Volumetric imaging of brain activity with spatial-frequency decoding of neuromagnetic signals

MiR-23b-3p Improves Brain Damage after Status Epilepticus by Reducing the Formation of Pathological High-Frequency Oscillations via Inhibition of cx43 in Rat Hippocampus

In order to investigate the effectiveness and safety of miR-23b-3p in anti-seizure activity and to elucidate the regulatory relationship between miR-23b-3p and Cx43 in the nervous system, we have established a lithium chloride-pilocarpine (PILO) status epilepticus (SE) model. Rats were randomly divided into the following groups: seizure control (PILO), valproate sodium (VPA+PILO), recombinant miR-23b-3p overexpression (miR+PILO), miR-23b-3p sponges (Sponges+PILO), and scramble sequence negative control (Scramble+PILO) (n = 6/group). After experiments, we got the following results. In the acute phase, the time required for rats to reach stage IV after PILO injection was significantly longer in VPA+PILO and miR+PILO. In the chronic phase after SE, the frequency of spontaneous recurrent seizures (SRSs) in VPA+PILO and miR+PILO was significantly reduced. At 10 min before seizure cessation, the average energy expression of fast ripples (FRs) in VPA+PILO and miR+PILO was significantly lower than in PILO. After 28 days of seizure, Cx43 expression in PILO was significantly increased, and Beclin1expression in all groups was significantly increased. After 28 days of SE,the number of synapses in the CA1 region of the hippocampus was significantly higher in the VPA+PILO and miR+PILO groups compared to that in the PILO group. After 28 days of SE ,hippocampal necrotic cells in the CA3 region were significantly lower in the VPA+PILO and miR+PILO groups compared to those in the PILO group. There were no significant differences in biochemical indicators among the experimental group rats 28 days after SE compared to the seizure control group. Based on the previous facts, we can reach the conclusion that MiR-23b-3p targets and blocks the expression of hippocampal Cx43 which can reduce the formation of pathological FRs, thereby alleviating the severity of seizures, improving seizure-induced brain damage.

The prospective study of 54 children with electrical status epilepticus during sleep: How to simplify the electroencephalogram diagnosis and guide the treatment

OBJECTIVE

To simplify the electroencephalogram (EEG) diagnosis and guide the treatment of electrical status epilepticus during sleep (ESES).

METHODS

We recruited 54 children with ESES from December 2019 to December 2020 and compared various spike-wave index (SWI) calculation methods. Time-frequency analysis assessed the correlation between high-frequency oscillations energy and the SWI. We divided 42 children into responder and non-responder treatment groups based on the observations made during a 12-month follow-up period and evaluate different treatment and the independent risk factors of refractory ESES.

RESULTS

The SWI of 5 min before the second sleep cycle of non-rapid eye movement (NREM; long method II) and that of all NREM sleep (total method) were not significantly different (p = .06). The average energy of γ (r = .288, p = .002) and ripple (r = .203, p = .04) oscillations were correlated with the SWI. Multivariable logistic regression analysis showed that encephalomalacia was an independent risk factor for refractory ESES (OR: 10.48, 95% CI: 1.62-67.63). The clinical seizure improvement rates of anti-seizure medications (ASMs), ASMs with benzodiazepines, and ASMs with benzodiazepines and steroids after 12 months were 9.3%, 42.8%, and 53.8%, EEG improvement rate were 5.5%, 30.9% and 37%, respectively. The intelligence of the children in the responder treatment group has improved during the 1-year follow-up.

SIGNIFICANCE

These findings demonstrate EEG and clinical features of ESES and may provide basis for simplifying diagnosis and guiding the treatment of children with ESES.

Dynamic effects of miR-20a-5p on hippocampal ripple energy after status epilepticus in rats

To determine the dynamic effects of miR-20a-5p on hippocampal ripple energy in rats after status epilepticus (SE). A lithium pilocarpine (LiCl-PILO)-induced rat model of status epilepticus (SE) was established, and the rats were divided into the normal control (Control, CTL), epileptic control (PILO), valproic acid (VPA + PILO), miR-20a-5p overexpression lentivirus vector (miR + PILO), sponges blocking lentivirus vector (Sponges + PILO), and scramble sequence negative control (Scramble + PILO) groups (n = 6). Electroencephalograms (EEGs) were used to analyze changes in hippocampal ripple energy before and after SE. Quantitative polymerase chain reaction (q-PCR) analysis showed that miR-20a-5p levels gradually increased after miR-20a-5p overexpression lentivirus vector injection into the lateral ventricle, and the miR-20a-5p levels were significantly higher than that in CTL group on days 7 and 36 (P < 0.001). The miR-20a-5p levels decreased significantly on days 7 and 36 after blocking by sponges lentivirus vector injected into the lateral ventricle (P < 0.001). After injection of PILO, the average ripple energy expression in each group gradually increased, and reached the peak before chloral hydrate injection (compared with 1 day before SE, P < 0.05). The ripple energy in the VPA + PILO and Sponges + PILO groups was significantly lower than that in the PILO group at 60 min and 70 min after PILO injection and before chloral hydrate injection (P < 0.05), and maintained lower until 2 h after chloral hydrate injection in VPA + PILO (P < 0.05). Compared with the VPA + PILO group, the mean ripple energy of the Sponges + PILO group had no difference at all time points (P ≥ 0.05). After SE, ripple distribution of space and energy is closely related to the occurrence of epilepsy. Inhibition of miR20a-5p expression can downregulate ripple oscillation energy during seizure.

Improved Biomagnetic Signal-To-Noise Ratio and Source Localization Using Optically Pumped Magnetometers with Synthetic Gradiometers

Optically pumped magnetometers (OPMs) can capture brain activity but are susceptible to magnetic noise. The objective of this study was to evaluate a novel methodology used to reduce magnetic noise in OPM measurements. A portable magnetoencephalography (MEG) prototype was developed with OPMs. The OPMs were divided into primary sensors and reference sensors. For each primary sensor, a synthetic gradiometer (SG) was constructed by computing a secondary sensor that simulated noise with signals from the reference sensors. MEG data from a phantom with known source signals and six human participants were used to assess the efficacy of the SGs. Magnetic noise in the OPM data appeared predominantly in a low frequency range (<4 Hz) and varied among OPMs. The SGs significantly reduced magnetic noise (p < 0.01), enhanced the signal-to-noise ratio (SNR) (p < 0.001) and improved the accuracy of source localization (p < 0.02). The SGs precisely revealed movement-evoked magnetic fields in MEG data recorded from human participants. SGs provided an effective method to enhance SNR and improve the accuracy of source localization by suppressing noise. Software-simulated SGs may provide new opportunities regarding the use of OPM measurements in various clinical and research applications, especially those in which movement is relevant.

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.

Relationship between brain activity, cognitive function, and sleep spiking activation in new-onset self-limited epilepsy with centrotemporal spikes

Objective

This study aimed to investigate the relationship between cognitive function sleep spiking activation and brain activity in self-limited epilepsy with centrotemporal spikes (SeLECTS).

Methods

We used spike-wave index (SWI), which means the percentage of the spike and slow wave duration to the total non-REM (NREM) sleep time, as the grouping standard. A total of 14 children with SeLECTS (SWI ≥ 50%), 21 children with SeLECTS (SWI &lt; 50%), and 20 healthy control children were recruited for this study. Cognitive function was evaluated using the Wechsler Intelligence Scale for Children, Fourth Edition (Chinese version) (WISC-IV). Magnetic source activity was assessed using magnetoencephalography calculated for each frequency band using the accumulated source imaging (ASI) technique.

