Electroencephalography Source Research Articles

EEG Source Imaging of Movement Decoding: The State of the Art and Future Directions

In this article, we provide an overview of electroencephalography (EEG) source imaging (ESI) of movement decoding for brain-computer interface (BCI) applications. The current state-of-the-art neuroimaging modality-functional magnetic resonance imaging (fMRI)-is expensive and nonportable and has poor temporal resolution. EEG, however, offers an attractive choice as a portable and cost-effective neuroimaging technique that delivers excellent temporal resolution, especially in reading dynamic human motor behavior.

Multimodal, noninvasive seizure network mapping software: A novel tool for preoperative epilepsy evaluation

BackgroundDespite rigorous preoperative evaluation, epilepsy surgery achieves seizure freedom in only two-thirds of cases. Current preoperative evaluation does not include a detailed network analysis despite the association of network-level changes with epilepsy. ObjectiveWe sought to create a software algorithm to map individualized epilepsy networks by combining noninvasive electroencephalography (EEG) source localization and nonconcurrent resting state functional magnetic resonance imaging (rsfMRI). MethodsScalp EEG and rsfMRI data were acquired for three sample cases: one healthy control case, one case of right temporal lobe epilepsy, and one case of bitemporal seizure onset. Data from rsfMRI were preprocessed, and a time-series function was extracted. Connection coefficients were used to threshold out spurious connections and model global functional networks in a 3D map. Epileptic discharges were localized using a forward model of cortical mesh dipoles followed by an empirical Bayesian approach of inverse source reconstruction and co-registered with rsfMRI. Co-activating brain regions were mapped. ResultsThree illustrative sample cases are presented. In the healthy control case, the software showed symmetrical global connectivity. In the right temporal lobe epilepsy case, asymmetry was found in the global connectivity metrics with a paucity of connectivity ipsilateral to the epileptogenic cortex. The superior longitudinal fasciculus, uncinate fasciculus, and commissural fibers connecting disparate and discontinuous cortical regions involved in the epilepsy network were visualized. In the case with bitemporal lobe epilepsy, global connectivity was symmetric. It showed a network of correlating cortical activity local to epileptogenic tissue in both temporal lobes. The network involved white matter tracks in a similar pattern to those seen in the right temporal case. ConclusionsThis modeling algorithm allows better definition of the global brain network and potentially demonstrates differences in connectivity between an epileptic and a non-epileptic brain. This finding may be useful for mapping cortico-cortical connections representing the putative epilepsy networks. With this methodology, we localized the epileptogenic brain and showed network asymmetry and long-distance cortical co-activation. This software tool is the first to use a multimodal, nonconcurrent, and noninvasive approach to model and visualize the epilepsy network.

Inferring multi-scale neural mechanisms with brain network modelling.

The neurophysiological processes underlying non-invasive brain activity measurements are incompletely understood. Here, we developed a connectome-based brain network model that integrates individual structural and functional data with neural population dynamics to support multi-scale neurophysiological inference. Simulated populations were linked by structural connectivity and, as a novelty, driven by electroencephalography (EEG) source activity. Simulations not only predicted subjects' individual resting-state functional magnetic resonance imaging (fMRI) time series and spatial network topologies over 20 minutes of activity, but more importantly, they also revealed precise neurophysiological mechanisms that underlie and link six empirical observations from different scales and modalities: (1) resting-state fMRI oscillations, (2) functional connectivity networks, (3) excitation-inhibition balance, (4, 5) inverse relationships between α-rhythms, spike-firing and fMRI on short and long time scales, and (6) fMRI power-law scaling. These findings underscore the potential of this new modelling framework for general inference and integration of neurophysiological knowledge to complement empirical studies.

