department of Neurology, St Vincent's Hospital, Fitzroy, Australia.,Department of Medicine, University of Melbourne, Parkville, Australia.,Graeme Clark Institute of Biomedical Engineering, University of Melbourne, Parkville, Australia
| | - David T J Liley
- School of Health Sciences, Swinburne University of Technology, Hawthorn, Australia.,Department of Medicine, University of Melbourne, Parkville, Australia.,Centre for Human Psychopharmacology, Swinburne University of Technology, Hawthorn, Australia
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24
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Wearable neuroimaging: Combining and contrasting magnetoencephalography and electroencephalography. Neuroimage 2019; 201:116099. [PMID: 31419612 PMCID: PMC8235152 DOI: 10.1016/j.neuroimage.2019.116099] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Revised: 06/27/2019] [Accepted: 08/12/2019] [Indexed: 02/04/2023] Open
Abstract
One of the most severe limitations of functional neuroimaging techniques, such as magnetoencephalography (MEG), is that participants must maintain a fixed head position during data acquisition. This imposes restrictions on the characteristics of the experimental cohorts that can be scanned and the experimental questions that can be addressed. For these reasons, the use of 'wearable' neuroimaging, in which participants can move freely during scanning, is attractive. The most successful example of wearable neuroimaging is electroencephalography (EEG), which employs lightweight and flexible instrumentation that makes it useable in almost any experimental setting. However, EEG has major technical limitations compared to MEG, and therefore the development of wearable MEG, or hybrid MEG/EEG systems, is a compelling prospect. In this paper, we combine and compare EEG and MEG measurements, the latter made using a new generation of optically-pumped magnetometers (OPMs). We show that these new second generation commercial OPMs, can be mounted on the scalp in an 'EEG-like' cap, enabling the acquisition of high fidelity electrophysiological measurements. We show that these sensors can be used in conjunction with conventional EEG electrodes, offering the potential for the development of hybrid MEG/EEG systems. We compare concurrently measured signals, showing that, whilst both modalities offer high quality data in stationary subjects, OPM-MEG measurements are less sensitive to artefacts produced when subjects move. Finally, we show using simulations that OPM-MEG offers a fundamentally better spatial specificity than EEG. The demonstrated technology holds the potential to revolutionise the utility of functional brain imaging, exploiting the flexibility of wearable systems to facilitate hitherto impractical experimental paradigms.
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25
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Lyu B, Choi HS, Marslen-Wilson WD, Clarke A, Randall B, Tyler LK. Neural dynamics of semantic composition. Proc Natl Acad Sci U S A 2019; 116:21318-21327. [PMID: 31570590 PMCID: PMC6800340 DOI: 10.1073/pnas.1903402116] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
Human speech comprehension is remarkable for its immediacy and rapidity. The listener interprets an incrementally delivered auditory input, millisecond by millisecond as it is heard, in terms of complex multilevel representations of relevant linguistic and nonlinguistic knowledge. Central to this process are the neural computations involved in semantic combination, whereby the meanings of words are combined into more complex representations, as in the combination of a verb and its following direct object (DO) noun (e.g., "eat the apple"). These combinatorial processes form the backbone for incremental interpretation, enabling listeners to integrate the meaning of each word as it is heard into their dynamic interpretation of the current utterance. Focusing on the verb-DO noun relationship in simple spoken sentences, we applied multivariate pattern analysis and computational semantic modeling to source-localized electro/magnetoencephalographic data to map out the specific representational constraints that are constructed as each word is heard, and to determine how these constraints guide the interpretation of subsequent words in the utterance. Comparing context-independent semantic models of the DO noun with contextually constrained noun models reflecting the semantic properties of the preceding verb, we found that only the contextually constrained model showed a significant fit to the brain data. Pattern-based measures of directed connectivity across the left hemisphere language network revealed a continuous information flow among temporal, inferior frontal, and inferior parietal regions, underpinning the verb's modification of the DO noun's activated semantics. These results provide a plausible neural substrate for seamless real-time incremental interpretation on the observed millisecond time scales.
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Affiliation(s)
- Bingjiang Lyu
- Centre for Speech, Language and the Brain, Department of Psychology, University of Cambridge, CB2 3EB Cambridge, United Kingdom
| | - Hun S Choi
- Centre for Speech, Language and the Brain, Department of Psychology, University of Cambridge, CB2 3EB Cambridge, United Kingdom
| | - William D Marslen-Wilson
- Centre for Speech, Language and the Brain, Department of Psychology, University of Cambridge, CB2 3EB Cambridge, United Kingdom
| | - Alex Clarke
- Centre for Speech, Language and the Brain, Department of Psychology, University of Cambridge, CB2 3EB Cambridge, United Kingdom
| | - Billi Randall
- Centre for Speech, Language and the Brain, Department of Psychology, University of Cambridge, CB2 3EB Cambridge, United Kingdom
| | - Lorraine K Tyler
- Centre for Speech, Language and the Brain, Department of Psychology, University of Cambridge, CB2 3EB Cambridge, United Kingdom
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26
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Antonakakis M, Schrader S, Wollbrink A, Oostenveld R, Rampp S, Haueisen J, Wolters CH. The effect of stimulation type, head modeling, and combined EEG and MEG on the source reconstruction of the somatosensory P20/N20 component. Hum Brain Mapp 2019; 40:5011-5028. [PMID: 31397966 PMCID: PMC6865415 DOI: 10.1002/hbm.24754] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2019] [Revised: 07/23/2019] [Accepted: 07/28/2019] [Indexed: 11/06/2022] Open
Abstract
Modeling and experimental parameters influence the Electro- (EEG) and Magnetoencephalography (MEG) source analysis of the somatosensory P20/N20 component. In a sensitivity group study, we compare P20/N20 source analysis due to different stimulation type (Electric-Wrist [EW], Braille-Tactile [BT], or Pneumato-Tactile [PT]), measurement modality (combined EEG/MEG - EMEG, EEG, or MEG) and head model (standard or individually skull-conductivity calibrated including brain anisotropic conductivity). Considerable differences between pairs of stimulation types occurred (EW-BT: 8.7 ± 3.3 mm/27.1° ± 16.4°, BT-PT: 9 ± 5 mm/29.9° ± 17.3°, and EW-PT: 9.8 ± 7.4 mm/15.9° ± 16.5° and 75% strength reduction of BT or PT when compared to EW) regardless of the head model used. EMEG has nearly no localization differences to MEG, but large ones to EEG (16.1 ± 4.9 mm), while source orientation differences are non-negligible to both EEG (14° ± 3.7°) and MEG (12.5° ± 10.9°). Our calibration results show a considerable inter-subject variability (3.1-14 mS/m) for skull conductivity. The comparison due to different head model show localization differences smaller for EMEG (EW: 3.4 ± 2.4 mm, BT: 3.7 ± 3.4 mm, and PT: 5.9 ± 6.8 mm) than for EEG (EW: 8.6 ± 8.3 mm, BT: 11.8 ± 6.2 mm, and PT: 10.5 ± 5.3 mm), while source orientation differences for EMEG (EW: 15.4° ± 6.3°, BT: 25.7° ± 15.2° and PT: 14° ± 11.5°) and EEG (EW: 14.6° ± 9.5°, BT: 16.3° ± 11.1° and PT: 12.9° ± 8.9°) are in the same range. Our results show that stimulation type, modality and head modeling all have a non-negligible influence on the source reconstruction of the P20/N20 component. The complementary information of both modalities in EMEG can be exploited on the basis of detailed and individualized head models.
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Affiliation(s)
- Marios Antonakakis
- Institute for Biomagnetism and Biosignalanalysis, University of Muenster, Muenster, Germany
| | - Sophie Schrader
- Institute for Biomagnetism and Biosignalanalysis, University of Muenster, Muenster, Germany
| | - Andreas Wollbrink
- Institute for Biomagnetism and Biosignalanalysis, University of Muenster, Muenster, Germany
| | - Robert Oostenveld
- Donders Institute, Radboud University, Nijmegen, Netherlands.,Karolinska Institute, Stockholm, Sweden
| | - Stefan Rampp
- Department of Neurosurgery, University Hospital Erlangen, Erlangen, Germany
| | - Jens Haueisen
- Institute for Biomedical Engineering and Informatics, Technical University of Ilmenau, Ilmenau, Germany
| | - Carsten H Wolters
- Institute for Biomagnetism and Biosignalanalysis, University of Muenster, Muenster, Germany.,Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, Münster, Germany
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27
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Vorwerk J, Aydin Ü, Wolters CH, Butson CR. Influence of Head Tissue Conductivity Uncertainties on EEG Dipole Reconstruction. Front Neurosci 2019; 13:531. [PMID: 31231178 PMCID: PMC6558618 DOI: 10.3389/fnins.2019.00531] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2019] [Accepted: 05/08/2019] [Indexed: 11/28/2022] Open
Abstract
Reliable EEG source analysis depends on sufficiently detailed and accurate head models. In this study, we investigate how uncertainties inherent to the experimentally determined conductivity values of the different conductive compartments influence the results of EEG source analysis. In a single source scenario, the superficial and focal somatosensory P20/N20 component, we analyze the influence of varying conductivities on dipole reconstructions using a generalized polynomial chaos (gPC) approach. We find that in particular the conductivity uncertainties for skin and skull have a significant influence on the EEG inverse solution, leading to variations in source localization by several centimeters. The conductivity uncertainties for gray and white matter were found to have little influence on the source localization, but a strong influence on the strength and orientation of the reconstructed source, respectively. As the CSF conductivity is most accurately determined of all conductivities in a realistic head model, CSF conductivity uncertainties had a negligible influence on the source reconstruction. This small uncertainty is a further benefit of distinguishing the CSF in realistic volume conductor models.