Results

Children with SeLECTS (SWI ≥ 50%) had the lowest cognitive function scores, followed by those with SeLECTS (SWI &lt; 50%) and then healthy controls. There were significant differences in the localization of magnetic source activity between the three groups: in the alpha (8–12 Hz) frequency band, children with SeLECTS (SWI ≥ 50%) showed deactivation of the medial frontal cortex (MFC) region; in the beta (12–30 Hz) frequency band, children with SeLECTS (SWI ≥ 50%) showed deactivation of the posterior cingulate cortex (PCC) segment; and in the gamma (30–80 Hz) frequency band, children in the healthy group showed activation of the PCC region.

Conclusion

This study revealed significant decreases in cognitive function in children with SeLECTS (SWI ≥ 50%) compared to children with SeLECTS (SWI &lt; 50%) and healthy children, as well as significant differences in magnetic source activity between the three groups. The findings suggest that deactivation of magnetic source activity in the PCC and MFC regions is the main cause of cognitive function decline in SeLECTS patients with some frequency dependence.

Altered Neuromagnetic Activity in Persistent Postural-Perceptual Dizziness: A Multifrequency Magnetoencephalography Study

Objective

The aim of our study was to investigate abnormal changes in brain activity in patients with persistent postural-perceptual dizziness (PPPD) using magnetoencephalography (MEG).

Methods

Magnetoencephalography recordings from 18 PPPD patients and 18 healthy controls were analyzed to determine the source of brain activity in seven frequency ranges using accumulated source imaging (ASI).

Results

Our study showed that significant changes in the patterns of localization in the temporal-parietal junction (TPJ) were observed at 1–4, 4–8, and 12–30 Hz in PPPD patients compared with healthy controls, and changes in the frontal cortex were found at 1–4, 80–250, and 250–500 Hz in PPPD patients compared with controls. The neuromagnetic activity in TPJ was observed increased significantly in 1–4 and 4–8 Hz, while the neuromagnetic activity in frontal cortex was found increased significantly in 1–4 Hz. In addition, the localized source strength in TPJ in 1–4 Hz was positively correlated with DHI score (r = 0.7085, p < 0.05), while the localized source strength in frontal cortex in 1–4 Hz was positively correlated with HAMA score (r = 0.5542, p < 0.05).

Conclusion

Our results demonstrated that alterations in the TPJ and frontal cortex may play a critical role in the pathophysiological mechanism of PPPD. The neuromagnetic activity in TPJ may be related to dizziness symptom of PPPD patients, while the neuromagnetic activity in frontal lobe may be related to emotional symptoms of PPPD patients. In addition, frequency-dependent changes in neuromagnetic activity, especially neuromagnetic activity in low frequency bands, were involved in the pathophysiology of PPPD.

Transformer-Based High-Frequency Oscillation Signal Detection on Magnetoencephalography From Epileptic Patients

High-frequency oscillations (HFOs), observed within 80–500 Hz of magnetoencephalography (MEG) data, are putative biomarkers to localize epileptogenic zones that are critical for the success of surgical epilepsy treatment. It is crucial to accurately detect HFOs for improving the surgical outcome of patients with epilepsy. However, in clinical practices, detecting HFOs in MEG signals mainly depends on visual inspection by clinicians, which is very time-consuming, labor-intensive, subjective, and error-prone. To accurately and automatically detect HFOs, machine learning approaches have been developed and have demonstrated the promising results of automated HFO detection. More recently, the transformer-based model has attracted wide attention and achieved state-of-the-art performance on many machine learning tasks. In this paper, we are investigating the suitability of transformer-based models on the detection of HFOs. Specifically, we propose a transformer-based HFO detection framework for biomedical MEG one-dimensional signal data. For signal classification, we develop a transformer-based HFO (TransHFO) classification model. Then, we investigate the relationship between depth of deep learning models and classification performance. The experimental results show that the proposed framework outperforms the state-of-the-art HFO classifiers, increasing classification accuracy by 7%. Furthermore, we find that shallow TransHFO (< 10 layers) outperforms deep TransHFO models (≥10 layers) on most data augmented factors.

Altered effective connectivity in migraine patients during emotional stimuli: a multi-frequency magnetoencephalography study

BACKGROUND

Migraine is a common and disabling primary headache, which is associated with a wide range of psychiatric comorbidities. However, the mechanisms of emotion processing in migraine are not fully understood yet. The present study aimed to investigate the neural network during neutral, positive, and negative emotional stimuli in the migraine patients.

METHODS

A total of 24 migraine patients and 24 age- and sex-matching healthy controls were enrolled in this study. Neuromagnetic brain activity was recorded using a whole-head magnetoencephalography (MEG) system upon exposure to human facial expression stimuli. MEG data were analyzed in multi-frequency ranges from 1 to 100 Hz.

RESULTS

The migraine patients exhibited a significant enhancement in the effective connectivity from the prefrontal lobe to the temporal cortex during the negative emotional stimuli in the gamma frequency (30-90 Hz). Graph theory analysis revealed that the migraine patients had an increased degree and clustering coefficient of connectivity in the delta frequency range (1-4 Hz) upon exposure to positive emotional stimuli and an increased degree of connectivity in the delta frequency range (1-4 Hz) upon exposure to negative emotional stimuli. Clinical correlation analysis showed that the history, attack frequency, duration, and neuropsychological scales of the migraine patients had a negative correlation with the network parameters in certain frequency ranges.

CONCLUSIONS

The results suggested that the individuals with migraine showed deviant effective connectivity in viewing the human facial expressions in multi-frequencies. The prefrontal-temporal pathway might be related to the altered negative emotional modulation in migraine. These findings suggested that migraine might be characterized by more universal altered cerebral processing of negative stimuli. Since the significant result in this study was frequency-specific, more independent replicative studies are needed to confirm these results, and to elucidate the neurocircuitry underlying the association between migraine and emotional conditions.

Frequency-Dependent Dynamics of Functional Connectivity Networks During Seizure Termination in Childhood Absence Epilepsy: A Magnetoencephalography Study

Objective: Our aim was to investigate the dynamics of functional connectivity (FC) networks during seizure termination in patients with childhood absence epilepsy (CAE) using magnetoencephalography (MEG) and graph theory (GT) analysis.

Methods: MEG data were recorded from 22 drug-naïve patients diagnosed with CAE. FC analysis was performed to evaluate the FC networks in seven frequency bands of the MEG data. GT analysis was used to assess the topological properties of FC networks in different frequency bands.

Results: The patterns of FC networks involving the frontal cortex were altered significantly during seizure termination compared with those during the ictal period. Changes in the topological parameters of FC networks were observed in specific frequency bands during seizure termination compared with those in the ictal period. In addition, the connectivity strength at 250–500 Hz during the ictal period was negatively correlated with seizure frequency.

Conclusions: FC networks associated with the frontal cortex were involved in the termination of absence seizures. The topological properties of FC networks in different frequency bands could be used as new biomarkers to characterize the dynamics of FC networks related to seizure termination.

Modulating Gamma Oscillations Promotes Brain Connectivity to Improve Cognitive Impairment

Dementia causes a substantial global economic burden, but effective treatment is lacking. Recently, studies have revealed that gamma-band waves of electrical brain activity, particularly 40 Hz oscillations, are closely associated with high-order cognitive functions and can activate microglia to clear amyloid-β deposition. Here, we found that compared with sham stimulation, applying 40-Hz high-frequency repetitive transcranial magnetic stimulation (rTMS) over the bilateral angular gyrus in patients with probable Alzheimer's disease (AD; n = 37) resulted in up to 8 weeks of significantly improved cognitive function. Power spectral density analysis of the resting-state electroencephalography (EEG) demonstrated that 40-Hz rTMS modulated gamma-band oscillations in the left posterior temporoparietal region. Further testing with magnetic resonance imaging and TMS-EEG revealed the following: 40-Hz rTMS 1) prevented gray matter volume loss, 2) enhanced local functional integration within bilateral angular gyrus, as well as global functional integration in bilateral angular gyrus and the left middle frontal gyrus, 3) strengthened information flow from the left posterior temporoparietal region to the frontal areas and strengthened the dynamic connectivity between anterior and posterior brain regions. These findings demonstrate that modulating gamma-band oscillations effectively improves cognitive function in patients with probable AD by promoting local, long-range, and dynamic connectivity within the brain.