P263 Effect of structural complexities in head modelling on neonatal EEG source analysis

Objective The accuracy of electroencephalography source reconstruction largely depends on the accuracy of head model, which, in turn, is dependent on the geometry and electrical properties of head tissues. Methods Based on a MR/CT coregistered images of one neonate we created a highly realistic 6 compartment head model. using a state of art finite element method, we performed numerical simulations to investigate localization errors in dipole source position, orientation and magnitude caused by CSF and fontanel exclusion and GM/WM distinction. Results Our results showed that exclusion of CSF from the head model caused source localization errors up to 7.5 mm. GM/WM distinction affected widely all sources with localization errors up to 4.3 mm. Exclusion of the fontanels led to localization errors of less than 4.9 mm specifically for sources located in the areas beneath the fontanels. The majority of sources showed orientation errors up to 24.6°, 19.2° and 17.6°, caused by CSF exclusion, GM/WM distinction and fontanel exclusion, respectively. Discussion Our results systematically emphasized the importance of the inclusion of the CSF as a highly conductive layer and GM/WM distinction in head model construction. The exclusion of fontanels also led to substantial local localization errors for sources located in the areas beneath the fontanels. Conclusion In this study we investigated the effect of different head compartments in neonatal head models on EEG source analysis. Significance Our findings have practical implications for a better understanding of the importance of inaccuracies in head model and their impact on localization of brain electrical activity in neonates.

Electroencephalography Source Functional Connectivity Reveals Abnormal High-Frequency Communication Among Large-Scale Functional Networks in Depression

BackgroundFunctional magnetic resonance imaging studies of resting-state functional connectivity have shown that major depressive disorder (MDD) is characterized by increased connectivity within the default mode network (DMN) and between the DMN and the frontoparietal network (FPN). However, much remains unknown about abnormalities in higher frequency (>1 Hz) synchronization. Findings of abnormal synchronization in specific frequencies would contribute to a better understanding of the potential neurophysiological origins of disrupted functional connectivity in MDD. MethodsWe used the high temporal resolution of electroencephalography to compare the spectral properties of resting-state functional connectivity in individuals with MDD (n = 65) with healthy control subjects (n = 79) and examined the extent to which connectivity disturbances were evident in a third sample of individuals in remission from depression (n = 30). Exact low resolution electromagnetic tomography was used to compute intracortical activity from regions within the DMN and FPN, and functional connectivity was computed using lagged phase synchronization. ResultsCompared to control subjects, the MDD group showed greater within-DMN beta 2 band (18.5–21 Hz) connectivity and greater beta 1 band (12.5–18 Hz) connectivity between the DMN and FPN. This hyperconnectivity was not observed in the remitted MDD group. However, greater beta 1 band DMN–FPN connectivity was associated with more frequent depressive episodes since first depression onset, even after controlling for current symptom severity. ConclusionsThese findings extend our understanding of the neurophysiological basis of abnormal resting-state functional connectivity in MDD and indicate that elevations in high-frequency DMN–FPN connectivity may be a neural marker linked to a more recurrent illness course.

Comprehensive preoperative work-up and surgical treatment of low grade tumor/benign lesion related temporal lobe epilepsy

ObjectiveGenerally low-grade tumor/benign lesion related temporal lobe epilepsy (LGT/BL-TLE) is considered easier to treat and has better prognosis when compared to non-lesional TLE. However, multiple disputes exist in surgical management of this epilepsy entity. This study aims to discuss comprehensive preoperative work-up, surgical strategies and outcome of it. MethodsA retrospective review of sixty LGT/BL-TLE cases which underwent comprehensive preoperative work-up and then resective surgeries was conducted. Surgical strategies were categorized into limited and expanded resections. Surgical efficacy was evaluated using Engel grading after telephone or clinic follow-up and compared statistically. ResultsPreoperative work-up includes magnetic resonance imaging (MRI), conventional electroencephalography, semiology evaluation, positron emission tomography (PET) and 256-channel dense-array electroencephalography source imaging (256-ch dESI). In aspect of concordance with epileptic lesions demonstrated on MRI, 256-ch dESI was more accurate than PET (72.7% vs. 39.4%) (p<0.05). Limited resections were performed in 28 cases while expanded resections in 32 cases. Altogether the surgical efficacy was: Engel grade I 86.7%, I+II 95.0%. Comparison of surgical outcome showed neither the outcome between limited and expanded resection nor the outcome between mesial and neocortical TLE (mTLE & nTLE) undergoing limited resections was significantly different (p>0.05). ConclusionsFor LGT/BL-TLE, most surgical strategies can be made preoperatively after comprehensive work-up rather than intraoperatively. Limited and expanded strategies yield similar surgical outcome in either nTLE or mTLE as long as comprehensive work-up supports the strategy and the epileptic lesion is totally removed. 256-ch dESI which can visualize both structural and electrophysiological lesions may be contributable to surgical planning of this entity.

