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Rubega M, Storti SF, Pascucci D. Editorial: Chasing brain dynamics at their speed: what can time-varying functional connectivity tell us about brain function? Front Neurosci 2023; 17:1223955. [PMID: 37389369 PMCID: PMC10299920 DOI: 10.3389/fnins.2023.1223955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 05/30/2023] [Indexed: 07/01/2023] Open
Affiliation(s)
- Maria Rubega
- Section of Rehabilitation, Department of Neuroscience, University of Padua, Padua, Italy
| | | | - David Pascucci
- Laboratory of Psychophysics, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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2
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Mittal A, Singh Dhanota DP, Saggar K, Singh G, Ahluwalia A. Role of Interictal Arterial Spin Labeling Magnetic Resonance Perfusion in Mesial Temporal Lobe Epilepsy. Ann Indian Acad Neurol 2021; 24:495-500. [PMID: 34728940 PMCID: PMC8513983 DOI: 10.4103/aian.aian_1274_20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 01/31/2021] [Accepted: 04/14/2021] [Indexed: 11/18/2022] Open
Abstract
Context: Electrophysiological and hemodynamic data can be integrated to accurately identify the generators of abnormal electrical activity in drug-resistant focal epilepsy. Arterial Spin Labeling (ASL), a magnetic resonance imaging (MRI) technique for quantitative noninvasive measurement of cerebral blood flow (CBF), can provide a direct measure of variations in cerebral perfusion associated with the epileptogenic zone. Aims: 1. To evaluate usefulness of ASL for detecting interictal temporal hypoperfusion to localize the epileptogenic zone in patients of drug resistant mesial temporal lobe epilepsy (MTLE). 2. Correlation of localization of epileptogenic zone on ASL MR perfusion with structural MRI and EEG. Methods and Materials: 30 patients with MTLE and10 age and gender matched normal controls were studied. All patients underwent ictal video EEG monitoring non-invasively, MR imaging with epilepsy protocol and pseudocontinuous ASL (PCASL) perfusion study. Relative CBF (rCBF) values in bilateral mesial temporal lobes were measured utilizing quantitative analysis of perfusion images. A perfusion asymmetry index (AI) was calculated for each region. Results: In patients, ipsilateral mesial temporal rCBF was significantly decreased compared with contralateral mesial temporal rCBF (p = 0.021). Mesial temporal blood flow was more asymmetric in patients than in normal control participants (p = 0.000). Clear perfusion asymmetry on PCASL-MRI was identified despite normal structural-MRI in 5 cases, agreeing with EEG laterality. Conclusions: Pseudo-continuous ASL offers a promising approach to detect interictal hypoperfusion in TLE and as a clinical alternative to SPECT and PET due to non-invasiveness and easy accessibility. Incorporation of ASL into routine pre-surgical evaluation protocols can help to localize epileptogenic zone in surgical candidates.
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Affiliation(s)
- Ashima Mittal
- Department of Radiodiagnosis and Imaging, Dayanand Medical College and Hospital, Ludhiana, Punjab, India
| | - Devinder Pal Singh Dhanota
- Department of Radiodiagnosis and Imaging, Dayanand Medical College and Hospital, Ludhiana, Punjab, India
| | - Kavita Saggar
- Department of Radiodiagnosis and Imaging, Dayanand Medical College and Hospital, Ludhiana, Punjab, India
| | - Gagandeep Singh
- Department of Neurology, Dayanand Medical College and Hospital, Ludhiana, Punjab, India
| | - Archana Ahluwalia
- Department of Radiodiagnosis and Imaging, Dayanand Medical College and Hospital, Ludhiana, Punjab, India
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3
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Sadjadi SM, Ebrahimzadeh E, Shams M, Seraji M, Soltanian-Zadeh H. Localization of Epileptic Foci Based on Simultaneous EEG-fMRI Data. Front Neurol 2021; 12:645594. [PMID: 33986718 PMCID: PMC8110922 DOI: 10.3389/fneur.2021.645594] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 03/11/2021] [Indexed: 02/01/2023] Open
Abstract
Combining functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) enables a non-invasive investigation of the human brain function and evaluation of the correlation of these two important modalities of brain activity. This paper explores recent reports on using advanced simultaneous EEG–fMRI methods proposed to map the regions and networks involved in focal epileptic seizure generation. One of the applications of EEG and fMRI combination as a valuable clinical approach is the pre-surgical evaluation of patients with epilepsy to map and localize the precise brain regions associated with epileptiform activity. In the process of conventional analysis using EEG–fMRI data, the interictal epileptiform discharges (IEDs) are visually extracted from the EEG data to be convolved as binary events with a predefined hemodynamic response function (HRF) to provide a model of epileptiform BOLD activity and use as a regressor for general linear model (GLM) analysis of the fMRI data. This review examines the methodologies involved in performing such studies, including techniques used for the recording of EEG inside the scanner, artifact removal, and statistical analysis of the fMRI signal. It then discusses the results reported for patients with primary generalized epilepsy and patients with different types of focal epileptic disorders. An important matter that these results have brought to light is that the brain regions affected by interictal epileptic discharges might not be limited to the ones where they have been generated. The developed methods can help reveal the regions involved in or affected by a seizure onset zone (SOZ). As confirmed by the reviewed literature, EEG–fMRI provides information that comes particularly useful when evaluating patients with refractory epilepsy for surgery.
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Affiliation(s)
- Seyyed Mostafa Sadjadi
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
| | - Elias Ebrahimzadeh
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.,Neuroimage Signal and Image Analysis Group, School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | - Mohammad Shams
- Neural Engineering Laboratory, Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, United States
| | - Masoud Seraji
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, United States.,Behavioral and Neural Sciences Graduate Program, Rutgers University, Newark, NJ, United States
| | - Hamid Soltanian-Zadeh
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.,Neuroimage Signal and Image Analysis Group, School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran.,Medical Image Analysis Laboratory, Departments of Radiology and Research Administration, Henry Ford Health System, Detroit, MI, United States
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4
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Van Eyndhoven S, Dupont P, Tousseyn S, Vervliet N, Van Paesschen W, Van Huffel S, Hunyadi B. Augmenting interictal mapping with neurovascular coupling biomarkers by structured factorization of epileptic EEG and fMRI data. Neuroimage 2020; 228:117652. [PMID: 33359347 PMCID: PMC7903163 DOI: 10.1016/j.neuroimage.2020.117652] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Revised: 11/28/2020] [Accepted: 12/04/2020] [Indexed: 12/20/2022] Open
Abstract
EEG-correlated fMRI analysis is widely used to detect regional BOLD fluctuations that are synchronized to interictal epileptic discharges, which can provide evidence for localizing the ictal onset zone. However, the typical, asymmetrical and mass-univariate approach cannot capture the inherent, higher order structure in the EEG data, nor multivariate relations in the fMRI data, and it is nontrivial to accurately handle varying neurovascular coupling over patients and brain regions. We aim to overcome these drawbacks in a data-driven manner by means of a novel structured matrix-tensor factorization: the single-subject EEG data (represented as a third-order spectrogram tensor) and fMRI data (represented as a spatiotemporal BOLD signal matrix) are jointly decomposed into a superposition of several sources, characterized by space-time-frequency profiles. In the shared temporal mode, Toeplitz-structured factors account for a spatially specific, neurovascular 'bridge' between the EEG and fMRI temporal fluctuations, capturing the hemodynamic response's variability over brain regions. By analyzing interictal data from twelve patients, we show that the extracted source signatures provide a sensitive localization of the ictal onset zone (10/12). Moreover, complementary parts of the IOZ can be uncovered by inspecting those regions with the most deviant neurovascular coupling, as quantified by two entropy-like metrics of the hemodynamic response function waveforms (9/12). Hence, this multivariate, multimodal factorization provides two useful sets of EEG-fMRI biomarkers, which can assist the presurgical evaluation of epilepsy. We make all code required to perform the computations available at https://github.com/svaneynd/structured-cmtf.