Impact of Antiepileptic Drugs on Cognition and Neuromagnetic Activity in Childhood Epilepsy With Centrotemporal Spikes: A Magnetoencephalography Study

Objective: Childhood epilepsy with centrotemporal spikes (CECTS), the most common childhood epilepsy, still lacks longitudinal imaging studies involving antiepileptic drugs (AEDs). In order to examine the effect of AEDs on cognition and brain activity. We investigated the neuromagnetic activities and cognitive profile in children with CECTS before and after 1 year of treatment.

Methods: Fifteen children with CECTS aged 6–12 years underwent high-sampling magnetoencephalography (MEG) recordings before treatment and at 1 year after treatment, and 12 completed the cognitive assessment (The Wechsler Intelligence Scale for Children). Next, magnetic source location and functional connectivity (FC) were investigated in order to characterize interictal neuromagnetic activity in the seven frequency sub-bands, including: 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).

Results: After 1 year of treatment, children with CECTS had increased scores on full-scale intelligence quotient, verbal comprehension index (VCI) and perceptual reasoning index (PRI). Alterations of neural activity occurred in specific frequency bands. Source location, in the 30–80 Hz frequency band, was significantly increased in the posterior cingulate cortex (PCC) after treatment. Moreover, FC analysis demonstrated that after treatment, the connectivity between the PCC and the medial frontal cortex (MFC) was enhanced in the 8–12 Hz frequency band. Additionally, the whole-brain network distribution was more dispersed in the 80–250 Hz frequency band.

Conclusion: Intrinsic neural activity has frequency-dependent characteristic. AEDs have impact on regional activity and FC of the default mode network (DMN). Normalization of aberrant DMN in children with CECTS after treatment is likely the reason for improvement of cognitive function.

Altered functional connectivity in newly diagnosed benign epilepsy with unilateral or bilateral centrotemporal spikes: A multi-frequency MEG study

OBJECTIVE

Rolandic epilepsy (RE) is one of the most common forms of epilepsy syndromes in children. The condition is usually accompanied with either unilateral or bilateral centrotemporal epileptic discharge. Despite the term "benign", many studies have reported that children with benign epilepsy with centrotemporal spikes (BECTS) display a range of pervasive cognitive difficulties. In addition, existing research suggests that unilateral and bilateral centrotemporal spikes may affect cognition through different mechanisms. Consequently, the present study aimed to investigate cognitive impairment and the resting-state network topology of children with benign epilepsy with unilateral centrotemporal spikes (U-BECTS) and with bilateral centrotemporal spikes (B-BECTS).

METHODS

This study recruited 14 children with U-BECTS and 14 with B-BECTS. Thereafter, cognition was assessed in 28 children with BECTS and 14 healthy controls, using the fourth edition of the Wechsler Intelligence Scale (WISC-IV). Additionally, the functional network of the brain was constructed through magnetoencephalography (MEG) to record the resting-state brain magnetic signals of the brain and by computing virtual sensor waveforms at the source level. Moreover, graph theory (GT) analysis was used to assess the properties of the brain network.

RESULTS

Children in the B-BECTS group had an earlier onset of epilepsy compared to those in the U-BECTS category. In addition, both the B-BECTS and U-BECTS groups had lower Full Scale Intelligence Quotient (FSIQ), Verbal Comprehension Index (VCI), and Working Memory Index (WMI) scores, compared to the healthy controls although only children in the B-BECTS category had lower Perceptual Reasoning Index (PRI) scores. The results also showed that both BECTS groups had increased frontal cortex connectivity in specific frequency bands. Notably, children with B-BECTS showed a more disorderly and randomized network in the 1-4-Hz and 80-250-Hz frequency bands. Moreover, GT analysis showed that children with B-BECTS had lower clustering coefficient and characteristic path length in the 80-250-Hz frequency bands and higher connection strength in the 4-8-Hz frequency bands. On the other hand, the U-BECTS group had a higher clustering coefficient in the 8-12-Hz frequency bands, compared to the healthy controls. Correlation analysis revealed that there were negative correlations between network parameters, clinical characteristics, and neuropsychological data in the U-BECTS category.

CONCLUSION

The findings revealed that children with BECTS display a diffuse early cognitive deficit. In addition, resting-state suboptimal network topology may be the mechanism of cognitive impairment in children with BECTS. The study also showed that and children with B-BECTS may be at a higher risk of cognitive impairment.

Pretreatment Source Location and Functional Connectivity Network Correlated With Therapy Response in Childhood Absence Epilepsy: A Magnetoencephalography Study

Objective: This study aims to investigate the differences between antiepileptic drug (AED) responders and nonresponders among patients with childhood absence epilepsy (CAE) using magnetoencephalography (MEG) and to additionally evaluate whether the neuromagnetic signals of the brain neurons were correlated with the response to therapy.

Methods: Twenty-four drug-naïve patients were subjected to MEG under six frequency bandwidths during ictal periods. The source location and functional connectivity were analyzed using accumulated source imaging and correlation analysis, respectively. All patients were treated with appropriate AED, at least 1 year after their MEG recordings, their outcome was assessed, and they were consequently divided into responders and nonresponders.

Results: The source location of the nonresponders was mainly in the frontal cortex at a frequency range of 8–12 and 30–80 Hz, especially 8–12 Hz, while the source location of the nonresponders was mostly in the medial frontal cortex, which was chosen as the region of interest. The nonresponders showed strong positive local frontal connections and deficient anterior and posterior connections at 80–250 Hz.

Conclusion: The frontal cortex and especially the medial frontal cortex at α band might be relevant to AED-nonresponsive CAE patients. The local frontal positive epileptic network at 80–250 Hz in our study might further reveal underlying cerebral abnormalities even before treatment in CAE patients, which could cause them to be nonresponsive to AED. One single mechanism cannot explain AED resistance; the nonresponders may represent a subgroup of CAE who is refractory to several antiepileptic drugs.

Effect of gap junction blockers on hippocampal ripple energy expression in rats with status epilepticus

OBJECTIVES

To study the effect of gap junction blockers, quinine (QUIN) and carbenoxolone (CBX), on hippocampal ripple energy expression in rats with status epilepticus (SE).

METHODS

A total of 24 rats were randomly divided into four groups: model, QUIN, valproic acid (VPA), and CBX (n=6 each). A rat model of SE induced by lithium-pilocarpine (PILO) was prepared. The QUIN, VPA, and CBX groups were given intraperitoneal injection of QUIN (50 mg/kg), VPA by gavage (200 mg/kg), and intraperitoneal injection of CBX (50 mg/kg) respectively, at 3 days before PILO injection. Electroencephalography was used to analyze the change in hippocampal ripple energy before and after modeling, as well as before and after chloral hydrate injection to control seizures.