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Affiliation(s)
- Johannes Vorwerk
- Scientific Computing & Imaging (SCI) Institute, University of Utah, Salt Lake City, UT, United States
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
- Institute of Electrical and Biomedical Engineering, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
| | - Ümit Aydin
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
- Multimodal Functional Imaging Lab, Department of Physics and PERFORM Centre, Concordia University, Montreal, QC, Canada
| | - 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
| | - Christopher R. Butson
- Scientific Computing & Imaging (SCI) Institute, University of Utah, Salt Lake City, UT, United States
- Departments of Biomedical Engineering, Neurology, and Psychiatry, University of Utah, Salt Lake City, UT, United States
- Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, Salt Lake City, UT, United States
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28
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Duez L, Tankisi H, Hansen PO, Sidenius P, Sabers A, Pinborg LH, Fabricius M, Rásonyi G, Rubboli G, Pedersen B, Leffers AM, Uldall P, Jespersen B, Brennum J, Henriksen OM, Fuglsang-Frederiksen A, Beniczky S. Electromagnetic source imaging in presurgical workup of patients with epilepsy: A prospective study. Neurology 2019; 92:e576-e586. [PMID: 30610090 PMCID: PMC6382058 DOI: 10.1212/wnl.0000000000006877] [Citation(s) in RCA: 61] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2018] [Accepted: 10/02/2018] [Indexed: 11/23/2022] Open
Abstract
Objective To determine the diagnostic accuracy and clinical utility of electromagnetic source imaging (EMSI) in presurgical evaluation of patients with epilepsy. Methods We prospectively recorded magnetoencephalography (MEG) simultaneously with EEG and performed EMSI, comprising electric source imaging, magnetic source imaging, and analysis of combined MEG-EEG datasets, using 2 different software packages. As reference standard for irritative zone (IZ) and seizure onset zone (SOZ), we used intracranial recordings and for localization accuracy, outcome 1 year after operation. Results We included 141 consecutive patients. EMSI showed localized epileptiform discharges in 94 patients (67%). Most of the epileptiform discharge clusters (72%) were identified by both modalities, 15% only by EEG, and 14% only by MEG. Agreement was substantial between inverse solutions and moderate between software packages. EMSI provided new information that changed the management plan in 34% of the patients, and these changes were useful in 80%. Depending on the method, EMSI had a concordance of 53% to 89% with IZ and 35% to 73% with SOZ. Localization accuracy of EMSI was between 44% and 57%, which was not significantly different from MRI (49%–76%) and PET (54%–85%). Combined EMSI achieved significantly higher odds ratio compared to electric source imaging and magnetic source imaging. Conclusion EMSI has accuracy similar to established imaging methods and provides clinically useful, new information in 34% of the patients. Classification of evidence This study provides Class IV evidence that EMSI had a concordance of 53%–89% and 35%–73% (depending on analysis) for the localization of epileptic focus as compared with intracranial recordings—IZ and SOZ, respectively.
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Affiliation(s)
- Lene Duez
- From the Departments of Clinical Neurophysiology (L.D., H.T., P.O.H., A.F.-F., S.B.) and Neurology (P.S.), Aarhus University Hospital; Departments of Neurology (A.S., L.H.P.), Clinical Neurophysiology (M.F., G. Rásonyi), Pediatrics, Child Neurology (P.U.), Neurosurgery (B.J., J.B.), and Clinical Physiology, Nuclear Medicine and PET (O.M.H.), Copenhagen University Hospital Rigshospitalet; Danish Epilepsy Centre (G. Rubboli, B.P., S.B.), Dianalund; and Department of Diagnostic Radiology (A.-M.L.), Hvidovre Hospital, Denmark
| | - Hatice Tankisi
- From the Departments of Clinical Neurophysiology (L.D., H.T., P.O.H., A.F.-F., S.B.) and Neurology (P.S.), Aarhus University Hospital; Departments of Neurology (A.S., L.H.P.), Clinical Neurophysiology (M.F., G. Rásonyi), Pediatrics, Child Neurology (P.U.), Neurosurgery (B.J., J.B.), and Clinical Physiology, Nuclear Medicine and PET (O.M.H.), Copenhagen University Hospital Rigshospitalet; Danish Epilepsy Centre (G. Rubboli, B.P., S.B.), Dianalund; and Department of Diagnostic Radiology (A.-M.L.), Hvidovre Hospital, Denmark
| | - Peter Orm Hansen
- From the Departments of Clinical Neurophysiology (L.D., H.T., P.O.H., A.F.-F., S.B.) and Neurology (P.S.), Aarhus University Hospital; Departments of Neurology (A.S., L.H.P.), Clinical Neurophysiology (M.F., G. Rásonyi), Pediatrics, Child Neurology (P.U.), Neurosurgery (B.J., J.B.), and Clinical Physiology, Nuclear Medicine and PET (O.M.H.), Copenhagen University Hospital Rigshospitalet; Danish Epilepsy Centre (G. Rubboli, B.P., S.B.), Dianalund; and Department of Diagnostic Radiology (A.-M.L.), Hvidovre Hospital, Denmark
| | - Per Sidenius
- From the Departments of Clinical Neurophysiology (L.D., H.T., P.O.H., A.F.-F., S.B.) and Neurology (P.S.), Aarhus University Hospital; Departments of Neurology (A.S., L.H.P.), Clinical Neurophysiology (M.F., G. Rásonyi), Pediatrics, Child Neurology (P.U.), Neurosurgery (B.J., J.B.), and Clinical Physiology, Nuclear Medicine and PET (O.M.H.), Copenhagen University Hospital Rigshospitalet; Danish Epilepsy Centre (G. Rubboli, B.P., S.B.), Dianalund; and Department of Diagnostic Radiology (A.-M.L.), Hvidovre Hospital, Denmark
| | - Anne Sabers
- From the Departments of Clinical Neurophysiology (L.D., H.T., P.O.H., A.F.-F., S.B.) and Neurology (P.S.), Aarhus University Hospital; Departments of Neurology (A.S., L.H.P.), Clinical Neurophysiology (M.F., G. Rásonyi), Pediatrics, Child Neurology (P.U.), Neurosurgery (B.J., J.B.), and Clinical Physiology, Nuclear Medicine and PET (O.M.H.), Copenhagen University Hospital Rigshospitalet; Danish Epilepsy Centre (G. Rubboli, B.P., S.B.), Dianalund; and Department of Diagnostic Radiology (A.-M.L.), Hvidovre Hospital, Denmark
| | - Lars H Pinborg
- From the Departments of Clinical Neurophysiology (L.D., H.T., P.O.H., A.F.-F., S.B.) and Neurology (P.S.), Aarhus University Hospital; Departments of Neurology (A.S., L.H.P.), Clinical Neurophysiology (M.F., G. Rásonyi), Pediatrics, Child Neurology (P.U.), Neurosurgery (B.J., J.B.), and Clinical Physiology, Nuclear Medicine and PET (O.M.H.), Copenhagen University Hospital Rigshospitalet; Danish Epilepsy Centre (G. Rubboli, B.P., S.B.), Dianalund; and Department of Diagnostic Radiology (A.-M.L.), Hvidovre Hospital, Denmark
| | - Martin Fabricius
- From the Departments of Clinical Neurophysiology (L.D., H.T., P.O.H., A.F.-F., S.B.) and Neurology (P.S.), Aarhus University Hospital; Departments of Neurology (A.S., L.H.P.), Clinical Neurophysiology (M.F., G. Rásonyi), Pediatrics, Child Neurology (P.U.), Neurosurgery (B.J., J.B.), and Clinical Physiology, Nuclear Medicine and PET (O.M.H.), Copenhagen University Hospital Rigshospitalet; Danish Epilepsy Centre (G. Rubboli, B.P., S.B.), Dianalund; and Department of Diagnostic Radiology (A.-M.L.), Hvidovre Hospital, Denmark
| | - György Rásonyi
- From the Departments of Clinical Neurophysiology (L.D., H.T., P.O.H., A.F.-F., S.B.) and Neurology (P.S.), Aarhus University Hospital; Departments of Neurology (A.S., L.H.P.), Clinical Neurophysiology (M.F., G. Rásonyi), Pediatrics, Child Neurology (P.U.), Neurosurgery (B.J., J.B.), and Clinical Physiology, Nuclear Medicine and PET (O.M.H.), Copenhagen University Hospital Rigshospitalet; Danish Epilepsy Centre (G. Rubboli, B.P., S.B.), Dianalund; and Department of Diagnostic Radiology (A.-M.L.), Hvidovre Hospital, Denmark
| | - Guido Rubboli
- From the Departments of Clinical Neurophysiology (L.D., H.T., P.O.H., A.F.-F., S.B.) and Neurology (P.S.), Aarhus University Hospital; Departments of Neurology (A.S., L.H.P.), Clinical Neurophysiology (M.F., G. Rásonyi), Pediatrics, Child Neurology (P.U.), Neurosurgery (B.J., J.B.), and Clinical Physiology, Nuclear Medicine and PET (O.M.H.), Copenhagen University Hospital Rigshospitalet; Danish Epilepsy Centre (G. Rubboli, B.P., S.B.), Dianalund; and Department of Diagnostic Radiology (A.-M.L.), Hvidovre Hospital, Denmark
| | - Birthe Pedersen
- From the Departments of Clinical Neurophysiology (L.D., H.T., P.O.H., A.F.-F., S.B.) and Neurology (P.S.), Aarhus University Hospital; Departments of Neurology (A.S., L.H.P.), Clinical Neurophysiology (M.F., G. Rásonyi), Pediatrics, Child Neurology (P.U.), Neurosurgery (B.J., J.B.), and Clinical Physiology, Nuclear Medicine and PET (O.M.H.), Copenhagen University Hospital Rigshospitalet; Danish Epilepsy Centre (G. Rubboli, B.P., S.B.), Dianalund; and Department of Diagnostic Radiology (A.-M.L.), Hvidovre Hospital, Denmark
| | - Anne-Mette Leffers
- From the Departments of Clinical Neurophysiology (L.D., H.T., P.O.H., A.F.-F., S.B.) and Neurology (P.S.), Aarhus University Hospital; Departments of Neurology (A.S., L.H.P.), Clinical Neurophysiology (M.F., G. Rásonyi), Pediatrics, Child Neurology (P.U.), Neurosurgery (B.J., J.B.), and Clinical Physiology, Nuclear Medicine and PET (O.M.H.), Copenhagen University Hospital Rigshospitalet; Danish Epilepsy Centre (G. Rubboli, B.P., S.B.), Dianalund; and Department of Diagnostic Radiology (A.-M.L.), Hvidovre Hospital, Denmark
| | - Peter Uldall
- From the Departments of Clinical Neurophysiology (L.D., H.T., P.O.H., A.F.-F., S.B.) and Neurology (P.S.), Aarhus University Hospital; Departments of Neurology (A.S., L.H.P.), Clinical Neurophysiology (M.F., G. Rásonyi), Pediatrics, Child Neurology (P.U.), Neurosurgery (B.J., J.B.), and Clinical Physiology, Nuclear Medicine and PET (O.M.H.), Copenhagen University Hospital Rigshospitalet; Danish Epilepsy Centre (G. Rubboli, B.P., S.B.), Dianalund; and Department of Diagnostic Radiology (A.-M.L.), Hvidovre Hospital, Denmark
| | - Bo Jespersen
- From the Departments of Clinical Neurophysiology (L.D., H.T., P.O.H., A.F.-F., S.B.) and Neurology (P.S.), Aarhus University Hospital; Departments of Neurology (A.S., L.H.P.), Clinical Neurophysiology (M.F., G. Rásonyi), Pediatrics, Child Neurology (P.U.), Neurosurgery (B.J., J.B.), and Clinical Physiology, Nuclear Medicine and PET (O.M.H.), Copenhagen University Hospital Rigshospitalet; Danish Epilepsy Centre (G. Rubboli, B.P., S.B.), Dianalund; and Department of Diagnostic Radiology (A.-M.L.), Hvidovre Hospital, Denmark
| | - Jannick Brennum
- From the Departments of Clinical Neurophysiology (L.D., H.T., P.O.H., A.F.-F., S.B.) and Neurology (P.S.), Aarhus University Hospital; Departments of Neurology (A.S., L.H.P.), Clinical Neurophysiology (M.F., G. Rásonyi), Pediatrics, Child Neurology (P.U.), Neurosurgery (B.J., J.B.), and Clinical Physiology, Nuclear Medicine and PET (O.M.H.), Copenhagen University Hospital Rigshospitalet; Danish Epilepsy Centre (G. Rubboli, B.P., S.B.), Dianalund; and Department of Diagnostic Radiology (A.-M.L.), Hvidovre Hospital, Denmark
| | - Otto Mølby Henriksen
- From the Departments of Clinical Neurophysiology (L.D., H.T., P.O.H., A.F.-F., S.B.) and Neurology (P.S.), Aarhus University Hospital; Departments of Neurology (A.S., L.H.P.), Clinical Neurophysiology (M.F., G. Rásonyi), Pediatrics, Child Neurology (P.U.), Neurosurgery (B.J., J.B.), and Clinical Physiology, Nuclear Medicine and PET (O.M.H.), Copenhagen University Hospital Rigshospitalet; Danish Epilepsy Centre (G. Rubboli, B.P., S.B.), Dianalund; and Department of Diagnostic Radiology (A.-M.L.), Hvidovre Hospital, Denmark
| | - Anders Fuglsang-Frederiksen
- From the Departments of Clinical Neurophysiology (L.D., H.T., P.O.H., A.F.-F., S.B.) and Neurology (P.S.), Aarhus University Hospital; Departments of Neurology (A.S., L.H.P.), Clinical Neurophysiology (M.F., G. Rásonyi), Pediatrics, Child Neurology (P.U.), Neurosurgery (B.J., J.B.), and Clinical Physiology, Nuclear Medicine and PET (O.M.H.), Copenhagen University Hospital Rigshospitalet; Danish Epilepsy Centre (G. Rubboli, B.P., S.B.), Dianalund; and Department of Diagnostic Radiology (A.-M.L.), Hvidovre Hospital, Denmark
| | - Sándor Beniczky
- From the Departments of Clinical Neurophysiology (L.D., H.T., P.O.H., A.F.-F., S.B.) and Neurology (P.S.), Aarhus University Hospital; Departments of Neurology (A.S., L.H.P.), Clinical Neurophysiology (M.F., G. Rásonyi), Pediatrics, Child Neurology (P.U.), Neurosurgery (B.J., J.B.), and Clinical Physiology, Nuclear Medicine and PET (O.M.H.), Copenhagen University Hospital Rigshospitalet; Danish Epilepsy Centre (G. Rubboli, B.P., S.B.), Dianalund; and Department of Diagnostic Radiology (A.-M.L.), Hvidovre Hospital, Denmark.
