MEG's ability to localise accurately weak transient neural sources

Towards Biomarkers for Autism Spectrum Disorder: Contributions of Magnetoencephalography (MEG)

There is no simple blood test for autism. Consequently, much attention has been paid to identifying noninvasive biomarkers using imaging (e.g., Magnetic resonance imaging, MRI) and electrophysiological (e.g., electroencephalography, EEG and magnetoencephalography, MEG) methods. While, in general, these lack direct biological specificity, they can (in principle) provide a useful tool, or suite of tools, for diagnostic, prognostic, stratification, and response monitoring purposes.This chapter focuses on the pursuit of biomarkers using magnetoencephalography (MEG). While closely related to the more common electroencephalography (EEG), MEG offers some unique characteristics (such as improved spatial resolution, in combination with real-time temporal resolution and spectral discrimination), that might be considered impactful in the pursuit of biomarkers.Given the widely-acknowledged heterogeneity of ASD ("if you've seen one child with autism, then you've seen one child with autism"), the tide of research is perhaps shifting away from diagnostic biomarkers toward biomarkers that can help stratify patients according to some similarity in biological basis, etiology, or pathway. This approach, somewhat pragmatic, may be of benefit when designing and conducting clinical trials of putative therapeutics, or when optimally designing behavioral supports (when "therapy" may not be indicated).Ultimately, MEG-derived biomarkers, however advantageous in themselves, may likely find a place as reference in the prioritization and roll-out of candidate biomarkers established using other modalities, more accessible and available to the global community.

Electromagnetic source imaging predicts surgical outcome in children with focal cortical dysplasia

OBJECTIVE

To evaluate the diagnostic accuracy of electromagnetic source imaging (EMSI) in localizing spikes and predict surgical outcome in children with drug resistant epilepsy (DRE) due to focal cortical dysplasia (FCD).

METHODS

We retrospectively analyzed magnetoencephalography (MEG) and high-density (HD-EEG) data from 23 children with FCD-associated DRE who underwent intracranial EEG and surgery. We localized spikes using equivalent current dipole (ECD) fitting, dipole clustering, and dynamical statistical parametric mapping (dSPM) on EMSI, electric source imaging (ESI), and magnetic source imaging (MSI). We calculated the distance from the seizure onset zone (DSOZ) and resection (DRES). We estimated receiver operating characteristic (ROC) curves with Youden's index (J) to predict outcome.

RESULTS

EMSI presented shorter DSOZ (15.18 ± 9.06 mm) and DRES (8.56 ± 6.24 mm) compared to ESI (DSOZ: 25.04 ± 16.20 mm, p < 0.009; DRES: 18.88 ± 17.30 mm, p < 0.03) and MSI (DSOZ: 23.37 ± 8.98 mm, p < 0.03; DRES: 15.51 ± 10.11 mm, p < 0.02) for clustering in patients with good outcome. Clustering showed shorter DSOZ and DRES compared to ECD fitting and dSPM (p < 0.05). EMSI had higher performance as outcome predictor (J = 70.63%) compared to ESI (J = 41.27%) and MSI (J = 33.33%) for clustering.

CONCLUSIONS

EMSI provides superior localization and improved predictive performance than individual modalities.

SIGNIFICANCE

EMSI can help the surgical planning and facilitate the localization of epileptogenic foci.

A multi-head self-attention deep learning approach for detection and recommendation of neuromagnetic high frequency oscillations in epilepsy

Magnetoencephalography is a noninvasive neuromagnetic technology to record epileptic activities for the pre-operative localization of epileptogenic zones, which has received increasing attention in the diagnosis and surgery of epilepsy. As reported by recent studies, pathological high frequency oscillations (HFOs), when utilized as a biomarker to localize the epileptogenic zones, result in a significant reduction in seizure frequency, even seizure elimination in around 80% of cases. Thus, objective, rapid, and automatic detection and recommendation of HFOs are highly desirable for clinicians to alleviate the burden of reviewing a large amount of MEG data from a given patient. Despite the advantage, the performance of existing HFOs rarely satisfies the clinical requirement. Consequently, no HFOs have been successfully applied to real clinical applications so far. In this work, we propose a multi-head self-attention-based detector for recommendation, termed MSADR, to detect and recommend HFO signals. Taking advantage of the state-of-the-art multi-head self-attention mechanism in deep learning, the proposed MSADR achieves a more superior accuracy of 88.6% than peer machine learning models in both detection and recommendation tasks. In addition, the robustness of MSADR is also extensively assessed with various ablation tests, results of which further demonstrate the effectiveness and generalizability of the proposed approach.

Case Report: Laser Ablation Guided by State of the Art Source Imaging Ends an Adolescent's 16-Year Quest for Seizure Freedom

Epilepsy surgery is the most effective therapeutic approach for children with drug resistant epilepsy (DRE). Recent advances in neurosurgery, such as the Laser Interstitial Thermal Therapy (LITT), improved the safety and non-invasiveness of this method. Electric and magnetic source imaging (ESI/MSI) plays critical role in the delineation of the epileptogenic focus during the presurgical evaluation of children with DRE. Yet, they are currently underutilized even in tertiary epilepsy centers. Here, we present a case of an adolescent who suffered from DRE for 16 years and underwent surgery at Cook Children's Medical Center (CCMC). The patient was previously evaluated in a level 4 epilepsy center and treated with multiple antiseizure medications for several years. Presurgical evaluation at CCMC included long-term video electroencephalography (EEG), magnetoencephalography (MEG) with simultaneous conventional EEG (19 channels) and high-density EEG (256 channels) in two consecutive sessions, MRI, and fluorodeoxyglucose - positron emission tomography (FDG-PET). Video long-term EEG captured nine focal-onset clinical seizures with a maximal evolution over the right frontal/frontal midline areas. MRI was initially interpreted as non-lesional. FDG-PET revealed a small region of hypometabolism at the anterior right superior temporal gyrus. ESI and MSI performed with dipole clustering showed a tight cluster of dipoles in the right anterior insula. The patient underwent intracranial EEG which indicated the right anterior insular as seizure onset zone. Eventually LITT rendered the patient seizure free (Engel 1; 12 months after surgery). Retrospective analysis of ESI and MSI clustered dipoles found a mean distance of dipoles from the ablated volume ranging from 10 to 25 mm. Our findings highlight the importance of recent technological advances in the presurgical evaluation and surgical treatment of children with DRE, and the underutilization of epilepsy surgery in children with DRE.

Multifrequency Dynamics of Cortical Neuromagnetic Activity Underlying Seizure Termination in Absence Epilepsy

Purpose

This study aimed to investigate the spectral and spatial signatures of neuromagnetic activity underlying the termination of absence seizures.

Methods

Magnetoencephalography (MEG) data were recorded from 18 drug-naive patients with childhood absence epilepsy (CAE). Accumulated source imaging (ASI) was used to analyze MEG data at the source level in seven frequency ranges: delta (1–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), beta (12–30 Hz), gamma (30–80 Hz), ripple (80–250 Hz), and fast ripple (250–500 Hz).

Result

In the 1–4, 4–8, and 8–12 Hz ranges, the magnetic source during seizure termination appeared to be consistent over the ictal period and was mainly localized in the frontal cortex (FC) and parieto-occipito-temporal junction (POT). In the 12–30 and 30–80 Hz ranges, a significant reduction in source activity was observed in the frontal lobe during seizure termination as well as a decrease in peak source strength. The ictal peak source strength in the 1–4 Hz range was negatively correlated with the ictal duration of the seizure, whereas in the 30–80 Hz range, it was positively correlated with the course of epilepsy.