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Affiliation(s)
- Simon Van Eyndhoven
- Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Belgium.
| | - Patrick Dupont
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium; Leuven Brain Institute, Leuven, Belgium
| | - Simon Tousseyn
- Academic Center for Epileptology, Kempenhaeghe and Maastricht UMC+, Heeze, the Netherlands
| | - Nico Vervliet
- Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Belgium
| | - Wim Van Paesschen
- Laboratory for Epilepsy Research, KU Leuven, Leuven, Belgium; Department of Neurology, University Hospitals Leuven, Leuven, Belgium
| | - Sabine Van Huffel
- Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Belgium
| | - Borbála Hunyadi
- Circuits and Systems Group (CAS), Department of Microelectronics, Delft University of Technology, Delft, the Netherlands
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5
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Hosseini MP, Tran TX, Pompili D, Elisevich K, Soltanian-Zadeh H. Multimodal data analysis of epileptic EEG and rs-fMRI via deep learning and edge computing. Artif Intell Med 2020; 104:101813. [DOI: 10.1016/j.artmed.2020.101813] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Revised: 12/26/2019] [Accepted: 01/31/2020] [Indexed: 11/28/2022]
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6
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Cury C, Maurel P, Gribonval R, Barillot C. A Sparse EEG-Informed fMRI Model for Hybrid EEG-fMRI Neurofeedback Prediction. Front Neurosci 2020; 13:1451. [PMID: 32076396 PMCID: PMC7006471 DOI: 10.3389/fnins.2019.01451] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Accepted: 12/30/2019] [Indexed: 01/06/2023] Open
Abstract
Measures of brain activity through functional magnetic resonance imaging (fMRI) or electroencephalography (EEG), two complementary modalities, are ground solutions in the context of neurofeedback (NF) mechanisms for brain rehabilitation protocols. While NF-EEG (in which real-time neurofeedback scores are computed from EEG signals) has been explored for a very long time, NF-fMRI (in which real-time neurofeedback scores are computed from fMRI signals) appeared more recently and provides more robust results and more specific brain training. Using fMRI and EEG simultaneously for bi-modal neurofeedback sessions (NF-EEG-fMRI, in which real-time neurofeedback scores are computed from fMRI and EEG) is very promising for the design of brain rehabilitation protocols. However, fMRI is cumbersome and more exhausting for patients. The original contribution of this paper concerns the prediction of bi-modal NF scores from EEG recordings only, using a training phase where EEG signals as well as the NF-EEG and NF-fMRI scores are available. We propose a sparse regression model able to exploit EEG only to predict NF-fMRI or NF-EEG-fMRI in motor imagery tasks. We compared different NF-predictors stemming from the proposed model. We showed that predicting NF-fMRI scores from EEG signals adds information to NF-EEG scores and significantly improves the correlation with bi-modal NF sessions compared to classical NF-EEG scores.
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Affiliation(s)
- Claire Cury
- University of Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, Empenn Team ERL U 1228, Rennes, France.,University of Rennes, CNRS, Inria, IRISA UMR 6074, PANAMA Team, Rennes, France
| | - Pierre Maurel
- University of Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, Empenn Team ERL U 1228, Rennes, France
| | - Rémi Gribonval
- University of Rennes, CNRS, Inria, IRISA UMR 6074, PANAMA Team, Rennes, France
| | - Christian Barillot
- University of Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, Empenn Team ERL U 1228, Rennes, France
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7
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Marino M, Arcara G, Porcaro C, Mantini D. Hemodynamic Correlates of Electrophysiological Activity in the Default Mode Network. Front Neurosci 2019; 13:1060. [PMID: 31636535 PMCID: PMC6788217 DOI: 10.3389/fnins.2019.01060] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Accepted: 09/20/2019] [Indexed: 12/16/2022] Open
Abstract
Hemodynamic fluctuations in the default mode network (DMN), observed through functional magnetic resonance imaging (fMRI), have been linked to electrophysiological oscillations detected by electroencephalography (EEG). It has been reported that, among the electrophysiological oscillations, those in the alpha frequency range (8–13 Hz) are the most dominant during resting state. We hypothesized that DMN spatial configuration closely depends on the specific neuronal oscillations considered, and that alpha oscillations would mainly correlate with increased blood oxygen-level dependent (BOLD) signal in the DMN. To test this hypothesis, we used high-density EEG (hdEEG) data simultaneously collected with fMRI scanning in 20 healthy volunteers at rest. We first detected the DMN from source reconstructed hdEEG data for multiple frequency bands, and we then mapped the correlation between temporal profile of hdEEG-derived DMN activity and fMRI–BOLD signals on a voxel-by-voxel basis. In line with our hypothesis, we found that the correlation map associated with alpha oscillations, more than with any other frequency bands, displayed a larger overlap with DMN regions. Overall, our study provided further evidence for a primary role of alpha oscillations in supporting DMN functioning. We suggest that simultaneous EEG–fMRI may represent a powerful tool to investigate the neurophysiological basis of human brain networks.
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Affiliation(s)
- Marco Marino
- Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, Venice, Italy
| | - Giorgio Arcara
- Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, Venice, Italy
| | - Camillo Porcaro
- Institute of Cognitive Sciences and Technologies (ISTC) - National Research Council (CNR), Rome, Italy.,S. Anna Institute and Research in Advanced Neurorehabilitation (RAN), Crotone, Italy.,Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.,Research Center for Motor Control and Neuroplasticity, KU Leuven, Leuven, Belgium
| | - Dante Mantini
- Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, Venice, Italy.,Research Center for Motor Control and Neuroplasticity, KU Leuven, Leuven, Belgium
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8
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Ebrahimzadeh E, Shams M, Fayaz F, Rajabion L, Mirbagheri M, Nadjar Araabi B, Soltanian-Zadeh H. Quantitative determination of concordance in localizing epileptic focus by component-based EEG-fMRI. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2019; 177:231-241. [PMID: 31319952 DOI: 10.1016/j.cmpb.2019.06.003] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2018] [Revised: 05/07/2019] [Accepted: 06/04/2019] [Indexed: 02/01/2023]
Abstract
BACKGROUND AND OBJECTIVE Accurate seizure onset zone (SOZ) localization is an essential step in pre-surgical assessment of patients with refractory focal epilepsy. Complex pathophysiology of epileptic cerebral structures, seizure types and frequencies have not been considered as influential features for accurate identification of SOZ using EEG-fMRI. There is a crucial need to quantitatively measure concordance between presumed SOZ and IED-related BOLD response in different brain regions to improve SOZ delineation. METHODS A novel component-based EEG-fMRI approach is proposed to measure physical distance between BOLD clusters and selected component dipole location using patient-specific high resolution anatomical images. The method is applied on 18 patients with refractory focal epilepsy to localize epileptic focus and determine concordance quantitatively and compare between maximum BOLD cluster with identified component dipole. To measure concordance, distance from a voxel with maximal z-score of maximum BOLD to center of extracted component dipole is measured. RESULTS BOLD clusters to spikes distances for concordant (<25 mm), partially concordant (25-50 mm), and discordant (>50 mm) groups were significantly different (p < 0.0001). The results showed full concordance in 17 IED types (17.85 ± 4.69 mm), partial concordance in 4 (36.47 ± 8.84 mm), and nodiscordance, which is a significant rise compared to the existing literature. The proposed method is premised on the cross-correlation between the spike template outside the scanner and the highly-ranked extracted components. It successfully surpasses the limitations of conventional EEG-fMRI studies which are largely dependent on inside-scanner spikes. More significantly, the proposed method improves localization accuracy to 97% which marks a dramatic rise compared to conventional works. CONCLUSIONS This study demonstrated that BOLD changes were related to epileptic spikes in different brain regions in patients with refractory focal epilepsy. In a systematic quantitative approach, concordance levels based on the distance between center of maximum BOLD cluster and dipole were determined by component-based EEG-fMRI method. Therefore, component-based EEG-fMRI can be considered as a reliable predictor of SOZ in patients with focal epilepsy and included as part of clinical evaluation for patients with medically resistant epilepsy.