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29
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Rimpiläinen V, Koulouri A, Lucka F, Kaipio JP, Wolters CH. Improved EEG source localization with Bayesian uncertainty modelling of unknown skull conductivity. Neuroimage 2018; 188:252-260. [PMID: 30529398 DOI: 10.1016/j.neuroimage.2018.11.058] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Accepted: 11/30/2018] [Indexed: 10/27/2022] Open
Abstract
Electroencephalography (EEG) source imaging is an ill-posed inverse problem that requires accurate conductivity modelling of the head tissues, especially the skull. Unfortunately, the conductivity values are difficult to determine in vivo. In this paper, we show that the exact knowledge of the skull conductivity is not always necessary when the Bayesian approximation error (BAE) approach is exploited. In BAE, we first postulate a probability distribution for the skull conductivity that describes our (lack of) knowledge on its value, and model the effects of this uncertainty on EEG recordings with the help of an additive error term in the observation model. Before the Bayesian inference, the likelihood is marginalized over this error term. Thus, in the inversion we estimate only our primary unknown, the source distribution. We quantified the improvements in the source localization when the proposed Bayesian modelling was used in the presence of different skull conductivity errors and levels of measurement noise. Based on the results, BAE was able to improve the source localization accuracy, particularly when the unknown (true) skull conductivity was much lower than the expected standard conductivity value. The source locations that gained the highest improvements were shallow and originally exhibited the largest localization errors. In our case study, the benefits of BAE became negligible when the signal-to-noise ratio dropped to 20 dB.
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Affiliation(s)
- Ville Rimpiläinen
- Department of Physics, University of Bath, Claverton Down, Bath, BA2 7AY, United Kingdom; Institute for Biomagnetism and Biosignalanalysis, University of Münster, Malmedyweg 15, D-48149, Münster, Germany.
| | - Alexandra Koulouri
- Laboratory of Mathematics, Tampere University of Technology, P. O. Box 692, 33101, Tampere, Finland; Department of Physics, Aristotle University of Thessaloniki, Thessaloniki, 541 24, Greece
| | - Felix Lucka
- Computational Imaging, Centrum Wiskunde & Informatica, Science Park 123, 1098 XG, Amsterdam, the Netherlands; Centre for Medical Image Computing, University College London, Gower Street, London, WC1E 6BT, United Kingdom
| | - Jari P Kaipio
- Department of Mathematics, University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand; Department of Applied Physics, University of Eastern Finland, FI-90211, Kuopio, Finland
| | - Carsten H Wolters
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Malmedyweg 15, D-48149, Münster, Germany
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30
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Chowdhury RA, Pellegrino G, Aydin Ü, Lina JM, Dubeau F, Kobayashi E, Grova C. Reproducibility of EEG-MEG fusion source analysis of interictal spikes: Relevance in presurgical evaluation of epilepsy. Hum Brain Mapp 2017; 39:880-901. [PMID: 29164737 DOI: 10.1002/hbm.23889] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2017] [Revised: 11/03/2017] [Accepted: 11/07/2017] [Indexed: 11/06/2022] Open
Abstract
Fusion of electroencephalography (EEG) and magnetoencephalography (MEG) data using maximum entropy on the mean method (MEM-fusion) takes advantage of the complementarities between EEG and MEG to improve localization accuracy. Simulation studies demonstrated MEM-fusion to be robust especially in noisy conditions such as single spike source localizations (SSSL). Our objective was to assess the reliability of SSSL using MEM-fusion on clinical data. We proposed to cluster SSSL results to find the most reliable and consistent source map from the reconstructed sources, the so-called consensus map. Thirty-four types of interictal epileptic discharges (IEDs) were analyzed from 26 patients with well-defined epileptogenic focus. SSSLs were performed on EEG, MEG, and fusion data and consensus maps were estimated using hierarchical clustering. Qualitative (spike-to-spike reproducibility rate, SSR) and quantitative (localization error and spatial dispersion) assessments were performed using the epileptogenic focus as clinical reference. Fusion SSSL provided significantly better results than EEG or MEG alone. Fusion found at least one cluster concordant with the clinical reference in all cases. This concordant cluster was always the one involving the highest number of spikes. Fusion yielded highest reproducibility (SSR EEG = 55%, MEG = 71%, fusion = 90%) and lowest localization error. Also, using only few channels from either modality (21EEG + 272MEG or 54EEG + 25MEG) was sufficient to reach accurate fusion. MEM-fusion with consensus map approach provides an objective way of finding the most reliable and concordant generators of IEDs. We, therefore, suggest the pertinence of SSSL using MEM-fusion as a valuable clinical tool for presurgical evaluation of epilepsy.
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Affiliation(s)
- Rasheda Arman Chowdhury
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montreal, Québec, Canada
| | | | - Ümit Aydin
- Multimodal Functional Imaging Lab, Department of Physics and PERFORM Centre, Concordia University, Montreal, Québec, Canada
| | - Jean-Marc Lina
- Ecole de Technologie Supérieure, Montréal, Québec, Canada.,Centre de Recherches Mathématiques, Université de Montréal, Montréal, Québec, Canada
| | - François Dubeau
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
| | - Eliane Kobayashi
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
| | - Christophe Grova
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montreal, Québec, Canada.,Centre de Recherches Mathématiques, Université de Montréal, Montréal, Québec, Canada.,Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada.,Multimodal Functional Imaging Lab, Department of Physics and PERFORM Centre, Concordia University, Montreal, Québec, Canada
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31
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Neugebauer F, Möddel G, Rampp S, Burger M, Wolters CH. The Effect of Head Model Simplification on Beamformer Source Localization. Front Neurosci 2017; 11:625. [PMID: 29209157 PMCID: PMC5701642 DOI: 10.3389/fnins.2017.00625] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2017] [Accepted: 10/26/2017] [Indexed: 11/13/2022] Open
Abstract
Beamformers are a widely-used tool in brain analysis with magnetoencephalography (MEG) and electroencephalography (EEG). For the construction of the beamformer filters realistic head volume conductor modeling is necessary for accurately computing the EEG and MEG leadfields, i.e., for solving the EEG and MEG forward problem. In this work, we investigate the influence of including realistic head tissue compartments into a finite element method (FEM) model on the beamformer's localization ability. Specifically, we investigate the effect of including cerebrospinal fluid, gray matter, and white matter distinction, as well as segmenting the skull bone into compacta and spongiosa, and modeling white matter anisotropy. We simulate an interictal epileptic measurement with white sensor noise. Beamformer filters are constructed with unit gain, unit array gain, and unit noise gain constraint. Beamformer source positions are determined by evaluating power and excess sample kurtosis (g2) of the source-waveforms at all source space nodes. For both modalities, we see a strong effect of modeling the cerebrospinal fluid and white and gray matter. Depending on the source position, both effects can each be in the magnitude of centimeters, rendering their modeling necessary for successful localization. Precise skull modeling mainly effected the EEG up to a few millimeters, while both modalities could profit from modeling white matter anisotropy to a smaller extent of 5-10 mm. The unit noise gain or neural activity index beamformer behaves similarly to the array gain beamformer when noise strength is sufficiently high. Variance localization seems more robust against modeling errors than kurtosis.