Conclusion

The termination of absence seizures is associated with a dynamic neuromagnetic process. Frequency-dependent changes in the FC were observed during seizure termination, which may be involved in the process of neural network interaction. Neuromagnetic activity in different frequency bands may play different roles in the pathophysiological mechanism during absence seizures.

Pediatric Magnetoencephalography in Clinical Practice and Research

Magnetoencephalography (MEG) is a noninvasive neuroimaging technique that measures the electromagnetic fields generated by the human brain. This article highlights the benefits that pediatric MEG has to offer to clinical practice and pediatric research, particularly for infants and young children; reviews the existing literature on adult MEG systems for pediatric use; briefly describes the few pediatric MEG systems currently extant; and draws attention to future directions of research, with focus on the clinical use of MEG for patients with drug-resistant epilepsy.

MEEGIPS-A Modular EEG Investigation and Processing System for Visual and Automated Detection of High Frequency Oscillations

High frequency oscillations (HFOs) are electroencephalographic correlates of brain activity detectable in a frequency range above 80 Hz. They co-occur with physiological processes such as saccades, movement execution, and memory formation, but are also related to pathological processes in patients with epilepsy. Localization of the seizure onset zone, and, more specifically, of the to-be resected area in patients with refractory epilepsy seems to be supported by the detection of HFOs. The visual identification of HFOs is very time consuming with approximately 8 h for 10 min and 20 channels. Therefore, automated detection of HFOs is highly warranted. So far, no software for visual marking or automated detection of HFOs meets the needs of everyday clinical practice and research. In the context of the currently available tools and for the purpose of related local HFO study activities we aimed at converging the advantages of clinical and experimental systems by designing and developing a comprehensive and extensible software framework for HFO analysis that, on the one hand, focuses on the requirements of clinical application and, on the other hand, facilitates the integration of experimental code and algorithms. The development project included the definition of use cases, specification of requirements, software design, implementation, and integration. The work comprised the engineering of component-specific requirements, component design, as well as component- and integration-tests. A functional and tested software package is the deliverable of this activity. The project MEEGIPS, a Modular EEG Investigation and Processing System for visual and automated detection of HFOs, introduces a highly user friendly software that includes five of the most prominent automated detection algorithms. Future evaluation of these, as well as implementation of further algorithms is facilitated by the modular software architecture.

A Stacked Sparse Autoencoder-Based Detector for Automatic Identification of Neuromagnetic High Frequency Oscillations in Epilepsy

High-frequency oscillations (HFOs) are spontaneous magnetoencephalography (MEG) patterns that have been acknowledged as a putative biomarker to identify epileptic foci. Correct detection of HFOs in the MEG signals is crucial for the accurate and timely clinical evaluation. Since the visual examination of HFOs is time-consuming, error-prone, and with poor inter-reviewer reliability, an automatic HFOs detector is highly desirable in clinical practice. However, the existing approaches for HFOs detection may not be applicable for MEG signals with noisy background activity. Therefore, we employ the stacked sparse autoencoder (SSAE) and propose an SSAE-based MEG HFOs (SMO) detector to facilitate the clinical detection of HFOs. To the best of our knowledge, this is the first attempt to conduct HFOs detection in MEG using deep learning methods. After configuration optimization, our proposed SMO detector is outperformed other classic peer models by achieving 89.9% in accuracy, 88.2% in sensitivity, and 91.6% in specificity. Furthermore, we have tested the performance consistency of our model using various validation schemes. The distribution of performance metrics demonstrates that our model can achieve steady performance.

Ictal Source Locations and Cortico-Thalamic Connectivity in Childhood Absence Epilepsy: Associations with Treatment Response

Childhood absence epilepsy (CAE), the most common pediatric epilepsy syndrome, is usually treated with valproic acid (VPA) and lamotrigine (LTG) in China. This study aimed to investigate the ictal source locations and functional connectivity (FC) networks between the cortices and thalamus that are related to treatment response. Magnetoencephalography (MEG) data from 25 patients with CAE were recorded at 300 Hz and analyzed in 1-30 Hz frequency bands. Neuromagnetic sources were volumetrically scanned with accumulated source imaging. The FC networks between the cortices and thalamus were evaluated at the source level through a connectivity analysis. Treatment outcome was assessed after 36-66 months following MEG recording. The children with CAE were divided into LTG responder, LTG non-responder, VPA responder and VPA non-responder groups. The ictal source locations and cortico-thalamic FC networks were compared to the treatment response. The ictal source locations in the post-dorsal medial frontal cortex (post-DMFC, including the medial primary motor cortex and the supplementary sensorimotor area) were observed in all LTG non-responders but in all LTG responders. At 1-7 Hz, patients with fronto-thalamo-parietal/occipital (F-T-P/O) networks were older than those with fronto-thalamic (F-T) networks or other cortico-thalamic networks (p = 0.000). The duration of seizures in patients with F-T-P/O networks at 1-7 Hz was longer than that in patients with F-T networks or other cortico-thalamic networks (p = 0.001). The ictal post-DMFC source localizations suggest that children with CAE might experience initial LTG monotherapy failure. Moreover, the cortico-thalamo-cortical network is associated with age. Finally, the cortico-thalamo-cortical network consists of anterior and posterior cortices and might contribute to the maintenance of discharges.

Surgical resection of ripple onset predicts outcome in pediatric epilepsy

OBJECTIVE

In patients with medically refractory epilepsy (MRE), interictal ripples (80-250Hz) are observed in large brain areas whose resection may be unnecessary for seizure freedom. This limits their utility as epilepsy biomarkers for surgery. We assessed the spatiotemporal propagation of interictal ripples on intracranial electroencephalography (iEEG) in children with MRE, compared it with the propagation of spikes, identified ripples that initiated propagation (onset-ripples), and evaluated their clinical value as epilepsy biomarkers.

METHODS

Twenty-seven children who underwent epilepsy surgery were studied. We identified propagation sequences of ripples and spikes across multiple iEEG contacts and calculated each ripple or spike latency from the propagation onset. We classified ripples and spikes into categories (ie, onset, spread, and isolated) based on their spatiotemporal characteristics and correlated their mean rate inside and outside resection with outcome (good outcome, Engel 1 versus poor outcome, Engel≥2). We determined, as onset-zone, spread-zone, and isolated-zone, the areas generating the corresponding ripple or spike category and evaluated the predictive value of their resection.

RESULTS

We observed ripple propagation in all patients and spike propagation in 25 patients. Mean rate of onset-ripples inside resection predicted the outcome (odds ratio = 5.37; p = 0.02) and correlated with Engel class (rho = -0.55; p = 0.003). Resection of the onset-ripple-zone was associated with good outcome (p = 0.047). No association was found for the spread-ripple-zone, isolated-ripple-zone, or any spike-zone.

INTERPRETATION

Interictal ripples propagate across iEEG contacts in children with MRE. The association between the onset-ripple-zone resection and good outcome indicates that onset-ripples are promising epilepsy biomarkers, which estimate the epileptogenic tissue better than spread-ripples or onset-spikes. Ann Neurol 2018;84:331-346.