A Sparse Dictionary Learning Framework to Discover Discriminative Source Activations in EEG Brain Mapping

Electroencephalography (EEG) source analysis is one of the most important noninvasive human brain imaging tools that provides millisecond temporal accuracy. However, discovering essential activated brain sources associated with different brain status is still a challenging problem. In this study, we propose for the first time that the ill-posed EEG inverse problem can be formulated and solved as a sparse over-complete dictionary learning problem. In particular, a novel supervised sparse dictionary learning framework was developed for EEG source reconstruction. A revised version of discriminative K-SVD (DK-SVD) algorithm is exploited to solve the formulated supervised dictionary learning problem. As the proposed learning framework incorporated the EEG label information of different brain status, it is capable of learning a sparse representation that reveal the most discriminative brain activity sources among different brain states. Compared to the state-of-the-art EEG source analysis methods, proposed sparse dictionary learning framework achieved significant superior performance in both computing speed and accuracy for the challenging EEG source reconstruction problem through extensive numerical experiments. More importantly, the experimental results also validated that the proposed sparse learning framework is effective to discover the discriminative task-related brain activation sources, which shows the potential to advance the high resolution EEG source analysis for real-time non-invasive brain imaging research.

A Discontinuous Galerkin Method to Solve the EEG Forward Problem Using the Subtraction Approach

In order to perform electroencephalography (EEG) source reconstruction, i.e., to localize the sources underlying a measured EEG, the electric potential distribution at the electrodes generated by a dipolar current source in the brain has to be simulated, which is the so-called EEG forward problem. To solve it accurately, it is necessary to apply numerical methods that are able to take the individual geometry and conductivity distribution of the subject's head into account. In this context, the finite element (FE) method (FEM) has shown high numerical accuracy with the possibility to model complex geometries and conductive features, e.g., white matter conductivity anisotropy. In this article, we introduce and analyze the application of a discontinuous Galerkin (DG) method, an FEM that includes features of the finite volume framework, to the EEG forward problem. The DG-FEM approach fulfills the conservation property of electric charge also in the discrete case, making it attractive for a variety of applicat...

Vector tomography for reconstructing electric fields with non-zero divergence in bounded domains

In vector tomography (VT), the aim is to reconstruct an unknown multi-dimensional vector field using line integral data. In the case of a 2-dimensional VT, two types of line integral data are usually required. These data correspond to integration of the parallel and perpendicular projection of the vector field along the integration lines and are called the longitudinal and transverse measurements, respectively. In most cases, however, the transverse measurements cannot be physically acquired. Therefore, the VT methods are typically used to reconstruct divergence-free (or source-free) velocity and flow fields that can be reconstructed solely from the longitudinal measurements. In this paper, we show how vector fields with non-zero divergence in a bounded domain can also be reconstructed from the longitudinal measurements without the need of explicitly evaluating the transverse measurements. To the best of our knowledge, VT has not previously been used for this purpose. In particular, we study low-frequency, time-harmonic electric fields generated by dipole sources in convex bounded domains which arise, for example, in electroencephalography (EEG) source imaging. We explain in detail the theoretical background, the derivation of the electric field inverse problem and the numerical approximation of the line integrals. We show that fields with non-zero divergence can be reconstructed from the longitudinal measurements with the help of two sparsity constraints that are constructed from the transverse measurements and the vector Laplace operator. As a comparison to EEG source imaging, we note that VT does not require mathematical modeling of the sources. By numerical simulations, we show that the pattern of the electric field can be correctly estimated using VT and the location of the source activity can be determined accurately from the reconstructed magnitudes of the field.