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Affiliation(s)
- Frank Neugebauer
- Institute for Biomagnetism und Biosignalanalysis, University of Münster, Münster, Germany
| | - Gabriel Möddel
- Department of Sleep Medicine and Neuromuscular Disorders, Epilepsy Center Münster-Osnabrück, University of Münster, Münster, Germany
| | - Stefan Rampp
- Department of Neurosurgery, University Hospital Erlangen, Erlangen, Germany
| | - Martin Burger
- Institute for Computational and Applied Mathematics, University of Münster, Münster, Germany
| | - Carsten H. Wolters
- Institute for Biomagnetism und Biosignalanalysis, University of Münster, Münster, Germany
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32
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Huang MX, Swan AR, Quinto AA, Matthews S, Harrington DL, Nichols S, Bruder BJ, Snook CC, Huang CW, Baker DG, Lee RR. A pilot treatment study for mild traumatic brain injury: Neuroimaging changes detected by MEG after low-intensity pulse-based transcranial electrical stimulation. Brain Inj 2017; 31:1951-1963. [DOI: 10.1080/02699052.2017.1363409] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- Ming-Xiong Huang
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Ashley Robb Swan
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Annemarie Angeles Quinto
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Scott Matthews
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- ASPIRE Center, VASDHS Residential Rehabilitation Treatment Program, San Diego, CA, USA
| | - Deborah L. Harrington
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Sharon Nichols
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
| | | | | | - Charles W. Huang
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
| | - Dewleen G. Baker
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- VA Center of Excellence for Stress and Mental Health, San Diego, CA, USA
| | - Roland R. Lee
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
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33
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Cichy RM, Pantazis D. Multivariate pattern analysis of MEG and EEG: A comparison of representational structure in time and space. Neuroimage 2017; 158:441-454. [DOI: 10.1016/j.neuroimage.2017.07.023] [Citation(s) in RCA: 66] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2016] [Revised: 06/03/2017] [Accepted: 07/12/2017] [Indexed: 11/24/2022] Open
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34
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Aydin Ü, Rampp S, Wollbrink A, Kugel H, Cho JH, Knösche TR, Grova C, Wellmer J, Wolters CH. Zoomed MRI Guided by Combined EEG/MEG Source Analysis: A Multimodal Approach for Optimizing Presurgical Epilepsy Work-up and its Application in a Multi-focal Epilepsy Patient Case Study. Brain Topogr 2017; 30:417-433. [PMID: 28510905 PMCID: PMC5495874 DOI: 10.1007/s10548-017-0568-9] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2016] [Accepted: 04/25/2017] [Indexed: 10/25/2022]
Abstract
In recent years, the use of source analysis based on electroencephalography (EEG) and magnetoencephalography (MEG) has gained considerable attention in presurgical epilepsy diagnosis. However, in many cases the source analysis alone is not used to tailor surgery unless the findings are confirmed by lesions, such as, e.g., cortical malformations in MRI. For many patients, the histology of tissue resected from MRI negative epilepsy shows small lesions, which indicates the need for more sensitive MR sequences. In this paper, we describe a technique to maximize the synergy between combined EEG/MEG (EMEG) source analysis and high resolution MRI. The procedure has three main steps: (1) construction of a detailed and calibrated finite element head model that considers the variation of individual skull conductivities and white matter anisotropy, (2) EMEG source analysis performed on averaged interictal epileptic discharges (IED), (3) high resolution (0.5 mm) zoomed MR imaging, limited to small areas centered at the EMEG source locations. The proposed new diagnosis procedure was then applied in a particularly challenging case of an epilepsy patient: EMEG analysis at the peak of the IED coincided with a right frontal focal cortical dysplasia (FCD), which had been detected at standard 1 mm resolution MRI. Of higher interest, zoomed MR imaging (applying parallel transmission, 'ZOOMit') guided by EMEG at the spike onset revealed a second, fairly subtle, FCD in the left fronto-central region. The evaluation revealed that this second FCD, which had not been detectable with standard 1 mm resolution, was the trigger of the seizures.
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Affiliation(s)
- Ü Aydin
- Institute for Biomagnetism und Biosignalanalysis, University of Münster, Malmedyweg 15, 48149, Münster, Germany. .,Multimodal Functional Imaging Lab, Department of Physics and PERFORM Centre, Concordia University, Montreal, Quebec, Canada.
| | - S Rampp
- Department of Neurosurgery, University Hospital Erlangen, Erlangen, Germany
| | - A Wollbrink
- Institute for Biomagnetism und Biosignalanalysis, University of Münster, Malmedyweg 15, 48149, Münster, Germany
| | - H Kugel
- Department of Clinical Radiology, University Hospital Münster, Münster, Germany
| | - J -H Cho
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - T R Knösche
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - C Grova
- Multimodal Functional Imaging Lab, Department of Physics and PERFORM Centre, Concordia University, Montreal, Quebec, Canada.,Multimodal Functional Imaging Lab, Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada.,Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - J Wellmer
- Ruhr-Epileptology, Department of Neurology, University Hospital Knappschaftskrankenhaus Bochum, Bochum, Germany
| | - C H Wolters
- Institute for Biomagnetism und Biosignalanalysis, University of Münster, Malmedyweg 15, 48149, Münster, Germany
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35
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Huang MX, Harrington DL, Robb Swan A, Angeles Quinto A, Nichols S, Drake A, Song T, Diwakar M, Huang CW, Risbrough VB, Dale A, Bartsch H, Matthews S, Huang JW, Lee RR, Baker DG. Resting-State Magnetoencephalography Reveals Different Patterns of Aberrant Functional Connectivity in Combat-Related Mild Traumatic Brain Injury. J Neurotrauma 2016; 34:1412-1426. [PMID: 27762653 DOI: 10.1089/neu.2016.4581] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Blast mild traumatic brain injury (mTBI) is a leading cause of sustained impairment in military service members and veterans. However, the mechanism of persistent disability is not fully understood. The present study investigated disturbances in brain functioning in mTBI participants using a source-imaging-based approach to analyze functional connectivity (FC) from resting-state magnetoencephalography (rs-MEG). Study participants included 26 active-duty service members or veterans who had blast mTBI with persistent post-concussive symptoms, and 22 healthy control active-duty service members or veterans. The source time courses from regions of interest (ROIs) were used to compute ROI to whole-brain (ROI-global) FC for different frequency bands using two different measures: 1) time-lagged cross-correlation and 2) phase-lock synchrony. Compared with the controls, blast mTBI participants showed increased ROI-global FC in beta, gamma, and low-frequency bands, but not in the alpha band. Sources of abnormally increased FC included the: 1) prefrontal cortex (right ventromedial prefrontal cortex [vmPFC], right rostral anterior cingulate cortex [rACC]), and left ventrolateral and dorsolateral prefrontal cortex; 2) medial temporal lobe (bilateral parahippocampus, hippocampus, and amygdala); and 3) right putamen and cerebellum. In contrast, the blast mTBI group also showed decreased FC of the right frontal pole. Group differences were highly consistent across the two different FC measures. FC of the left ventrolateral prefrontal cortex correlated with executive functioning and processing speed in mTBI participants. Altogether, our findings of increased and decreased regionalpatterns of FC suggest that disturbances in intrinsic brain connectivity may be the result of multiple mechanisms, and are associated with cognitive sequelae of the injury.
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Affiliation(s)
- Ming-Xiong Huang
- 1 Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System , San Diego, California.,2 Department of Radiology, University of California , San Diego, California
| | - Deborah L Harrington
- 1 Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System , San Diego, California.,2 Department of Radiology, University of California , San Diego, California
| | - Ashley Robb Swan
- 1 Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System , San Diego, California.,2 Department of Radiology, University of California , San Diego, California
| | - Annemarie Angeles Quinto
- 1 Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System , San Diego, California.,2 Department of Radiology, University of California , San Diego, California
| | - Sharon Nichols
- 3 Department of Neuroscience, University of California , San Diego, California
| | | | - Tao Song
- 2 Department of Radiology, University of California , San Diego, California
| | - Mithun Diwakar
- 2 Department of Radiology, University of California , San Diego, California
| | - Charles W Huang
- 5 Department of Bioengineering, University of California , San Diego, California
| | - Victoria B Risbrough
- 6 Department of Psychiatry, University of California , San Diego, California.,7 VA Center of Excellence for Stress and Mental Health , San Diego, California
| | - Anders Dale
- 2 Department of Radiology, University of California , San Diego, California
| | - Hauke Bartsch
- 2 Department of Radiology, University of California , San Diego, California
| | - Scott Matthews
- 1 Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System , San Diego, California.,6 Department of Psychiatry, University of California , San Diego, California.,8 Aspire Center , VASDHS Residential Rehabilitation Treatment Program, San Diego, California
| | | | - Roland R Lee
- 1 Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System , San Diego, California.,2 Department of Radiology, University of California , San Diego, California
| | - Dewleen G Baker
- 1 Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System , San Diego, California.,6 Department of Psychiatry, University of California , San Diego, California.,7 VA Center of Excellence for Stress and Mental Health , San Diego, California
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36
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Huang CW, Huang MX, Ji Z, Swan AR, Angeles AM, Song T, Huang JW, Lee RR. High-resolution MEG source imaging approach to accurately localize Broca’s area in patients with brain tumor or epilepsy. Clin Neurophysiol 2016; 127:2308-16. [DOI: 10.1016/j.clinph.2016.02.007] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2015] [Revised: 12/15/2015] [Accepted: 02/09/2016] [Indexed: 11/28/2022]
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37
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Chen YH, Stone-Howell B, Edgar JC, Huang M, Wootton C, Hunter MA, Lu BY, Sadek JR, Miller GA, Cañive JM. Frontal slow-wave activity as a predictor of negative symptoms, cognition and functional capacity in schizophrenia. Br J Psychiatry 2016; 208:160-7. [PMID: 26206861 PMCID: PMC4837382 DOI: 10.1192/bjp.bp.114.156075] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2014] [Revised: 11/04/2014] [Accepted: 11/08/2014] [Indexed: 12/30/2022]
Abstract
BACKGROUND Increased temporal and frontal slow-wave delta (1-4 Hz) and theta (4-7 Hz) activities are the most consistent resting-state neural abnormalities reported in schizophrenia. The frontal lobe is associated with negative symptoms and cognitive abilities such as attention, with negative symptoms and impaired attention associated with poor functional capacity. AIMS To establish whether frontal dysfunction, as indexed by slowing, would be associated with functional impairments. METHOD Eyes-closed magnetoencephalography data were collected in 41 participants with schizophrenia and 37 healthy controls, and frequency-domain source imaging localised delta and theta activity. RESULTS Elevated delta and theta activity in right frontal and right temporoparietal regions was observed in the schizophrenia v. CONTROL GROUP In schizophrenia, right-frontal delta activity was uniquely associated with negative but not positive symptoms. In the full sample, increased right-frontal delta activity predicted poorer attention and functional capacity. CONCLUSIONS Our findings suggest that treatment-associated decreases in slow-wave activity could be accompanied by improved functional outcome and thus better prognosis.
