MEG and EEG in epilepsy

Somatosensory evoked spikes in normal adults detected by magnetoencephalography

OBJECTIVE

Somatosensory evoked spikes (SESs) have been reported only in children aged under 14 years and are considered as an age-dependent phenomenon. However, we detected SESs in adult patients with epilepsy using magnetoencephalography (MEG). The present study investigated whether MEG can detect SESs in normal adults.

METHODS

Spontaneous MEG was recorded during measurement of somatosensory evoked fields (SEFs) for bilateral electrical median nerve stimuli in 30 healthy adults.

RESULTS

Bilateral SESs were observed in 10 adults but none in the other 20 subjects. SESs consisted of one or two peaks, and the first peak latency corresponded to that of the second peak (M2) of SEFs. The first SES peak was identical to the M2 in isofield map pattern, as well as location and orientation of the equivalent current dipole (ECD). M2 ECD strength in the 10 subjects with SESs was larger (p <0.0001) than in 20 without SESs.

CONCLUSIONS

All-or-nothing detection of bilateral SESs by MEG in normal adults must depend on the signal-to-noise issue of symmetrical SEFs and background brain activity.

SIGNIFICANCE

Our results further confirm the higher sensitivity of MEG compared to scalp EEG for the detection of focal cortical sources tangential to the scalp such as SESs.

EEG/MEG source imaging of deep brain activity within the maximum entropy on the mean framework: Simulations and validation in epilepsy

Electro/Magneto-EncephaloGraphy (EEG/MEG) source imaging (EMSI) of epileptic activity from deep generators is often challenging due to the higher sensitivity of EEG/MEG to superficial regions and to the spatial configuration of subcortical structures. We previously demonstrated the ability of the coherent Maximum Entropy on the Mean (cMEM) method to accurately localize the superficial cortical generators and their spatial extent. Here, we propose a depth-weighted adaptation of cMEM to localize deep generators more accurately. These methods were evaluated using realistic MEG/high-density EEG (HD-EEG) simulations of epileptic activity and actual MEG/HD-EEG recordings from patients with focal epilepsy. We incorporated depth-weighting within the MEM framework to compensate for its preference for superficial generators. We also included a mesh of both hippocampi, as an additional deep structure in the source model. We generated 5400 realistic simulations of interictal epileptic discharges for MEG and HD-EEG involving a wide range of spatial extents and signal-to-noise ratio (SNR) levels, before investigating EMSI on clinical HD-EEG in 16 patients and MEG in 14 patients. Clinical interictal epileptic discharges were marked by visual inspection. We applied three EMSI methods: cMEM, depth-weighted cMEM and depth-weighted minimum norm estimate (MNE). The ground truth was defined as the true simulated generator or as a drawn region based on clinical information available for patients. For deep sources, depth-weighted cMEM improved the localization when compared to cMEM and depth-weighted MNE, whereas depth-weighted cMEM did not deteriorate localization accuracy for superficial regions. For patients' data, we observed improvement in localization for deep sources, especially for the patients with mesial temporal epilepsy, for which cMEM failed to reconstruct the initial generator in the hippocampus. Depth weighting was more crucial for MEG (gradiometers) than for HD-EEG. Similar findings were found when considering depth weighting for the wavelet extension of MEM. In conclusion, depth-weighted cMEM improved the localization of deep sources without or with minimal deterioration of the localization of the superficial sources. This was demonstrated using extensive simulations with MEG and HD-EEG and clinical MEG and HD-EEG for epilepsy patients.

From cryogenic to on-scalp magnetoencephalography for the evaluation of paediatric epilepsy

Magnetoencephalography (MEG) is a neurophysiological technique based on the detection of brain magnetic fields. Whole-head MEG systems typically house a few hundred sensors requiring cryogenic cooling in a rigid one-size-fits-all (commonly adult-sized) helmet to keep a thermal insulation space. This leads to an increased brain-to-sensor distance in children, because of their smaller head circumference, and decreased signal-to-noise ratio. MEG allows detection and localization of interictal and ictal epileptiform discharges, and pathological high frequency oscillations, as a part of the presurgical assessment of children with refractory focal epilepsy, where electroencephalography is not contributive. MEG can also map the eloquent cortex before surgical resection. MEG also provides insights into the physiopathology of both generalized and focal epilepsy. On-scalp recordings based on cryogenic-free sensors have demonstrated their use in the field of childhood focal epilepsy and should become a reference technique for diagnosing epilepsy in the paediatric population. WHAT THIS PAPER ADDS: Magnetoencephalography (MEG) contributes to the diagnosis and understanding of paediatric epilepsy. On-scalp MEG recordings demonstrate some advantages over cryogenic MEG.

Physiological and pathological neuronal connectivity in the living human brain based on intracranial EEG signals: the current state of research

Over the past decades, studies of human brain networks have received growing attention as the assessment and modelling of connectivity in the brain is a topic of high impact with potential application in the understanding of human brain organization under both physiological as well as various pathological conditions. Under specific diagnostic settings, human neuronal signal can be obtained from intracranial EEG (iEEG) recording in epilepsy patients that allows gaining insight into the functional organisation of living human brain. There are two approaches to assess brain connectivity in the iEEG-based signal: evaluation of spontaneous neuronal oscillations during ongoing physiological and pathological brain activity, and analysis of the electrophysiological cortico-cortical neuronal responses, evoked by single pulse electrical stimulation (SPES). Both methods have their own advantages and limitations. The paper outlines available methodological approaches and provides an overview of current findings in studies of physiological and pathological human brain networks, based on intracranial EEG recordings.

Magnetoencephalographic spikes with small spikes on simultaneous electroencephalography have high spatial clustering in temporal lobe epilepsy

OBJECTIVE

To classify magnetoencephalographic (MEG) spikes according to the findings of simultaneous scalp electroencephalography (EEG) to study dipole estimation in patients with temporal lobe epilepsy.

METHODS

We analyzed MEG and simultaneous scalp EEG in 27 patients with intractable temporal lobe epilepsy. We classified MEG spikes into three groups (H-EM-spikes, L-EM-spikes, M-spikes) based on the amplitude of simultaneous EEG (50 μV or higher, lower than 50 μV, no spike morphology on EEG, respectively). We calculated parameters of the dipoles, such as goodness of fit (GOF), current moment, and location.

RESULTS

We detected 707 MEG spikes, consisting of 175 H-EM-spikes, 245 L-EM-spikes, and 287 M-spikes. Dipoles of H-EM-spikes showed the highest current moment among the three spike groups. Dipoles of L-EM-spikes showed the highest GOF, a moderate current moment, the highest density to cluster, and the highest proportion of being located in the temporal lobe among the three groups. Dipoles of M-spikes showed the lowest GOF and current moment among the three groups.

CONCLUSIONS

The characteristics of the dipoles of the MEG spikes differ depending on the simultaneous scalp EEG findings, though most of the MEG spikes were located in the temporal lobe. MEG spikes with concurrent small spikes on simultaneous scalp EEG may have higher spatial clustering in temporal lobe epilepsy.