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Affiliation(s)
- Elias Ebrahimzadeh
- CIPCE, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran; Seaman Family MR Research Centre, University of Calgary, Calgary, Alberta, Canada.
| | - Mohammad Shams
- Department of Biomedical Engineering, George Washington University, Washington D.C., USA
| | - Farahnaz Fayaz
- Biomedical Engineering Department, School of Electrical Engineering, Payame Noor University of North Tehran, Tehran, Iran
| | - Lila Rajabion
- Department of IT, College of Business, University of South Florida Sarasota-Manatee, USA
| | - Mahya Mirbagheri
- CIPCE, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
| | - Babak Nadjar Araabi
- CIPCE, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
| | - Hamid Soltanian-Zadeh
- CIPCE, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran; Image Analysis Laboratory, Department of Radiology, Henry Ford Hospital, Detroit, MI, USA
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9
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Abreu R, Leal A, Figueiredo P. EEG-Informed fMRI: A Review of Data Analysis Methods. Front Hum Neurosci 2018; 12:29. [PMID: 29467634 PMCID: PMC5808233 DOI: 10.3389/fnhum.2018.00029] [Citation(s) in RCA: 71] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2017] [Accepted: 01/18/2018] [Indexed: 01/17/2023] Open
Abstract
The simultaneous acquisition of electroencephalography (EEG) with functional magnetic resonance imaging (fMRI) is a very promising non-invasive technique for the study of human brain function. Despite continuous improvements, it remains a challenging technique, and a standard methodology for data analysis is yet to be established. Here we review the methodologies that are currently available to address the challenges at each step of the data analysis pipeline. We start by surveying methods for pre-processing both EEG and fMRI data. On the EEG side, we focus on the correction for several MR-induced artifacts, particularly the gradient and pulse artifacts, as well as other sources of EEG artifacts. On the fMRI side, we consider image artifacts induced by the presence of EEG hardware inside the MR scanner, and the contamination of the fMRI signal by physiological noise of non-neuronal origin, including a review of several approaches to model and remove it. We then provide an overview of the approaches specifically employed for the integration of EEG and fMRI when using EEG to predict the blood oxygenation level dependent (BOLD) fMRI signal, the so-called EEG-informed fMRI integration strategy, the most commonly used strategy in EEG-fMRI research. Finally, we systematically review methods used for the extraction of EEG features reflecting neuronal phenomena of interest.
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Affiliation(s)
- Rodolfo Abreu
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico - Universidade de Lisboa, Lisbon, Portugal
| | - Alberto Leal
- Department of Neurophysiology, Centro Hospitalar Psiquiátrico de Lisboa, Lisbon, Portugal
| | - Patrícia Figueiredo
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico - Universidade de Lisboa, Lisbon, Portugal
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10
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Abreu R, Leal A, Lopes da Silva F, Figueiredo P. EEG synchronization measures predict epilepsy-related BOLD-fMRI fluctuations better than commonly used univariate metrics. Clin Neurophysiol 2018; 129:618-635. [PMID: 29414405 DOI: 10.1016/j.clinph.2017.12.038] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2017] [Revised: 11/29/2017] [Accepted: 12/22/2017] [Indexed: 10/18/2022]
Abstract
OBJECTIVE We hypothesize that the hypersynchronization associated with epileptic activity is best described by EEG synchronization measures, and propose to use these as predictors of epilepsy-related BOLD fluctuations. METHODS We computed the phase synchronization index (PSI) and global field synchronization (GFS), within two frequency bands, a broadband (1-45 Hz) and a narrower band focused on the presence of epileptic activity (3-10 Hz). The associated epileptic networks were compared with those obtained using conventional unitary regressors and two power-weighted metrics (total power and root mean square frequency), on nine simultaneous EEG-fMRI datasets from four epilepsy patients, exhibiting inter-ictal epileptiform discharges (IEDs). RESULTS The average PSI within 3-10 Hz achieved the best performance across several measures reflecting reliability in all datasets. The results were cross-validated through electrical source imaging of the IEDs. The applicability of PSI when no IEDs are recorded on the EEG was evaluated on three additional patients, yielding partially plausible networks in all cases. CONCLUSIONS Epileptic networks can be mapped based on the EEG PSI metric within an IED-specific frequency band, performing better than commonly used EEG metrics. SIGNIFICANCE This is the first study to investigate EEG synchronization measures as potential predictors of epilepsy-related BOLD fluctuations.
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Affiliation(s)
- Rodolfo Abreu
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico - Universidade de Lisboa, Portugal.
| | - Alberto Leal
- Department of Neurophysiology, Centro Hospitalar Psiquiátrico de Lisboa, Lisbon, Portugal
| | | | - Patrícia Figueiredo
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico - Universidade de Lisboa, Portugal
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11
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Detecting sub-second changes in brain activation patterns during interictal epileptic spike using simultaneous EEG-fMRI. Clin Neurophysiol 2017; 129:377-389. [PMID: 29288994 DOI: 10.1016/j.clinph.2017.11.018] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2017] [Revised: 09/29/2017] [Accepted: 11/16/2017] [Indexed: 11/21/2022]
Abstract
OBJECTIVE Epileptic spikes are associated with rapidly changing brain activation involving the epileptic foci and other brain regions in the "epileptic network". We aim to resolve these activation changes using simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) recordings. METHODS Simultaneous EEG-fMRI recordings from 9 patients with epilepsy were used in the analysis. Our method employed the whole scalp EEG data to generate regressors for the analysis of fMRI data using the general linear model. RESULTS We were able to resolve, with milliseconds temporal resolution, changes in activation patterns involving suspected epileptic foci and other brain regions in the epileptic network during spike and slow wave. Using summary maps (called SSWAS maps) which show the activation frequency of voxels, we found that suspected epileptic foci tend to be significantly active during this interval. SSWAS maps also enabled the detection of the epileptic foci in 4 of 5 patients where the conventional event-timing-based analysis failed to identify. CONCLUSION These findings demonstrated the efficacy of the method and the potential application of SSWAS maps to identify epileptic foci. SIGNIFICANCE The method could help resolve activation changes during epileptic spike and could provide insights into the underlying pathophysiology of these changes.
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12
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Seizures and brain regulatory systems: consciousness, sleep, and autonomic systems. J Clin Neurophysiol 2016; 32:188-93. [PMID: 25233249 DOI: 10.1097/wnp.0000000000000133] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Research into the physiologic underpinnings of epilepsy has revealed reciprocal relationships between seizures and the activity of several regulatory systems in the brain. This review highlights recent progress in understanding and using the relationships between seizures and the arousal or consciousness system, the sleep-wake and associated circadian system, and the central autonomic network.