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Affiliation(s)
- Yu-Han Chen
- Yu-Han Chen, PhD, The Children's Hospital of Philadelphia and University of Pennsylvania, Department of Radiology, Philadelphia; Breannan Stone-Howell, MS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico; J. Christopher Edgar, PhD, The Children's Hospital of Philadelphia and University of Pennsylvania, Department of Radiology, Philadelphia; Mingxiong Huang, PhD, University of California, San Diego, Department of Radiology, and San Diego VA Healthcare System, Department of Radiology, San Diego, California; Cassandra Wootton, BS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico; Michael A. Hunter, BS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, The University of New Mexico School of Medicine, Department of Psychiatry and Department of Psychology, Albuquerque, New Mexico; Brett Y. Lu, MD, PhD, The University of Hawaii at Manoa, Department of Psychiatry, Honolulu, Hawaii; Joseph R. Sadek, PhD, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, New Mexico; Gregory A. Miller, PhD, University of California, Los Angeles, Department of Psychology, Los Angeles, California; José M. Canĩve, MD, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico, USA
| | - Breannan Stone-Howell
- Yu-Han Chen, PhD, The Children's Hospital of Philadelphia and University of Pennsylvania, Department of Radiology, Philadelphia; Breannan Stone-Howell, MS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico; J. Christopher Edgar, PhD, The Children's Hospital of Philadelphia and University of Pennsylvania, Department of Radiology, Philadelphia; Mingxiong Huang, PhD, University of California, San Diego, Department of Radiology, and San Diego VA Healthcare System, Department of Radiology, San Diego, California; Cassandra Wootton, BS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico; Michael A. Hunter, BS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, The University of New Mexico School of Medicine, Department of Psychiatry and Department of Psychology, Albuquerque, New Mexico; Brett Y. Lu, MD, PhD, The University of Hawaii at Manoa, Department of Psychiatry, Honolulu, Hawaii; Joseph R. Sadek, PhD, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, New Mexico; Gregory A. Miller, PhD, University of California, Los Angeles, Department of Psychology, Los Angeles, California; José M. Canĩve, MD, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico, USA
| | - J Christopher Edgar
- Yu-Han Chen, PhD, The Children's Hospital of Philadelphia and University of Pennsylvania, Department of Radiology, Philadelphia; Breannan Stone-Howell, MS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico; J. Christopher Edgar, PhD, The Children's Hospital of Philadelphia and University of Pennsylvania, Department of Radiology, Philadelphia; Mingxiong Huang, PhD, University of California, San Diego, Department of Radiology, and San Diego VA Healthcare System, Department of Radiology, San Diego, California; Cassandra Wootton, BS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico; Michael A. Hunter, BS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, The University of New Mexico School of Medicine, Department of Psychiatry and Department of Psychology, Albuquerque, New Mexico; Brett Y. Lu, MD, PhD, The University of Hawaii at Manoa, Department of Psychiatry, Honolulu, Hawaii; Joseph R. Sadek, PhD, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, New Mexico; Gregory A. Miller, PhD, University of California, Los Angeles, Department of Psychology, Los Angeles, California; José M. Canĩve, MD, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico, USA
| | - Mingxiong Huang
- Yu-Han Chen, PhD, The Children's Hospital of Philadelphia and University of Pennsylvania, Department of Radiology, Philadelphia; Breannan Stone-Howell, MS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico; J. Christopher Edgar, PhD, The Children's Hospital of Philadelphia and University of Pennsylvania, Department of Radiology, Philadelphia; Mingxiong Huang, PhD, University of California, San Diego, Department of Radiology, and San Diego VA Healthcare System, Department of Radiology, San Diego, California; Cassandra Wootton, BS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico; Michael A. Hunter, BS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, The University of New Mexico School of Medicine, Department of Psychiatry and Department of Psychology, Albuquerque, New Mexico; Brett Y. Lu, MD, PhD, The University of Hawaii at Manoa, Department of Psychiatry, Honolulu, Hawaii; Joseph R. Sadek, PhD, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, New Mexico; Gregory A. Miller, PhD, University of California, Los Angeles, Department of Psychology, Los Angeles, California; José M. Canĩve, MD, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico, USA
| | - Cassandra Wootton
- Yu-Han Chen, PhD, The Children's Hospital of Philadelphia and University of Pennsylvania, Department of Radiology, Philadelphia; Breannan Stone-Howell, MS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico; J. Christopher Edgar, PhD, The Children's Hospital of Philadelphia and University of Pennsylvania, Department of Radiology, Philadelphia; Mingxiong Huang, PhD, University of California, San Diego, Department of Radiology, and San Diego VA Healthcare System, Department of Radiology, San Diego, California; Cassandra Wootton, BS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico; Michael A. Hunter, BS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, The University of New Mexico School of Medicine, Department of Psychiatry and Department of Psychology, Albuquerque, New Mexico; Brett Y. Lu, MD, PhD, The University of Hawaii at Manoa, Department of Psychiatry, Honolulu, Hawaii; Joseph R. Sadek, PhD, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, New Mexico; Gregory A. Miller, PhD, University of California, Los Angeles, Department of Psychology, Los Angeles, California; José M. Canĩve, MD, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico, USA
| | - Michael A Hunter
- Yu-Han Chen, PhD, The Children's Hospital of Philadelphia and University of Pennsylvania, Department of Radiology, Philadelphia; Breannan Stone-Howell, MS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico; J. Christopher Edgar, PhD, The Children's Hospital of Philadelphia and University of Pennsylvania, Department of Radiology, Philadelphia; Mingxiong Huang, PhD, University of California, San Diego, Department of Radiology, and San Diego VA Healthcare System, Department of Radiology, San Diego, California; Cassandra Wootton, BS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico; Michael A. Hunter, BS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, The University of New Mexico School of Medicine, Department of Psychiatry and Department of Psychology, Albuquerque, New Mexico; Brett Y. Lu, MD, PhD, The University of Hawaii at Manoa, Department of Psychiatry, Honolulu, Hawaii; Joseph R. Sadek, PhD, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, New Mexico; Gregory A. Miller, PhD, University of California, Los Angeles, Department of Psychology, Los Angeles, California; José M. Canĩve, MD, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico, USA
| | - Brett Y Lu
- Yu-Han Chen, PhD, The Children's Hospital of Philadelphia and University of Pennsylvania, Department of Radiology, Philadelphia; Breannan Stone-Howell, MS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico; J. Christopher Edgar, PhD, The Children's Hospital of Philadelphia and University of Pennsylvania, Department of Radiology, Philadelphia; Mingxiong Huang, PhD, University of California, San Diego, Department of Radiology, and San Diego VA Healthcare System, Department of Radiology, San Diego, California; Cassandra Wootton, BS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico; Michael A. Hunter, BS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, The University of New Mexico School of Medicine, Department of Psychiatry and Department of Psychology, Albuquerque, New Mexico; Brett Y. Lu, MD, PhD, The University of Hawaii at Manoa, Department of Psychiatry, Honolulu, Hawaii; Joseph R. Sadek, PhD, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, New Mexico; Gregory A. Miller, PhD, University of California, Los Angeles, Department of Psychology, Los Angeles, California; José M. Canĩve, MD, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico, USA
| | - Joseph R Sadek
- Yu-Han Chen, PhD, The Children's Hospital of Philadelphia and University of Pennsylvania, Department of Radiology, Philadelphia; Breannan Stone-Howell, MS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico; J. Christopher Edgar, PhD, The Children's Hospital of Philadelphia and University of Pennsylvania, Department of Radiology, Philadelphia; Mingxiong Huang, PhD, University of California, San Diego, Department of Radiology, and San Diego VA Healthcare System, Department of Radiology, San Diego, California; Cassandra Wootton, BS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico; Michael A. Hunter, BS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, The University of New Mexico School of Medicine, Department of Psychiatry and Department of Psychology, Albuquerque, New Mexico; Brett Y. Lu, MD, PhD, The University of Hawaii at Manoa, Department of Psychiatry, Honolulu, Hawaii; Joseph R. Sadek, PhD, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, New Mexico; Gregory A. Miller, PhD, University of California, Los Angeles, Department of Psychology, Los Angeles, California; José M. Canĩve, MD, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico, USA
| | - Gregory A Miller
- Yu-Han Chen, PhD, The Children's Hospital of Philadelphia and University of Pennsylvania, Department of Radiology, Philadelphia; Breannan Stone-Howell, MS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico; J. Christopher Edgar, PhD, The Children's Hospital of Philadelphia and University of Pennsylvania, Department of Radiology, Philadelphia; Mingxiong Huang, PhD, University of California, San Diego, Department of Radiology, and San Diego VA Healthcare System, Department of Radiology, San Diego, California; Cassandra Wootton, BS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico; Michael A. Hunter, BS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, The University of New Mexico School of Medicine, Department of Psychiatry and Department of Psychology, Albuquerque, New Mexico; Brett Y. Lu, MD, PhD, The University of Hawaii at Manoa, Department of Psychiatry, Honolulu, Hawaii; Joseph R. Sadek, PhD, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, New Mexico; Gregory A. Miller, PhD, University of California, Los Angeles, Department of Psychology, Los Angeles, California; José M. Canĩve, MD, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico, USA
| | - José M Cañive
- Yu-Han Chen, PhD, The Children's Hospital of Philadelphia and University of Pennsylvania, Department of Radiology, Philadelphia; Breannan Stone-Howell, MS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico; J. Christopher Edgar, PhD, The Children's Hospital of Philadelphia and University of Pennsylvania, Department of Radiology, Philadelphia; Mingxiong Huang, PhD, University of California, San Diego, Department of Radiology, and San Diego VA Healthcare System, Department of Radiology, San Diego, California; Cassandra Wootton, BS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico; Michael A. Hunter, BS, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, The University of New Mexico School of Medicine, Department of Psychiatry and Department of Psychology, Albuquerque, New Mexico; Brett Y. Lu, MD, PhD, The University of Hawaii at Manoa, Department of Psychiatry, Honolulu, Hawaii; Joseph R. Sadek, PhD, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, New Mexico; Gregory A. Miller, PhD, University of California, Los Angeles, Department of Psychology, Los Angeles, California; José M. Canĩve, MD, New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, and The University of New Mexico School of Medicine, Department of Psychiatry, Albuquerque, New Mexico, USA
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Akalin Acar Z, Acar CE, Makeig S. Simultaneous head tissue conductivity and EEG source location estimation. Neuroimage 2016; 124:168-180. [PMID: 26302675 PMCID: PMC4651780 DOI: 10.1016/j.neuroimage.2015.08.032] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2014] [Revised: 08/02/2015] [Accepted: 08/11/2015] [Indexed: 10/23/2022] Open
Abstract
Accurate electroencephalographic (EEG) source localization requires an electrical head model incorporating accurate geometries and conductivity values for the major head tissues. While consistent conductivity values have been reported for scalp, brain, and cerebrospinal fluid, measured brain-to-skull conductivity ratio (BSCR) estimates have varied between 8 and 80, likely reflecting both inter-subject and measurement method differences. In simulations, mis-estimation of skull conductivity can produce source localization errors as large as 3cm. Here, we describe an iterative gradient-based approach to Simultaneous tissue Conductivity And source Location Estimation (SCALE). The scalp projection maps used by SCALE are obtained from near-dipolar effective EEG sources found by adequate independent component analysis (ICA) decomposition of sufficient high-density EEG data. We applied SCALE to simulated scalp projections of 15cm(2)-scale cortical patch sources in an MR image-based electrical head model with simulated BSCR of 30. Initialized either with a BSCR of 80 or 20, SCALE estimated BSCR as 32.6. In Adaptive Mixture ICA (AMICA) decompositions of (45-min, 128-channel) EEG data from two young adults we identified sets of 13 independent components having near-dipolar scalp maps compatible with a single cortical source patch. Again initialized with either BSCR 80 or 25, SCALE gave BSCR estimates of 34 and 54 for the two subjects respectively. The ability to accurately estimate skull conductivity non-invasively from any well-recorded EEG data in combination with a stable and non-invasively acquired MR imaging-derived electrical head model could remove a critical barrier to using EEG as a sub-cm(2)-scale accurate 3-D functional cortical imaging modality.