Neurobiological Correlates of Inhibition of the Right Broca Homolog during New-Word Learning.

Repetitive transcranial magnetic stimulation (rTMS) has demonstrated beneficial effects on motor learning. It would be important to obtain a similar enhancement for verbal learning. However, previous studies have mostly assessed short-term effects of rTMS on language performance and the effect on learning is largely unknown. This study examined whether an inhibition of the right Broca homolog has long-term impact on neural processes underlying the acquisition of new words in healthy individuals. Sixteen young participants trained a new-word learning paradigm with rare, mostly unknown objects and their corresponding words immediately after continuous theta burst stimulation (cTBS) or sham stimulation of right inferior frontal gyrus (IFG) in a cross-over design. Neural effects were assessed with electroencephalography (EEG) source power analyses during the naming task as well as coherence analyses at rest 1 day before and after training. Inhibition of the right Broca homolog did not affect new word learning performance at the group level. Behavioral and neural responses to cTBS were variable across participants and were associated with the magnitude of resting-state alpha-band coherence between the stimulated area and the rest of the brain before stimulation. Only participants with high intrinsic alpha-band coherence between the stimulated area and the rest of the brain before stimulation showed the expected inhibition during naming and greater learning performance. In conclusion, our study confirms that cTBS can induce lasting modulations of neural processes which are associated with learning, but the effect depends on the individual network state.

The diagnostic utility of 3D-ESI rotating and moving dipole methodology in the pre-surgical evaluation of MRI-negative childhood epilepsy due to focal cortical dysplasia.

This study investigates whether a combined rotating dipole (RD) and moving dipole (MD) solution enhances three-dimensional electroencephalography (EEG) source imaging (3D-ESI) localization in magnetic resonance imaging (MRI)-negative pediatric patients with focal cortical dysplasia (FCD). We retrospectively selected 14 MRI-negative patients with FCD from a cohort of 60 pediatric patients previously used to evaluate the diagnostic utility of 3D-ESI in epilepsy surgery. Patients were younger than 18years at time of surgery and had at least 1year of outcome data. RD and MD models were constructed for each interictal spike or sharp wave, and it was determined whether each inverse algorithm localized within the surgical resection cavity (SRC). We also compared the 3D-ESI findings and surgical outcome with positron emission tomography (PET) and ictal single photon emission computed tomography (iSPECT). RD analyses revealed a high concordance with the SRC (78.6%), particularly for temporal lobe resection (100.0%), and showed superior localization compared to PET and iSPECT, with the highest correlation in FCD type I and temporal lobe resection. Furthermore, the RD method was superior to iSPECT in FCD type II cases and to PET in extratemporal resections. RD and MD results were comparable, but in 18.2% of patients with FCD type I with localizing RDs, the MD solution was only partially within the SRC; in all of these patients 3D-ESI also correlated with superior surgical outcome compared to PET and iSPECT, especially when RD and MD solutions were analyzed together. 3D-ESI in MRI-negative cases showed superior localization compared to iSPECT or PET, especially in FCD type I and temporal lobe epilepsy, and correlated with superior surgical outcome compared to iSPECT and PET at 1 year and 2years postoperatively, especially when RD and MD solutions were analyzed together. These findings suggest that 3D-ESI based on a combined RD-MD solution improves surgical accuracy in MRI-negative patients with FCD.

Current use of imaging and electromagnetic source localization procedures in epilepsy surgery centers across Europe.

