MEG and EEG Sensitivity in a Case of Medial Occipital Epilepsy

The impact of ROI extraction method for MEG connectivity estimation: practical recommendations for the study of resting state data

Magnetoencephalography and electroencephalography (M/EEG) seed-based connectivity analysis requires the extraction of measures from regions of interest (ROI). M/EEG ROI-derived source activity can be treated in different ways. It is possible, for instance, to average each ROI's time series prior to calculating connectivity measures. Alternatively, one can compute connectivity maps for each element of the ROI prior to dimensionality reduction to obtain a single map. The impact of these different strategies on connectivity results is still unclear. Here, we address this question within a large MEG resting state cohort (N=113) and within simulated data. We consider 68 ROIs (Desikan-Kiliany atlas), two measures of connectivity (phase locking value-PLV, and its imaginary counterpart- ciPLV), and three frequency bands (theta 4-8 Hz, alpha 9-12 Hz, beta 15-30 Hz). We compare four extraction methods: (i) mean, or (ii) PCA of the activity within the seed or ROI before computing connectivity, map of the (iii) average, or (iv) maximum connectivity after computing connectivity for each element of the seed. Hierarchical clustering is then applied to compare connectivity outputs across multiple strategies, followed by direct contrasts across extraction methods. Finally, the results are validated by using a set of realistic simulations. We show that ROI-based connectivity maps vary remarkably across strategies in terms of connectivity magnitude and spatial distribution. Dimensionality reduction procedures conducted after computing connectivity are more similar to each-other, while PCA before approach is the most dissimilar to other approaches. Although differences across methods are consistent across frequency bands, they are influenced by the connectivity metric and ROI size. Greater differences were observed for ciPLV than PLV, and in larger ROIs. Realistic simulations confirmed that after aggregation procedures are generally more accurate but have lower specificity (higher rate of false positive connections). Though computationally demanding, after dimensionality reduction strategies should be preferred when higher sensitivity is desired. Given the remarkable differences across aggregation procedures, caution is warranted in comparing results across studies applying different methods.

Practical Fundamentals of Clinical MEG Interpretation in Epilepsy

Magnetoencephalography (MEG) is a neurophysiologic test that offers a functional localization of epileptic sources in patients considered for epilepsy surgery. The understanding of clinical MEG concepts, and the interpretation of these clinical studies, are very involving processes that demand both clinical and procedural expertise. One of the major obstacles in acquiring necessary proficiency is the scarcity of fundamental clinical literature. To fill this knowledge gap, this review aims to explain the basic practical concepts of clinical MEG relevant to epilepsy with an emphasis on single equivalent dipole (sECD), which is one the most clinically validated and ubiquitously used source localization method, and illustrate and explain the regional topology and source dynamics relevant for clinical interpretation of MEG-EEG.

Impact of skull-to-brain conductivity ratio for high resolution EEG source localization

Objective. To measure the impact of skull-to-brain conductivity ratios on interictal spikes source localizations, using high resolution EEG (HR EEG). In previous studies, two ratios were mainly employed: 1/80 and 1/40. Consequences of the employed ratios on source localization results are poorly studied.Methods. Twenty patients with drug-resistant epilepsy were studied using HR EEG (sixty-four scalp electrodes). For each patient, three-layers realistic head models based on individual MRI were elaborated using boundary element model. For each interictal spike, source localization was performed six times, using six skull-to-brain conductivity ratios (1/80, 1/50, 1/40, 1/30, 1/20 and 1/10), exploring all the spectrum of values reported in the literature. We then measured distances between the different sources obtained and between the sources and the anterior commissure (in order to estimate sources depth).Results. We measured a mean distance of 5.3 mm (sd: 3 mm) between the sources obtained with 1/40 versus 1/80 ratio. This distance increased when the discrepancy between the two evaluated ratios increased. We measured a mean distance of 14.2 mm (sd: 4.9 mm) between sources obtained with 1/10 ratio versus 1/80 ratio. Sources localized using 1/40 ratio were 4.3 mm closer to the anterior commissure than sources localized using 1/80 ratio.Significance. Skull-to-brain conductivity ratio is an often-neglected parameter in source localization studies. The different ratios mainly used in the litterature (1/80 and 1/40) lead to significant differences in source localizations. These variations mainly occur in source depth. A more accurate estimation of skull-to-brain conductivity is needed to increase source localization accuracy.Abbreviations. ECD: equivalent current dipole; EIT: electric impedance tomography, HR EEG: High resolution Electroencephalography, IIS: Inter ictal spikes, MEG: Magnetoencephalography, MRI: Magnetic resonance imaging, mS/m: milli-Siemens/m, S/m: Siemens/m, SD: Standard deviation.