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Affiliation(s)
- Zeynep Akalin Acar
- Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California, San Diego, La Jolla, CA 92093-0559, USA.
| | - Can E Acar
- Qualcomm Technologies, Inc., 5775 Morehouse Drive, San Diego, CA 92121, USA.
| | - Scott Makeig
- Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California, San Diego, La Jolla, CA 92093-0559, USA.
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EEG-MEG Integration Enhances the Characterization of Functional and Effective Connectivity in the Resting State Network. PLoS One 2015; 10:e0140832. [PMID: 26509448 PMCID: PMC4624977 DOI: 10.1371/journal.pone.0140832] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2015] [Accepted: 09/29/2015] [Indexed: 11/19/2022] Open
Abstract
At the sensor level many aspects, such as spectral power, functional and effective connectivity as well as relative-power-ratio ratio (RPR) and spatial resolution have been comprehensively investigated through both electroencephalography (EEG) and magnetoencephalography (MEG). Despite this, differences between both modalities have not yet been systematically studied by direct comparison. It remains an open question as to whether the integration of EEG and MEG data would improve the information obtained from the above mentioned parameters. Here, EEG (64-channel system) and MEG (275 sensor system) were recorded simultaneously in conditions with eyes open (EO) and eyes closed (EC) in 29 healthy adults. Spectral power, functional and effective connectivity, RPR, and spatial resolution were analyzed at five different frequency bands (delta, theta, alpha, beta and gamma). Networks of functional and effective connectivity were described using a spatial filter approach called the dynamic imaging of coherent sources (DICS) followed by the renormalized partial directed coherence (RPDC). Absolute mean power at the sensor level was significantly higher in EEG than in MEG data in both EO and EC conditions. At the source level, there was a trend towards a better performance of the combined EEG+MEG analysis compared with separate EEG or MEG analyses for the source mean power, functional correlation, effective connectivity for both EO and EC. The network of coherent sources and the spatial resolution were similar for both the EEG and MEG data if they were analyzed separately. Results indicate that the combined approach has several advantages over the separate analyses of both EEG and MEG. Moreover, by a direct comparison of EEG and MEG, EEG was characterized by significantly higher values in all measured parameters in both sensor and source level. All the above conclusions are specific to the resting state task and the specific analysis used in this study to have general conclusion multi-center studies would be helpful.
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40
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Huang M, Lee RR. Magnetoencephalography (MEG) Slow-Wave Imaging for Diagnosing Non-acute Mild Traumatic Brain Injury. CURRENT RADIOLOGY REPORTS 2015. [DOI: 10.1007/s40134-015-0121-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Schmidt C, Wagner S, Burger M, van Rienen U, Wolters CH. Impact of uncertain head tissue conductivity in the optimization of transcranial direct current stimulation for an auditory target. J Neural Eng 2015; 12:046028. [PMID: 26170066 PMCID: PMC4539365 DOI: 10.1088/1741-2560/12/4/046028] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
OBJECTIVE Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique to modify neural excitability. Using multi-array tDCS, we investigate the influence of inter-individually varying head tissue conductivity profiles on optimal electrode configurations for an auditory cortex stimulation. APPROACH In order to quantify the uncertainty of the optimal electrode configurations, multi-variate generalized polynomial chaos expansions of the model solutions are used based on uncertain conductivity profiles of the compartments skin, skull, gray matter, and white matter. Stochastic measures, probability density functions, and sensitivity of the quantities of interest are investigated for each electrode and the current density at the target with the resulting stimulation protocols visualized on the head surface. MAIN RESULTS We demonstrate that the optimized stimulation protocols are only comprised of a few active electrodes, with tolerable deviations in the stimulation amplitude of the anode. However, large deviations in the order of the uncertainty in the conductivity profiles could be noted in the stimulation protocol of the compensating cathodes. Regarding these main stimulation electrodes, the stimulation protocol was most sensitive to uncertainty in skull conductivity. Finally, the probability that the current density amplitude in the auditory cortex target region is supra-threshold was below 50%. SIGNIFICANCE The results suggest that an uncertain conductivity profile in computational models of tDCS can have a substantial influence on the prediction of optimal stimulation protocols for stimulation of the auditory cortex. The investigations carried out in this study present a possibility to predict the probability of providing a therapeutic effect with an optimized electrode system for future auditory clinical and experimental procedures of tDCS applications.
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Affiliation(s)
- Christian Schmidt
- Institute of General Electrical Engineering, University of Rostock, 18059 Rostock, Germany
| | - Sven Wagner
- Institute of Biomagnetism and Biosignalanalysis, University of Münster, 48149 Münster, Germany
| | - Martin Burger
- Institute for Computational and Applied Mathematics and Cells-in-Motion Cluster of Excellence, University of Münster, 48149 Münster, Germany
| | - Ursula van Rienen
- Institute of General Electrical Engineering, University of Rostock, 18059 Rostock, Germany
| | - Carsten H Wolters
- Institute of Biomagnetism and Biosignalanalysis, University of Münster, 48149 Münster, Germany
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42
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Robb Swan A, Nichols S, Drake A, Angeles A, Diwakar M, Song T, Lee RR, Huang MX. Magnetoencephalography Slow-Wave Detection in Patients with Mild Traumatic Brain Injury and Ongoing Symptoms Correlated with Long-Term Neuropsychological Outcome. J Neurotrauma 2015; 32:1510-21. [PMID: 25808909 DOI: 10.1089/neu.2014.3654] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Mild traumatic brain injury (mTBI) is common in the United States, accounting for as many as 75-80% of all TBIs. It is recognized as a significant public health concern, but there are ongoing controversies regarding the etiology of persistent symptoms post-mTBI. This constellation of nonspecific symptoms is referred to as postconcussive syndrome (PCS). The present study combined results from magnetoencephalography (MEG) and cognitive assessment to examine group differences and relationships between brain activity and cognitive performance in 31 military and civilian individuals with a history of mTBI+PCS and 33 matched healthy control subjects. An operator-free analysis was used for MEG data to increase reliability of the technique. Subjects completed a comprehensive neuropsychological assessment, and measures of abnormal slow-wave activity from MEG were collected. Results demonstrated significant group differences on measures of executive functioning and processing speed. In addition, significant correlations between slow-wave activity on MEG and patterns of cognitive functioning were found in cortical areas, consistent with cognitive impairments on exams. Results provide more objective evidence that there may be subtle changes to the neurobiological integrity of the brain that can be detected by MEG. Further, these findings suggest that these abnormalities are associated with cognitive outcomes and may account, at least in part, for long-term PCS in those who have sustained an mTBI.
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Affiliation(s)
- Ashley Robb Swan
- 1 Research Services, VA San Diego Healthcare System , San Diego, California.,3 Department of Radiology, University of California , San Diego, San Diego, California
| | - Sharon Nichols
- 4 Department of Neuroscience, University of California , San Diego, San Diego, California
| | - Angela Drake
- 5 Department of Community Health, National University , San Diego, California
| | - AnneMarie Angeles
- 1 Research Services, VA San Diego Healthcare System , San Diego, California.,3 Department of Radiology, University of California , San Diego, San Diego, California
| | - Mithun Diwakar
- 3 Department of Radiology, University of California , San Diego, San Diego, California
| | - Tao Song
- 3 Department of Radiology, University of California , San Diego, San Diego, California
| | - Roland R Lee
- 1 Research Services, VA San Diego Healthcare System , San Diego, California.,2 Radiology Services, VA San Diego Healthcare System , San Diego, California.,3 Department of Radiology, University of California , San Diego, San Diego, California
| | - Ming-Xiong Huang
- 1 Research Services, VA San Diego Healthcare System , San Diego, California.,2 Radiology Services, VA San Diego Healthcare System , San Diego, California.,3 Department of Radiology, University of California , San Diego, San Diego, California
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Diwakar M, Harrington DL, Maruta J, Ghajar J, El-Gabalawy F, Muzzatti L, Corbetta M, Huang MX, Lee RR. Filling in the gaps: Anticipatory control of eye movements in chronic mild traumatic brain injury. NEUROIMAGE-CLINICAL 2015; 8:210-23. [PMID: 26106545 PMCID: PMC4473731 DOI: 10.1016/j.nicl.2015.04.011] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/21/2015] [Revised: 04/10/2015] [Accepted: 04/12/2015] [Indexed: 01/18/2023]
Abstract
A barrier in the diagnosis of mild traumatic brain injury (mTBI) stems from the lack of measures that are adequately sensitive in detecting mild head injuries. MRI and CT are typically negative in mTBI patients with persistent symptoms of post-concussive syndrome (PCS), and characteristic difficulties in sustaining attention often go undetected on neuropsychological testing, which can be insensitive to momentary lapses in concentration. Conversely, visual tracking strongly depends on sustained attention over time and is impaired in chronic mTBI patients, especially when tracking an occluded target. This finding suggests deficient internal anticipatory control in mTBI, the neural underpinnings of which are poorly understood. The present study investigated the neuronal bases for deficient anticipatory control during visual tracking in 25 chronic mTBI patients with persistent PCS symptoms and 25 healthy control subjects. The task was performed while undergoing magnetoencephalography (MEG), which allowed us to examine whether neural dysfunction associated with anticipatory control deficits was due to altered alpha, beta, and/or gamma activity. Neuropsychological examinations characterized cognition in both groups. During MEG recordings, subjects tracked a predictably moving target that was either continuously visible or randomly occluded (gap condition). MEG source-imaging analyses tested for group differences in alpha, beta, and gamma frequency bands. The results showed executive functioning, information processing speed, and verbal memory deficits in the mTBI group. Visual tracking was impaired in the mTBI group only in the gap condition. Patients showed greater error than controls before and during target occlusion, and were slower to resynchronize with the target when it reappeared. Impaired tracking concurred with abnormal beta activity, which was suppressed in the parietal cortex, especially the right hemisphere, and enhanced in left caudate and frontal–temporal areas. Regional beta-amplitude demonstrated high classification accuracy (92%) compared to eye-tracking (65%) and neuropsychological variables (80%). These findings show that deficient internal anticipatory control in mTBI is associated with altered beta activity, which is remarkably sensitive given the heterogeneity of injuries. Neuropsychological test performance was impaired in mTBI patients. Visual tracking was impaired in the gap task, where targets were randomly occluded. Impaired visual tracking concurred with abnormal MEG beta activity. Beta was suppressed in parietal and enhanced in caudate and frontal–temporal areas. Regional MEG beta-amplitude demonstrated high classification accuracy (92%).