EEG Microstate Features as an Automatic Recognition Model of High-Density Epileptic EEG Using Support Vector Machine

Epilepsy is one of the most serious nervous system diseases; it can be diagnosed accurately by video electroencephalogram. In this study, we analyzed microstate epileptic electroencephalogram (EEG) to aid in the diagnosis and identification of epilepsy. We recruited patients with focal epilepsy and healthy participants from the Third Xiangya Hospital and recorded their resting EEG data. In this study, the EEG data were analyzed by microstate analysis, and the support vector machine (SVM) classifier was used for automatic epileptic EEG classification based on features of the EEG microstate series, including microstate parameters (duration, occurrence, and coverage), linear features (median, second quartile, mean, kurtosis, and skewness) and non-linear features (Petrosian fractal dimension, approximate entropy, sample entropy, fuzzy entropy, and Lempel-Ziv complexity). In the gamma sub-band, the microstate parameters as a model were the best for interictal epilepsy recognition, with an accuracy of 87.18%, recall of 70.59%, and an area under the curve of 94.52%. There was a recognition effect of interictal epilepsy through the features extracted from the EEG microstate, which varied within the 4~45 Hz band with an accuracy of 79.55%. Based on the SVM classifier, microstate parameters and EEG features can be effectively used to classify epileptic EEG, and microstate parameters can better classify epileptic EEG compared with EEG features.

Changes in functional connectivity in newly diagnosed self-limited epilepsy with centrotemporal spikes and cognitive impairment: An MEG study

PURPOSE

Our purpose was to explore the relationship between cognitive impairment and neural network changes in patients newly diagnosed with self-limited epilepsy with centrotemporal spikes (SeLECTS).

METHODS

The Wechsler Intelligence Scale for Children, fourth edition was used to divide all SeLECTS patients into two groups: patients with full-scale intelligence quotient (FSIQ) below 80 that corresponded to cognitive impairment, and patients with FSIQ above 80 that corresponded to a normal cognitive function. The data on the resting state were recorded using magnetoencephalography. The properties of the networks were analyzed using graph theory (GT) analysis.

RESULTS

The functional connectivity (FC) of the frontal cortex in patients with FSIQ < 80 was reduced in the 12-30 Hz frequency band, and the FC of the posterior cingulate cortex was reduced in the 80-250 and 250-500 Hz frequency bands. The GT analysis showed that patients in the FSIQ < 80 group had higher strength in the 8-12 and 12-30 Hz frequency bands than those in the healthy control and FSIQ > 80 group. However, the path length was reduced in the 80-250 Hz band, and the clustering coefficient was reduced in the 12-30, 80-250, and 250-500 Hz frequency bands. Moreover, the receiver operator characteristic analysis showed that the clustering coefficient in the 12-30 and 80-250 Hz frequency bands, as well as the path length in the 80-250 Hz frequency band possessed a good discriminative ability in distinguishing the FSIQ > 80 group.

CONCLUSIONS

SeLECTS patients with cognitive impairment in the early stage of the disease developed disordered networks in cognitive-related brain regions. The clustering coefficient in the 12-30 and 80-250 Hz frequency bands as well as the path length in the 80-250 Hz frequency band might be good indicators to distinguish the cognitive impairment of SeLECTS patients at the early stage.

Wearable OPM-MEG: A changing landscape for epilepsy

Magnetoencephalography with optically pumped magnometers (OPM-MEG) is an emerging and novel, cost-effective wearable system that can simultaneously record neuronal activity with high temporal resolution ("when" neuronal activity occurs) and spatial resolution ("where" neuronal activity occurs). This paper will first outline recent methodological advances in OPM-MEG compared to conventional superconducting quantum interference device (SQUID)-MEG before discussing how OPM-MEG can become a valuable and noninvasive clinical support tool in epilepsy surgery evaluation. Although OPM-MEG and SQUID-MEG share similar data features, OPM-MEG is a wearable design that fits children and adults, and it is also robust to head motion within a magnetically shielded room. This means that OPM-MEG can potentially extend the application of MEG into the neurobiology of severe childhood epilepsies with intellectual disabilities (e.g., epileptic encephalopathies) without sedation. It is worth noting that most OPM-MEG sensors are heated, which may become an issue with large OPM sensor arrays (OPM-MEG currently has fewer sensors than SQUID-MEG). Future implementation of triaxial sensors may alleviate the need for large OPM sensor arrays. OPM-MEG designs allowing both awake and sleep recording are essential for potential long-term epilepsy monitoring.

Analysis of the robustness and dynamics of spin-locking preparations for the detection of oscillatory magnetic fields

Extracting quantitative information of neuronal signals by non-invasive imaging is an outstanding challenge for understanding brain function and pathology. However, state-of-the-art techniques offer low sensitivity to deep electrical sources. Stimulus induced rotary saturation is a recently proposed magnetic resonance imaging sequence that detects oscillatory magnetic fields using a spin-lock preparation. Phantom experiments and simulations proved its efficiency and sensitivity, but the susceptibility of the method to field inhomogeneities is still not well understood. In this study, we simulated and analyzed the dynamic of three spin-lock preparations and their response to field inhomogeneities in the presence of a resonant oscillating field. We show that the composite spin-lock preparation is more robust against field variations within the double resonance effect. In addition, we tested the capability of the chosen composite spin-lock preparation to recover information about the spectral components of a composite signal. This study sets the bases to move one step further towards the clinical application of MR-based neuronal current imaging.

Neuroimaging Assessment of Pain

Pain is an unpleasant sensory and emotional experience. Understanding the neural mechanisms of acute and chronic pain and the brain changes affecting pain factors is important for finding pain treatment methods. The emergence and progress of non-invasive neuroimaging technology can help us better understand pain at the neural level. Recent developments in identifying brain-based biomarkers of pain through advances in advanced imaging can provide some foundations for predicting and detecting pain. For example, a neurologic pain signature (involving brain regions that receive nociceptive afferents) and a stimulus intensity-independent pain signature (involving brain regions that do not show increased activity in proportion to noxious stimulus intensity) were developed based on multivariate modeling to identify processes related to the pain experience. However, an accurate and comprehensive review of common neuroimaging techniques for evaluating pain is lacking. This paper reviews the mechanism, clinical application, reliability, strengths, and limitations of common neuroimaging techniques for assessing pain to promote our further understanding of pain.

Alterations in the default mode network in rolandic epilepsy with mild spike-wave index in non-rapid eye movement sleep

Purpose

Rolandic epilepsy (RE) is one of the most common epilepsy syndromes during childhood. The aim of this study was to investigate the alterations in the default mode network (DMN) of RE patients whose spike-wave index (SWI) was within the 50–85% range during non-rapid eye movement (NREM) during sleep, as well as to detect early neuroimaging markers.