In 2014 the European Union-funded E-PILEPSY project was launched to improve awareness of, and accessibility to, epilepsy surgery across Europe. We aimed to investigate the current use of neuroimaging, electromagnetic source localization, and imaging postprocessing procedures in participating centers. A survey on the clinical use of imaging, electromagnetic source localization, and postprocessing methods in epilepsy surgery candidates was distributed among the 25 centers of the consortium. A descriptive analysis was performed, and results were compared to existing guidelines and recommendations. Response rate was 96%. Standard epilepsy magnetic resonance imaging (MRI) protocols are acquired at 3 Tesla by 15 centers and at 1.5 Tesla by 9 centers. Three centers perform 3T MRI only if indicated. Twenty-six different MRI sequences were reported. Six centers follow all guideline-recommended MRI sequences with the proposed slice orientation and slice thickness or voxel size. Additional sequences are used by 22 centers. MRI postprocessing methods are used in 16 centers. Interictal positron emission tomography (PET) is available in 22 centers; all using 18F-fluorodeoxyglucose (FDG). Seventeen centers perform PET postprocessing. Single-photon emission computed tomography (SPECT) is used by 19 centers, of which 15 perform postprocessing. Four centers perform neither PET nor SPECT in children. Seven centers apply magnetoencephalography (MEG) source localization, and nine apply electroencephalography (EEG) source localization. Fourteen combinations of inverse methods and volume conduction models are used. We report a large variation in the presurgical diagnostic workup among epilepsy surgery centers across Europe. This diversity underscores the need for high-quality systematic reviews, evidence-based recommendations, and harmonization of available diagnostic presurgical methods.

Compensation of domain modelling errors in the inverse source problem of the Poisson equation: Application in electroencephalographic imaging

In the inverse source problem of the Poisson equation, measurements on the domain boundaries are used to reconstruct sources inside the domain. The problem is an ill-posed inverse problem and it is sensitive to modelling errors of the domain. These errors can be boundary, structure and material property errors, for example. In this paper, we investigate whether the recently proposed Bayesian approximation error (BAE) approach could be used to alleviate the source estimation errors when an approximate model for the domain is employed. The BAE is based on postulating a probabilistic model for the uncertainties, in this case the geometry and structure of the domain, and to carry out approximate marginalization over these nuisance parameters. We particularly consider electroencephalography (EEG) source imaging as an application. EEG is a diagnostic brain imaging modality, and it can be used to reconstruct neural sources in the brain from electric potential measurements along the scalp. In the feasibility study, we assess to which degree one can recover from the modelling errors that are induced by the use of the three concentric circle head model instead of an anatomically accurate head model. The studied domain modelling errors include errors in the geometry of the exterior boundary and the structure of the interior. We show that, in particular with superficial dipole sources, the BAE yields estimates that can in some cases be considered adequately accurate. This would avoid the need for the extraction of the accurate head features which is conventionally carried out via expensive and time consuming auxiliary imaging modalities such as magnetic resonance imaging.

Mind-Wandering Tends to Occur under Low Perceptual Demands during Driving

Fluctuations in attention behind the wheel poses a significant risk for driver safety. During transient periods of inattention, drivers may shift their attention towards internally-directed thoughts or feelings at the expense of staying focused on the road. This study examined whether increasing task difficulty by manipulating involved sensory modalities as the driver detected the lane-departure in a simulated driving task would promote a shift of brain activity between different modes of processing, reflected by brain network dynamics on electroencephalographic sources. Results showed that depriving the driver of salient sensory information imposes a relatively more perceptually-demanding task, leading to a stronger activation in the task-positive network. When the vehicle motion feedback is available, the drivers may rely on vehicle motion to perceive the perturbations, which frees attentional capacity and tends to activate the default mode network. Such brain network dynamics could have major implications for understanding fluctuations in driver attention and designing advance driver assistance systems.

Degraded attentional modulation of cortical neural populations in strabismic amblyopia.