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13
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Song Y, Torres RA, Garcia S, Frometa Y, Bae J, Deshmukh A, Lin WC, Zheng Y, Riera JJ. Dysfunction of Neurovascular/Metabolic Coupling in Chronic Focal Epilepsy. IEEE Trans Biomed Eng 2016; 63:97-110. [DOI: 10.1109/tbme.2015.2461496] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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14
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Assessment of Event-Related EEG Power After Single-Pulse TMS in Unresponsive Wakefulness Syndrome and Minimally Conscious State Patients. Brain Topogr 2015; 29:322-33. [DOI: 10.1007/s10548-015-0461-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2015] [Accepted: 11/07/2015] [Indexed: 11/26/2022]
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15
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Abreu R, Leite M, Leal A, Figueiredo P. Objective selection of epilepsy-related independent components from EEG data. J Neurosci Methods 2015; 258:67-78. [PMID: 26484785 DOI: 10.1016/j.jneumeth.2015.10.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2015] [Revised: 09/26/2015] [Accepted: 10/09/2015] [Indexed: 11/24/2022]
Abstract
BACKGROUND Independent Component Analysis (ICA) is commonly used for the identification of sources of interest in electroencephalographic (EEG) data, but the selection of the relevant components remains an open issue depending on the specific application. NEW METHOD We propose a novel approach for the objective selection of epilepsy-related independent components (ICs) from EEG data collected during functional Magnetic Resonance Imaging (fMRI) acquisitions, called PROJection onto Independent Components (PROJIC). Inter-ictal epileptiform discharges (IEDs) are identified on a reference EEG dataset collected outside the MRI scanner by an expert neurophysiologist, and the resulting average IED is projected onto the IC space of the EEG data collected simultaneously with fMRI. The power of the IED projection is then used to inform a k-means clustering algorithm of the ICs, allowing for the classification of epilepsy-related ICs. COMPARISON WITH EXISTING METHODS The performance of PROJIC was compared with two methods previously proposed for the objective selection of EEG ICs of interest, which are based on the explicit similarity of the ICs with spatio-temporal templates of the events of interest, instead of the projection power. RESULTS The proposed PROJIC method outperformed the others for both artificial and real data (19 datasets collected from 6 patients with drug-refractory focal epilepsy), with an average accuracy of 98.6%. CONCLUSIONS The ability of our method to accurately and objectively select epilepsy-related ICs makes it an important contribution for simultaneous EEG-fMRI epilepsy studies, with potential applications in the analysis of event-related EEG activity more generally, and also in EEG artefact correction.
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Affiliation(s)
- Rodolfo Abreu
- Institute for Systems and Robotics and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal.
| | - Marco Leite
- Institute for Systems and Robotics and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal; Department of Clinical and Experimental Epilepsy and The Wellcome Trust Centre for Neuroimaging, University College London Institute of Neurology, Queen Square, London WC1N 3BG, UK
| | - Alberto Leal
- Centro de Investigação e Intervenção Social and Department of Neurophysiology, Centro Hospitalar Psiquiátrico de Lisboa, Lisbon, Portugal
| | - Patrícia Figueiredo
- Institute for Systems and Robotics and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
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16
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Ferdowsi S, Abolghasemi V, Sanei S. A new informed tensor factorization approach to EEG–fMRI fusion. J Neurosci Methods 2015; 254:27-35. [DOI: 10.1016/j.jneumeth.2015.07.018] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2015] [Revised: 06/27/2015] [Accepted: 07/20/2015] [Indexed: 11/29/2022]
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17
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Storti SF, Del Felice A, Formaggio E, Boscolo Galazzo I, Bongiovanni LG, Cerini R, Fiaschi A, Manganotti P. Spatial and Temporal EEG-fMRI Changes During Preictal and Postictal Phases in a Patient With Posttraumatic Epilepsy. Clin EEG Neurosci 2015; 46:247-52. [PMID: 24743547 DOI: 10.1177/1550059414523960] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2013] [Accepted: 01/17/2014] [Indexed: 11/17/2022]
Abstract
The combined use of electroencephalography (EEG) and functional magnetic resonance imaging (EEG-fMRI) in epilepsy allows the noninvasive hemodynamic characterization of epileptic discharge-related neuronal activations. The aim of this study was to investigate pathophysiologic mechanisms underlying epileptic activity by exploring the spatial and temporal distribution of fMRI signal modifications during seizure in a single patient with posttraumatic epilepsy. EEG and fMRI data were acquired during two scanning sessions: a spontaneous critical episode was observed during the first, and interictal events were recorded during the second. The EEG-fMRI data were analyzed using the general linear model (GLM). Blood oxygenation level-dependent (BOLD) localization derived from the preictal and artifact-free postictal phase was concordant with the BOLD localization of the interictal epileptiform discharges identified in the second session, pointing to a left perilesional mesiofrontal area. Of note, BOLD signal modifications were already visible several seconds before seizure onset. In brief, BOLD activations from the preictal, postictal, and interictal epileptiform discharge analysis appear to be concordant with the clinically driven localization hypothesis, whereas a widespread network of activations is detected during the ictal phase in a partial seizure.
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Affiliation(s)
- Silvia F Storti
- Department of Neurological and Movement Sciences, Section of Neurology, University of Verona, Verona, Italy
| | - Alessandra Del Felice
- Department of Neurological and Movement Sciences, Section of Neurology, University of Verona, Verona, Italy
| | - Emanuela Formaggio
- Department of Neurophysiology, Foundation IRCCS San Camillo Hospital, Venice, Italy
| | - Ilaria Boscolo Galazzo
- Department of Neurological and Movement Sciences, Section of Neurology, University of Verona, Verona, Italy
| | - Luigi G Bongiovanni
- Department of Neurological and Movement Sciences, Section of Neurology, University of Verona, Verona, Italy
| | - Roberto Cerini
- Department of Pathology and Diagnostics, University of Verona, Verona, Italy
| | - Antonio Fiaschi
- Department of Neurological and Movement Sciences, Section of Neurology, University of Verona, Verona, Italy Department of Neurophysiology, Foundation IRCCS San Camillo Hospital, Venice, Italy Clinical Neurophysiology and Functional Neuroimaging Unit, AOUI of Verona, Italy
| | - Paolo Manganotti
- Department of Neurological and Movement Sciences, Section of Neurology, University of Verona, Verona, Italy Department of Neurophysiology, Foundation IRCCS San Camillo Hospital, Venice, Italy Clinical Neurophysiology and Functional Neuroimaging Unit, AOUI of Verona, Italy
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18
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Patient-specific detection of cerebral blood flow alterations as assessed by arterial spin labeling in drug-resistant epileptic patients. PLoS One 2015; 10:e0123975. [PMID: 25946055 PMCID: PMC4422723 DOI: 10.1371/journal.pone.0123975] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2014] [Accepted: 02/24/2015] [Indexed: 11/19/2022] Open
Abstract
Electrophysiological and hemodynamic data can be integrated to accurately and precisely identify the generators of abnormal electrical activity in drug-resistant focal epilepsy. Arterial Spin Labeling (ASL), a magnetic resonance imaging (MRI) technique for quantitative noninvasive measurement of cerebral blood flow (CBF), can provide a direct measure of variations in cerebral perfusion associated with the epileptic focus. In this study, we aimed to confirm the ASL diagnostic value in the identification of the epileptogenic zone, as compared to electrical source imaging (ESI) results, and to apply a template-based approach to depict statistically significant CBF alterations. Standard video-electroencephalography (EEG), high-density EEG, and ASL were performed to identify clinical seizure semiology and noninvasively localize the epileptic focus in 12 drug-resistant focal epilepsy patients. The same ASL protocol was applied to a control group of 17 healthy volunteers from which a normal perfusion template was constructed using a mixed-effect approach. CBF maps of each patient were then statistically compared to the reference template to identify perfusion alterations. Significant hypo- and hyperperfused areas were identified in all cases, showing good agreement between ASL and ESI results. Interictal hypoperfusion was observed at the site of the seizure in 10/12 patients and early postictal hyperperfusion in 2/12. The epileptic focus was correctly identified within the surgical resection margins in the 5 patients who underwent lobectomy, all of which had good postsurgical outcomes. The combined use of ESI and ASL can aid in the noninvasive evaluation of drug-resistant epileptic patients.