Methods

Resting-state data was recorded for each subject using magnetoencephalography (MEG). DMN-related brain regions were chosen as regions of interest. The spectral power and functional connectivity (FC) of the DMN were estimated through the use of minimum norm estimation (MNE) combined with Welch technique and corrected amplitude envelope correlation (AEC-c).

Results

The patient group included 20 patients with NREM phase 50% ≤ SWI < 85% (mild SWI group), and 18 typical RE patients (SWI < 50% group). At the regional level, the mild SWI group exhibited enhanced spectral power in the delta band of the bilateral posterial cingulate cortex and attenuated the spectral power in the alpha band of the bilateral posterial cingulate cortex. Enhanced spectral power in the bilateral precuneus (PCu) in the delta band and attenuated spectral power in the right lateral temporal cortex (LTC) in the alpha band were common across all RE patients. At the FC level, patients in the mild SWI group indicated increased AEC-c values between the bilateral posterial cingulate cortex in the delta band and between the left medial frontal cortex (MFC) and bilateral posterial cingulate cortex in the alpha band. Increased AEC-c values between the right PCu and left MFC in the delta band, and between the left PCu and right MFC in the theta band, were common across all RE patients. Moreover, the spectral power in the bilateral posterial cingulate cortex in the alpha band and the AEC-c value between the bilateral posterial cingulate cortex in the delta band demonstrated good discrimination ability.

Conclusion

The spectral power of the bilateral posterior cingulate cortex (PCC) in the alpha band and the AEC-c value between the bilateral PCC in the delta band may be promising indicators of early differentiation between mild SWI and typical RE.

Therapeutic benefits of noninvasive somatosensory cortex stimulation on cortical plasticity and somatosensory function: a systematic review

Optimal limb coordination requires efficient transmission of somatosensory information to the sensorimotor cortex. The primary somatosensory cortex (S1) is frequently damaged by stroke, resulting in both somatosensory and motor impairments. Noninvasive brain stimulation (NIBS) to the primary motor cortex is thought to induce neural plasticity that facilitates neurorehabilitation. Several studies have also examined if NIBS to the S1 can enhance somatosensory processing as assessed by somatosensory-evoked potentials (SEPs) and improve behavioral task performance, but it remains uncertain if NIBS can reliably modulate S1 plasticity or even whether SEPs can reflect this plasticity. This systematic review revealed that NIBS has relatively minor effects on SEPs or somatosensory task performance, but larger early SEP changes after NIBS can still predict improved performance. Similarly, decreased paired-pulse inhibition in S1 post-NIBS is associated with improved somatosensory performance. However, several studies still debate the role of inhibitory function in somatosensory performance after NIBS in terms of the direction of the change (that, disinhibition or inhibition). Altogether, early SEP and paired-pulse inhibition (particularly inter-stimulus intervals of 30-100 ms) may become useful biomarkers for somatosensory deficits, but improved NIBS protocols are required for therapeutic applications.

Diagnostic added value of interictal magnetic source imaging in presurgical evaluation of persons with epilepsy: A prospective blinded study

BACKGROUND AND PURPOSE

In presurgical evaluation for epilepsy surgery, information is sourced from various imaging modalities to accurately localize the epileptogenic zone. Magnetoencephalography (MEG) is a newer noninvasive technique for localization. However, there is limited literature to evaluate if MEG provides additional advantage over the conventional imaging modalities in clinical decision making. The objective of this study was to assess the diagnostic added value of MEG in decision making before epilepsy surgery.

METHOD

This was a prospective observational study. Patients underwent 3 h of recording in a MEG scanner, and the resulting localizations were compared with other complimentary investigations. Added value of MEG (considered separately from high-density electroencephalography) was defined as the frequency of cases in which (i) the information provided by magnetic source imaging (MSI) avoided implantation of intracranial electrodes and the patient was directly cleared for surgery, and (ii) MSI indicated additional substrates for implantation of intracranial electrodes. Postoperative seizure freedom was used as the diagnostic reference by which to measure the localizing accuracy of MSI.

RESULTS

A total of 102 patients underwent epilepsy surgery. MEG provided nonredundant information, which contributed to deciding the course of surgery in 33% of the patients, and prevented intracranial recordings in 19%. A total of 76% of the patients underwent surgical resection in sublobes concordant with MSI localization, and the diagnostic odds ratio for good (Engel I) outcome in these patients was 2.3 (95% confidence interval 0.68, 7.86; p = 0.183) after long-term follow-up of 36 months.

CONCLUSION

Magnetic source imaging yields additional useful information which can significantly alter as well as improve the surgical strategy for persons with epilepsy.

Recurrent migraine aura-like symptoms in an elderly woman: symptomatic cortical spreading depression?

Cortical spreading depression (CSD) has been directly observed in humans with malignant stroke, traumatic brain injury and subarachnoid haemorrhage and is also considered to be the correlate of migraine aura. We report on a 76-year-old woman with new-onset episodes of headache, paraesthesia, hemiparesis and dysarthria, in whom a small cortical subarachnoid haemorrhage was diagnosed with MRI. Repeated diffusion-weighted MRI scans shortly after transient focal neurological episodes as well as diagnostic workup were normal, which makes recurrent transient ischaemic attacks unlikely. Ictal electroencephalogram recordings showed no epileptic activity. Long-term follow-up revealed a diagnosis of probable cerebral amyloid angiopathy. We propose that CSD could be a pathophysiological correlate of transient focal neurological deficits in patients with cortical bleeding.

A review of magnetoencephalography use in pediatric epilepsy: an update on best practice

Introduction: Magnetoencephalography (MEG) is a noninvasive technique that is used for presurgical evaluation of children with drug-resistant epilepsy (DRE).Areas covered: The contributions of MEG for localizing the epileptogenic zone are discussed, in particular in extra-temporal lobe epilepsy and focal cortical dysplasia, which are common in children, as well as in difficult to localize epilepsy such as operculo-insular epilepsy. Further, the authors review current evidence on MEG for mapping eloquent cortex, its performance, application in clinical practice, and potential challenges.Expert opinion: MEG could change the clinical management of children with DRE by directing placement of intracranial electrodes thereby enhancing their yield. With improved identification of a circumscribed epileptogenic zone, MEG could render more patients as suitable candidates for epilepsy surgery and increase utilization of surgery.

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.

Spatial fidelity of MEG/EEG source estimates: A general evaluation approach

Low spatial resolution is often cited as the most critical limitation of magneto- and electroencephalography (MEG and EEG), but a unifying framework for quantifying the spatial fidelity of M/EEG source estimates has yet to be established; previous studies have focused on linear estimation methods under ideal scenarios without noise. Here we present an approach that quantifies the spatial fidelity of M/EEG estimates from simulated patch activations over the entire neocortex superposed on measured resting-state data. This approach grants more generalizability in the evaluation process that allows for, e.g., comparing linear and non-linear estimates in the whole brain for different signal-to-noise ratios (SNR), number of active sources and activation waveforms. Using this framework, we evaluated the MNE, dSPM, sLORETA, eLORETA, and MxNE methods and found that the spatial fidelity varies significantly with SNR, following a largely sigmoidal curve whose shape varies depending on which aspect of spatial fidelity that is being quantified and the source estimation method. We believe that these methods and results will be useful when interpreting M/EEG source estimates as well as in methods development.