Magnetoencephalography: Clinical and Research Practices

Magnetoencephalography (MEG) is a neurophysiological technique that detects the magnetic fields associated with brain activity. Synthetic aperture magnetometry (SAM), a MEG magnetic source imaging technique, can be used to construct both detailed maps of global brain activity as well as virtual electrode signals, which provide information that is similar to invasive electrode recordings. This innovative approach has demonstrated utility in both clinical and research settings. For individuals with epilepsy, MEG provides valuable, nonredundant information. MEG accurately localizes the irritative zone associated with interictal spikes, often detecting epileptiform activity other methods cannot, and may give localizing information when other methods fail. These capabilities potentially greatly increase the population eligible for epilepsy surgery and improve planning for those undergoing surgery. MEG methods can be readily adapted to research settings, allowing noninvasive assessment of whole brain neurophysiological activity, with a theoretical spatial range down to submillimeter voxels, and in both humans and nonhuman primates. The combination of clinical and research activities with MEG offers a unique opportunity to advance translational research from bench to bedside and back.

Mapping the Spatiotemporal Evolution of Emotional Processing: An MEG Study Across Arousal and Valence Dimensions

Electrophysiological and functional neuroimaging findings indicate that the neural mechanisms underlying the processing of emotional dimensions (i.e., valence, arousal) constitute a spatially and temporally distributed emotional network, modulated by the arousal and/or valence of the emotional stimuli. We examined the time course and source distribution of gamma time-locked magnetoencephalographic activity in response to a series of emotional stimuli viewed by healthy adults. We used a beamformer and a sliding window analysis to generate a succession of spatial maps of event-related brain responses across distinct levels of valence (pleasant/unpleasant) and arousal (high/low) in 30–100 Hz. Our results show parallel emotion-related responses along specific temporal windows involving mainly dissociable neural pathways for valence and arousal during emotional picture processing. Pleasant valence was localized in the left inferior frontal gyrus, while unpleasant valence in the right occipital gyrus, the precuneus, and the left caudate nucleus. High arousal was processed by the left orbitofrontal cortex, amygdala, and inferior frontal gyrus, as well as the right middle temporal gyrus, inferior parietal lobule, and occipital gyrus. Pleasant by high arousal interaction was localized in the left inferior and superior frontal gyrus, as well as the right caudate nucleus, putamen, and gyrus rectus. Unpleasant by high arousal interaction was processed by the right superior parietal gyrus. Valence was prioritized (onset at ∼60 ms) to all other effects, while pleasant valence was short lived in comparison to unpleasant valence (offsets at ∼110 and ∼320 ms, respectively). Both arousal and valence × arousal interactions emerged relatively early (onset at ∼150 ms, and ∼170 ms, respectively). Our findings support the notion that brain regions differentiate between valence and arousal, and demonstrate, for the first time, that these brain regions may also respond to distinct combinations of these two dimensions within specific time windows.

Automated detection of epileptic ripples in MEG using beamformer-based virtual sensors

OBJECTIVE

In epilepsy, high-frequency oscillations (HFOs) are expressively linked to the seizure onset zone (SOZ). The detection of HFOs in the noninvasive signals from scalp electroencephalography (EEG) and magnetoencephalography (MEG) is still a challenging task. The aim of this study was to automate the detection of ripples in MEG signals by reducing the high-frequency noise using beamformer-based virtual sensors (VSs) and applying an automatic procedure for exploring the time-frequency content of the detected events.

APPROACH

Two-hundred seconds of MEG signal and simultaneous iEEG were selected from nine patients with refractory epilepsy. A two-stage algorithm was implemented. Firstly, beamforming was applied to the whole head to delimitate the region of interest (ROI) within a coarse grid of MEG-VS. Secondly, a beamformer using a finer grid in the ROI was computed. The automatic detection of ripples was performed using the time-frequency response provided by the Stockwell transform. Performance was evaluated through comparisons with simultaneous iEEG signals.

MAIN RESULTS

ROIs were located within the seizure-generating lobes in the nine subjects. Precision and sensitivity values were 79.18% and 68.88%, respectively, by considering iEEG-detected events as benchmarks. A higher number of ripples were detected inside the ROI compared to the same region in the contralateral lobe.

SIGNIFICANCE

The evaluation of interictal ripples using non-invasive techniques can help in the delimitation of the epileptogenic zone and guide placement of intracranial electrodes. This is the first study that automatically detects ripples in MEG in the time domain located within the clinically expected epileptic area taking into account the time-frequency characteristics of the events through the whole signal spectrum. The algorithm was tested against intracranial recordings, the current gold standard. Further studies should explore this approach to enable the localization of noninvasively recorded HFOs to help during pre-surgical planning and to reduce the need for invasive diagnostics.

Neonatal brain resting-state functional connectivity imaging modalities

Infancy is the most critical period in human brain development. Studies demonstrate that subtle brain abnormalities during this state of life may greatly affect the developmental processes of the newborn infants. One of the rapidly developing methods for early characterization of abnormal brain development is functional connectivity of the brain at rest. While the majority of resting-state studies have been conducted using magnetic resonance imaging (MRI), there is clear evidence that resting-state functional connectivity (rs-FC) can also be evaluated using other imaging modalities. The aim of this review is to compare the advantages and limitations of different modalities used for the mapping of infants' brain functional connectivity at rest. In addition, we introduce photoacoustic tomography, a novel functional neuroimaging modality, as a complementary modality for functional mapping of infants' brain.

Reorganization of the somatosensory cortex in hemiplegic cerebral palsy associated with impaired sensory tracts

Functional neuroimaging studies argue that sensory deficits in hemiplegic cerebral palsy (HCP) are related to deviant somatosensory processing in the ipsilesional primary somatosensory cortex (S1). A separate body of structural neuroimaging literature argues that these deficits are due to structural damage of the ascending sensory tracts (AST). The relationship between the functional and structural integrity of the somatosensory system and the sensory performance is largely unknown in HCP. To address this relationship, we combined findings from magnetoencephalography (MEG) and probabilistic diffusion tractography (PDT) in 10 children with HCP and 13 typically developing (TD) children. With MEG, we mapped the functionally active regions in the contralateral S1 during tactile stimulation of the thumb, middle, and little fingers of both hands. Using these MEG-defined functional active regions as regions of interest for PDT, we estimated the diffusion parameters of the AST. Somatosensory function was assessed via two-point discrimination tests. Our MEG data showed: (i) an abnormal somatotopic organization in all children with HCP in either one or both of their hemispheres; (ii) longer Euclidean distances between the digit maps in the S1 of children with HCP compared to TD children; (iii) suppressed gamma responses at early latencies for both hemispheres of children with HCP; and (iv) a positive correlation between the Euclidean distances and the sensory tests for the more affected hemisphere of children with HCP. Our MEG-guided PDT data showed: (i) higher mean and radian diffusivity of the AST in children with HCP; (ii) a positive correlation between the axial diffusivity of the AST with the sensory tests for the more affected hemisphere; and (iii) a negative correlation between the gamma power change and the AD of the AST for the MA hemisphere. Our findings associate for the first time bilateral cortical functional reorganization in the S1 of HCP children with abnormalities in the structural integrity of the AST, and correlate these abnormalities with behaviorally-assessed sensory deficits.