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Murta T, Leite M, Carmichael DW, Figueiredo P, Lemieux L. Electrophysiological correlates of the BOLD signal for EEG-informed fMRI. Hum Brain Mapp 2015; 36:391-414. [PMID: 25277370 PMCID: PMC4280889 DOI: 10.1002/hbm.22623] [Citation(s) in RCA: 111] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2014] [Revised: 07/04/2014] [Accepted: 08/20/2014] [Indexed: 12/11/2022] Open
Abstract
Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are important tools in cognitive and clinical neuroscience. Combined EEG-fMRI has been shown to help to characterise brain networks involved in epileptic activity, as well as in different sensory, motor and cognitive functions. A good understanding of the electrophysiological correlates of the blood oxygen level-dependent (BOLD) signal is necessary to interpret fMRI maps, particularly when obtained in combination with EEG. We review the current understanding of electrophysiological-haemodynamic correlates, during different types of brain activity. We start by describing the basic mechanisms underlying EEG and BOLD signals and proceed by reviewing EEG-informed fMRI studies using fMRI to map specific EEG phenomena over the entire brain (EEG-fMRI mapping), or exploring a range of EEG-derived quantities to determine which best explain colocalised BOLD fluctuations (local EEG-fMRI coupling). While reviewing studies of different forms of brain activity (epileptic and nonepileptic spontaneous activity; cognitive, sensory and motor functions), a significant attention is given to epilepsy because the investigation of its haemodynamic correlates is the most common application of EEG-informed fMRI. Our review is focused on EEG-informed fMRI, an asymmetric approach of data integration. We give special attention to the invasiveness of electrophysiological measurements and the simultaneity of multimodal acquisitions because these methodological aspects determine the nature of the conclusions that can be drawn from EEG-informed fMRI studies. We emphasise the advantages of, and need for, simultaneous intracranial EEG-fMRI studies in humans, which recently became available and hold great potential to improve our understanding of the electrophysiological correlates of BOLD fluctuations.
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Affiliation(s)
- Teresa Murta
- Department of Clinical and Experimental EpilepsyUCL Institute of Neurology, Queen SquareLondonUnited Kingdom
- Department of BioengineeringInstitute for systems and robotics, Instituto Superior Técnico, Universidade de LisboaLisbonPortugal
| | - Marco Leite
- Department of Clinical and Experimental EpilepsyUCL Institute of Neurology, Queen SquareLondonUnited Kingdom
- Department of BioengineeringInstitute for systems and robotics, Instituto Superior Técnico, Universidade de LisboaLisbonPortugal
| | - David W. Carmichael
- Imaging and Biophysics UnitUCL Institute of Child HealthLondonUnited Kingdom
| | - Patrícia Figueiredo
- Department of BioengineeringInstitute for systems and robotics, Instituto Superior Técnico, Universidade de LisboaLisbonPortugal
| | - Louis Lemieux
- Department of Clinical and Experimental EpilepsyUCL Institute of Neurology, Queen SquareLondonUnited Kingdom
- MRI Unit, Epilepsy SocietyChalfont St. PeterUnited Kingdom
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20
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Tousseyn S, Dupont P, Robben D, Goffin K, Sunaert S, Van Paesschen W. A reliable and time-saving semiautomatic spike-template-based analysis of interictal EEG-fMRI. Epilepsia 2014; 55:2048-58. [PMID: 25377892 DOI: 10.1111/epi.12841] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/16/2014] [Indexed: 11/26/2022]
Abstract
OBJECTIVE A prerequisite for the implementation of interictal electroencephalography-correlated functional magnetic resonance imaging (EEG-fMRI) in the presurgical work-up for epilepsy surgery is straightforward processing. We propose a new semi-automatic method as alternative for the challenging and time-consuming visual spike identification. METHODS Our method starts from a patient-specific spike-template, built by averaging spikes recorded on the EEG outside the scanner. Spatiotemporal cross-correlations between the template and the EEG measured during fMRI were calculated. To minimize false-positive detections, this time course of cross-correlations was binarized by means of a spike-template-specific threshold determined in healthy controls. To inform our model for statistical parametric mapping, this binarized regressor was convolved with the canonical hemodynamic response function. We validated our "template-based" method in 21 adult patients with refractory focal epilepsy with a well-defined epileptogenic zone and interictal spikes during EEG-fMRI. Sensitivity and specificity for detecting the epileptogenic zone were calculated and represented in receiver operating characteristic (ROC) curves. Our approach was compared with a previously proposed semiautomatic "topography-based" method that used the topographic amplitude distribution of spikes as a starting point for correlation-based fitting. RESULTS Good diagnostic performance could be reached with our template-based method. The optimal area under the ROC curve was 0.77. Diagnostic performance of the topography-based method was overall low. SIGNIFICANCE Our new template-based method is more standardized and time-saving than visual spike identification on intra-scanner EEG recordings, and preserves good diagnostic performance for detecting the epileptogenic zone.
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Affiliation(s)
- Simon Tousseyn
- Laboratory for Epilepsy Research, UZ Leuven & KU Leuven, Leuven, Belgium; Medical Imaging Research Center, UZ Leuven & KU Leuven, Leuven, Belgium
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21
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Storti SF, Boscolo Galazzo I, Del Felice A, Pizzini FB, Arcaro C, Formaggio E, Mai R, Manganotti P. Combining ESI, ASL and PET for quantitative assessment of drug-resistant focal epilepsy. Neuroimage 2014; 102 Pt 1:49-59. [DOI: 10.1016/j.neuroimage.2013.06.028] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2013] [Revised: 05/03/2013] [Accepted: 06/10/2013] [Indexed: 11/16/2022] Open
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22
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Biazoli CE, Sturzbecher M, White TP, Dos Santos Onias HH, Andrade KC, de Araujo DB, Sato JR. Application of partial directed coherence to the analysis of resting-state EEG-fMRI data. Brain Connect 2014; 3:563-8. [PMID: 23724827 DOI: 10.1089/brain.2012.0135] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The simultaneous acquisition of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data potentially allows measurement of brain signals with both high spatial and temporal resolution. Partial directed coherence (PDC) is a Granger causality measure in the frequency domain, which is often used to infer the intensity of information flow over the brain from EEG data. In the current study, we propose a new approach to investigate functional connectivity in resting-state (RS) EEG-fMRI data by combining time-varying PDC with the analysis of blood oxygenation level-dependent (BOLD) signal fluctuations. Basically, we aim to identify brain circuits that are more active when the information flow is increased between distinct remote neuronal modules. The usefulness of the proposed method is illustrated by application to simultaneously recorded EEG-fMRI data from healthy subjects at rest. Using this approach, we decomposed the nodes of RS networks in fMRI data according to the frequency band and directed flow of information provided from EEG. This approach therefore has the potential to inform our understanding of the regional characteristics of oscillatory processes in the human brain.
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23
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Formaggio E, Storti SF, Boscolo Galazzo I, Bongiovanni LG, Cerini R, Fiaschi A, Manganotti P. Reproducibility of EEG-fMRI results in a patient with fixation-off sensitivity. Clin EEG Neurosci 2014; 45:212-7. [PMID: 24048241 DOI: 10.1177/1550059413497946] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Blood oxygenation level-dependent (BOLD) activation associated with interictal epileptiform discharges in a patient with fixation-off sensitivity (FOS) was studied using a combined electroencephalography-functional magnetic resonance imaging (EEG-fMRI) technique. An automatic approach for combined EEG-fMRI analysis and a subject-specific hemodynamic response function was used to improve general linear model analysis of the fMRI data. The EEG showed the typical features of FOS, with continuous epileptiform discharges during elimination of central vision by eye opening and closing and fixation; modification of this pattern was clearly visible and recognizable. During all 3 recording sessions EEG-fMRI activations indicated a BOLD signal decrease related to epileptiform activity in the parietal areas. This study can further our understanding of this EEG phenomenon and can provide some insight into the reliability of the EEG-fMRI technique in localizing the irritative zone.