The relationship between epilepsy and cognitive function in benign childhood epilepsy with centrotemporal spikes

INTRODUCTION

This study was aimed to explore the relationship between neural network changes in newly diagnosed children with Benign Childhood Epilepsy with Centrotemporal Spikes (BECTS) and cognitive impairment.

METHODS

Children's cognition was evaluated using the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV). Magnetoencephalographic (MEG) data of 18 healthy children and 22 BECTS patients were recorded in order to construct a functional connectivity (FC) network, which was quantified by graph theory (GT).

RESULTS

The mean age of the control group was 7.94 ± 1.89 years, and the mean age of BECTS patients was 8.14 ± 1.73 years. Our results show that the WISC-IV index scores in the BECTS group were significantly lower than those in the control group. Besides, the FC network pattern of BECTS patients changed significantly in the 12-30, 30-80, and 250-500 Hz frequency band. The local functional connections between posterior cingulate cortex (PCC) and frontal lobe varied significantly in 12-30, 80-250, and 250-500 Hz. Our GT analysis shows that the connection strength of BECTS patients increases significantly in the 12-30 Hz frequency band, the path length decreases significantly in the 12-30 Hz and 30-80 Hz frequency bands, with the clustering coefficient decreasing significantly in the 12-30 Hz, 30-80 Hz, and 250-500 Hz frequency bands. Correlation analysis showed that the full-scale IQ (FSIQ) was positively correlated with the 12-30 Hz clustering coefficient, verbal comprehension index (VCI) was positively correlated with the 250-500 Hz clustering coefficient, perceptual reasoning index (PRI) was positively correlated with the 12-30 Hz clustering coefficient, and perceptual reasoning index (PSI) was negatively correlated with the 12-30 Hz path length.

CONCLUSION

There is a trend of cognitive impairment in patients with early BECTS. This trend of cognitive impairment in early BECTS children may be related to the changes in the FC network pattern.

Interrater Reliability of Experts in Identifying Interictal Epileptiform Discharges in Electroencephalograms

Importance

The validity of using electroencephalograms (EEGs) to diagnose epilepsy requires reliable detection of interictal epileptiform discharges (IEDs). Prior interrater reliability (IRR) studies are limited by small samples and selection bias.

Objective

To assess the reliability of experts in detecting IEDs in routine EEGs.

Design, Setting, and Participants

This prospective analysis conducted in 2 phases included as participants physicians with at least 1 year of subspecialty training in clinical neurophysiology. In phase 1, 9 experts independently identified candidate IEDs in 991 EEGs (1 expert per EEG) reported in the medical record to contain at least 1 IED, yielding 87 636 candidate IEDs. In phase 2, the candidate IEDs were clustered into groups with distinct morphological features, yielding 12 602 clusters, and a representative candidate IED was selected from each cluster. We added 660 waveforms (11 random samples each from 60 randomly selected EEGs reported as being free of IEDs) as negative controls. Eight experts independently scored all 13 262 candidates as IEDs or non-IEDs. The 1051 EEGs in the study were recorded at the Massachusetts General Hospital between 2012 and 2016.

Main Outcomes and Measures

Primary outcome measures were percentage of agreement (PA) and beyond-chance agreement (Gwet κ) for individual IEDs (IED-wise IRR) and for whether an EEG contained any IEDs (EEG-wise IRR). Secondary outcomes were the correlations between numbers of IEDs marked by experts across cases, calibration of expert scoring to group consensus, and receiver operating characteristic analysis of how well multivariate logistic regression models may account for differences in the IED scoring behavior between experts.

Results

Among the 1051 EEGs assessed in the study, 540 (51.4%) were those of females and 511 (48.6%) were those of males. In phase 1, 9 experts each marked potential IEDs in a median of 65 (interquartile range [IQR], 28-332) EEGs. The total number of IED candidates marked was 87 636. Expert IRR for the 13 262 individually annotated IED candidates was fair, with the mean PA being 72.4% (95% CI, 67.0%-77.8%) and mean κ being 48.7% (95% CI, 37.3%-60.1%). The EEG-wise IRR was substantial, with the mean PA being 80.9% (95% CI, 76.2%-85.7%) and mean κ being 69.4% (95% CI, 60.3%-78.5%). A statistical model based on waveform morphological features, when provided with individualized thresholds, explained the median binary scores of all experts with a high degree of accuracy of 80% (range, 73%-88%).

Conclusions and Relevance

This study's findings suggest that experts can identify whether EEGs contain IEDs with substantial reliability. Lower reliability regarding individual IEDs may be largely explained by various experts applying different thresholds to a common underlying statistical model.

Normal Variants in Magnetoencephalography

Normal variants, although not occurring frequently, may appear similar to epileptic activity. Misinterpretation may lead to false diagnoses. In the context of presurgical evaluation, normal variants may lead to mislocalizations with severe impact on the viability and success of surgical therapy. While the different variants are well known in EEG, little has been published in regard to their appearance in magnetoencephalography. Furthermore, there are some magnetoencephalography normal variants that have no counterparts in EEG. This article reviews benign epileptiform variants and provides examples in EEG and magnetoencephalography. In addition, the potential of oscillatory configurations in different frequency bands to appear as epileptic activity is discussed.

The relationship between neuromagnetic activity and cognitive function in benign childhood epilepsy with centrotemporal spikes

PURPOSE

Our aim was to explore the pathophysiological mechanism of cognitive function changes in early untreated children with benign childhood epilepsy with centrotemporal spikes (BECTS).

METHODS

Magnetoencephalography (MEG) was performed in 33 children with BECTS and 18 healthy children. Wechsler Intelligence Scale for Children, fourth edition (WISC-IV) was used to divide children with BECTS into two groups. Normal cognitive function was defined as a full-scale intelligence quotient (FSIQ) of >80, while decreased cognitive function was defined as a FSIQ of <80. Accumulated source imaging was used to evaluate the neuromagnetic source activity in multifrequency bands.

RESULTS

Of the 33 patients with early untreated BECTS, a total of 17 had a FSIQ of <80 and 16 had FSIQ of >80. The course of epilepsy and number of seizures in the FSIQ <80 group were higher than that in the FSIQ >80 group. Our MEG results showed that in the 4-8 Hz frequency band, both patient groups had inactivation of the posterior cingulate cortex (PCC) region compared with the healthy control group. In the 30-80 Hz frequency band, the FSIQ <80 group showed inactivation of the PCC region compared with both the healthy control group and the FSIQ >80 group. In the 80-250 Hz frequency band, the FSIQ <80 group had inactivated of the medial frontal cortex (MFC) region compared with the healthy control group. In the 30-80 Hz frequency band, the strength of neuromagnetic source in patients with BECTS with FSIQ <80 was higher than that in the FSIQ >80 group and the healthy control group.