RESULTS

Ripple expression was observed in the hippocampal CA1, CA3, and dentate gyrus regions of normal rats. After 10 minutes of PILO injection, all groups had a gradual increase in mean ripple energy expression compared with 1 day before modeling, with the highest expression level before chloral hydrate injection in the model, VPA and CBX groups (P<0.05). The QUIN group had the highest expression level of mean ripple energy 60 minutes after PILO injection. The mean ripple energy returned to normal levels in the three intervention groups immediately after chloral hydrate injection, while in the model group, the mean ripple energy returned to normal levels 1 hour after chloral hydrate injection. The mean ripple energy remained normal till to day 3 after SE in the four groups. The changing trend of maximum ripple energy was similar to that of mean ripple energy.

CONCLUSIONS

The change in ripple energy can be used as a quantitative indicator for early warning of seizures, while it cannot predict seizures in the interictal period. Gap junction blockers can reduce ripple energy during seizures.

Application of High-Frequency Oscillations on Scalp EEG in Infant Spasm: A Prospective Controlled Study

Objective

We quantitatively analyzed high-frequency oscillations (HFOs) using scalp electroencephalography (EEG) in patients with infantile spasms (IS).

Methods

We enrolled 60 children with IS hospitalized from January 2019 to August 2020. Sixty healthy age-matched children comprised the control group. Time-frequency analysis was used to quantify γ, ripple, and fast ripple (FR) oscillation energy changes.

Results

γ, ripple, and FR oscillations dominated in the temporal and frontal lobes. The average HFO energy of the sleep stage is lower than that of the wake stage in the same frequency bands in both the normal control (NC) and IS groups (P < 0.05). The average HFO energy of the IS group was significantly higher than that of the NC group in γ band during sleep stage (P < 0.01). The average HFO energy of S and Post-S stage were higher than that of sleep stage in γ band (P < 0.05). In the ripple band, the average HFO energy of Pre-S, S, and Post-S stage was higher than that of sleep stage (P < 0.05). Before treatment, there was no significant difference in BASED score between the effective and ineffective groups. The interaction of curative efficacy × frequency and the interaction of curative efficacy × state are statistically significant. The average HFO energy of the effective group was lower than that of the ineffective group in the sleep stage (P < 0.05). For the 16 children deemed "effective" in the IS group, the average HFO energy of three frequency bands was not significantly different before compared with after treatment.

Significance

Scalp EEG can record HFOs. The energy of HFOs can distinguish physiological HFOs from pathological ones more accurately than frequency. On scalp EEG, γ oscillations can better detect susceptibility to epilepsy than ripple and FR oscillations. HFOs can trigger spasms. The analysis of average HFO energy can be used as a predictor of the effectiveness of epilepsy treatment.

Neuromagnetic high frequency spikes are a new and noninvasive biomarker for localization of epileptogenic zones

OBJECTIVE

One barrier hindering high frequency brain signals (HFBS, >80 Hz) from wide clinical applications is that the brain generates both pathological and physiological HFBS. This study was to find specific biomarkers for localizing epileptogenic zones (EZs).

METHODS

Twenty three children with drug-resistant epilepsy and age/sex matched healthy controls were studied with magnetoencephalography (MEG). High frequency oscillations (HFOs, > 4 oscillatory waveforms) and high frequency spikes (HFSs, > 1 spiky or sharp waveforms) in 80-250 Hz and 250-600 Hz bands were blindly detected with an artificial intelligence method and validated with visual inspection. The magnitude of HFOs and HFSs were quantified with spectral analyses. Sources of HFSs and HFOs were localized and compared with clinical EZs determined by invasive recordings and surgical outcomes.

RESULTS

HFOs in 80-250 Hz and 250-600 Hz were identified in both epilepsy patients (18/23, 12/23, respectively) and healthy controls (6/23, 4/23, respectively). HFSs in 80-250 Hz and 250-600 Hz were detected in patients (16/23, 11/23, respectively) but not in healthy controls. A combination of HFOs and HFSs localized EZs for 22 (22/23, 96%) patients.

CONCLUSIONS

The results indicate, for the first time, that HFSs are a newer and more specific biomarker than HFOs for localizing EZs because HFOs appeared in both epilepsy patients and healthy controls while HFSs appeared only in epilepsy patients.

Delineation of epileptogenic zones with high frequency magnetic source imaging based on kurtosis and skewness

BACKGROUND

Neuromagnetic high frequency brain signals (HFBS, > 80 Hz) are a new biomarker for localization of epileptogenic zones (EZs) for pediatric epilepsy.

METHODS

Twenty three children with drug-resistant epilepsy and age/sex matched healthy controls were studied with magnetoencephalography (MEG). Epileptic HFBS in 80-250 Hz and 250-600 Hz were quantitatively determined by comparing with normative controls in terms of kurtosis and skewness. Magnetic sources of epileptic HFBS were localized and then compared to clinical EZs determined by invasive recordings and surgical outcomes.

RESULTS

Kurtosis and skewness of HFBS were significantly elevated in epilepsy patients compared to healthy controls (p < 0,001 and p < 0.0001, respectively). Sources of elevated MEG signals in comparison to normative data were co-localized to EZs for 22 (22/23, 96 %) patients.

CONCLUSIONS

The results indicate, for the first time, that epileptic HFBS can be noninvasively quantified by measuring kurtosis and skewness in MEG data. Magnetic source imaging based on kurtosis and skewness can accurately localize EZs.

SIGNIFICANCE

Source imaging of kurtosis and skewness of MEG HFBS provides a novel way for preoperative localization of EZs for epilepsy surgery.

Detecting High Frequency Oscillations for Stereoelectroencephalography in Epilepsy via Hypergraph Learning

Successful epilepsy surgeries depend highly on pre-operative localization of epileptogenic zones. Stereoelectroencephalography (SEEG) records interictal and ictal activities of the epilepsy in order to precisely find and localize epileptogenic zones in clinical practice. While it is difficult to find distinct ictal onset patterns generated the seizure onset zone from SEEG recordings in a confined region, high frequency oscillations are commonly considered as putative biomarkers for the identification of epileptogenic zones. Therefore, automatic and accurate detection of high frequency oscillations in SEEG signals is crucial for timely clinical evaluation. This work formulates the detection of high frequency oscillations as a signal segment classification problem and develops a hypergraph-based detector to automatically detect high frequency oscillations such that human experts can visually review SEEG signals. We evaluated our method on 4,000 signal segments from clinical SEEG recordings that contain both ictal and interictal data obtained from 19 patients who suffer from refractory focal epilepsy. The experimental results demonstrate the effectiveness of the proposed detector that can successfully localize interictal high frequency oscillations and outperforms multiple peer machine learning methods. In particular, the proposed detector achieved 90.7% in accuracy, 80.9% in sensitivity, and 96.9% in specificity.

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.

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.

Frequency-Dependent Interictal Neuromagnetic Activities in Children With Benign Epilepsy With Centrotemporal Spikes: A Magnetoencephalography (MEG) Study

Objective: This study aimed to investigate interictal neuromagnetic activities in the low- to high-frequency ranges in patients with benign epilepsy with centrotemporal spikes (BECTS), especially those without interictal epileptiform discharges (IEDs).

Methods: We studied 21 clinically-diagnosed BECTS patients and 11 age-matched healthy controls (HC) using high-sampling magnetoencephalography (MEG). Neuromagnetic sources were assessed with accumulated source imaging (ASI). The MEG data were analyzed in seven frequency bands. The MEG recordings distinguished BECTS without IEDs (n = 10) from those with IEDs (n = 11) and HC (n = 11).