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Affiliation(s)
- Emanuela Formaggio
- Department of Neurophysiology, Foundation IRCCS San Camillo Hospital, Venice, Italy
| | - Silvia Francesca Storti
- Clinical Neurophysiology and Functional Neuroimaging Unit, Department of Neurological and Movement Sciences, University Hospital, Verona, Italy
| | - Ilaria Boscolo Galazzo
- Clinical Neurophysiology and Functional Neuroimaging Unit, Department of Neurological and Movement Sciences, University Hospital, Verona, Italy
| | - Luigi Giuseppe Bongiovanni
- Clinical Neurophysiology and Functional Neuroimaging Unit, Department of Neurological and Movement Sciences, University Hospital, Verona, Italy
| | - Roberto Cerini
- Department of Pathology and Diagnostics, Section of Radiology, G.B. Rossi Hospital, University of Verona, Verona, Italy
| | - Antonio Fiaschi
- Department of Neurophysiology, Foundation IRCCS San Camillo Hospital, Venice, Italy
- Clinical Neurophysiology and Functional Neuroimaging Unit, Department of Neurological and Movement Sciences, University Hospital, Verona, Italy
| | - Paolo Manganotti
- Department of Neurophysiology, Foundation IRCCS San Camillo Hospital, Venice, Italy
- Clinical Neurophysiology and Functional Neuroimaging Unit, Department of Neurological and Movement Sciences, University Hospital, Verona, Italy
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24
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Formaggio E, Storti SF, Boscolo Galazzo I, Gandolfi M, Geroin C, Smania N, Fiaschi A, Manganotti P. Time–Frequency Modulation of ERD and EEG Coherence in Robot-Assisted Hand Performance. Brain Topogr 2014; 28:352-63. [DOI: 10.1007/s10548-014-0372-8] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2013] [Accepted: 04/27/2014] [Indexed: 01/19/2023]
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25
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Pittau F, Grouiller F, Spinelli L, Seeck M, Michel CM, Vulliemoz S. The role of functional neuroimaging in pre-surgical epilepsy evaluation. Front Neurol 2014. [PMID: 24715886 DOI: 10.3389/fneur.2014.00031.] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The prevalence of epilepsy is about 1% and one-third of cases do not respond to medical treatment. In an eligible subset of patients with drug-resistant epilepsy, surgical resection of the epileptogenic zone is the only treatment that can possibly cure the disease. Non-invasive techniques provide information for the localization of the epileptic focus in the majority of cases, whereas in others invasive procedures are required. In the last years, non-invasive neuroimaging techniques, such as simultaneous recording of functional magnetic resonance imaging and electroencephalogram (EEG-fMRI), positron emission tomography (PET), single photon emission computed tomography (SPECT), electric and magnetic source imaging (MSI, ESI), spectroscopy (MRS), have proved their usefulness in defining the epileptic focus. The combination of these functional techniques can yield complementary information and their concordance is crucial for guiding clinical decision, namely the planning of invasive EEG recordings or respective surgery. The aim of this review is to present these non-invasive neuroimaging techniques, their potential combination, and their role in the pre-surgical evaluation of patients with pharmaco-resistant epilepsy.
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Affiliation(s)
- Francesca Pittau
- Presurgical Epilepsy Evaluation Unit, Neurology Department, University Hospital of Geneva , Geneva , Switzerland
| | - Frédéric Grouiller
- Department of Radiology and Medical Informatics, University Hospital of Geneva , Geneva , Switzerland
| | - Laurent Spinelli
- Presurgical Epilepsy Evaluation Unit, Neurology Department, University Hospital of Geneva , Geneva , Switzerland
| | - Margitta Seeck
- Presurgical Epilepsy Evaluation Unit, Neurology Department, University Hospital of Geneva , Geneva , Switzerland
| | - Christoph M Michel
- Functional Brain Mapping Laboratory, Department of Fundamental Neurosciences, University of Geneva , Geneva , Switzerland
| | - Serge Vulliemoz
- Presurgical Epilepsy Evaluation Unit, Neurology Department, University Hospital of Geneva , Geneva , Switzerland
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26
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Pittau F, Grouiller F, Spinelli L, Seeck M, Michel CM, Vulliemoz S. The role of functional neuroimaging in pre-surgical epilepsy evaluation. Front Neurol 2014; 5:31. [PMID: 24715886 PMCID: PMC3970017 DOI: 10.3389/fneur.2014.00031] [Citation(s) in RCA: 66] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2013] [Accepted: 03/06/2014] [Indexed: 12/25/2022] Open
Abstract
The prevalence of epilepsy is about 1% and one-third of cases do not respond to medical treatment. In an eligible subset of patients with drug-resistant epilepsy, surgical resection of the epileptogenic zone is the only treatment that can possibly cure the disease. Non-invasive techniques provide information for the localization of the epileptic focus in the majority of cases, whereas in others invasive procedures are required. In the last years, non-invasive neuroimaging techniques, such as simultaneous recording of functional magnetic resonance imaging and electroencephalogram (EEG-fMRI), positron emission tomography (PET), single photon emission computed tomography (SPECT), electric and magnetic source imaging (MSI, ESI), spectroscopy (MRS), have proved their usefulness in defining the epileptic focus. The combination of these functional techniques can yield complementary information and their concordance is crucial for guiding clinical decision, namely the planning of invasive EEG recordings or respective surgery. The aim of this review is to present these non-invasive neuroimaging techniques, their potential combination, and their role in the pre-surgical evaluation of patients with pharmaco-resistant epilepsy.
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Affiliation(s)
- Francesca Pittau
- Presurgical Epilepsy Evaluation Unit, Neurology Department, University Hospital of Geneva , Geneva , Switzerland
| | - Frédéric Grouiller
- Department of Radiology and Medical Informatics, University Hospital of Geneva , Geneva , Switzerland
| | - Laurent Spinelli
- Presurgical Epilepsy Evaluation Unit, Neurology Department, University Hospital of Geneva , Geneva , Switzerland
| | - Margitta Seeck
- Presurgical Epilepsy Evaluation Unit, Neurology Department, University Hospital of Geneva , Geneva , Switzerland
| | - Christoph M Michel
- Functional Brain Mapping Laboratory, Department of Fundamental Neurosciences, University of Geneva , Geneva , Switzerland
| | - Serge Vulliemoz
- Presurgical Epilepsy Evaluation Unit, Neurology Department, University Hospital of Geneva , Geneva , Switzerland
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27
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Modelling hemodynamic response function in epilepsy. Clin Neurophysiol 2013; 124:2108-18. [DOI: 10.1016/j.clinph.2013.05.024] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2012] [Revised: 04/30/2013] [Accepted: 05/03/2013] [Indexed: 11/20/2022]
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28
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Effect of High-Frequency Repetitive Transcranial Magnetic Stimulation on Brain Excitability in Severely Brain-Injured Patients in Minimally Conscious or Vegetative State. Brain Stimul 2013; 6:913-21. [DOI: 10.1016/j.brs.2013.06.006] [Citation(s) in RCA: 56] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2013] [Revised: 05/30/2013] [Accepted: 06/30/2013] [Indexed: 11/18/2022] Open
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29
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Siero JC, Bhogal A, Jansma JM. Blood Oxygenation Level–dependent/Functional Magnetic Resonance Imaging. PET Clin 2013; 8:329-44. [DOI: 10.1016/j.cpet.2013.04.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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30
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Jorge J, van der Zwaag W, Figueiredo P. EEG-fMRI integration for the study of human brain function. Neuroimage 2013; 102 Pt 1:24-34. [PMID: 23732883 DOI: 10.1016/j.neuroimage.2013.05.114] [Citation(s) in RCA: 79] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2013] [Revised: 05/24/2013] [Accepted: 05/25/2013] [Indexed: 12/21/2022] Open
Abstract
Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) have proved to be extremely valuable tools for the non-invasive study of human brain function. Moreover, due to a notable degree of complementarity between the two modalities, the combination of EEG and fMRI data has been actively sought in the last two decades. Although initially focused on epilepsy, EEG-fMRI applications were rapidly extended to the study of healthy brain function, yielding new insights into its underlying mechanisms and pathways. Nevertheless, EEG and fMRI have markedly different spatial and temporal resolutions, and probe neuronal activity through distinct biophysical processes, many aspects of which are still poorly understood. The remarkable conceptual and methodological challenges associated with EEG-fMRI integration have motivated the development of a wide range of analysis approaches over the years, each relying on more or less restrictive assumptions, and aiming to shed further light on the mechanisms of brain function along with those of the EEG-fMRI coupling itself. Here, we present a review of the most relevant EEG-fMRI integration approaches yet proposed for the study of brain function, supported by a general overview of our current understanding of the biophysical mechanisms coupling the signals obtained from the two modalities.