CONCLUSIONS

The magnetic source inactivation of the MFC and PCC regions during the interictal time may be the reason for cognitive decline in early untreated children with BECTS. Children with BECTS with cognitive decline had a longer course of epilepsy and more seizures. The magnetic source localization in the 4-8 Hz frequency band may be a new imaging marker for the diagnosis of new BECTS.

A Combination of Particle Swarm Optimization and Minkowski Weighted K-Means Clustering: Application in Lateralization of Temporal Lobe Epilepsy

K-Means is one of the most popular clustering algorithms that partitions observations into nonoverlapping subgroups based on a predefined similarity metric. Its drawbacks include a sensitivity to noisy features and a dependency of its resulting clusters upon the initial selection of cluster centroids resulting in the algorithm converging to local optima. Minkowski weighted K-Means (MWK-Means) addresses the issue of sensitivity to noisy features, but is sensitive to the initialization of clusters, and so the algorithm may similarly converge to local optima. Particle Swarm Optimization (PSO) uses a globalized search method to solve this issue. We present a hybrid Particle Swarm Optimization (PSO) + MWK-Means clustering algorithm to address all the above problems in a single framework, while maintaining benefits of PSO and MWK Means methods. This study investigated the utility of this approach in lateralizing the epileptogenic hemisphere for temporal lobe epilepsy (TLE) cases using magnetoencephalography (MEG) coherence source imaging (CSI) and diffusion tensor imaging (DTI). Using MEG-CSI, we analyzed preoperative resting state MEG data from 17 adults TLE patients with Engel class I outcomes to determine coherence at 54 anatomical sites and compared the results with 17 age- and gender-matched controls. Fiber-tracking was performed through the same anatomical sites using DTI data. Indices of both MEG coherence and DTI nodal degree were calculated. A PSO + MWK-Means clustering algorithm was applied to identify the side of temporal lobe epileptogenicity and distinguish between normal and TLE cases. The PSO module was aimed at identifying initial cluster centroids and assigning initial feature weights to cluster centroids and, hence, transferring to the MWK-Means module for the final optimal clustering solution. We demonstrated improvements with the use of the PSO + MWK-Means clustering algorithm compared to that of K-Means and MWK-Means independently. PSO + MWK-Means was able to successfully distinguish between normal and TLE in 97.2% and 82.3% of cases for DTI and MEG data, respectively. It also lateralized left and right TLE in 82.3% and 93.6% of cases for DTI and MEG data, respectively. The proposed optimization and clustering methodology for MEG and DTI features, as they relate to focal epileptogenicity, would enhance the identification of the TLE laterality in cases of unilateral epileptogenicity.

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.

Revisiting the Functional Anatomy of the Human Brain: Toward a Meta-Networking Theory of Cerebral Functions

For more than one century, brain processing was mainly thought in a localizationist framework, in which one given function was underpinned by a discrete, isolated cortical area, and with a similar cerebral organization across individuals. However, advances in brain mapping techniques in humans have provided new insights into the organizational principles of anatomo-functional architecture. Here, we review recent findings gained from neuroimaging, electrophysiological, as well as lesion studies. Based on these recent data on brain connectome, we challenge the traditional, outdated localizationist view and propose an alternative meta-networking theory. This model holds that complex cognitions and behaviors arise from the spatiotemporal integration of distributed but relatively specialized networks underlying conation and cognition (e.g., language, spatial cognition). Dynamic interactions between such circuits result in a perpetual succession of new equilibrium states, opening the door to considerable interindividual behavioral variability and to neuroplastic phenomena. Indeed, a meta-networking organization underlies the uniquely human propensity to learn complex abilities, and also explains how postlesional reshaping can lead to some degrees of functional compensation in brain-damaged patients. We discuss the major implications of this approach in fundamental neurosciences as well as for clinical developments, especially in neurology, psychiatry, neurorehabilitation, and restorative neurosurgery.

The impact of MEG results on surgical outcomes in patients with drug-resistant epilepsy associated with focal encephalomalacia: a single-center experience

PURPOSE

To analyze the impact of magnetoencephalography (MEG) results on surgical outcomes in patients with drug-resistant epilepsy secondary to encephalomalacia.

METHODS

We retrospectively reviewed 121 patients with drug-resistant epilepsy associated with encephalomalacia who underwent MEG followed by resection surgery. Patients were subdivided into concordant MEG group and dis-concordant MEG group for analysis based on whether the MEG results were in concordance with epileptogenic zones or not.

RESULTS

121 patients were included in the present study. The MEG spike sources of 73 (60.33%) patients were in concordance with epileptogenic zones while the MEG spike sources of the other 48 (39.67%) were in dis-concordance with epileptogenic zones. Favorable seizure outcomes were achieved in 79.45% (58 of 73) of patients with concordant MEG results while only 62.50% (30 of 48) of patients with dis-concordant MEG results were seizure free with a follow-up of 2-10 years. The differences of seizure-free rate between patients with concordant MEG results and dis-concordant MEG results were statistically significant. For patients with concordant MEG results, bilateral lesions on MRI are the only independent predictor of unfavorable seizure outcomes. For patients with discordant MEG results, duration of seizures is the only independent predictor of unfavorable seizure outcomes.

CONCLUSIONS

Concordant MEG results are associated with favorable seizure outcomes. Bilateral lesions on MRI independently predict unfavorable seizure outcomes in patients with concordant MEG results while longer seizure durations independently predict unfavorable seizure outcomes in patients with dis-concordant MEG results.

Flexible Multi-Layer Semi-Dry Electrode for Scalp EEG Measurements at Hairy Sites

One of the major challenges of daily wearable electroencephalogram (EEG) monitoring is that there are rarely suitable EEG electrodes for hairy sites. Wet electrodes require conductive gels, which will dry over the acquisition time, making them unstable for long-term EEG monitoring. Additionally, the electrode–scalp impedances of most dry electrodes are not adequate for high quality EEG collection at hairy sites. In view of the above problems, a flexible multi-layer semi-dry electrode was proposed for EEG monitoring in this study. The semi-dry electrode contains a flexible electrode body layer, foam layer and reservoir layer. The probe structure of the electrode body layer enables the electrode to work effectively at hairy sites. During long-term EEG monitoring, electrolytes stored in the reservoir layer are continuously released through the foam layer to the electrode–scalp interface, ensuring a lower electrode–scalp contact impedance. The experimental results showed that the average electrode–scalp impedance of the semi-dry electrode at a hairy site was only 23.89 ± 7.44 KΩ at 10 Hz, and it was lower than 40 KΩ over a long-term use of 5 h. The electrode performed well in both static and dynamic EEG monitoring, where the temporal correlation with wet electrode signals at the hairy site could reach 94.25% and 90.65%, respectively, and specific evoked EEG signals could be collected. The flexible multi-layer semi-dry electrode can be well applied to scalp EEG monitoring at hairy sites, providing a promising solution for daily long-term monitoring of wearable EEGs.