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Affiliation(s)
- Mithun Diwakar
- Department of Radiology, University of California, San Diego, San Diego, CA, USA
| | - Deborah L Harrington
- Department of Radiology, University of California, San Diego, San Diego, CA, USA ; Radiology and Research Services, VA San Diego Healthcare System, San Diego, CA, USA
| | - Jun Maruta
- Brain Trauma Foundation, New York, NY, USA
| | - Jamshid Ghajar
- Brain Trauma Foundation, New York, NY, USA ; Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, USA
| | - Fady El-Gabalawy
- Department of Radiology, University of California, San Diego, San Diego, CA, USA
| | - Laura Muzzatti
- Department of Radiology, University of California, San Diego, San Diego, CA, USA
| | | | - Ming-Xiong Huang
- Department of Radiology, University of California, San Diego, San Diego, CA, USA ; Radiology and Research Services, VA San Diego Healthcare System, San Diego, CA, USA
| | - Roland R Lee
- Department of Radiology, University of California, San Diego, San Diego, CA, USA ; Radiology and Research Services, VA San Diego Healthcare System, San Diego, CA, USA
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44
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Aydin Ü, Vorwerk J, Dümpelmann M, Küpper P, Kugel H, Heers M, Wellmer J, Kellinghaus C, Haueisen J, Rampp S, Stefan H, Wolters CH. Combined EEG/MEG can outperform single modality EEG or MEG source reconstruction in presurgical epilepsy diagnosis. PLoS One 2015; 10:e0118753. [PMID: 25761059 PMCID: PMC4356563 DOI: 10.1371/journal.pone.0118753] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2014] [Accepted: 01/06/2015] [Indexed: 11/25/2022] Open
Abstract
We investigated two important means for improving source reconstruction in presurgical epilepsy diagnosis. The first investigation is about the optimal choice of the number of epileptic spikes in averaging to (1) sufficiently reduce the noise bias for an accurate determination of the center of gravity of the epileptic activity and (2) still get an estimation of the extent of the irritative zone. The second study focuses on the differences in single modality EEG (80-electrodes) or MEG (275-gradiometers) and especially on the benefits of combined EEG/MEG (EMEG) source analysis. Both investigations were validated with simultaneous stereo-EEG (sEEG) (167-contacts) and low-density EEG (ldEEG) (21-electrodes). To account for the different sensitivity profiles of EEG and MEG, we constructed a six-compartment finite element head model with anisotropic white matter conductivity, and calibrated the skull conductivity via somatosensory evoked responses. Our results show that, unlike single modality EEG or MEG, combined EMEG uses the complementary information of both modalities and thereby allows accurate source reconstructions also at early instants in time (epileptic spike onset), i.e., time points with low SNR, which are not yet subject to propagation and thus supposed to be closer to the origin of the epileptic activity. EMEG is furthermore able to reveal the propagation pathway at later time points in agreement with sEEG, while EEG or MEG alone reconstructed only parts of it. Subaveraging provides important and accurate information about both the center of gravity and the extent of the epileptogenic tissue that neither single nor grand-averaged spike localizations can supply.
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Affiliation(s)
- Ümit Aydin
- Institute for Biomagnetism and Biosignalanalysis, Westfälische Wilhelms-Universität Münster, Münster, Germany
- Institute for Biomedical Engineering and Informatics, Technische Universität Ilmenau, Ilmenau, Germany
- * E-mail:
| | - Johannes Vorwerk
- Institute for Biomagnetism and Biosignalanalysis, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Matthias Dümpelmann
- Epilepsy Center, Universitätsklinikum Freiburg, Freiburg im Breisgau, Germany
| | - Philipp Küpper
- Institute for Biomagnetism and Biosignalanalysis, Westfälische Wilhelms-Universität Münster, Münster, Germany
- Department of Neurology, Klinikum Osnabrück, Osnabrück, Germany
| | - Harald Kugel
- Department of Clinical Radiology, Universitätsklinikum Münster, Münster, Germany
| | - Marcel Heers
- Epilepsy Center, Universitätsklinikum Freiburg, Freiburg im Breisgau, Germany
- Ruhr-Epileptology Department of Neurology, Universitätsklinikum Knappschaftskrankenhaus Bochum, Bochum, Germany
| | - Jörg Wellmer
- Ruhr-Epileptology Department of Neurology, Universitätsklinikum Knappschaftskrankenhaus Bochum, Bochum, Germany
| | | | - Jens Haueisen
- Institute for Biomedical Engineering and Informatics, Technische Universität Ilmenau, Ilmenau, Germany
| | - Stefan Rampp
- Ruhr-Epileptology Department of Neurology, Universitätsklinikum Knappschaftskrankenhaus Bochum, Bochum, Germany
- Epilepsy Center, Department of Neurology, Universitätsklinikum Erlangen, Erlangen, Germany
| | - Hermann Stefan
- Epilepsy Center, Department of Neurology, Universitätsklinikum Erlangen, Erlangen, Germany
| | - Carsten H. Wolters
- Institute for Biomagnetism and Biosignalanalysis, Westfälische Wilhelms-Universität Münster, Münster, Germany
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45
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Dunkley BT, Da Costa L, Bethune A, Jetly R, Pang EW, Taylor MJ, Doesburg SM. Low-frequency connectivity is associated with mild traumatic brain injury. NEUROIMAGE-CLINICAL 2015; 7:611-21. [PMID: 25844315 PMCID: PMC4379387 DOI: 10.1016/j.nicl.2015.02.020] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/05/2014] [Revised: 02/05/2015] [Accepted: 02/27/2015] [Indexed: 01/18/2023]
Abstract
Mild traumatic brain injury (mTBI) occurs from a closed-head impact. Often referred to as concussion, about 20% of cases complain of secondary psychological sequelae, such as disorders of attention and memory. Known as post-concussive symptoms (PCS), these problems can severely disrupt the patient's quality of life. Changes in local spectral power, particularly low-frequency amplitude increases and/or peak alpha slowing have been reported in mTBI, but large-scale connectivity metrics based on inter-regional amplitude correlations relevant for integration and segregation in functional brain networks, and their association with disorders in cognition and behaviour, remain relatively unexplored. Here, we used non-invasive neuroimaging with magnetoencephalography to examine functional connectivity in a resting-state protocol in a group with mTBI (n = 20), and a control group (n = 21). We observed a trend for atypical slow-wave power changes in subcortical, temporal and parietal regions in mTBI, as well as significant long-range increases in amplitude envelope correlations among deep-source, temporal, and frontal regions in the delta, theta, and alpha bands. Subsequently, we conducted an exploratory analysis of patterns of connectivity most associated with variability in secondary symptoms of mTBI, including inattention, anxiety, and depression. Differential patterns of altered resting state neurophysiological network connectivity were found across frequency bands. This indicated that multiple network and frequency specific alterations in large scale brain connectivity may contribute to overlapping cognitive sequelae in mTBI. In conclusion, we show that local spectral power content can be supplemented with measures of correlations in amplitude to define general networks that are atypical in mTBI, and suggest that certain cognitive difficulties are mediated by disturbances in a variety of alterations in network interactions which are differentially expressed across canonical neurophysiological frequency ranges. Patients with mTBI display increased connectivity in low-frequency resting state. Elevated low-frequency power observed in temporal and deep-grey regions in mTBI Frontal, temporal and deep-grey regions show increased amplitude correlations in mTBI. Disorders of attention, anxiety and depression are associated with distinct, frequency-specific networks across the brain.
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Affiliation(s)
- B T Dunkley
- Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, Canada ; Neuroscience & Mental Health Program, The Hospital for Sick Children Research Institute, Toronto, Canada
| | - L Da Costa
- Division of Neurosurgery, Sunnybrook Hospital, Toronto, Canada
| | - A Bethune
- Division of Neurosurgery, Sunnybrook Hospital, Toronto, Canada
| | - R Jetly
- Directorate of Mental Health, Canadian Forces Health Services, Ottawa, Canada
| | - E W Pang
- Neuroscience & Mental Health Program, The Hospital for Sick Children Research Institute, Toronto, Canada ; Division of Neurology, The Hospital for Sick Children, Toronto, Canada
| | - M J Taylor
- Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, Canada ; Neuroscience & Mental Health Program, The Hospital for Sick Children Research Institute, Toronto, Canada ; Division of Neurology, The Hospital for Sick Children, Toronto, Canada ; Department of Medical Imaging, University of Toronto, Toronto, Canada
| | - S M Doesburg
- Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, Canada ; Neuroscience & Mental Health Program, The Hospital for Sick Children Research Institute, Toronto, Canada ; Department of Psychology, University of Toronto, Toronto, Canada ; Department of Medical Imaging, University of Toronto, Toronto, Canada
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46
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Edgar JC, Heiken K, Chen YH, Herrington JD, Chow V, Liu S, Bloy L, Huang M, Pandey J, Cannon KM, Qasmieh S, Levy SE, Schultz RT, Roberts TPL. Resting-state alpha in autism spectrum disorder and alpha associations with thalamic volume. J Autism Dev Disord 2015; 45:795-804. [PMID: 25231288 PMCID: PMC6102716 DOI: 10.1007/s10803-014-2236-1] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
Alpha circuits (8-12 Hz), necessary for basic and complex brain processes, are abnormal in autism spectrum disorder (ASD). The present study obtained estimates of resting-state (RS) alpha activity in children with ASD and examined associations between alpha activity, age, and clinical symptoms. Given that the thalamus modulates cortical RS alpha rhythms, associations between thalamic structure and alpha activity were examined. RS magnetoencephalography was obtained from 47 typically-developing children (TDC) and 41 children with ASD. RS alpha activity was measured using distributed source localization. Left and right thalamic volume measurements were also obtained. In both groups, the strongest alpha activity was observed in Calcarine Sulcus regions. In Calcarine regions, only TDC showed the expected association between age and alpha peak frequency. ASD had more alpha activity than TDC in regions bordering the Central Sulcus as well as parietal association cortices. In ASD, whereas greater left Central Sulcus relative alpha activity was associated with higher Social Responsiveness Scale (SRS) scores, greater Calcarine region relative alpha activity was associated with lower SRS scores. Although thalamic volume group differences were not observed, relationships between thalamic volume and Calcarine alpha power were unique to TDC. The present study also identified a failure to shift peak alpha frequency as a function of age in primary alpha-generating areas in children with ASD. Findings suggested that increased RS alpha activity in primary motor and somatosensory as well as parietal multimodal areas-with increased alpha thought to reflect greater inhibition-might impair the ability to identify or interpret social cues. Finally, to our knowledge, this is the first study to report associations between thalamic volume and alpha power, an association observed only in TDC. The lack of thalamic and alpha associations in ASD suggests thalamic contributions to RS alpha abnormalities in ASD.