The 10 Common Evidence-Supported Indications for MEG in Epilepsy Surgery: An Illustrated Compendium

Unfamiliarity with the indications for and benefits of magnetoencephalography (MEG) persists, even in the epilepsy community, and hinders its acceptance to clinical practice, despite the evidence. The wide treatment gap for patients with drug-resistant epilepsy and immense underutilization of epilepsy surgery had similar effects. Thus, educating referring physicians (epileptologists, neurologists, and neurosurgeons) both about the value of epilepsy surgery and about the potential benefits of MEG can achieve synergy and greatly improve the process of selecting surgical candidates. As a practical step toward a comprehensive educational process to benefit potential MEG users, current MEG referrers, and newcomers to MEG, the authors have elected to provide an illustrated guide to 10 everyday situations where MEG can help in the evaluation of people with drug-resistant epilepsy. They are as follows: (1) lacking or imprecise hypothesis regarding a seizure onset; (2) negative MRI with a mesial temporal onset suspected; (3) multiple lesions on MRI; (4) large lesion on MRI; (5) diagnostic or therapeutic reoperation; (6) ambiguous EEG findings suggestive of "bilateral" or "generalized" pattern; (7) intrasylvian onset suspected; (8) interhemispheric onset suspected; (9) insular onset suspected; and (10) negative (i.e., spikeless) EEG. Only their practical implementation and furtherance of personal and collective education will lead to the potentially impactful synergy of the two-MEG and epilepsy surgery. Thus, while fulfilling our mission as physicians, we must not forget that ignoring the wealth of evidence about the vast underutilization of epilepsy surgery - and about the usefulness and value of MEG in selecting surgical candidates - is far from benign neglect.

Recognizing and Correcting MEG Artifacts

Noise sources in magnetoencephalography (MEG) include: (1) interference from outside the shielded room, (2) other people and devices inside the shielded room, (3) physiologic or nonphysiologic sources inside the patient, (4) activity from inside the head that is unrelated to the signal of interest, (5) intrinsic sensor and recording electronics noise, and (6) artifacts from other apparatus used during recording such as evoked response stimulators. There are other factors which corrupt MEG recording and interpretation and should also be considered "artifacts": (7) inadequate positioning of the patient, (8) changes in the head position during the recording, (9) incorrect co-registration, (10) spurious signals introduced during postprocessing, and (11) errors in fitting. The major means whereby magnetic interference can be reduced or eliminated are by recording inside a magnetically shielded room, using gradiometers that measure differential magnetic fields, real-time active compensation using reference sensors, and postprocessing with advanced spatio-temporal filters. Many of the artifacts that plague MEG are also seen in EEG, so an experienced electroencephalographer will have the advantage of being able to transfer his knowledge about artifacts to MEG. However, many of the procedures and software used during acquisition and analysis may themselves contribute artifact or distortion that must be recognized or prevented. In summary, MEG artifacts are not worse than EEG artifacts, but many are different, and-as with EEG-must be attended to.

MEG for Greater Sensitivity and More Precise Localization in Epilepsy

Magnetoencephalography is the noninvasive measurement of miniscule magnetic fields produced by brain electrical currents, and is used most fruitfully to evaluate epilepsy patients. While other modalities infer brain function indirectly by measuring changes in blood flow, metabolism, and oxygenation, magnetoencephalography measures neuronal and synaptic function directly with submillisecond temporal resolution. The brain's magnetic field is recorded by neuromagnetometers surrounding the head in a helmet-shaped sensor array. Because magnetic signals are not distorted by anatomy, magnetoencephalography allows for a more accurate measurement and localization of brain activities than electroencephalography. Magnetoencephalography has become an indispensable part of the armamentarium at epilepsy centers.

Evidence for the Role of Magnetic Source Imaging in the Presurgical Evaluation of Refractory Epilepsy Patients

Magnetoencephalography (MEG) in the field of epilepsy has multiple advantages; just like electroencephalography (EEG), MEG is able to measure the epilepsy specific information (i.e., the brain activity reflecting seizures and/or interictal epileptiform discharges) directly, non-invasively and with a very high temporal resolution (millisecond-range). In addition MEG has a unique sensitivity for tangential sources, resulting in a full picture of the brain activity when combined with EEG. It accurately allows to perform source imaging of focal epileptic activity and functional cortex and shows a specific high sensitivity for a source in the neocortex. In this paper the current evidence and practice for using magnetic source imaging of focal interictal and ictal epileptic activity during the presurgical evaluation of drug resistant patients is being reviewed.