Behavioral studies have reported reduced spatial attention in amblyopia, a developmental disorder of spatial vision. However, the neural populations in the visual cortex linked with these behavioral spatial attention deficits have not been identified. Here, we use functional MRI–informed electroencephalography source imaging to measure the effect of attention on neural population activity in the visual cortex of human adult strabismic amblyopes who were stereoblind. We show that compared with controls, the modulatory effects of selective visual attention on the input from the amblyopic eye are substantially reduced in the primary visual cortex (V1) as well as in extrastriate visual areas hV4 and hMT+. Degraded attentional modulation is also found in the normal-acuity fellow eye in areas hV4 and hMT+ but not in V1. These results provide electrophysiological evidence that abnormal binocular input during a developmental critical period may impact cortical connections between the visual cortex and higher level cortices beyond the known amblyopic losses in V1 and V2, suggesting that a deficit of attentional modulation in the visual cortex is an important component of the functional impairment in amblyopia. Furthermore, we find that degraded attentional modulation in V1 is correlated with the magnitude of interocular suppression and the depth of amblyopia. These results support the view that the visual suppression often seen in strabismic amblyopia might be a form of attentional neglect of the visual input to the amblyopic eye.

Antiretroviral therapy affects the z-score index of deviant cortical EEG rhythms in naïve HIV individuals.

ObjectiveHere we tested the effect of combined antiretroviral therapy (cART) on deviant electroencephalographic (EEG) source activity in treatment-naïve HIV individuals.MethodsResting state eyes-closed EEG data were recorded before and after 5 months of cART in 48 male HIV subjects, who were naïve at the study start. The EEG data were also recorded in 59 age- and sex-matched healthy subjects as a control group. Frequency bands of interest included delta, theta, alpha1, alpha2 and alpha3, based on alpha frequency peak specific to each individual. They also included beta1 (13–20 Hz) and beta2 (20–30 Hz). Low-resolution brain electromagnetic tomography (LORETA) estimated EEG cortical source activity in frontal, central, temporal, parietal, and occipital regions.ResultsBefore the therapy, the HIV group showed greater parietal delta source activity and lower spatially diffuse alpha source activity compared to the control group. Thus, the ratio of parietal delta and alpha3 source activity served as an EEG marker. The z-score showed a statistically deviant EEG marker (EEG +) in 50% of the HIV individuals before therapy (p < 0.05). After 5 months of cART, delta source activity decreased, and alpha3 source activity increased in the HIV subjects with EEG + (about 50% of them showed a normalized EEG marker).ConclusionsThis procedure detected a deviant EEG marker before therapy and its post-therapy normalization in naïve HIV single individuals.SignificanceThe parietal delta/alpha3 EEG marker may be used to monitor cART effects on brain function in such individuals.

Evaluation of Electroencephalography Source Localization Algorithms with Multiple Cortical Sources.

BackgroundSource localization algorithms often show multiple active cortical areas as the source of electroencephalography (EEG). Yet, there is little data quantifying the accuracy of these results. In this paper, the performance of current source density source localization algorithms for the detection of multiple cortical sources of EEG data has been characterized.MethodsEEG data were generated by simulating multiple cortical sources (2–4) with the same strength or two sources with relative strength ratios of 1:1 to 4:1, and adding noise. These data were used to reconstruct the cortical sources using current source density (CSD) algorithms: sLORETA, MNLS, and LORETA using a p-norm with p equal to 1, 1.5 and 2. Precision (percentage of the reconstructed activity corresponding to simulated activity) and Recall (percentage of the simulated sources reconstructed) of each of the CSD algorithms were calculated.ResultsWhile sLORETA has the best performance when only one source is present, when two or more sources are present LORETA with p equal to 1.5 performs better. When the relative strength of one of the sources is decreased, all algorithms have more difficulty reconstructing that source. However, LORETA 1.5 continues to outperform other algorithms. If only the strongest source is of interest sLORETA is recommended, while LORETA with p equal to 1.5 is recommended if two or more of the cortical sources are of interest. These results provide guidance for choosing a CSD algorithm to locate multiple cortical sources of EEG and for interpreting the results of these algorithms.

The diagnostic utility of 3D electroencephalography source imaging in pediatric epilepsy surgery.