Assessing the localization accuracy and clinical utility of electric and magnetic source imaging in children with epilepsy

OBJECTIVE

To evaluate the accuracy and clinical utility of conventional 21-channel EEG (conv-EEG), 72-channel high-density EEG (HD-EEG) and 306-channel MEG in localizing interictal epileptiform discharges (IEDs).

METHODS

Twenty-four children who underwent epilepsy surgery were studied. IEDs on conv-EEG, HD-EEG, MEG and intracranial EEG (iEEG) were localized using equivalent current dipoles and dynamical statistical parametric mapping (dSPM). We compared the localization error (E_Loc) with respect to the ground-truth Irritative Zone (IZ), defined by iEEG sources, between non-invasive modalities and the distance from resection (D_res) between good- (Engel 1) and poor-outcomes. For each patient, we estimated the resection percentage of IED sources and tested whether it predicted outcome.

RESULTS

MEG presented lower E_Loc than HD-EEG and conv-EEG. For all modalities, D_res was shorter in good-outcome than poor-outcome patients, but only the resection percentage of the ground-truth IZ and MEG-IZ predicted surgical outcome.

CONCLUSIONS

MEG localizes the IZ more accurately than conv-EEG and HD-EEG. MSI may help the presurgical evaluation in terms of patient's outcome prediction. The promising clinical value of ESI for both conv-EEG and HD-EEG prompts the use of higher-density EEG-systems to possibly achieve MEG performance.

SIGNIFICANCE

Localizing the IZ non-invasively with MSI/ESI facilitates presurgical evaluation and surgical prognosis assessment.

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.

Magnetoencephalography as a Prognostic Tool in Patients with Medically Intractable Temporal Lobe Epilepsy

BACKGROUND

Most surgical treatments for medically intractable temporal lobe epilepsy are helpful. When a patient has persistent symptoms after surgery, there are no tests that accurately predict whether a patient will have remnant epileptic foci. The aim of this study was to evaluate the usefulness of magnetoencephalography (MEG) as a prognostic tool in patients with temporal lobe epilepsy.

METHODS

From July 2012 to July 2016, 21 patients underwent preoperative and postoperative MEG at our center. Postoperative MEG was performed within 2 weeks after surgery. We analyzed MEG by estimating the time-frequency component of the signal to define gamma oscillations (GOs), which are an indicator of epileptogenic foci. We analyzed the relationship between GOs on MEG and surgical outcomes.

RESULTS

Mean follow-up period was 28.3 months (range, 13-44 months). At the last follow-up visit, patients were divided into 2 groups according to surgical outcome. All patients showed spike waves and GOs on preoperative electroencephalography and MEG. In the seizure control group (16 patients), spike waves (2 patients) and GOs (2 patients) were seen postoperatively despite absence of symptoms. In the recurrent seizure group (5 patients), whereas 3 patients showed spike waves, all 5 patients showed GOs on MEG postoperatively. There was a significant association between presence of GOs on postoperative MEG and surgical outcome (P = 0.01).

CONCLUSIONS

MEG can provide valuable postsurgical information on epileptic foci in patients with recurrent symptoms; GOs on postoperative MEG were especially correlated with epileptic recurrence. Our data show that GOs on postoperative MEG may have prognostic value.

A bi-planar coil system for nulling background magnetic fields in scalp mounted magnetoencephalography

Small, commercially-available Optically Pumped Magnetometers (OPMs) can be used to construct a wearable Magnetoencephalography (MEG) system that allows large head movements to be made during recording. The small dynamic range of these sensors however means that movement in the residual static magnetic field found inside typical Magnetically Shielded Rooms (MSRs) can saturate the sensor outputs, rendering the data unusable. This problem can be ameliorated by using a set of electromagnetic coils to attenuate the spatially-varying remnant field. Here, an array of bi-planar coils, which produce an open and accessible scanning environment, was designed and constructed. The coils were designed using a harmonic minimisation method previously used for gradient coil design in Magnetic Resonance Imaging (MRI). Six coils were constructed to null Bx, By and Bz as well as the three dominant field gradients dBx/dz, dBy/dz and dBz/dz. The coils produce homogeneous (within ±5%) fields or field gradients over a volume of 40 × 40 × 40 cm3. This volume is sufficient to contain an array of OPMs, mounted in a 3D-printed scanner-cast, during basic and natural movements. Automated control of the coils using reference sensor measurements allows reduction of the largest component of the static field (Bx) from 21.8 ± 0.2 nT to 0.47 ± 0.08 nT. The largest gradient (dBx/dz) was reduced from 7.4 nT/m to 0.55 nT/m. High precision optical tracking allowed experiments involving controlled and measured head movements, which revealed that a rotation of the scanner-cast by ±34° and translation of ±9.7 cm of the OPMs in this field generated only a 1 nT magnetic field variation across the OPM array, when field nulling was applied. This variation could be further reduced to 0.04 nT by linear regression of field variations that were correlated with the measured motion parameters. To demonstrate the effectiveness of the bi-planar coil field cancellation system in a real MEG experiment, a novel measurement of retinotopy was investigated, where the stimulus remains fixed and head movements made by the subject shift the visual presentation to the lower left or right quadrants of the field of view. Left and right visual field stimulation produced the expected responses in the opposing hemisphere. This simple demonstration shows that the bi-planar coil system allows accurate OPM-MEG recordings to be made on an unrestrained subject.

Lateralization Value of Low Frequency Band Beamformer Magnetoencephalography Source Imaging in Temporal Lobe Epilepsy

Objective: In presurgical evaluation of temporal lobe epilepsy (TLE), selection of the resection side is challenging when bilateral temporal epileptiform discharges or structural abnormalities are present. We aim to evaluate the lateralization value of beamformer analysis of magnetoencephalography (MEG) in TLE. Methods: MEG data from 14 TLE patients were analyzed through beamformer analysis. We measured the hemispherical power distribution of beamformer sources and calculated the lateralization index (LI). We calculated the LI at multiple frequencies to explore the frequency dependency and at the delta frequency to define laterality. LI values ranging from -1 to -0.05 indicated right hemispheric dominance. LI values ranging from 0.05 to 1 indicated left hemispheric dominance. LI values ranging from -0.05 to 0.05 defined bilaterality. We measured the power of beamformer sources with a 9-s duration to explore time dependency. Results: The beamformer analysis showed that 10/14 patients had power dominance ipsilateral to resection. The delta frequency band had a higher lateralization value than other frequency bands. A time-dependent power fluctuation was found in the delta frequency band. Conclusions: MEG beamformer analysis, especially in the delta band, might efficiently provide additional information regarding lateralization in TLE.