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Affiliation(s)
- J Christopher Edgar
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, 34th and Civic Center Blvd, Wood Building, Suite 2115, Philadelphia, PA, 10104, USA,
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47
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Influence of the head model on EEG and MEG source connectivity analyses. Neuroimage 2015; 110:60-77. [PMID: 25638756 DOI: 10.1016/j.neuroimage.2015.01.043] [Citation(s) in RCA: 73] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2014] [Revised: 12/06/2014] [Accepted: 01/23/2015] [Indexed: 11/21/2022] Open
Abstract
The results of brain connectivity analysis using reconstructed source time courses derived from EEG and MEG data depend on a number of algorithmic choices. While previous studies have investigated the influence of the choice of source estimation method or connectivity measure, the effects of the head modeling errors or simplifications have not been studied sufficiently. In the present simulation study, we investigated the influence of particular properties of the head model on the reconstructed source time courses as well as on source connectivity analysis in EEG and MEG. Therefore, we constructed a realistic head model and applied the finite element method to solve the EEG and MEG forward problems. We considered the distinction between white and gray matter, the distinction between compact and spongy bone, the inclusion of a cerebrospinal fluid (CSF) compartment, and the reduction to a simple 3-layer model comprising only the skin, skull, and brain. Source time courses were reconstructed using a beamforming approach and the source connectivity was estimated by the imaginary coherence (ICoh) and the generalized partial directed coherence (GPDC). Our results show that in both EEG and MEG, neglecting the white and gray matter distinction or the CSF causes considerable errors in reconstructed source time courses and connectivity analysis, while the distinction between spongy and compact bone is just of minor relevance, provided that an adequate skull conductivity value is used. Large inverse and connectivity errors are found in the same regions that show large topography errors in the forward solution. Moreover, we demonstrate that the very conservative ICoh is relatively safe from the crosstalk effects caused by imperfect head models, as opposed to the GPDC.
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48
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Muthuraman M, Hellriegel H, Hoogenboom N, Anwar AR, Mideksa KG, Krause H, Schnitzler A, Raethjen J, Deuschl G. Coherent source and connectivity analysis on simultaneously measured EEG and MEG data during isometric contraction. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2015; 2014:6365-8. [PMID: 25571452 DOI: 10.1109/embc.2014.6945084] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
The most well-known non-invasive electric and magnetic field measurement modalities are the electroencephalography (EEG) and magnetoencephalography (MEG). The first aim of the study was to implement the recently developed realistic head model which uses an integrative approach for both the modalities. The second aim of this study was to find the network of coherent sources and the modes of interactions within this network during isometric contraction (ISC) at (15-30 Hz) in healthy subjects. The third aim was to test the effective connectivity revealed by both the modalities analyzing them separately and combined. The Welch periodogram method was used to estimate the coherence spectrum between the EEG and the electromyography (EMG) signals followed by the realistic head modelling and source analysis method dynamic imaging of coherent sources (DICS) to find the network of coherent sources at the individual peak frequency within the beta band in healthy subjects. The last step was to identify the effective connectivity between the identified sources using the renormalized partial directed coherence method. The cortical and sub-cortical network comprised of the primary sensory motor cortex (PSMC), secondary motor area (SMA), and the cerebellum (C). The cortical and sub-cortical network responsible for the isometric contraction was similar in both the modalities when analysing them separately and combined. The SNR was not significantly different between the two modalities separately and combined. However, the coherence values were significantly higher in the combined modality in comparison to each of the modality separately. The effective connectivity analysis revealed plausible additional connections in the combined modality analysis.
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49
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Huang MX, Yurgil KA, Robb A, Angeles A, Diwakar M, Risbrough VB, Nichols SL, McLay R, Theilmann RJ, Song T, Huang CW, Lee RR, Baker DG. Voxel-wise resting-state MEG source magnitude imaging study reveals neurocircuitry abnormality in active-duty service members and veterans with PTSD. NEUROIMAGE-CLINICAL 2014; 5:408-19. [PMID: 25180160 PMCID: PMC4145534 DOI: 10.1016/j.nicl.2014.08.004] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/28/2014] [Revised: 07/25/2014] [Accepted: 08/02/2014] [Indexed: 11/25/2022]
Abstract
Post-traumatic stress disorder (PTSD) is a leading cause of sustained impairment, distress, and poor quality of life in military personnel, veterans, and civilians. Indirect functional neuroimaging studies using PET or fMRI with fear-related stimuli support a PTSD neurocircuitry model that includes amygdala, hippocampus, and ventromedial prefrontal cortex (vmPFC). However, it is not clear if this model can fully account for PTSD abnormalities detected directly by electromagnetic-based source imaging techniques in resting-state. The present study examined resting-state magnetoencephalography (MEG) signals in 25 active-duty service members and veterans with PTSD and 30 healthy volunteers. In contrast to the healthy volunteers, individuals with PTSD showed: 1) hyperactivity from amygdala, hippocampus, posterolateral orbitofrontal cortex (OFC), dorsomedial prefrontal cortex (dmPFC), and insular cortex in high-frequency (i.e., beta, gamma, and high-gamma) bands; 2) hypoactivity from vmPFC, Frontal Pole (FP), and dorsolateral prefrontal cortex (dlPFC) in high-frequency bands; 3) extensive hypoactivity from dlPFC, FP, anterior temporal lobes, precuneous cortex, and sensorimotor cortex in alpha and low-frequency bands; and 4) in individuals with PTSD, MEG activity in the left amygdala and posterolateral OFC correlated positively with PTSD symptom scores, whereas MEG activity in vmPFC and precuneous correlated negatively with symptom score. The present study showed that MEG source imaging technique revealed new abnormalities in the resting-state electromagnetic signals from the PTSD neurocircuitry. Particularly, posterolateral OFC and precuneous may play important roles in the PTSD neurocircuitry model. Resting-state MEG detects abnormal electromagnetic activity in PTSD neurocircuitry PTSD showed hyperactivity in amygdala, hippocampus, and orbitofrontal cortex PTSD showed hypoactivity in vmPFC, frontal pole, and dlPFC PTSD symptom score correlated with MEG activity
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Affiliation(s)
- Ming-Xiong Huang
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA ; Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Kate A Yurgil
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA ; VA Center of Excellence for Stress and Mental Health, San Diego, CA, USA
| | - Ashley Robb
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
| | - Annemarie Angeles
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
| | - Mithun Diwakar
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Victoria B Risbrough
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA ; VA Center of Excellence for Stress and Mental Health, San Diego, CA, USA ; Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Sharon L Nichols
- Department of Neurosciences, University of California San Diego, San Diego, CA, USA
| | - Robert McLay
- Naval Medical Center San Diego, San Diego, CA, USA
| | - Rebecca J Theilmann
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Tao Song
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Charles W Huang
- Department of Bioengineering, University of California San Diego, San Diego, CA, USA
| | - Roland R Lee
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA ; Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Dewleen G Baker
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA ; VA Center of Excellence for Stress and Mental Health, San Diego, CA, USA ; Department of Psychiatry, University of California San Diego, San Diego, CA, USA
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50
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Vorwerk J, Cho JH, Rampp S, Hamer H, Knösche TR, Wolters CH. A guideline for head volume conductor modeling in EEG and MEG. Neuroimage 2014; 100:590-607. [PMID: 24971512 DOI: 10.1016/j.neuroimage.2014.06.040] [Citation(s) in RCA: 172] [Impact Index Per Article: 17.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2014] [Revised: 05/30/2014] [Accepted: 06/18/2014] [Indexed: 11/30/2022] Open
Abstract
For accurate EEG/MEG source analysis it is necessary to model the head volume conductor as realistic as possible. This includes the distinction of the different conductive compartments in the human head. In this study, we investigated the influence of modeling/not modeling the conductive compartments skull spongiosa, skull compacta, cerebrospinal fluid (CSF), gray matter, and white matter and of the inclusion of white matter anisotropy on the EEG/MEG forward solution. Therefore, we created a highly realistic 6-compartment head model with white matter anisotropy and used a state-of-the-art finite element approach. Starting from a 3-compartment scenario (skin, skull, and brain), we subsequently refined our head model by distinguishing one further of the above-mentioned compartments. For each of the generated five head models, we measured the effect on the signal topography and signal magnitude both in relation to a highly resolved reference model and to the model generated in the previous refinement step. We evaluated the results of these simulations using a variety of visualization methods, allowing us to gain a general overview of effect strength, of the most important source parameters triggering these effects, and of the most affected brain regions. Thereby, starting from the 3-compartment approach, we identified the most important additional refinement steps in head volume conductor modeling. We were able to show that the inclusion of the highly conductive CSF compartment, whose conductivity value is well known, has the strongest influence on both signal topography and magnitude in both modalities. We found the effect of gray/white matter distinction to be nearly as big as that of the CSF inclusion, and for both of these steps we identified a clear pattern in the spatial distribution of effects. In comparison to these two steps, the introduction of white matter anisotropy led to a clearly weaker, but still strong, effect. Finally, the distinction between skull spongiosa and compacta caused the weakest effects in both modalities when using an optimized conductivity value for the homogenized compartment. We conclude that it is highly recommendable to include the CSF and distinguish between gray and white matter in head volume conductor modeling. Especially for the MEG, the modeling of skull spongiosa and compacta might be neglected due to the weak effects; the simplification of not modeling white matter anisotropy is admissible considering the complexity and current limitations of the underlying modeling approach.
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Affiliation(s)
- Johannes Vorwerk
- Institut für Biomagnetismus und Biosignalanalyse, Westfälische Wilhelms-Universität, Münster, Germany.
| | - Jae-Hyun Cho
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Stefan Rampp
- Epilepsiezentrum, Universitätsklinikum Erlangen, Erlangen, Germany
| | - Hajo Hamer
- Epilepsiezentrum, Universitätsklinikum Erlangen, Erlangen, Germany
| | - Thomas R Knösche
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Carsten H Wolters
- Institut für Biomagnetismus und Biosignalanalyse, Westfälische Wilhelms-Universität, Münster, Germany
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