The aim of this study was to investigate the utility of three-dimensional electroencephalography source imaging (3D-ESI) with low-resolution electroencephalographic data in the pediatric noninvasive presurgical evaluation, and to compare the findings with positron emission tomography (PET) and ictal single-photon emission computed tomography (iSPECT). We retrospectively selected 60 patients from a database of 594 patients who underwent excisional surgery for drug-resistant epilepsy. Patients were <18 years at time of surgery, had at least one presurgical volumetric brain magnetic resonance imaging (MRI), and at least 1 year of outcome data. 3D-ESI was performed with NeuroScan software CURRY V.7.0. For each patient the surgical resection was planned utilizing 3D-ESI as an adjunctive tool to supplement MRI and electrocorticographic data. Our analyses addressed three critical variables: pathology (focal cortical dysplasia vs. other pathologies), imaging (MRI negative vs. positive cases), and surgery (temporal resection vs. extratemporal and multilobar resections). We also compared the localizing utility and surgical outcome of 3D-ESI findings with PET, iSPECT, and the colocalized surgical resection. Statistical analyses were performed using the Statistical Package for the Social Sciences, Version 20. Mean age at surgery was 11.18 years (range 1-18 years). 3D-ESI showed a strong correlation with the surgical resection cavity (65.0%), particularly within the temporal lobe. 3D-ESI demonstrated better localization in MRI-negative cases (78.6%), which was not statistically significant. 3D-ESI also correlated with a superior surgical outcome profile compared to PET and iSPECT. Our findings demonstrate that 3D-ESI data obtained with low-resolution electroencephalography achieves reasonably accurate noninvasive localization of epileptic spikes in pediatric focal epilepsy, especially in temporal lobe and MRI-negative cases, and is comparable to iSPECT and PET. Given its lesser expense and lack of radiation exposure, 3D-ESI is a useful and efficient tool for evaluating surgical candidacy in pediatric epilepsy surgery centers, particularly if PET and iSPECT are unavailable.

High-resolution imaging-guided electroencephalography source localization: temporal effect regularization incorporation in LORETA inverse solution

Electroencephalography (EEG) and magnetic resonance imaging (MRI) are noninvasive neuroimag- ing modalities. They are widely used and could be complementary. The fusion of these modalities may enhance some emerging research fields targeting the exploration better brain activities. Such research attracted various scientific investigators especially to provide a convivial and helpful advanced clinical-aid tool enabling better neurological explorations. Our present research was, in fact, in the context of EEG inverse problem resolution and investigated an advanced estimation methodology for the localization of the cerebral activity. Our focus was, therefore, on the integration of temporal priors to low-resolution brain electromagnetic tomography (LORETA) formalism and to solve the inverse problem in the EEG. The main idea behind our proposed method was in the integration of a temporal projection matrix within the LORETA weighting matrix. A hyperparameter is the principal fact for such a temporal integration, and its importance would be obvious when obtaining a regularized smooth- ness solution. Our experimental results clearly confirmed the impact of such an optimization procedure adopted for the temporal regularization parameter comparatively to the LORETA method. © 2015 SPIE and IS&T (DOI: 10

Ictal EEG Source Imaging for Presurgical Evaluation of Refractory Focal Epilepsy

Electroencephalography source imaging (ESI) is a promising tool for localizing the cortical sources of both ictal and interictal epileptic activities. Many studies have shown the clinical usefulness of interictal ESI, but very few have investigated the utility of ictal ESI. The aim of this article is to examine the clinical usefulness of ictal ESI for epileptic focus localization in patients with refractory focal epilepsy, especially extratemporal lobe epilepsy. Both ictal and interictal ESI were performed by the use of patient-specific realistic forward models and 3 different linear distributed inverse models. Lateralization as well as concordance between ESI-estimated focuses and single-photon emission computed tomography (SPECT) focuses were assessed. All the ESI focuses (both ictal and interictal) were found lateralized to the same hemisphere as ictal SPECT focuses. Lateralization results also were in agreement with the lesion sides as visualized on magnetic resonance imaging. Ictal ESI results, obtained from the best-performing inverse model, were fully concordant with the same cortical lobe as SPECT focuses, whereas the corresponding concordance rate is 87.50% in case of interictal ESI. Our findings show that ictal ESI gives fully lateralized and highly concordant results with ictal SPECT and may provide a cost-effective substitute for ictal SPECT.