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Affiliation(s)
- João Jorge
- Institute for Systems and Robotics, Department of Bioengineering, Instituto Superior Técnico, Technical University of Lisbon, Lisbon, Portugal; Biomedical Imaging Research Center, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Wietske van der Zwaag
- Biomedical Imaging Research Center, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Patrícia Figueiredo
- Institute for Systems and Robotics, Department of Bioengineering, Instituto Superior Técnico, Technical University of Lisbon, Lisbon, Portugal.
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31
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Leite M, Leal A, Figueiredo P. Transfer Function between EEG and BOLD Signals of Epileptic Activity. Front Neurol 2013; 4:1. [PMID: 23355832 PMCID: PMC3554836 DOI: 10.3389/fneur.2013.00001] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2012] [Accepted: 01/04/2013] [Indexed: 11/13/2022] Open
Abstract
Simultaneous electroencephalogram (EEG)-functional Magnetic Resonance Imaging (fMRI) recordings have seen growing application in the evaluation of epilepsy, namely in the characterization of brain networks related to epileptic activity. In EEG-correlated fMRI studies, epileptic events are usually described as boxcar signals based on the timing information retrieved from the EEG, and subsequently convolved with a hemodynamic response function to model the associated Blood Oxygen Level Dependent (BOLD) changes. Although more flexible approaches may allow a higher degree of complexity for the hemodynamics, the issue of how to model these dynamics based on the EEG remains an open question. In this work, a new methodology for the integration of simultaneous EEG-fMRI data in epilepsy is proposed, which incorporates a transfer function from the EEG to the BOLD signal. Independent component analysis of the EEG is performed, and a number of metrics expressing different models of the EEG-BOLD transfer function are extracted from the resulting time courses. These metrics are then used to predict the fMRI data and to identify brain areas associated with the EEG epileptic activity. The methodology was tested on both ictal and interictal EEG-fMRI recordings from one patient with a hypothalamic hamartoma. When compared to the conventional analysis approach, plausible, consistent, and more significant activations were obtained. Importantly, frequency-weighted EEG metrics yielded superior results than those weighted solely on the EEG power, which comes in agreement with previous literature. Reproducibility, specificity, and sensitivity should be addressed in an extended group of patients in order to further validate the proposed methodology and generalize the presented proof of concept.
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Affiliation(s)
- Marco Leite
- Department of Bioengineering, Instituto Superior Técnico, Technical University of Lisbon Lisbon, Portugal ; Institute for Systems and Robotics Lisbon, Portugal
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32
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Zhang J, Liu Q, Mei S, Zhang X, Wang X, Liu W, Chen H, Xia H, Zhou Z, Li Y. Presurgical EEG-fMRI in a complex clinical case with seizure recurrence after epilepsy surgery. Neuropsychiatr Dis Treat 2013; 9:1003-10. [PMID: 23926432 PMCID: PMC3732198 DOI: 10.2147/ndt.s47099] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Epilepsy surgery has improved over the last decade, but non-seizure-free outcome remains at 10%-40% in temporal lobe epilepsy (TLE) and 40%-60% in extratemporal lobe epilepsy (ETLE). This paper reports a complex multifocal case. With a normal magnetic resonance imaging (MRI) result and nonlocalizing electroencephalography (EEG) findings (bilateral TLE and ETLE, with more interictal epileptiform discharges [IEDs] in the right frontal and temporal regions), a presurgical EEG-functional MRI (fMRI) was performed before the intraoperative intracranial EEG (icEEG) monitoring (icEEG with right hemispheric coverage). Our previous EEG-fMRI analysis results (IEDs in the left hemisphere alone) were contradictory to the EEG and icEEG findings (IEDs in the right frontal and temporal regions). Thus, the EEG-fMRI data were reanalyzed with newly identified IED onsets and different fMRI model options. The reanalyzed EEG-fMRI findings were largely concordant with those of EEG and icEEG, and the failure of our previous EEG-fMRI analysis may lie in the inaccurate identification of IEDs and wrong usage of model options. The right frontal and temporal regions were resected in surgery, and dual pathology (hippocampus sclerosis and focal cortical dysplasia in the extrahippocampal region) was found. The patient became seizure-free for 3 months, but his seizures restarted after antiepileptic drugs (AEDs) were stopped. The seizures were not well controlled after resuming AEDs. Postsurgical EEGs indicated that ictal spikes in the right frontal and temporal regions reduced, while those in the left hemisphere became prominent. This case suggested that (1) EEG-fMRI is valuable in presurgical evaluation, but requires caution; and (2) the intact seizure focus in the remaining brain may cause the non-seizure-free outcome.
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Affiliation(s)
- Jing Zhang
- School of Biomedical Engineering, Capital Medical University, Beijing, People's Republic of China
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33
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Lenkov DN, Volnova AB, Pope ARD, Tsytsarev V. Advantages and limitations of brain imaging methods in the research of absence epilepsy in humans and animal models. J Neurosci Methods 2012; 212:195-202. [PMID: 23137652 DOI: 10.1016/j.jneumeth.2012.10.018] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2012] [Revised: 10/24/2012] [Accepted: 10/25/2012] [Indexed: 12/18/2022]
Abstract
The purpose of this review is to analyze research possibilities and limitations of several methods, technical tools and their combinations for elucidation of absence epilepsy mechanisms, particularly the childhood absences. Despite the notable collection of simultaneous recording of clinical electroencephalography (EEG) and behavioral changes in relation to absence seizures, shortcomings of scalp EEG in both spatial resolution and precise detection of subcortical centers have limited the understanding of the fundamental mechanisms of altered brain function during and after recurrent epileptic paroxysms. Therefore, in the past decade, EEG recordings have often been combined with simultaneous imaging methods in epilepsy studies. Among imaging methods, the following ones are used regularly: functional magnetic resonance imaging (fMRI), positron-emission tomography (PET), low-resolution electromagnetic tomography (LORETA), single photon emission spectroscopy (SPECT), near-infrared spectroscopy (NIRS), and optical imaging of intrinsic signals (IOS). In addition, voltage-sensitive dye optical imaging method and even photoacoustic microscopy can be applied to animal models of epilepsy. Samplings of some of the most relevant data obtained by the above methods are presented. It appears that the elaboration of more adequate animal models of the patterns of absence seizures during the early postnatal period is necessary for better correspondence of human and animal absence phenomena.
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Affiliation(s)
- Dmitry N Lenkov
- Nevsky Center of Scientific Collaboration-Saint Petersburg, Razjezshaya 43/1 Liter A, Suite 8N, Saint Petersburg 192119, Russia
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Bercovici E, Kumar BS, Mirsattari SM. Neocortical temporal lobe epilepsy. EPILEPSY RESEARCH AND TREATMENT 2012; 2012:103160. [PMID: 22953057 PMCID: PMC3420667 DOI: 10.1155/2012/103160] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/20/2011] [Revised: 01/04/2012] [Accepted: 05/22/2012] [Indexed: 01/15/2023]
Abstract
Complex partial seizures (CPSs) can present with various semiologies, while mesial temporal lobe epilepsy (mTLE) is a well-recognized cause of CPS, neocortical temporal lobe epilepsy (nTLE) albeit being less common is increasingly recognized as separate disease entity. Differentiating the two remains a challenge for epileptologists as many symptoms overlap due to reciprocal connections between the neocortical and the mesial temporal regions. Various studies have attempted to correctly localize the seizure focus in nTLE as patients with this disorder may benefit from surgery. While earlier work predicted poor outcomes in this population, recent work challenges those ideas yielding good outcomes in part due to better localization using improved anatomical and functional techniques. This paper provides a comprehensive review of the diagnostic workup, particularly the application of recent advances in electroencephalography and functional brain imaging, in neocortical temporal lobe epilepsy.