Using MEG to Understand the Progression of Light Sleep and the Emergence and Functional Roles of Spindles and K-Complexes

We used tomographic analysis of MEG signals to characterize regional spectral changes in the brain at sleep onset and during light sleep. We identified two key processes that may causally link to loss of consciousness during the quiet or "core" periods of NREM1. First, active inhibition in the frontal lobe leads to delta and theta spectral power increases. Second, activation suppression leads to sharp drop of spectral power in alpha and higher frequencies in posterior parietal cortex. During NREM2 core periods, the changes identified in NREM1 become more widespread, but focal increases also emerge in alpha and low sigma band power in frontal midline cortical structures, suggesting reemergence of some monitoring of internal and external environment. Just before spindles and K-complexes (KCs), the hallmarks of NREM2, we identified focal spectral power changes in pre-frontal cortex, mid cingulate, and areas involved in environmental and internal monitoring, i.e., the rostral and sub-genual anterior cingulate. During both spindles and KCs, alpha and low sigma bands increases. Spindles emerge after further active inhibition (increase in delta power) of the frontal areas responsible for environmental monitoring, while in posterior parietal cortex, power increases in low and high sigma bands. KCs are correlated with increase in alpha power in the monitoring areas. These specific regional changes suggest strong and varied vigilance changes for KCs, but vigilance suppression and sharpening of cognitive processing for spindles. This is consistent with processes designed to ensure accurate and uncorrupted memory consolidation. The changes during KCs suggest a sentinel role: evaluation of the salience of provoking events to decide whether to increase processing and possibly wake up, or to actively inhibit further processing of intruding influences. The regional spectral patterns of NREM1, NREM2, and their dynamic changes just before spindles and KCs reveal an edge effect facilitating the emergence of spindles and KCs and defining the precise loci where they might emerge. In the time domain, the spindles are seen in widespread areas of the cortex just as reported from analysis of intracranial data, consistent with the emerging consensus of a differential topography that depends on the kind of memory stored.

Quantify neuromagnetic network changes from pre-ictal to ictal activities in absence seizures

OBJECTIVE

The cortico-thalamo-cortical network plays a key role in childhood absence epilepsy (CAE). However, the exact interaction between the cortex and the thalamus remains incompletely understood. This study aimed to investigate the dynamic changes of frequency-dependent neural networks during the initialization of absence seizures.

METHODS

Magnetoencephalography data from 14 patients with CAE were recorded during and between seizures at a sampling rate of 6000Hz and analyzed in seven frequency bands. Neuromagnetic sources were volumetrically scanned with accumulated source imaging. Effective connectivity networks of the entire brain, including the cortico-thalamo-cortical network, were evaluated at the source level through Granger causality analysis.

RESULTS

The low-frequency (1-80Hz) activities showed significant frontal cortical and parieto-occipito-temporal junction source localization around seizures. The high-frequency (80-250Hz) oscillations showed predominant activities consistently localized in deep brain areas and medial frontal cortex. The increased cortico-thalamic effective connectivity was observed around seizures in both low- and high-frequency ranges. The direction was predominantly from the cortex to the thalamus at the early time, although the cortex that drove connectivity varied among subjects.

CONCLUSIONS

The cerebral cortex plays a key role in driving the cortico-thalamic connections at the early portion of the initialization of absence seizures. The oscillatory activities in the thalamus could be triggered by networks from various regions in the cortex.

SIGNIFICANCE

The dynamic changes of neural network provide evidences that absence seizures are probably resulted from cortical initialized cortico-thalamic network.

Technological advances in pediatric epilepsy surgery: implications for tuberous sclerosis complex

In selected children with tuberous sclerosis complex, epilepsy surgery leads to seizure freedom or seizure reduction. The current standard involves a multimodal pre-surgical workup followed by invasive electrocorticographic monitoring and resective surgery. Recent insights in the disorder and novel technologies are changing the approach to pediatric epilepsy surgery in tuberous sclerosis complex. New evidence suggests tubers are poorly delineated, and epileptogenic activity may originate in the perituber tissue. Novel imaging modalities relevant to surgical planning include high-resolution MRI, α-methyl-l-tryptophan or fluorodeoxyglucose PET with diffusion tensor imaging. Advanced neurophysiological techniques have improved identification of the surgical target, including magnetoencephalography, electrical source imaging of high-density electroencephalograph data, and high-frequency oscillations in electrocorticography data. Simultaneously, novel surgical tools including stereo-electroencephalography and laser-induced thermal therapy have become available for children. This article reviews the literature in the light of these rapidly changing technologies.

Automated detection of high-frequency oscillations in electrophysiological signals: Methodological advances

In recent years, new recording technologies have advanced such that oscillations of neuronal networks can be identified from simultaneous, multisite recordings at high temporal and spatial resolutions. However, because of the deluge of multichannel data generated by these experiments, achieving the full potential of parallel neuronal recordings also depends on the development of new mathematical methods capable of extracting meaningful information related to time, frequency and space. In this review, we aim to bridge this gap by focusing on the new analysis tools developed for the automated detection of high-frequency oscillations (HFOs, >40Hz) in local field potentials. For this, we provide a revision of different aspects associated with physiological and pathological HFOs as well as the several stages involved in their automatic detection including preprocessing, selection, rejection and analysis through time-frequency processes. Beyond basic research, the automatic detection of HFOs would greatly assist diagnosis of epilepsy disorders based on the recognition of these typical pathological patterns in the electroencephalogram (EEG). Also, we emphasize how these HFO detection methods can be applied and the properties that might be inferred from neuronal signals, indicating potential future directions.

Current and Emerging Potential of Magnetoencephalography in the Detection and Localization of High-Frequency Oscillations in Epilepsy

Up to one-third of patients with epilepsy are medically intractable and need resective surgery. To be successful, epilepsy surgery requires a comprehensive preoperative evaluation to define the epileptogenic zone (EZ), the brain area that should be resected to achieve seizure freedom. Due to lack of tools and methods that measure the EZ directly, this area is defined indirectly based on concordant data from a multitude of presurgical non-invasive tests and intracranial recordings. However, the results of these tests are often insufficiently concordant or inconclusive. Thus, the presurgical evaluation of surgical candidates is frequently challenging or unsuccessful. To improve the efficacy of the surgical treatment, there is an overriding need for reliable biomarkers that can delineate the EZ. High-frequency oscillations (HFOs) have emerged over the last decade as new potential biomarkers for the delineation of the EZ. Multiple studies have shown that HFOs are spatially associated with the EZ. Despite the encouraging findings, there are still significant challenges for the translation of HFOs as epileptogenic biomarkers to the clinical practice. One of the major barriers is the difficulty to detect and localize them with non-invasive techniques, such as magnetoencephalography (MEG) or scalp electroencephalography (EEG). Although most literature has studied HFOs using invasive recordings, recent studies have reported the detection and localization of HFOs using MEG or scalp EEG. MEG seems to be particularly advantageous compared to scalp EEG due to its inherent advantages of being less affected by skull conductivity and less susceptible to contamination from muscular activity. The detection and localization of HFOs with MEG would largely expand the clinical utility of these new promising biomarkers to an earlier stage in the diagnostic process and to a wider range of patients with epilepsy. Here, we conduct a thorough critical review of the recent MEG literature that investigates HFOs in patients with epilepsy, summarizing the different methodological approaches and the main findings. Our goal is to highlight the emerging potential of MEG in the non-invasive detection and localization of HFOs for the presurgical evaluation of patients with medically refractory epilepsy (MRE).

Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy

Crucial to the success of epilepsy surgery is the availability of a robust biomarker that identifies the Epileptogenic Zone (EZ). High Frequency Oscillations (HFOs) have emerged as potential presurgical biomarkers for the identification of the EZ in addition to Interictal Epileptiform Discharges (IEDs) and ictal activity. Although they are promising to localize the EZ, they are not yet suited for the diagnosis or monitoring of epilepsy in clinical practice. Primary barriers remain: the lack of a formal and global definition for HFOs; the consequent heterogeneity of methodological approaches used for their study; and the practical difficulties to detect and localize them noninvasively from scalp recordings. Here, we present a methodology for the recording, detection, and localization of interictal HFOs from pediatric patients with refractory epilepsy. We report representative data of HFOs detected noninvasively from interictal scalp EEG and MEG from two children undergoing surgery.