Recording Brain Electromagnetic Activity During the Administration of the Gaseous Anesthetic Agents Xenon and Nitrous Oxide in Healthy Volunteers

Anesthesia arguably provides one of the only systematic ways to study the neural correlates of global consciousness/unconsciousness. However to date most neuroimaging or neurophysiological investigations in humans have been confined to the study of γ-Amino-Butyric-Acid-(GABA)-receptor-agonist-based anesthetics, while the effects of dissociative N-Methyl-D-Aspartate-(NMDA)-receptor-antagonist-based anesthetics ketamine, nitrous oxide (N2O) and xenon (Xe) are largely unknown. This paper describes the methods underlying the simultaneous recording of magnetoencephalography (MEG) and electroencephalography (EEG) from healthy males during inhalation of the gaseous anesthetic agents N2O and Xe. Combining MEG and EEG data enables the assessment of electromagnetic brain activity during anesthesia at high temporal, and moderate spatial, resolution. Here we describe a detailed protocol, refined over multiple recording sessions, that includes subject recruitment, anesthesia equipment setup in the MEG scanner room, data collection and basic data analysis. In this protocol each participant is exposed to varying levels of Xe and N2O in a repeated measures cross-over design. Following relevant baseline recordings participants are exposed to step-wise increasing inspired concentrations of Xe and N2O of 8, 16, 24 and 42%, and 16, 32 and 47% respectively, during which their level of responsiveness is tracked with an auditory continuous performance task (aCPT). Results are presented for a number of recordings to highlight the sensor-level properties of the raw data, the spectral topography, the minimization of head movements, and the unequivocal level dependent effects on the auditory evoked responses. This paradigm describes a general approach to the recording of electromagnetic signals associated with the action of different kinds of gaseous anesthetics, which can be readily adapted to be used with volatile and intravenous anesthetic agents. It is expected that the method outlined can contribute to the understanding of the macro-scale mechanisms of anesthesia by enabling methodological extensions involving source space imaging and functional network analysis.

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.

Epileptic spikes in Rasmussen's encephalitis: Migratory pattern and short-term evolution. A MEG study

OBJECTIVE

We aimed this study at identifying cortical areas involved in the generation of interictal spikes in Rasmussen's Encephalitis (RE) patients using magnetoencephalography (MEG), at comparing spike localization with the degree of cortical atrophy detected by MRI, and at identifying short-term changes during the follow-up.

METHODS

Five patients with RE underwent two MEG and magnetic resonance imaging (MRI) (six months interval). The sources of visually detected spikes were estimated using equivalent current dipoles technique; these were then superimposed on individual MRI and clustered; the locations of the clusters were related to the MRI stage of cortical atrophy.

RESULTS

All patients showed spikes and clusters located in different cortical areas in both recordings; the locations had a limited correspondence with cortical atrophy. The second recordings showed changes in the localisation of spikes and clusters, and confirmed the dissimilarities with neuroradiological abnormalities.

CONCLUSIONS

The presence of clusters of spikes of variable localisation suggests that RE progresses in a multifocal and fluctuating manner. The cortical areas most involved in epileptogenesis did not completely coincide with the most atrophic areas.

SIGNIFICANCE

MEG can contribute to evaluating multifocal hemispheric spikes in RE and to better understand the time course of epileptogenic process.

Multimodal investigation of epileptic networks: The case of insular cortex epilepsy

The insula is a deep cortical structure sharing extensive synaptic connections with a variety of brain regions, including several frontal, temporal, and parietal structures. The identification of the insular connectivity network is obviously valuable for understanding a number of cognitive processes, but also for understanding epilepsy since insular seizures involve a number of remote brain regions. Ultimately, knowledge of the structure and causal relationships within the epileptic networks associated with insular cortex epilepsy can offer deeper insights into this relatively neglected type of epilepsy enabling the refining of the clinical approach in managing patients affected by it. In the present chapter, we first review the multimodal noninvasive tests performed during the presurgical evaluation of epileptic patients with drug refractory focal epilepsy, with particular emphasis on their value for the detection of insular cortex epilepsy. Second, we review the emerging multimodal investigation techniques in the field of epilepsy, that aim to (1) enhance the detection of insular cortex epilepsy and (2) unveil the architecture and causal relationships within epileptic networks. We summarize the results of these approaches with emphasis on the specific case of insular cortex epilepsy.

Multimodal brain imaging with magnetoencephalography: A method for measuring blood pressure and cardiorespiratory oscillations

Studies with magnetoencephalography (MEG) are still quite rarely combined simultaneously with methods that can provide a metabolic dimension to MEG investigations. In addition, continuous blood pressure measurements which comply with MEG compatibility requirements are lacking. For instance, by combining methods reflecting neurovascular status one could obtain more information on low frequency fluctuations that have recently gained increasing interest as a mediator of functional connectivity within brain networks. This paper presents a multimodal brain imaging setup, capable to non-invasively and continuously measure cerebral hemodynamic, cardiorespiratory and blood pressure oscillations simultaneously with MEG. In the setup, all methods apart from MEG rely on the use of fibre optics. In particular, we present a method for measuring of blood pressure and cardiorespiratory oscillations continuously with MEG. The potential of this type of multimodal setup for brain research is demonstrated by our preliminary studies on human, showing effects of mild hypercapnia, gathered simultaneously with the presented modalities.

Application of MEG coherence in lateralization of mTLE

Magnetoencephalography (MEG) is a noninvasive imaging method for localization of focal epileptiform activity in patients with epilepsy. This study investigates the cerebral functional abnormalities quantified by MEG coherence laterality in mesial temporal lobe epilepsy (mTLE). Resting state MEG data was analyzed using MEG coherence source imaging (MEG-CSI) method to determine the coherence in 54 anatomical sites in 12 adult mTLE patients and 12 age- and gender-matched controls. MEG coherence laterality, after Bonferroni adjustment, showed significant differences for right versus left mTLE in insular cortex and both lateral orbitofrontal and superior temporal gyri (p<;0.025). None of these anatomical sites showed statistically significant differences in coherence laterality between right and left sides of controls. Coherence laterality was in agreement with the declared side of epileptogenicity in insular cortex (in 75% of patients) and both lateral orbitofrontal (83%) and superior temporal gyri (84%). Combining all significant laterality indices improved the lateralization accuracy to 92%. The proposed methodology for using MEG to investigate the abnormalities related to focal epileptogenicity and propagation can provide a further means of noninvasive lateralization.