Differences in MEG and EEG power-law scaling explained by a coupling between spatial coherence and frequency: a simulation study

Electrophysiological signals (electroencephalography, EEG, and magnetoencephalography, MEG), as many natural processes, exhibit scale-invariance properties resulting in a power-law (1/f) spectrum. Interestingly, EEG and MEG differ in their slopes, which could be explained by several mechanisms, including non-resistive properties of tissues. Our goal in the present study is to estimate the impact of space/frequency structure of source signals as a putative mechanism to explain spectral scaling properties of neuroimaging signals. We performed simulations based on the summed contribution of cortical patches with different sizes (ranging from 0.4 to 104.2 cm²). Small patches were attributed signals of high frequencies, whereas large patches were associated with signals of low frequencies, on a logarithmic scale. The tested parameters included i) the space/frequency structure (range of patch sizes and frequencies) and ii) the amplitude factor c parametrizing the spatial scale ratios. We found that the space/frequency structure may cause differences between EEG and MEG scale-free spectra that are compatible with real data findings reported in previous studies. We also found that below a certain spatial scale, there were no more differences between EEG and MEG, suggesting a limit for the resolution of both methods.Our work provides an explanation of experimental findings. This does not rule out other mechanisms for differences between EEG and MEG, but suggests an important role of spatio-temporal structure of neural dynamics. This can help the analysis and interpretation of power-law measures in EEG and MEG, and we believe our results can also impact computational modeling of brain dynamics, where different local connectivity structures could be used at different frequencies.

Magnetoencephalography for localizing and characterizing the epileptic focus

Magnetoencephalography (MEG) is the noninvasive measurement of the miniscule magnetic fields produced by electrical currents flowing in the brain-the same neuroelectric activity that produces the EEG. MEG is one of several diagnostic tests employed in the evaluation of patients with epilepsy, but without the need to expose the patient to any potentially harmful agents. MEG is especially important in those being considered for epilepsy surgery, in whom accurate localization of the epileptic focus is paramount. While other modalities infer brain function indirectly by measuring changes in blood flow, metabolism, oxygenation, etc., MEG, as well as EEG, measures neuronal and synaptic function directly and, like EEG, MEG enjoys submillisecond temporal resolution. The measurement of magnetic fields provides information not only about the amplitude of the current but also its orientation. MEG picks up the magnetic field from neuromagnetometers surrounding the head in a helmet-shaped array of sensors. Clinical whole-head systems currently have 200-300 magnetic sensors, thereby offering very high resolution. The magnetic signals are not distorted by anatomy, because magnetic susceptibility is the same for all tissues, including the skull. Hence, MEG allows for a more accurate measurement and localization of brain activities than does EEG. Because one of its primary strengths is the ability to precisely localize electromagnetic activity within brain areas, MEG results are always coregistered to the patient's MRI. When combined in this way with structural imaging, it has been called magnetic source imaging (MSI), but MEG is properly understood as a clinical neurophysiologic diagnostic test. Signal processing and clinical interpretation in magnetoencephalography require sophisticated noise reduction and computerized mathematical modeling. Technological advances in these areas have brought MEG to the point where it is now part of routine clinical practice. MEG has become an indispensable part of the armamentarium at epilepsy centers where MEG laboratories are located, especially when patients are MRI-negative or where results of other structural and functional tests are not entirely concordant.

IFCN-endorsed practical guidelines for clinical magnetoencephalography (MEG)

Magnetoencephalography (MEG) records weak magnetic fields outside the human head and thereby provides millisecond-accurate information about neuronal currents supporting human brain function. MEG and electroencephalography (EEG) are closely related complementary methods and should be interpreted together whenever possible. This manuscript covers the basic physical and physiological principles of MEG and discusses the main aspects of state-of-the-art MEG data analysis. We provide guidelines for best practices of patient preparation, stimulus presentation, MEG data collection and analysis, as well as for MEG interpretation in routine clinical examinations. In 2017, about 200 whole-scalp MEG devices were in operation worldwide, many of them located in clinical environments. Yet, the established clinical indications for MEG examinations remain few, mainly restricted to the diagnostics of epilepsy and to preoperative functional evaluation of neurosurgical patients. We are confident that the extensive ongoing basic MEG research indicates potential for the evaluation of neurological and psychiatric syndromes, developmental disorders, and the integrity of cortical brain networks after stroke. Basic and clinical research is, thus, paving way for new clinical applications to be identified by an increasing number of practitioners of MEG.

Magnetoencephalographic Identification of Epileptic Focus in Children With Generalized Electroencephalographic (EEG) Features but Focal Imaging Abnormalities

PURPOSE

Children with generalized seizures are often excluded as epilepsy surgery candidates. This prospective study was conducted to evaluate the utility of magnetoencephalography (MEG) to refine the location of the "irritative zone" in children with single lesions on magnetic resonance imaging (MRI) but with generalized ictal electroencephalographic (EEG) findings.