The underlying generators of HFOs were localized by solving the inverse problem and their localization was compared to the Seizure Onset Zone (SOZ) as this was defined by the epileptologists. For both patients, Interictal Epileptogenic Discharges (IEDs) and HFOs were localized with source imaging at concordant locations. For one patient, intracranial EEG (iEEG) data were also available. For this patient, we found that the HFOs localization was concordant between noninvasive and invasive methods. The comparison of iEEG with the results from scalp recordings served to validate these findings. To our best knowledge, this is the first study that presents the source localization of scalp HFOs from simultaneous EEG and MEG recordings comparing the results with invasive recordings. These findings suggest that HFOs can be reliably detected and localized noninvasively with scalp EEG and MEG. We conclude that the noninvasive localization of interictal HFOs could significantly improve the presurgical evaluation for pediatric patients with epilepsy.

Detection and Magnetic Source Imaging of Fast Oscillations (40-160 Hz) Recorded with Magnetoencephalography in Focal Epilepsy Patients

We present a framework to detect fast oscillations (FOs) in magnetoencephalography (MEG) and to perform magnetic source imaging (MSI) to determine the location and extent of their generators in the cortex. FOs can be of physiologic origin associated to sensory processing and memory consolidation. In epilepsy, FOs are of pathologic origin and biomarkers of the epileptogenic zone. Seventeen patients with focal epilepsy previously confirmed with identified FOs in scalp electroencephalography (EEG) were evaluated. To handle data deriving from large number of sensors (275 axial gradiometers) we used an automatic detector with high sensitivity. False positives were discarded by two human experts. MSI of the FOs was performed with the wavelet based maximum entropy on the mean method. We found FOs in 11/17 patients, in only one patient the channel with highest FO rate was not concordant with the epileptogenic region and might correspond to physiologic oscillations. MEG FOs rates were very low: 0.02–4.55 per minute. Compared to scalp EEG, detection sensitivity was lower, but the specificity higher in MEG. MSI of FOs showed concordance or partial concordance with proven generators of seizures and epileptiform activity in 10/11 patients. We have validated the proposed framework for the non-invasive study of FOs with MEG. The excellent overall concordance with other clinical gold standard evaluation tools indicates that MEG FOs can provide relevant information to guide implantation for intracranial EEG pre-surgical evaluation and for surgical treatment, and demonstrates the important added value of choosing appropriate FOs detection and source localization methods.

Mapping entrained brain oscillations during transcranial alternating current stimulation (tACS)

Transcranial alternating current stimulation (tACS), a non-invasive and well-tolerated form of electric brain stimulation, can influence perception, memory, as well as motor and cognitive function. While the exact underlying neurophysiological mechanisms are unknown, the effects of tACS are mainly attributed to frequency-specific entrainment of endogenous brain oscillations in brain areas close to the stimulation electrodes, and modulation of spike timing dependent plasticity reflected in gamma band oscillatory responses. tACS-related electromagnetic stimulator artifacts, however, impede investigation of these neurophysiological mechanisms. Here we introduce a novel approach combining amplitude-modulated tACS during whole-head magnetoencephalography (MEG) allowing for artifact-free source reconstruction and precise mapping of entrained brain oscillations underneath the stimulator electrodes. Using this approach, we show that reliable reconstruction of neuromagnetic low- and high-frequency oscillations including high gamma band activity in stimulated cortical areas is feasible opening a new window to unveil the mechanisms underlying the effects of stimulation protocols that entrain brain oscillatory activity.

Atypical spatiotemporal signatures of working memory brain processes in autism

Working memory (WM) impairments may contribute to the profound behavioural manifestations in children with autism spectrum disorder (ASD). However, previous behavioural results are discrepant as are the few functional magnetic resonance imaging (fMRI) results collected in adults and adolescents with ASD. Here we investigate the precise temporal dynamics of WM-related brain activity using magnetoencephalography (MEG) in 20 children with ASD and matched controls during an n-back WM task across different load levels (1-back vs 2-back). Although behavioural results were similar between ASD and typically developing (TD) children, the between-group comparison performed on functional brain activity showed atypical WM-related brain processes in children with ASD compared with TD children. These atypical responses were observed in the ASD group from 200 to 600 ms post stimulus in both the low- (1-back) and high- (2-back) memory load conditions. During the 1-back condition, children with ASD showed reduced WM-related activations in the right hippocampus and the cingulate gyrus compared with TD children who showed more activation in the left dorso-lateral prefrontal cortex and the insulae. In the 2-back condition, children with ASD showed less activity in the left insula and midcingulate gyrus and more activity in the left precuneus than TD children. In addition, reduced activity in the anterior cingulate cortex was correlated with symptom severity in children with ASD. Thus, this MEG study identified the precise timing and sources of atypical WM-related activity in frontal, temporal and parietal regions in children with ASD. The potential impacts of such atypicalities on social deficits of autism are discussed.

Group differences in MEG-ICA derived resting state networks: Application to major depressive disorder

Functional magnetic resonance imaging (fMRI) studies have revealed the existence of robust, interconnected brain networks exhibiting correlated low frequency fluctuations during rest, which can be derived by examining inherent spatio-temporal patterns in functional scans independent of any a priori model. In order to explore the electrophysiological underpinnings of these networks, analogous techniques have recently been applied to magnetoencephalography (MEG) data, revealing similar networks that exhibit correlated low frequency fluctuations in the power envelope of beta band (14-30Hz) power. However, studies to date using this technique have concentrated on healthy subjects, and no method has yet been presented for group comparisons. We extended the ICA resting state MEG method to enable group comparisons, and demonstrate the technique in a sample of subjects with major depressive disorder (MDD). We found that the intrinsic resting state networks evident in fMRI appeared to be disrupted in individuals with MDD compared to healthy participants, particularly in the subgenual cingulate, although the electrophysiological correlates of this are unknown. Networks extracted from a combined group of healthy and MDD participants were examined for differences between groups. Individuals with MDD showed reduced correlations between the subgenual anterior cingulate (sgACC) and hippocampus in a network with primary nodes in the precentral and middle frontal gyri. Individuals with MDD also showed increased correlations between insulo-temporal nodes and amygdala compared to healthy controls. To further support our methods and findings, we present test/re-test reliability on independent recordings acquired within the same session. Our results demonstrate that group analyses are possible with the resting state MEG-independent component analysis (ICA) technique, highlighting a new pathway for analysis and discovery. This study also provides the first evidence of altered sgACC connectivity with a motor network. This finding, reliable across multiple sessions, suggests that the sgACC may partially mediate the psychomotor symptoms of MDD via synchronized changes in beta-band power, and expands the idea of the sgACC as a hub region mediating cognitive and emotional symptomatic domains in MDD. Findings of increased connectivity between the amygdala and cortical nodes further support the role of amygdalar networks in mediated depressive symptomatology.

CLINICAL TRIALS IDENTIFIER

NCT00024635 (ZIA-MH002927-04).