MEG Coherence and DTI Connectivity in mTLE

Magnetoencephalography (MEG) is a noninvasive imaging method for localization of focal epileptiform activity in patients with epilepsy. Diffusion tensor imaging (DTI) is a noninvasive imaging method for measuring the diffusion properties of the underlying white matter tracts through which epileptiform activity is propagated. This study investigates the relationship between the cerebral functional abnormalities quantified by MEG coherence and structural abnormalities quantified by DTI in mesial temporal lobe epilepsy (mTLE). Resting state MEG data was analyzed using MEG coherence source imaging (MEG-CSI) method to determine the coherence in 54 anatomical sites in 17 adult mTLE patients with surgical resection and Engel class I outcome, and 17 age- and gender- matched controls. DTI tractography identified the fiber tracts passing through these same anatomical sites of the same subjects. Then, DTI nodal degree and laterality index were calculated and compared with the corresponding MEG coherence and laterality index. MEG coherence laterality, after Bonferroni adjustment, showed significant differences for right versus left mTLE in insular cortex and both lateral orbitofrontal and superior temporal gyri (p < 0.017). Likewise, DTI nodal degree laterality, after Bonferroni adjustment, showed significant differences for right versus left mTLE in gyrus rectus, insular cortex, precuneus and superior temporal gyrus (p < 0.017). In insular cortex, MEG coherence laterality correlated with DTI nodal degree laterality ([Formula: see text] in the cases of mTLE. None of these anatomical sites showed statistically significant differences in coherence laterality between right and left sides of the controls. Coherence laterality was in agreement with the declared side of epileptogenicity in insular cortex (in 82 % of patients) and both lateral orbitofrontal (88 %) and superior temporal gyri (88 %). Nodal degree laterality was also in agreement with the declared side of epileptogenicity in gyrus rectus (in 88 % of patients), insular cortex (71 %), precuneus (82 %) and superior temporal gyrus (94 %). Combining all significant laterality indices improved the lateralization accuracy to 94 % and 100 % for the coherence and nodal degree laterality indices, respectively. The associated variations in diffusion properties of fiber tracts quantified by DTI and coherence measures quantified by MEG with respect to epileptogenicity possibly reflect the chronic microstructural cerebral changes associated with functional interictal activity. The proposed methodology for using MEG and DTI to investigate diffusion abnormalities related to focal epileptogenicity and propagation may provide a further means of noninvasive lateralization.

Multi-frequency analysis of brain connectivity networks in migraineurs: a magnetoencephalography study

Background

Although alterations in resting-state neural network have been previously reported in migraine using functional MRI, whether this atypical neural network is frequency dependent remains unknown. The aim of this study was to investigate the alterations of the functional connectivity of neural network and their frequency specificity in migraineurs as compared with healthy controls by using magnetoencephalography (MEG) and concepts from graph theory.

Methods

Twenty-three episodic migraine patients with and without aura, during the interictal period, and 23 age- and gender-matched healthy controls at resting state with eye-closed were studied with MEG. Functional connectivity of neural network from low (0.1–1 Hz) to high (80–250 Hz) frequency ranges was analyzed with topographic patterns and quantified with graph theory.

Results

The topographic patterns of neural network showed that the migraineurs had significantly increased functional connectivity in the slow wave (0.1–1 Hz) band in the frontal area as compared with controls. Compared with the migraineurs without aura (MwoA), the migraineurs with aura (MwA) had significantly increased functional connectivity in the theta (4–8 Hz) band in the occipital area. Graph theory analysis revealed that the migraineurs had significantly increased connection strength in the slow wave (0.1–1 Hz) band, increased path length in the theta (4–8 Hz) and ripple (80–250 Hz) bands, and increased clustering coefficient in the slow wave (0.1–1 Hz) and theta (4–8 Hz) bands. The clinical characteristics had no significant correlation with interictal MEG parameters.

Conclusions

Results indicate that functional connectivity of neural network in migraine is significantly impaired in both low- and high-frequency ranges. The alteration of neural network may imply that migraine is associated with functional brain reorganization.

Functional Brain Dysfunction in Patients with Benign Childhood Epilepsy as Revealed by Graph Theory

There is growing evidence that brain networks are altered in epileptic subjects. In this study, we investigated the functional connectivity and brain network properties of benign childhood epilepsy with centrotemporal spikes using graph theory. Benign childhood epilepsy with centrotemporal spikes is the most common form of idiopathic epilepsy in young children under the age of 16 years. High-density EEG data were recorded from patients and controls in resting state with eyes closed. Data were preprocessed and spike and spike-free segments were selected for analysis. Phase locking value was calculated for all paired combinations of channels and for five frequency bands (δ, θ, α, β₁ and β₂). We computed the degree and small-world parameters—clustering coefficient (C) and path length (L)—and compared the two patient conditions to controls. A higher degree at epileptic zones during interictal epileptic spikes (IES) was observed in all frequency bands. Both patient conditions reduced connection at the occipital and right frontal regions close to the epileptic zone in the α band. The “small-world” features (high C and short L) were deviated in patients compared to controls. A changed from an ordered network in the δ band to a more randomly organized network in the α band was observed in patients compared to healthy controls. These findings show that the benign epileptic brain network is disrupted not only at the epileptic zone, but also in other brain regions especially frontal regions.

Toward Epileptic Brain Region Detection Based on Magnetic Nanoparticle Patterning

Resection of the epilepsy foci is the best treatment for more than 15% of epileptic patients or 50% of patients who are refractory to all forms of medical treatment. Accurate mapping of the locations of epileptic neuronal networks can result in the complete resection of epileptic foci. Even though currently electroencephalography is the best technique for mapping the epileptic focus, it cannot define the boundary of epilepsy that accurately. Herein we put forward a new accurate brain mapping technique using superparamagnetic nanoparticles (SPMNs). The main hypothesis in this new approach is the creation of super-paramagnetic aggregates in the epileptic foci due to high electrical and magnetic activities. These aggregates may improve tissue contrast of magnetic resonance imaging (MRI) that results in improving the resection of epileptic foci. In this paper, we present the mathematical models before discussing the simulation results. Furthermore, we mimic the aggregation of SPMNs in a weak magnetic field using a low-cost microfabricated device. Based on these results, the SPMNs may play a crucial role in diagnostic epilepsy and the subsequent treatment of this disease.

MEG-EEG Information Fusion and Electromagnetic Source Imaging: From Theory to Clinical Application in Epilepsy

The purpose of this study is to develop and quantitatively assess whether fusion of EEG and MEG (MEEG) data within the maximum entropy on the mean (MEM) framework increases the spatial accuracy of source localization, by yielding better recovery of the spatial extent and propagation pathway of the underlying generators of inter-ictal epileptic discharges (IEDs). The key element in this study is the integration of the complementary information from EEG and MEG data within the MEM framework. MEEG was compared with EEG and MEG when localizing single transient IEDs. The fusion approach was evaluated using realistic simulation models involving one or two spatially extended sources mimicking propagation patterns of IEDs. We also assessed the impact of the number of EEG electrodes required for an efficient EEG–MEG fusion. MEM was compared with minimum norm estimate, dynamic statistical parametric mapping, and standardized low-resolution electromagnetic tomography. The fusion approach was finally assessed on real epileptic data recorded from two patients showing IEDs simultaneously in EEG and MEG. Overall the localization of MEEG data using MEM provided better recovery of the source spatial extent, more sensitivity to the source depth and more accurate detection of the onset and propagation of IEDs than EEG or MEG alone. MEM was more accurate than the other methods. MEEG proved more robust than EEG and MEG for single IED localization in low signal-to-noise ratio conditions. We also showed that only few EEG electrodes are required to bring additional relevant information to MEG during MEM fusion.