Results: At 1–4 Hz, the neuromagnetic activities in healthy subjects tended to locate at the precuneus/posterior cingulate, while those of the BECTS patients without IEDs tended to locate at the medial frontal cortex (MFC) compared to BECTS patients with IEDs. The MEG source imaging at 30–80 Hz revealed that BECTS patients without IEDs had higher occurrences of interictal brain activity in the medial temporal lobe (MTL) compared to controls and the brain activity strength seemed to be weaker. There was a significant correlation between the source strength of the interictal gamma oscillations of BECTS patients without IEDs and the duration of epilepsy.

Conclusions: IEDs might disrupt the default mode network (DMN). Aberrant brain activities in BECTS patients without IEDs were associated with cognitive areas of the brain. The strength of gamma oscillations in the chronic epilepsy state reflected the duration of BECTS.

Significance: MEG could reveal the aberrant neural activities in BECTS patients during the interictal period, and such abnormality is frequency-dependent. Gamma oscillations could be used to identify BECTS patients without IEDs.

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.

Automatic and Accurate Epilepsy Ripple and Fast Ripple Detection via Virtual Sample Generation and Attention Neural Networks

About 1% of the population around the world suffers from epilepsy. The success of epilepsy surgery depends critically on pre-operative localization of epileptogenic zones. High frequency oscillations including ripples (80-250 Hz) and fast ripples (250-500 Hz) are commonly used as biomarkers to localize epileptogenic zones. Recent literature demonstrated that fast ripples indicate epileptogenic zones better than ripples. Thus, it is crucial to accurately detect fast ripples from ripples signals of magnetoencephalography for improving outcome of epilepsy surgery. This paper proposes an automatic and accurate ripple and fast ripple detection method that employs virtual sample generation and neural networks with an attention mechanism. We evaluate our proposed detector on patient data with 50 ripples and 50 fast ripples labeled by two experts. The experimental results show that our new detector outperforms multiple traditional machine learning models. In particular, our method can achieve a mean accuracy of 89.3% and an average area under the receiver operating characteristic curve of 0.88 in 50 repeats of random subsampling validation. In addition, we experimentally demonstrate the effectiveness of virtual sample generation, attention mechanism, and architecture of neural network models.

Expert consensus on clinical applications of high-frequency oscillations in epilepsy

Studies in animal models of epilepsy and pre-surgical patients have unanimously found a strong correlation between high-frequency oscillations (HFOs, > 80 Hz) and the epileptogenic zone, suggesting that HFOs can be a potential biomarker of epileptogenicity and epileptogenesis. This consensus includes the definition and standard detection techniques of HFOs, the localizing value of pathological HFOs for epileptic foci, and different ways to distinguish physiological from epileptic HFOs. The latest clinical applications of HFOs in epilepsy and the related findings are also discussed. HFOs will advance our understanding of the pathophysiology of epilepsy.

Identifying the Epileptogenic Zone With the Relative Strength of High-Frequency Oscillation: A Stereoelectroencephalography Study

Background

High-frequency oscillation (HFO) represents a promising biomarker of epileptogenicity. However, the significant interindividual differences among patients limit its application in clinical practice. Here, we applied and evaluated an individualized, frequency-based approach of HFO analysis in stereoelectroencephalography (SEEG) data for localizing the epileptogenic zones (EZs).

Methods

Clinical and SEEG data of 19 patients with drug-resistant focal epilepsy were retrospectively analyzed. The individualized spectral power of all signals recorded by electrode array, i.e., the relative strength of HFO, was computed with a wavelet method for each patient. Subsequently, the clinical value of the relative strength of HFO for identifying the EZ was evaluated.

Results

Focal increase in the relative strength of HFO in SEEG recordings were identified in all 19 patients. HFOs identified inside the clinically identified seizure onset zone had more spectral power than those identified outside (p < 0.001), and HFOs in 250–500 Hz band (fast ripples) seemed to be more specific identifying the EZ than in those in 80–250 Hz band (ripples) (p < 0.01). The resection of brain regions generating HFOs resulted in a favorable seizure outcome in 17 patients (17/19; 89.5%), while in the cases of other patients with poor outcomes, the brain regions generating HFOs were not removed completely.

Conclusion

The relative strength of HFO, especially fast ripples, is a promising effective biomarker for identifying the EZ and can lead to a favorable seizure outcome if used to guide epilepsy surgery.

Kurtosis and skewness of high-frequency brain signals are altered in paediatric epilepsy

Intracranial studies provide solid evidence that high-frequency brain signals are a new biomarker for epilepsy. Unfortunately, epileptic (pathological) high-frequency signals can be intermingled with physiological high-frequency signals making these signals difficult to differentiate. Recent success in non-invasive detection of high-frequency brain signals opens a new avenue for distinguishing pathological from physiological high-frequency signals. The objective of the present study is to characterize pathological and physiological high-frequency signals at source levels by using kurtosis and skewness analyses. Twenty-three children with medically intractable epilepsy and age-/gender-matched healthy controls were studied using magnetoencephalography. Magnetoencephalographic data in three frequency bands, which included 2–80 Hz (the conventional low-frequency signals), 80–250 Hz (ripples) and 250–600 Hz (fast ripples), were analysed. The kurtosis and skewness of virtual electrode signals in eight brain regions, which included left/right frontal, temporal, parietal and occipital cortices, were calculated and analysed. Differences between epilepsy and controls were quantitatively compared for each cerebral lobe in each frequency band in terms of kurtosis and skewness measurements. Virtual electrode signals from clinical epileptogenic zones and brain areas outside of the epileptogenic zones were also compared with kurtosis and skewness analyses. Compared to controls, patients with epilepsy showed significant elevation in kurtosis and skewness of virtual electrode signals. The spatial and frequency patterns of the kurtosis and skewness of virtual electrode signals among the eight cerebral lobes in three frequency bands were also significantly different from that of the controls (2–80 Hz, P < 0.001; 80–250 Hz, P < 0.00001; 250–600 Hz, P < 0.0001). Compared to signals from non-epileptogenic zones, virtual electrode signals from epileptogenic zones showed significantly altered kurtosis and skewness (P < 0.001). Compared to normative data from the control group, aberrant virtual electrode signals were, for each patient, more pronounced in the epileptogenic lobes than in other lobes(kurtosis analysis of virtual electrode signals in 250–600 Hz; odds ratio = 27.9; P < 0.0001). The kurtosis values of virtual electrode signals in 80–250 and 250–600 Hz showed the highest sensitivity (88.23%) and specificity (89.09%) for revealing epileptogenic lobe, respectively. The combination of virtual electrode and kurtosis/skewness measurements provides a new quantitative approach to distinguishing pathological from physiological high-frequency signals for paediatric epilepsy. Non-invasive identification of pathological high-frequency signals may provide novel important information to guide clinical invasive recordings and direct surgical treatment of epilepsy.

Frequency-specific changes in the default mode network in patients with cingulate gyrus epilepsy

To identify abnormal functional connectivity of the default mode network in cingulate gyrus epilepsy, which may yield new information about the default mode network and suggest a new cingulate gyrus epilepsy biomarker. Fifteen patients with cingulate gyrus epilepsy (mean age = 21 years) and 15 healthy controls (mean age = 24 years) were studied in the resting state using magnetoencephalography. Twelve brain areas of interest in the default mode network were extracted and investigated with multifrequency signals that included alpha (α, 8–13 Hz), beta (β, 14–30 Hz), and gamma (γ, 31–80 Hz) band oscillations. Patients with cingulate gyrus epilepsy had significantly greater connectivity in all three frequency bands (α, β, γ). A frequency‐specific elevation of functional connectivity was found in patients compared to controls. The greater functional connectivity in the γ band was significantly more prominent than that of the α and β bands. Patients with cingulate gyrus epilepsy and controls differed significantly in functional connectivity between the left angular gyrus and left posterior cingulate cortex in the α, β, and γ bands. The results of the node degree analysis were similar to those of the functional connectivity analysis. Our findings reveal for the first time that brain activity in the γ band may play a key role in the default mode network in cingulate gyrus epilepsy. Altered functional connectivity of the left angular gyrus and left posterior cingulate cortex may be a new biomarker for cingulate gyrus epilepsy.