Cortical somatosensory reorganization in children with spastic cerebral palsy: a multimodal neuroimaging study

Although cerebral palsy (CP) is among the most common causes of physical disability in early childhood, we know little about the functional and structural changes of this disorder in the developing brain. Here, we investigated with three different neuroimaging modalities [magnetoencephalography (MEG), diffusion tensor imaging (DTI), and resting-state fMRI] whether spastic CP is associated with functional and anatomical abnormalities in the sensorimotor network. Ten children participated in the study: four with diplegic CP (DCP), three with hemiplegic CP (HCP), and three typically developing (TD) children. Somatosensory (SS)-evoked fields (SEFs) were recorded in response to pneumatic stimuli applied to digits D1, D3, and D5 of both hands. Several parameters of water diffusion were calculated from DTI between the thalamus and the pre-central and post-central gyri in both hemispheres. The sensorimotor resting-state networks (RSNs) were examined by using an independent component analysis method. Tactile stimulation of the fingers elicited the first prominent cortical response at ~50 ms, in all except one child, localized over the primary SS cortex (S1). In five CP children, abnormal somatotopic organization was observed in the affected (or more affected) hemisphere. Euclidean distances were markedly different between the two hemispheres in the HCP children, and between DCP and TD children for both hemispheres. DTI analysis revealed decreased fractional anisotropy and increased apparent diffusion coefficient for the thalamocortical pathways in the more affected compared to less affected hemisphere in CP children. Resting-state functional MRI results indicated absent and/or abnormal sensorimotor RSNs for children with HCP and DCP consistent with the severity and location of their lesions. Our findings suggest an abnormal SS processing mechanism in the sensorimotor network of children with CP possibly as a result of diminished thalamocortical projections.

Encoding cortical dynamics in sparse features

Distributed cortical solutions of magnetoencephalography (MEG) and electroencephalography (EEG) exhibit complex spatial and temporal dynamics. The extraction of patterns of interest and dynamic features from these cortical signals has so far relied on the expertise of investigators. There is a definite need in both clinical and neuroscience research for a method that will extract critical features from high-dimensional neuroimaging data in an automatic fashion. We have previously demonstrated the use of optical flow techniques for evaluating the kinematic properties of motion field projected on non-flat manifolds like in a cortical surface. We have further extended this framework to automatically detect features in the optical flow vector field by using the modified and extended 2-Riemannian Helmholtz–Hodge decomposition (HHD). Here, we applied these mathematical models on simulation and MEG data recorded from a healthy individual during a somatosensory experiment and an epilepsy pediatric patient during sleep. We tested whether our technique can automatically extract salient dynamical features of cortical activity. Simulation results indicated that we can precisely reproduce the simulated cortical dynamics with HHD; encode them in sparse features and represent the propagation of brain activity between distinct cortical areas. Using HHD, we decoded the somatosensory N20 component into two HHD features and represented the dynamics of brain activity as a traveling source between two primary somatosensory regions. In the epilepsy patient, we displayed the propagation of the epileptic activity around the margins of a brain lesion. Our findings indicate that HHD measures computed from cortical dynamics can: (i) quantitatively access the cortical dynamics in both healthy and disease brain in terms of sparse features and dynamic brain activity propagation between distinct cortical areas, and (ii) facilitate a reproducible, automated analysis of experimental and clinical MEG/EEG source imaging data.

Accumulated source imaging of brain activity with both low and high-frequency neuromagnetic signals

Recent studies have revealed the importance of high-frequency brain signals (>70 Hz). One challenge of high-frequency signal analysis is that the size of time-frequency representation of high-frequency brain signals could be larger than 1 terabytes (TB), which is beyond the upper limits of a typical computer workstation's memory (<196 GB). The aim of the present study is to develop a new method to provide greater sensitivity in detecting high-frequency magnetoencephalography (MEG) signals in a single automated and versatile interface, rather than the more traditional, time-intensive visual inspection methods, which may take up to several days. To address the aim, we developed a new method, accumulated source imaging, defined as the volumetric summation of source activity over a period of time. This method analyzes signals in both low- (1~70 Hz) and high-frequency (70~200 Hz) ranges at source levels. To extract meaningful information from MEG signals at sensor space, the signals were decomposed to channel-cross-channel matrix (CxC) representing the spatiotemporal patterns of every possible sensor-pair. A new algorithm was developed and tested by calculating the optimal CxC and source location-orientation weights for volumetric source imaging, thereby minimizing multi-source interference and reducing computational cost. The new method was implemented in C/C++ and tested with MEG data recorded from clinical epilepsy patients. The results of experimental data demonstrated that accumulated source imaging could effectively summarize and visualize MEG recordings within 12.7 h by using approximately 10 GB of computer memory. In contrast to the conventional method of visually identifying multi-frequency epileptic activities that traditionally took 2–3 days and used 1–2 TB storage, the new approach can quantify epileptic abnormalities in both low- and high-frequency ranges at source levels, using much less time and computer memory.

Localization of the epileptogenic foci in tuberous sclerosis complex: a pediatric case report

Tuberous sclerosis complex (TSC) is a rare disorder of tissue growth and differentiation, characterized by benign hamartomas in the brain and other organs. Up to 90% of TSC patients develop epilepsy and 50% become medically intractable requiring resective surgery. The surgical outcome of TSC patients depends on the accurate identification of the epileptogenic zone consisting of tubers and the surrounding epileptogenic tissue. There is conflicting evidence whether the epileptogenic zone is in the tuber itself or in abnormally developed surrounding cortex. Here, we report the localization of the epileptiform activity among the many cortical tubers in a 4-year-old patient with TSC-related refractory epilepsy undergoing magnetoencephalography (MEG), electroencephalography (EEG), and diffusion tensor imaging (DTI). For MEG, we used a prototype system that offers higher spatial resolution and sensitivity compared to the conventional adult systems. The generators of interictal activity were localized using both EEG and MEG with equivalent current dipole (ECD) and minimum norm estimation (MNE) methods according to the current clinical standards. For DTI, we calculated four diffusion scalar parameters for the fibers passing through four ROIs defined: (i) at a large cortical tuber identified at the right quadrant, (ii) at the normal appearing tissue contralateral to the tuber, (iii) at the cluster formed by ECDs fitted at the peak of interictal spikes, and (iv) at the normal appearing tissue contralateral to the cluster. ECDs were consistently clustered at the vicinity of the large calcified cortical tuber. MNE and ECDs indicated epileptiform activity in the same areas. DTI analysis showed differences between the scalar values of the tracks passing through the tuber and the ECD cluster. In this illustrative case, we provide evidence from different neuroimaging modalities, which support the view that epileptiform activity may derive from abnormally developed tissue surrounding the tuber rather than the tuber itself.

Distinguishable neural correlates of verbs and nouns: a MEG study on homonyms

The dissociability of nouns and verbs and of their morphosyntactic operations has been firmly established by lesion data. However, the hypothesis that they are processed by distinct neural substrates is inconsistently supported by neuroimaging studies. We tackled this issue in a silent reading experiment during MEG. Participants silently read noun/verb homonyms in minimal syntactic context: article-noun (NPs), pronoun-verb (VPs) (e.g., il ballo/i balli, the dance/the dances; io ballo/tu balli, I dance/you dance). Homonyms allow to rule out prelexical or postlexical nuisance factors-they are orthographically and phonologically identical, but serve different grammatical functions depending on context. Under these experimental conditions, different activity to nouns and verbs can be confidently attributed to representational/processing distinctions. At the sensor level, three components of event-related magnetic fields were observed for the function word and four for the content word, but Global Field Power (GFP) analysis only showed differences between VPs and NPs at several but very short time windows. By contrast, source level analysis based on Minimum Norm Estimates (MNE) yielded significantly greater activity for VPs in left frontal areas and in a left frontoparietal network at late time windows (380-397 and 393-409 ms). These results are fully consistent with lesion data, and show that verbs and nouns are processed differently in the brain. Frontal and parietal activation to verbs might correspond to morphosyntactic processes and to working memory recruitment (or thematic role assignment), respectively. Findings are consistent with the view that nouns and verbs and their morphosyntactic operations involve at least partially distinct neural substrates. However, they do not entirely rule out that nouns and verbs are processed in a shared neural substrate, and that differences result from greater complexity of verbal morphosyntax.