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Affiliation(s)
- Eduard Bercovici
- Division of Neurology, University of Toronto, Toronto, ON, Canada
| | - Balagobal Santosh Kumar
- Department of Clinical Neurological Sciences, University of Western Ontario, London, ON, Canada
| | - Seyed M. Mirsattari
- Department of Clinical Neurological Sciences, University of Western Ontario, London, ON, Canada
- Department of Medical Imaging, University of Western Ontario, London, ON, Canada
- Department of Medical Biophysics, University of Western Ontario, London, ON, Canada
- Department of Psychology, University of Western Ontario, London, ON, Canada
- London Health Sciences Centre, B10-110, London, ON, Canada N6A 5A5
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Storti SF, Formaggio E, Franchini E, Bongiovanni LG, Cerini R, Fiaschi A, Michel CM, Manganotti P. A multimodal imaging approach to the evaluation of post-traumatic epilepsy. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2012; 25:345-60. [PMID: 22592963 PMCID: PMC3458199 DOI: 10.1007/s10334-012-0316-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/27/2011] [Revised: 04/16/2012] [Accepted: 04/17/2012] [Indexed: 11/11/2022]
Abstract
Object Electroencephalography-functional magnetic resonance imaging (EEG-fMRI) coregistration and high-density EEG (hdEEG) can be combined to map noninvasively abnormal brain activation elicited by epileptic processes. By combining noninvasive imaging techniques in a multimodal approach, we sought to investigate pathophysiological mechanisms underlying epileptic activity in seven patients with severe traumatic brain injury. Materials and methods Standard EEG and fMRI data were acquired during a single scanning session. The EEG-fMRI data were analyzed using the general linear model and independent component analysis. Source localization of interictal epileptiform discharges (IEDs) was performed using 256-channel hdEEG. Blood oxygenation level dependent (BOLD) localizations were then compared to EEG source reconstruction. Results On hdEEG, focal source localization was detected in all seven patients; in six out of seven it was concordant with the expected epileptic activity as defined by EEG data and clinical evaluation; and in four out of seven in whom IEDs were recorded, BOLD signal changes were observed. These activities were partially concordant with the source localization. Conclusion Multimodal integration of EEG-fMRI and hdEEG combining two different methods to localize the same epileptic foci appears to be a promising tool to noninvasively map abnormal brain activation in patients with post-traumatic brain injury.
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Affiliation(s)
- Silvia F Storti
- Department of Neurological, Neuropsychological, Morphological and Movement Sciences, Section of Clinical Neurology, University of Verona, Policlinico G.B. Rossi, P.le L.A. Scuro 10, 37134, Verona, Italy.
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Manganotti P, Formaggio E, Storti SF, De Massari D, Zamboni A, Bertoldo A, Fiaschi A, Toffolo GM. Time-frequency analysis of short-lasting modulation of EEG induced by intracortical and transcallosal paired TMS over motor areas. J Neurophysiol 2012; 107:2475-84. [DOI: 10.1152/jn.00543.2011] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Dynamic changes in spontaneous electroencephalogram (EEG) rhythms can be seen to occur with a high rate of variability. An innovative method to study brain function is by triggering oscillatory brain activity with transcranial magnetic stimulation (TMS). EEG-TMS coregistration was performed on five healthy subjects during a 1-day experimental session that involved four steps: baseline acquisition, unconditioned single-pulse TMS, intracortical inhibition (ICI, 3 ms) paired-pulse TMS, and transcallosal stimulation over left and right primary motor cortex (M1). A time-frequency analysis based on the wavelet method was used to characterize rapid modifications of oscillatory EEG rhythms induced by TMS. Single, paired, and transcallosal TMS applied on the sensorimotor areas induced rapid desynchronization over the frontal and central-parietal electrodes mainly in the alpha and beta bands, followed by a rebound of synchronization, and rapid synchronization of delta and theta activity. Wavelet analysis after a perturbation approach is a novel way to investigate modulation of oscillatory brain activity. The main findings are consistent with the concept that the human motor system may be based on networklike oscillatory cortical activity and might be modulated by single, paired, and transcallosal magnetic pulses applied to M1, suggesting a phenomenon of fast brain activity resetting and triggering of slow activity.
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Affiliation(s)
- Paolo Manganotti
- Department of Neurological, Neuropsychological, Morphological and Movement Sciences, Section of Clinical Neurology, G. B. Rossi Hospital, University of Verona, Verona
- Department of Neurophysiology, IRCCS San Camillo, Venice; and
| | | | - Silvia Francesca Storti
- Department of Neurological, Neuropsychological, Morphological and Movement Sciences, Section of Clinical Neurology, G. B. Rossi Hospital, University of Verona, Verona
| | - Daniele De Massari
- Department of Information Engineering, University of Padova, Padua, Italy
| | - Alessandro Zamboni
- Department of Information Engineering, University of Padova, Padua, Italy
| | | | - Antonio Fiaschi
- Department of Neurological, Neuropsychological, Morphological and Movement Sciences, Section of Clinical Neurology, G. B. Rossi Hospital, University of Verona, Verona
- Department of Neurophysiology, IRCCS San Camillo, Venice; and
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Hauf M, Jann K, Schindler K, Scheidegger O, Meyer K, Rummel C, Mariani L, Koenig T, Wiest R. Localizing seizure-onset zones in presurgical evaluation of drug-resistant epilepsy by electroencephalography/fMRI: effectiveness of alternative thresholding strategies. AJNR Am J Neuroradiol 2012; 33:1818-24. [PMID: 22538072 DOI: 10.3174/ajnr.a3052] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Simultaneous EEG/fMRI is an effective noninvasive tool for identifying and localizing the SOZ in patients with focal epilepsy. In this study, we evaluated different thresholding strategies in EEG/fMRI for the assessment of hemodynamic responses to IEDs in the SOZ of drug-resistant epilepsy. MATERIALS AND METHODS Sixteen patients with focal epilepsy were examined by using simultaneous 92-channel EEG and BOLD fMRI. The temporal fluctuation of epileptiform signals on the EEG was extracted by independent component analysis to predict the hemodynamic responses to the IEDs. We applied 3 different threshold criteria to detect hemodynamic responses within the SOZ: 1) PA, 2) a fixed threshold at P < .05 corrected for multiple comparison (FWE), and 3) FAV (4000 ± 200 activated voxels within the brain). RESULTS PA identified the SOZ in 9 of 16 patients; FWE resulted in concordant BOLD signal correlates in 11 of 16, and FAV in 13 of 16 patients. Hemodynamic responses were detected within the resected areas in 5 (PA), 6 (FWE), and 8 (FAV) of 10 patients who remained seizure-free after surgery. CONCLUSIONS EEG/fMRI is a noninvasive tool for the presurgical work-up of patients with epilepsy, which can be performed during seizure-free periods and is complementary to the ictal electroclinical assessment. Our findings suggest that the effectiveness of EEG/fMRI in delineating the SOZ may be further improved by the additional use of alternative analysis strategies such as FAV.
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Affiliation(s)
- M Hauf
- Support Center of Advanced Neuroimaging, Inselspital, University of Bern, Switzerland.
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