Differences Between Interictal and Ictal Generalized Spike-Wave Discharges in Childhood Absence Epilepsy: A MEG Study

Purpose: To investigate the differences between interictal and ictal generalized spike-wave discharges (GSWDs) for insights on how epileptic activity propagates and the physiopathological mechanisms underlying childhood absence epilepsy (CAE).

Methods: Twenty-five patients with CAE were studied using magnetoencephalography (MEG). MEG data were digitized at 6,000 Hz during the interictal and ictal GSWDs. GSWDs were analyzed at both neural magnetic source levels and functional connectivity (FC) in multifrequency bands: 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). Brain FC was studied with the posterior cingulate cortex/precuneus (PCC/pC) as the seed region.

Results: The magnetic source of interictal GSWDs mainly locates in the PCC/pC region at 4–8 and 8–12 Hz, while that of ictal GSWDs mainly locates in the medial frontal cortex (MFC) at 80–250 Hz. There were statistically significant differences between interictal and ictal GSWDs (p < 0.05). The FC network involving the PCC/pC showed strong connections in the anterior-posterior pathways (mainly with the frontal cortex) at 80–250 Hz during ictal GSWDs, while the interictal GSWDs FC were mostly limited to the posterior cortex region. There was no significant difference in the magnetic source strength among interictal and ictal GSWDs at all bandwidths.

Conclusions: There are significant disparities in the source localization and FC between interictal and ictal GSWDs. Low-frequency activation in the PCC/pC during inhibition of seizures possibly relates to the maintenance of consciousness during interictal GSWDs. High-frequency oscillations (HFOs) of the MFC during CAE may associate with the inducing or occurrence of GSWDs. Weakened network connections may be in favor of preventing overexcitability and relates to the termination of GSWDs.

Altered effective connectivity network in patients with insular epilepsy: A high-frequency oscillations magnetoencephalography study

OBJECTIVE

The project aimed to determine the alterations in the effective connectivity (EC) neural network in patients with insular epilepsy based on interictal high-frequency oscillations (HFOs) from magnetoencephalography (MEG) data.

METHODS

We studied MEG data from 22 insular epilepsy patients and 20 normal subjects. Alterations in spatial pattern and connection properties of the patients with insular epilepsy were investigated in the entire brain network and insula-based network.

RESULTS

Analyses of the parameters of graph theory revealed the over-connectivity and small-world configuration of the global connectivity patterns observed in the patients. In the insula-based network, the insular cortex ipsilateral to the seizure onset displayed increased efferent and afferentEC. Left insular epilepsy featured strong connectivity with the bilateral hemispheres, whereas right insular epilepsy featured increased connectivity with only the ipsilateral hemisphere.

CONCLUSIONS

Patients with insular epilepsy display alterations in the EC network in terms of both whole-brain connectivity and the insula-based network during interictal HFOs.

SIGNIFICANCE

Alterations of interictal HFO-based networks provide evidence that epilepsy networks, instead of epileptic foci, play a key role in the complex pathophysiological mechanisms of insular epilepsy. The dysfunction of HFO networks may prove to be a novel promising biomarker and the cause of interictal brain dysfunctions in insular epilepsy.

Screen-exposure and altered brain activation related to attention in preschool children: An EEG study

Exposure to screens has been shown to reduce attention span in children. Increased slow-wave (theta band) and decreased fast-wave (beta and gamma bands) generated from EEG, as well as increased theta/beta ratio, have been observed in children with Attention-Deficit-Hyperactivity-Disorder (ADHD). This study examined the relationship between 6-weeks screen exposure and attention abilities in typically developing preschoolers using EEG during rest. Theta and beta bands were compared, and visual attention and parental reports for attention abilities were controlled. Results suggested that the active control group showed improved visual-attention abilities following the exposure to stories, whereas the screen group did not show improved visual attention. EEG results suggested a higher connectivity in theta vs. beta bands in the screen group, but not in the control group. Results support the negative relationship between screen exposure and attention-related patterns generated from EEG in typically developing preschool children.

Dynamic Neuromagnetic Network Changes of Seizure Termination in Absence Epilepsy: A Magnetoencephalography Study

Objective: With increasing efforts devoted to investigating the generation and propagation mechanisms of spontaneous spike and wave discharges (SWDs), little attention has been paid to network mechanisms associated with termination patterns of SWDs to date. In the current study, we aimed to identify the frequency-dependent neural network dynamics during the offset of absence seizures.

Methods: Fifteen drug-naïve patients with childhood absence epilepsy (CAE) were assessed with a 275-Channel Magnetoencephalography (MEG) system. MEG data were recorded during and between seizures at a sampling rate of 6,000 Hz and analyzed in seven frequency bands. Source localization was performed with accumulated source imaging. Granger causality analysis was used to evaluate effective connectivity networks of the entire brain at the source level.

Results: At the low-frequency (1–80 Hz) bands, activities were predominantly distributed in the frontal cortical and parieto–occipito–temporal junction at the offset transition periods. The high-frequency oscillations (HFOs, 80–500 Hz) analysis indicated significant source localization in the medial frontal cortex and deep brain areas (mainly thalamus) during both the termination transition and interictal periods. Furthermore, an enhanced positive cortico–thalamic effective connectivity was observed around the discharge offset at all of the seven analyzed bands, the direction of which was primarily from various cortical regions to the thalamus.

Conclusions: Seizure termination is a gradual process that involves both the cortices and the thalamus in CAE. Cortico–thalamic coupling is observed at the termination transition periods, and the cerebral cortex acts as the driving force.

A Magnetoencephalography Study of Pediatric Interictal Neuromagnetic Activity Changes and Brain Network Alterations Caused by Epilepsy in the High Frequency (80-1000 Hz)

More and more studies propose that high frequency brain signals are promising biomarkers of epileptogenic zone. In this paper, our aim is to investigate the neuromagnetic changes and brain network topological alterations during an interictal period at high frequency ranges (80-1000 Hz) between healthy controls and epileptic patients with Magnetoencephalography. We analyzed neuromagnetic activities with accumulated source imaging, and constructed brain network based on graph theory. Neuromagnetic activity changes and brain network alterations between two groups were analyzed in three frequency bands: ripple (80-250 Hz), fast ripples (FRs, 250-500 Hz), and very high frequency oscillations (VHFO, 500-1000 Hz). We found that epileptic patients showed significantly altered patterns of neuromagnetic source localization and altered brain network patterns. And, we also found that mean functional connectivity and the number of modules from epileptic patients significantly increased in the ripple and FRs bands, and mean clustering coefficient from epileptic patients significantly decreased in the ripple and FRs bands. We also found that the mean functional connectivity was positively correlated with duration of epilepsy in the ripple and VHFO bands, and the number of modules was positively correlated with the duration of epilepsy in the ripple, FRs, and VHFO bands. Our results indicate that epilepsy can alter patients' neuromagnetic activities and brain networks in the high-frequency ranges, and these alterations become more pathological as the duration of epilepsy grows longer.

Abnormal functional connectivity under somatosensory stimulation in migraine: a multi-frequency magnetoencephalography study

BACKGROUND

Although altered neural networks have been demonstrated in recent MEG (magnetoencephalography) research in migraine patients during resting state, it is unknown whether this alteration can be detected in task-related networks. The present study aimed to investigate the abnormalities of the frequency-specific somatosensory-related network in migraine patients by using MEG.