Neuromagnetic abnormality of motor cortical activation and phases of headache attacks in childhood migraine

The cerebral cortex serves a primary role in the pathogenesis of migraine. This aberrant brain activation in migraine can be noninvasively detected with magnetoencephalography (MEG). The objective of this study was to investigate the differences in motor cortical activation between attacks (ictal) and pain free intervals (interictal) in children and adolescents with migraine using both low- and high-frequency neuromagnetic signals. Thirty subjects with an acute migraine and 30 subjects with a history of migraine, while pain free, were compared to age- and gender-matched controls using MEG. Motor cortical activation was elicited by a standardized, validated finger-tapping task. Low-frequency brain activation (1∼50 Hz) was analyzed with waveform measurements and high-frequency oscillations (65–150 Hz) were analyzed with wavelet-based beamforming. MEG waveforms showed that the ictal latency of low-frequency brain activation was significantly delayed as compared with controls, while the interictal latency of brain activation was similar to that of controls. The ictal amplitude of low-frequency brain activation was significantly increased as compared with controls, while the interictal amplitude of brain activation was similar to that of controls. The ictal source power of high-frequency oscillations was significantly stronger than that of the controls, while the interictal source power of high-frequency oscillations was significantly weaker than that of controls. The results suggest that aberrant low-frequency brain activation in migraine during a headache attack returned to normal interictally. However, high-frequency oscillations changed from ictal hyper-activation to interictal hypo-activation. Noninvasive assessment of cortical abnormality in migraine with MEG opens a new window for developing novel therapeutic strategies for childhood migraine by maintaining a balanced cortical excitability.

MEG reveals a fast pathway from somatosensory cortex to occipital areas via posterior parietal cortex in a blind subject

Cross-modal activity in visual cortex of blind subjects has been reported during performance of variety of non-visual tasks. A key unanswered question is through which pathways non-visual inputs are funneled to the visual cortex. Here we used tomographic analysis of single trial magnetoencephalography (MEG) data recorded from one congenitally blind and two sighted subjects after stimulation of the left and right median nerves at three intensities: below sensory threshold, above sensory threshold and above motor threshold; the last sufficient to produce thumb twitching. We identified reproducible brain responses in the primary somatosensory (S1) and motor (M1) cortices at around 20 ms post-stimulus, which were very similar in sighted and blind subjects. Time-frequency analysis revealed strong 45-70 Hz activity at latencies of 20-50 ms in S1 and M1, and posterior parietal cortex Brodmann areas (BA) 7 and 40, which compared to lower frequencies, were substantially more pronounced in the blind than the sighted subjects. Critically, at frequencies from α-band up to 100 Hz we found clear, strong, and widespread responses in the visual cortex of the blind subject, which increased with the intensity of the somatosensory stimuli. Time-delayed mutual information (MI) revealed that in blind subject the stimulus information is funneled from the early somatosensory to visual cortex through posterior parietal BA 7 and 40, projecting first to visual areas V5 and V3, and eventually V1. The flow of information through this pathway occurred in stages characterized by convergence of activations into specific cortical regions. In sighted subjects, no linked activity was found that led from the somatosensory to the visual cortex through any of the studied brain regions. These results provide the first evidence from MEG that in blind subjects, tactile information is routed from primary somatosensory to occipital cortex via the posterior parietal cortex.

Rapid and multiple-stage activation of the human amygdala for processing facial signals

Human faces transmit multiple valuable signals, and neuroimaging studies have shown that the amygdala is active in response to facial stimuli. However, little has been known about the temporal profile of amygdala activation during facial signal processing until recently. Here we review three recent studies conducted by our group in which we recorded amygdala intracranial electroencephalography in humans. The subjects were engaged in tasks that required automatic processing of faces, eye gazes and emotional expressions. Time-frequency statistical parametric mapping analyses revealed that the amygdala showed gamma-band activation in response to emotional expressions, gazes and faces, with peak latencies at about 100 ms, 200 ms and 250 ms, respectively. These results suggest that: (1) the amygdala performs multiple-stage processing in response to these facial signals using different visual input routes, and (2) amygdala activation for processing all of these facial signals is rapid, which could be prior to or simultaneous with conscious awareness of faces.

Alcohol affects the brain's resting-state network in social drinkers

Acute alcohol intake is known to enhance inhibition through facilitation of GABA(A) receptors, which are present in 40% of the synapses all over the brain. Evidence suggests that enhanced GABAergic transmission leads to increased large-scale brain connectivity. Our hypothesis is that acute alcohol intake would increase the functional connectivity of the human brain resting-state network (RSN). To test our hypothesis, electroencephalographic (EEG) measurements were recorded from healthy social drinkers at rest, during eyes-open and eyes-closed sessions, after administering to them an alcoholic beverage or placebo respectively. Salivary alcohol and cortisol served to measure the inebriation and stress levels. By calculating Magnitude Square Coherence (MSC) on standardized Low Resolution Electromagnetic Tomography (sLORETA) solutions, we formed cortical networks over several frequency bands, which were then analyzed in the context of functional connectivity and graph theory. MSC was increased (p<0.05, corrected with False Discovery Rate, FDR corrected) in alpha, beta (eyes-open) and theta bands (eyes-closed) following acute alcohol intake. Graph parameters were accordingly altered in these bands quantifying the effect of alcohol on the structure of brain networks; global efficiency and density were higher and path length was lower during alcohol (vs. placebo, p<0.05). Salivary alcohol concentration was positively correlated with the density of the network in beta band. The degree of specific nodes was elevated following alcohol (vs. placebo). Our findings support the hypothesis that short-term inebriation considerably increases large-scale connectivity in the RSN. The increased baseline functional connectivity can -at least partially- be attributed to the alcohol-induced disruption of the delicate balance between inhibitory and excitatory neurotransmission in favor of inhibitory influences. Thus, it is suggested that short-term inebriation is associated, as expected, to increased GABA transmission and functional connectivity, while long-term alcohol consumption may be linked to exactly the opposite effect.

Magnetoencephalography evidence for different brain subregions serving two musical cultures

Individuals who have been exposed to two different musical cultures (bimusicals) can be differentiated from those exposed to only one musical culture (monomusicals). Just as bilingual speakers handle the distinct language-syntactic rules of each of two languages, bimusical listeners handle two distinct musical-syntactic rules (e.g., tonal schemas) in each musical culture. This study sought to determine specific brain activities that contribute to differentiating two culture-specific tonal structures. We recorded magnetoencephalogram (MEG) responses of bimusical Japanese nonmusicians and amateur musicians as they monitored unfamiliar Western melodies and unfamiliar, but traditional, Japanese melodies, both of which contained tonal deviants (out-of-key tones). Previous studies with Western monomusicals have shown that tonal deviants elicit an early right anterior negativity (mERAN) originating in the inferior frontal cortex. In the present study, tonal deviants in both Western and Japanese melodies elicited mERANs with characteristics fitted by dipoles around the inferior frontal gyrus in the right hemisphere and the premotor cortex in the left hemisphere. Comparisons of the nature of mERAN activity to Western and Japanese melodies showed differences in the dipoles' locations but not in their peak latency or dipole strength. These results suggest that the differentiation between a tonal structure of one culture and that of another culture correlates with localization differences in brain subregions around the inferior frontal cortex and the premotor cortex.