METHODS

Patients admitted with refractory epilepsy with imaging studies showing focal or hemispheric abnormalities but scalp video EEG showing generalized or multiregional epileptiform abnormalities were included. Patients were encouraged into natural sleep, and simultaneous whole-head MEG/EEG was recorded. Source localization of epileptic spikes on MEG was carried out while blinded to other results. Acceptable dipoles were classified into 3 groups: focal, hemispheric clusters, and single focal cluster with additional widespread dipoles.

RESULTS

Nine patients (4 female, 5 males; ages 10 months to 15 years) were included. Two had focal features on clinical semiology, whereas all had generalized or multiregional interictal and ictal EEG. Etiologies included tuberous sclerosis complex (2), postencephalitic sequelae (1), focal cortical dysplasia (1), and unknown (2). Five patients had clear focal lesions on brain MRI whereas the other 2 had focal positron emission tomography (PET) abnormalities. An average of 38 spikes were accepted (average goodness of fit = 85.3%). A single tight cluster of dipoles was identified in 5 patients, 1 had dipoles with propagation from left occipital to right temporal. One patient had 2 distinct dipole clusters. MEG demonstrated focal findings 9 times more often than the simultaneously recorded scalp EEG, and 3 times more often than the associated multiday video EEG recordings.

CONCLUSION

This study shows that neurophysiologic evidence of focal epileptiform abnormalities in patients with focal brain lesions and generalized EEG findings can be strengthened using MEG. Further feasibility of surgical candidacy should be evaluated in these patients.

Intracranial EEG potentials estimated from MEG sources: A new approach to correlate MEG and iEEG data in epilepsy

Detection of epileptic spikes in MagnetoEncephaloGraphy (MEG) requires synchronized neuronal activity over a minimum of 4cm2. We previously validated the Maximum Entropy on the Mean (MEM) as a source localization able to recover the spatial extent of the epileptic spike generators. The purpose of this study was to evaluate quantitatively, using intracranial EEG (iEEG), the spatial extent recovered from MEG sources by estimating iEEG potentials generated by these MEG sources. We evaluated five patients with focal epilepsy who had a pre-operative MEG acquisition and iEEG with MRI-compatible electrodes. Individual MEG epileptic spikes were localized along the cortical surface segmented from a pre-operative MRI, which was co-registered with the MRI obtained with iEEG electrodes in place for identification of iEEG contacts. An iEEG forward model estimated the influence of every dipolar source of the cortical surface on each iEEG contact. This iEEG forward model was applied to MEG sources to estimate iEEG potentials that would have been generated by these sources. MEG-estimated iEEG potentials were compared with measured iEEG potentials using four source localization methods: two variants of MEM and two standard methods equivalent to minimum norm and LORETA estimates. Our results demonstrated an excellent MEG/iEEG correspondence in the presumed focus for four out of five patients. In one patient, the deep generator identified in iEEG could not be localized in MEG. MEG-estimated iEEG potentials is a promising method to evaluate which MEG sources could be retrieved and validated with iEEG data, providing accurate results especially when applied to MEM localizations. Hum Brain Mapp 37:1661-1683, 2016. © 2016 Wiley Periodicals, Inc.

A magnetoencephalography study of visual processing of pain anticipation

Anticipating pain is important for avoiding injury; however, in chronic pain patients, anticipatory behavior can become maladaptive, leading to sensitization and limiting function. Knowledge of networks involved in pain anticipation and conditioning over time could help devise novel, better-targeted therapies. With the use of magnetoencephalography, we evaluated in 10 healthy subjects the neural processing of pain anticipation. Anticipatory cortical activity elicited by consecutive visual cues that signified imminent painful stimulus was compared with cues signifying nonpainful and no stimulus. We found that the neural processing of visually evoked pain anticipation involves the primary visual cortex along with cingulate and frontal regions. Visual cortex could quickly and independently encode and discriminate between visual cues associated with pain anticipation and no pain during preconscious phases following object presentation. When evaluating the effect of task repetition on participating cortical areas, we found that activity of prefrontal and cingulate regions was mostly prominent early on when subjects were still naive to a cue's contextual meaning. Visual cortical activity was significant throughout later phases. Although visual cortex may precisely and time efficiently decode cues anticipating pain or no pain, prefrontal areas establish the context associated with each cue. These findings have important implications toward processes involved in pain anticipation and maladaptive pain conditioning.

The role of functional neuroimaging in pre-surgical epilepsy evaluation

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.

The role of functional neuroimaging in pre-surgical epilepsy evaluation

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.