METHODS

Twenty-two migraineurs in the interictal phase and twenty-two sex- and age-matched healthy volunteers were studied using a whole-head magnetoencephalography (MEG) system. Electrical stimuli were delivered alternately to the median nerve on the right wrists of all subjects. MEG data were analyzed in a frequency range of 1-1000 Hz in multiple bands.

RESULTS

The brain network patterns revealed that the patients with migraine exhibited remarkably increased functional connectivity in the high-frequency (250-1000 Hz) band between the sensory cortex and the frontal lobe. The results of quantitative analysis of graph theory showed that the patients had (1) an increased degree of connectivity in the theta (4-8 Hz), beta (13-30 Hz) and gamma (30-80 Hz) bands; (2) an increased connectivity strength in the beta (13-30 Hz) and gamma (30-80 Hz) bands; (3) an increased path length in the beta (13-30 Hz), gamma (30-80 Hz) and ripple (80-250 Hz) bands; and (4) an increased clustering coefficient in the theta (4-8 Hz), beta (13-30 Hz) and gamma (30-80 Hz) bands.

CONCLUSIONS

The results indicate that migraine is associated with aberrant connections from the somatosensory cortex to the frontal lobe. The frequency-specific increases in connectivity in terms of strength, path length and clustering coefficients support the notion that migraineurs have elevated cortical networks. This alteration in functional connectivity may be involved in somatosensory processing in migraine patients and may contribute to understanding migraine pathophysiology and to providing convincing evidence for a spatially targeted migraine therapy.

Histopathologic and Clinical Correlation of Aberrant Neuromagnetic Activities with Low to High Frequency of Gliomas

OBJECTIVE

To quantify the low- to high-frequency range of abnormal brain activities and assess the histopathologic and clinical correlation in patients with glioma.

METHODS

Twenty-five patients with glioma and 20 healthy controls were examined with a magnetoencephalography (MEG) system. MEG data collected in 6 frequency bands, including 1-4 Hz, 4-8 Hz, 8-12 Hz, 12-30 Hz, 30-45 Hz, and 55-75 Hz, were analyzed by neuropathology to assess neuromagnetic signatures of glioma grade.

RESULTS

Compared with controls, patients with glioma showed greatly altered brain activities in 4-8 Hz, 8-12 Hz, and 55-75 Hz. Magnetic source power of brain activities in 4-8 Hz and 55-75 Hz in patients with high-grade gliomas significantly differed from that in patients with low-grade gliomas. The magnitude of source power of brain activities in 4-8 Hz and 55-75 Hz had marked correlation with the grading of gliomas in histopathological analyses.

CONCLUSIONS

The degree of neuromagnetic source abnormality is a potential biomarker for noninvasive assessment of glioma grade. Because MEG tests can be performed noninvasively and preoperatively, MEG may play an important role in clinical biopsies and surgical planning for patients with brain gliomas in the future.

A study for the mechanism of sensory disorder in restless legs syndrome based on magnetoencephalography

In spite of the relatively high incidence rate, the etiology and pathogenesis of restless legs syndrome (RLS) are still unclear. Long-term drug treatments fail to achieve satisfying curative effects, which is reflected by rebound and augmentation of related symptoms. An electrophysiological endophenotype experiment was done to investigate the mechanism of somatosensory disorder among RLS patients. Together with 15 normal subjects as the control group, with comparable ages and genders to the RLS patients, 15 primitive RLS patients were scanned by Magnetoencephalography (MEG) under natural conditions; furthermore, the somatosensory evoked magnetic field (SEF) with single and paired stimuli, was also measured. Compared to the control group, the SEF intensities of RLS patients' lower limbs were higher, and the paired-pulse depression (PPD) for SEF in RLS patients was attenuated. It was also revealed by time-frequency analysis of somatosensory induced oscillation (SIO) in RLS patients, that 93.3% of somatosensory induced Alpha (8-12 Hz) oscillations were successfully elicited, while 0% somatosensory induced Gamma (30-55 Hz) oscillations were elicited; which was significantly different from the control group. Additionally, in RLS patients exhibit increased excitability of the sensorimotor cortex, a remarkable abnormality existing in early somatosensory gating control (GC) and an attenuated inhibitory interneuron network, which consequently results in a compensatory mechanism through which RLS patients increase their attention-driven lower limb sensory gating control via somatosensory-induced Alpha (8-12 Hz) oscillation. This hyperexcitability, partially due to an electrocortical disinhibition, may have an important therapeutical implication, and become an important target of neuromodulatory interventions.

Detection and localization of interictal ripples with magnetoencephalography in the presurgical evaluation of drug-resistant insular epilepsy

Precise noninvasive presurgical localization of insular epilepsy is important. The objective of the present study was to detect and localize interictal high-frequency oscillations (HFOs) in patients with insular epilepsy at the source levels using magnetoencephalography (MEG). We investigated whether HFOs can delineate epileptogenic areas. We analysed MEG data with new accumulated source imaging (HFOs, 80-250 Hz ripples during spikes) and conventional dipole modelling (spikes) methods for localizing epileptic foci. We evaluated the relationship of the resection of focal brain regions containing interictal HFOs and the spikes with the postsurgical seizure outcome. Interictal HFOs were localized in the insular epileptogenic zone (EZ) in 18 out of 21 patients undergoing surgical treatment for clinically diagnosed insular epilepsy. While dipole clusters of spikes were involved in the insular EZ in 15 patients. Both the HFOs and the dipole cluster were localized in the insula in 14 patients. The seizure-free percentage was 87% for the resection of brain regions generating HFOs, whereas 80% for the resection of brain regions generating spikes. There was a much higher chance of freedom from seizures with complete resection of the HFO-generating regions than with partial resection or no resection (P = 0.031). No such difference was seen for spike-generating regions. Our results suggest that HFOs from insular epilepsy could be noninvasively detected and quantitatively assessed with MEG technology. MEG HFOs (ripples during spikes) may be valuable for the localization of the epileptogenic zone in insular epilepsy.

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.

Neuromagnetic correlates of audiovisual word processing in the developing brain

The brain undergoes enormous changes during childhood. Little is known about how the brain develops to serve word processing. The objective of the present study was to investigate the maturational changes of word processing in children and adolescents using magnetoencephalography (MEG). Responses to a word processing task were investigated in sixty healthy participants. Each participant was presented with simultaneous visual and auditory word pairs in "match" and "mismatch" conditions. The patterns of neuromagnetic activation from MEG recordings were analyzed at both sensor and source levels. Topography and source imaging revealed that word processing transitioned from bilateral connections to unilateral connections as age increased from 6 to 17 years old. Correlation analyses of language networks revealed that the path length of word processing networks negatively correlated with age (r = -0.833, p < 0.0001), while the connection strength (r = 0.541, p < 0.01) and the clustering coefficient (r = 0.705, p < 0.001) of word processing networks were positively correlated with age. In addition, males had more visual connections, whereas females had more auditory connections. The correlations between gender and path length, gender and connection strength, and gender and clustering coefficient demonstrated a developmental trend without reaching statistical significance. The results indicate that the developmental trajectory of word processing is gender specific. Since the neuromagnetic signatures of these gender-specific paths to adult word processing were determined using non-invasive, objective, and quantitative methods, the results may play a key role in understanding language impairments in pediatric patients in the future.

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.