An MEG compatible system for measuring skin conductance responses

We present the design of a low-cost system for recording galvanic skin conductance responses (SCRs) from humans in a magnetically shielded room (MSR) simultaneously to magnetoencephalography (MEG). Such a system was so far not available to the MEG community. Its availability is of utmost importance for neuroscience, since it will allow the concurrent assessment of the autonomic and central nervous system activity. The overall system design optimizes high signal to noise ratio (SNR) of SCRs and achieves minimal distortion of the MEG signal. Its development was based on a fiber-optic transformer, with voltage to optical transduction inside the MSR and demodulation outside the MSR. The system was calibrated and tested inside the MEG environment by using a 151-channel CTF whole head system (VSM MedTech Ltd.). MEG measurements were recorded simultaneously to SCRs from five healthy participants to test whether the developed system does not generate artifacts in the MEG data. Two measurements were performed for each participant; one without the system in the MSR, and one with the system in the MSR, connected to the participant and in operation. The data were analyzed using the time and frequency domains in separate statistical analysis. No significant differences were observed between the two sessions for any statistic index. Our results show that the system allows high quality simultaneous recordings of SCRs and MEG signals in the MSR, and can therefore be used as routine addendum to neuroscience experiments.

Impaired gamma-band activity during perceptual organization in adults with autism spectrum disorders: evidence for dysfunctional network activity in frontal-posterior cortices

Current theories of the pathophysiology of autism spectrum disorders (ASD) have focused on abnormal temporal coordination of neural activity in cortical circuits as a core impairment of the disorder. In the current study, we examined the possibility that gamma-band activity may be crucially involved in aberrant brain functioning in ASD. Magneto-encephalographic (MEG) data were recorded from 13 adult human participants with ASD and 16 controls during the presentation of Mooney faces. MEG data were analyzed in the 25-150 Hz frequency range and a beamforming approach was used to identify the sources of spectral power. Participants with ASD showed elevated reaction times and reduced detection rates during the perception of upright Mooney faces, while responses to inverted stimuli were in the normal range. Impaired perceptual organization in the ASD group was accompanied by a reduction in both the amplitude and phase locking of gamma-band activity. A beamforming approach identified distinct networks during perceptual organization in controls and participants with ASD. In controls, perceptual organization of Mooney faces involved increased 60-120 Hz activity in a frontoparietal network, while in the ASD group stronger activation was found in visual regions. These findings highlight the contribution of impaired gamma-band activity toward complex visual processing in ASD, suggesting atypical modulation of high-frequency power in frontoposterior networks.

Spatiotemporal profiles of visual processing with and without primary visual cortex

The spatiotemporal profiles of visual processing are normally distributed in two temporal phases, each lasting about 100 ms. Within each phase, cortical processing begins in V1 and traverses the visual cortical hierarchy. However, the causal role of V1 in starting each of these two phases is unknown. Here we used magnetoencephalography to study the spatiotemporal profiles of visual processing and the causal contribution of V1 in three neurologically intact participants and in a rare patient (GY) with unilateral destruction of V1, in whom residual visual functions mediated by the extra-geniculostriate pathways have been reported. In healthy subjects, visual processing in the first 200 ms post-stimulus onset proceeded in the two usual phases. Normally perceived stimuli in the left hemifield of GY elicited a spatiotemporal profile in the intact right hemisphere that closely matched that of healthy subjects. However, stimuli presented in the cortically blind hemifield produced no detectable response during the first phase of processing, indicating that the responses in extrastriate visual areas during this phase are determined by the feedforward progression of activity initiated in V1. The first responses occurred during the second processing phase, in the ipsilesional high-level visual areas. The activity then spread forward toward higher-level areas and backward toward lower-level areas. However, in contrast to responses in the intact hemisphere, the back-propagated activity in the early visual cortex did not exhibit the classic retinotopic organization and did not have well-defined response peaks.

Source activity correlation effects on LCMV beamformers in a realistic measurement environment

In EEG and MEG studies on brain functional connectivity and source interactions can be performed at sensor or source level. Beamformers are well-established source-localization tools for MEG/EEG signals, being employed in source connectivity studies both in time and frequency domain. However, it has been demonstrated that beamformers suffer from a localization bias due to correlation between source time courses. This phenomenon has been ascertained by means of theoretical proofs and simulations. Nonetheless, the impact of correlated sources on localization outputs with real data has been disputed for a long time. In this paper, by means of a phantom, we address the correlation issue in a realistic MEG environment. Localization performances in the presence of simultaneously active sources are studied as a function of correlation degree and distance between sources. A linear constrained minimum variance (LCMV) beamformer is applied to the oscillating signals generated by the current dipoles within the phantom. Results show that high correlation affects mostly dipoles placed at small distances (1, 5 centimeters). In this case the sources merge. If the dipoles lie 3 centimeters apart, the beamformer localization detects attenuated power amplitudes and blurred sources as the correlation level raises.

Can magnetoencephalography track the afferent information flow along white matter thalamo-cortical fibers?

White matter thalamo-cortical fibers allow the communication of distant brain regions by carrying neuronal signals. Mapping non-invasively the information flow within white matter fibers is regarded so far as impossible. We investigated here whether information flow propagating along thalamo-cortical fibers can be detected using magnetoencephalography (MEG). Somatosensory evoked fields (SEFs) were recorded from healthy subjects and a patient with a unilateral, prenatally acquired, white matter lesion, which had induced the development of an abnormal trajectory of thalamo-cortical fibers. Equivalent current dipole (ECD) was used to model sources of SEFs. ECD at ~15 ms after stimulus onset was located within or close to the contralateral thalamus at the proximity of a hemodynamic response detected during a similar fMRI experiment. At the M20 peak latency, ECD was localized within the hand area of the contralateral primary somatosensory cortex (Brodmann area 3b (BA3b)). In healthy subjects, ECD changed dynamically position from thalamus to BA3b following a curved path, which was partially overlapping the thalamo-cortical fibers reconstructed by tractography. In the patient, ECD followed a similar path only in the intact hemisphere. In the affected hemisphere, the dipole trajectory circumnavigated the extended lesion on its way to the preserved primary somatosensory cortex--similar to the trajectory findings. Evidence from different methodological approaches converges on the conclusion that MEG can track the afferent information flow along thalamo-cortical fibers and in contrast to the traditional view can localize under presuppositions deep thalamic sources.

Temporal profile of amygdala γ oscillations in response to faces

Neuroimaging studies have reported greater activation of the human amygdala in response to faces than to nonfacial stimuli, yet little is known about the temporal profile of this activation. We investigated this issue by recording the intracranial field potentials of the amygdala in participants undergoing preneurosurgical assessment (n = 6). Participants observed faces, mosaics, and houses in upright and inverted orientations using a dummy target detection task. Time-frequency statistical parametric mapping analyses revealed that the amygdala showed greater gamma-band activity in response to faces than to mosaics at 200-300 msec, with a peak at 255 msec. Gamma-band activation with a similar temporal profile was also found in response to faces versus houses. Activation patterns did not differ between upright and inverted presentations of stimuli. These results suggest that the human amygdala is involved in the early stages of face processing, including the modulation of subjective perception of faces.

Rapid amygdala gamma oscillations in response to fearful facial expressions

Neuroimaging studies have reported greater activation of the human amygdala in response to emotional facial expressions, especially for fear. However, little is known about how fast this activation occurs. We investigated this issue by recording the intracranial field potentials of the amygdala in subjects undergoing pre-neurosurgical assessment (n=6). The subjects observed fearful, happy, and neutral facial expressions. Time-frequency statistical parametric mapping analyses revealed that the amygdala showed greater gamma-band activity in response to fearful compared with neutral facial expressions at 50-150 ms, with a peak at 135 ms. These results indicate that the human amygdala is able to rapidly process fearful facial expressions.