Altered Effective Connectivity Network in Childhood Absence Epilepsy: A Multi-frequency MEG Study

Using multi-frequency magnetoencephalography (MEG) data, we investigated whether the effective connectivity (EC) network of patients with childhood absence epilepsy (CAE) is altered during the inter-ictal period in comparison with healthy controls. MEG data from 13 untreated CAE patients and 10 healthy controls were recorded. Correlation analysis and Granger causality analysis were used to construct an EC network at the source level in eight frequency bands. Alterations in the spatial pattern and topology of the network in CAE were investigated by comparing the patients with the controls. The network pattern was altered mainly in 1-4 Hz, showing strong connections within the frontal cortex and weak connections in the anterior-posterior pathways. The EC involving the precuneus/posterior cingulate cortex (PC/PCC) significantly decreased in low-frequency bands. In addition, the parameters of graph theory were significantly altered in several low- and high-frequency bands. CAE patients display frequency-specific abnormalities in the network pattern even during the inter-ictal period, and the frontal cortex and PC/PCC might play crucial roles in the pathophysiology of CAE. The EC network of CAE patients was over-connective and random during the inter-ictal period. This study is the first to reveal the frequency-specific alteration in the EC network during the inter-ictal period in CAE patients. Multiple-frequency MEG data are useful in investigating the pathophysiology of CAE, which can serve as new biomarkers of this disorder.

Dynamic Changes in Spectral and Spatial Signatures of High Frequency Oscillations in Rat Hippocampi during Epileptogenesis in Acute and Chronic Stages

Objective

To analyze spectral and spatial signatures of high frequency oscillations (HFOs), which include ripples and fast ripples (FRs, >200 Hz) by quantitatively assessing average and peak spectral power in a rat model of different stages of epileptogenesis.

Methods

The lithium–pilocarpine model of temporal lobe epilepsy was used. The acute phase of epilepsy was assessed by recording intracranial electroencephalography (EEG) activity for 1 day after status epilepticus (SE). The chronic phase of epilepsy, including spontaneous recurrent seizures (SRSs), was assessed by recording EEG activity for 28 days after SE. Average and peak spectral power of five frequency bands of EEG signals in CA1, CA3, and DG regions of the hippocampus were analyzed with wavelet and digital filter.

Results

FRs occurred in the hippocampus in the animal model. Significant dynamic changes in the spectral power of FRS were identified in CA1 and CA3. The average spectral power of ripples increased at 20 min before SE (p < 0.05), peaked at 10 min before diazepam injection. It decreased at 10 min after diazepam (p < 0.05) and returned to baseline after 1 h. The average spectral power of FRs increased at 30 min before SE (p < 0.05) and peaked at 10 min before diazepam. It decreased at 10 min after diazepam (p < 0.05) and returned to baseline at 2 h after injection. The dynamic changes were similar between average and peak spectral power of FRs. Average and peak spectral power of both ripples and FRs in the chronic phase showed a gradual downward trend compared with normal rats 14 days after SE.

Significance

The spectral power of HFOs may be utilized to distinguish between normal and pathologic HFOs. Ictal average and peak spectral power of FRs were two parameters for predicting acute epileptic seizures, which could be used as a new quantitative biomarker and early warning marker of seizure. Changes in interictal HFOs power in the hippocampus at the chronic stage may be not related to seizure occurrence.

Quantitative neuromagnetic signatures of aberrant cortical excitability in pediatric chronic migraine

Background

Reports have suggested that abnormal cortical excitability may be associated with acute migraines. The present study quantitatively assesses the degree of cortical excitability in chronic migraine as compared to acute migraine and healthy controls within the pediatric population.

Methods

We investigated 27 children suffering from chronic migraine, 27 children suffering from acute migraine, and 27 healthy controls using a magnetoencephalography (MEG) system, recording at a sampling rate of 6000 Hz. All groups were age-matched and gender-matched. Neuromagnetic brain activation was elicited by a finger-tapping motor task. The spatiotemporal and spectral signatures of MEG data within a 5–2884 Hz range were analyzed using Morlet wavelet transform and beamformer analyses.

Results

Compared with controls, the chronic migraine group showed (1) significantly prolonged latencies of movement-elicited magnetic fields (MEFs) between 5 and 100 Hz; (2) increased spectral power between 100 and 200 Hz, and between 2200 and 2800 Hz; and (3) a higher likelihood of neuromagnetic activation in the ipsilateral sensorimotor cortices, supplementary motor area, and occipital regions. Compared with acute migraine group, chronic migraine patients showed (1) significantly higher odds of having strong MEFs after 150 ms; and (2) significantly higher odds of having neuromagnetic activation from the deep brain areas.

Conclusions

Results demonstrated that chronic migraine subjects were not only different from the healthy controls, but also different from acute migraine subjects. The chronification of migraines may be associated with elevated cortical excitability, delayed and spread neural response, as well as aberrant activation from deep brain areas.

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.

Spatial Heterogeneity of Cortical Excitability in Migraine Revealed by Multifrequency Neuromagnetic Signals

To investigate the spatial heterogeneity of cortical excitability in adolescents with migraine, magnetoencephalography (MEG) recordings at a sampling rate of 6,000 Hz were obtained from 35 adolescents with an acute migraine and 35 age- and sex-matched healthy control participants during an auditory-motor task. Neuromagnetic activation from low- to high-frequency ranges (5-1,000 Hz) was measured at sensor and source levels. The heterogeneity of cortical excitability was quantified within each functional modality (auditory vs motor) and hemispherical lateralization. MEG data showed that high-frequency, not low-frequency neuromagnetic signals, showed heterogeneous cortical activation in migraine subjects compared with control participants (P < .001). The alteration of the heterogeneity of cortical excitability in migraine subjects was independent of age and sex. The degree of the neuromagnetic heterogeneity of cortical activation was significantly correlated with headache frequency (r = .71, P < .005). The alteration of cortical excitability in migraine subjects was spatially heterogeneous and frequency dependent, which previously has not been reported. The finding may be critical for developing spatially targeted therapeutic strategies for normalizing cortical excitability with the purpose of reducing headache attacks.

PERSPECTIVE

This article presents a new approach to quantitatively measure the spatial heterogeneity of cortical excitability in adolescents with migraine using MEG signals in a frequency range of 5 to 1,000 Hz. The characteristics of the location and degree of cortical excitability may be critical for spatially targeted treatment for migraine.

Multi-frequency localization of aberrant brain activity in autism spectrum disorder

OBJECTIVE

The abnormality of intrinsic brain activity in autism spectrum disorders (ASDs) is still inconclusive. Contradictory results have been found pointing towards hyper-activity or hypo-activity in various brain regions. The present research aims to investigate the spatial and spectral signatures of aberrant brain activity in an unprecedented frequency range of 1-2884 Hz at source levels in ASD using newly developed methods.

MATERIALS AND METHODS

Seven ASD subjects and age- and gender-matched controls were studied using a high-sampling rate magnetoencephalography (MEG) system. Brain activity in delta (1-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), beta (12-30 Hz), low gamma (30-55 Hz), high gamma (65-90 Hz), ripples (90-200 Hz), high-frequency oscillations (HFOs, 200-1000 Hz), and very high-frequency oscillations (VHFOs, 1000-2884 Hz) was volumetrically localized and measured using wavelet and beamforming.

RESULTS

In comparison to controls, ASD subjects had significantly higher odds of alpha activity (8-12 Hz) in the sensorimotor cortex (mu rhythm), and generally high-frequency activity (90-2884 Hz) in the frontal cortex. The source power of HFOs (200-1000 Hz) in the frontal cortex in ASD was significantly elevated as compared with controls.

CONCLUSION

The results suggest that ASD has significantly altered intrinsic brain activity in both low- and high-frequency ranges. Increased intrinsic high-frequency activity in the frontal cortex may play a key role in ASD.