Reconstruction and localization of auditory sources from intracerebral SEEG using independent component analysis.

Stereo-electroencephalography (SEEG) is the surgical implantation of electrodes in the brain to better localize the epileptic network in pharmaco-resistant epileptic patients. This technique has exquisite spatial and temporal resolution. Still, the number and the position of the electrodes in the brain is limited and determined by the semiology and/or preliminary non-invasive examinations, leading to a large number of unexplored brain structures in each patient. Here, we propose a new approach to reconstruct the activity of non-sampled structures in SEEG, based on independent component analysis (ICA) and dipole source localization. We have tested this approach with an auditory stimulation dataset in ten patients. The activity directly recorded from the auditory cortex served as ground truth and was compared to the ICA applied on all non-auditory electrodes. Our results show that the activity from the auditory cortex can be reconstructed at the single trial level from contacts as far as ∼40 mm from the source. Importantly, this reconstructed activity is localized via dipole fitting in the proximity of the original source. In addition, we show that the size of the confidence interval of the dipole fitting is a good indicator of the reliability of the result, which depends on the geometry of the SEEG implantation. Overall, our approach allows reconstructing the activity of structures far from the electrode locations, partially overcoming the spatial sampling limitation of intracerebral recordings.

Comparison of beamformer and ICA for dynamic connectivity analysis: A simultaneous MEG-SEEG study.

Magnetoencephalography (MEG) is a powerful tool for estimating brain connectivity with both good spatial and temporal resolution. It is particularly helpful in epilepsy to characterize non-invasively the epileptic networks. However, using MEG to map brain networks requires solving a difficult inverse problem that introduces uncertainty in the activity localization and connectivity measures. Our goal here was to compare independent component analysis (ICA) followed by dipole source localization and the linearly constrained minimum-variance beamformer (LCMV-BF) for characterizing regions with interictal epileptic activity and their dynamic connectivity. After a simulation study, we compared ICA and LCMV-BF results with intracerebral EEG (stereotaxic EEG, SEEG) recorded simultaneously in 8 epileptic patients, which provide a unique 'ground truth' to which non-invasive results can be confronted. We compared the signal time courses extracted applying ICA and LCMV-BF on MEG data to that of SEEG, both for the actual signals and the dynamic connectivity computed using cross-correlation (evolution of links in time). With our simulations, we illustrated the different effect of the temporal and spatial correlation among sources on the two methods. While ICA was more affected by the temporal correlation but robust against spatial configurations, LCMV-BF showed opposite behavior. Moreover, ICA seems more suited to retrieve the simulated networks. In case of real patient data, good MEG/SEEG correlation and good localization were obtained in 6 out of 8 patients. In 4 of them ICA had the best performance (higher correlation, lower localization distance). In terms of dynamic connectivity, the evolution in time of the cross-correlation links could be retrieved in 5 patients out of 6, however, with more variable results in terms of correlation and distance. In two patients LCMV-BF had better results than ICA. In one patient the two methods showed equally good outcomes, and in the remaining two patients ICA performed best. In conclusion, our results obtained by exploiting simultaneous MEG/SEEG recordings suggest that ICA and LCMV-BF have complementary qualities for retrieving the dynamics of interictal sources and their network interactions.

Virtual MEG sensors based on beamformer and independent component analysis can reconstruct epileptic activity as measured on simultaneous intracerebral recordings.

The prevailing gold standard for presurgical determination of epileptogenic brain networks is intracerebral EEG, a potent yet invasive approach. Magnetoencephalography (MEG) is a state-of-the art non-invasive method for investigating epileptiform discharges. However, it is not clear at what level the precision offered by MEG can reach that of SEEG. Here, we present a strategy for non-invasively retrieving the constituents of the interictal network, with high spatial and temporal precision. Our method is based on MEG and a combination of spatial filtering and independent component analysis (ICA). We validated this approach in twelve patients with drug-resistant focal epilepsy, thanks to the unprecedented ground truth provided by simultaneous recordings of MEG and SEEG. A minimum variance adaptive beamformer estimated the source time series and ICA was used to further decompose these time series into network constituents (MEG-ICs), each having a time series (virtual electrode) and a topography (spatial distribution of amplitudes in the brain). We show that MEG has a considerable sensitivity of 0.80 and 0.84 and a specificity of 0.93 and 0.91 for reconstructing deep and superficial sources, respectively, when compared to the ground truth (SEEG). For each epileptic MEG-IC (n = 131), we found at least one significantly correlating SEEG contact close to zero lag after correcting for multiple comparisons. All the patients except one had at least one epileptic component that was highly correlated (Spearman rho>0.3) with that of SEEG traces. MEG-ICs correlated well with SEEG traces. The strength of correlation coefficients did not depend on the depth of the SEEG contacts or the clinical outcome of the patient. A significant proportion of the MEG-ICs (n = 83/131) were localized in proximity with their maximally correlating SEEG, within a mean distance of 20±12.18mm. Our research is the first to validate the MEG-retrieved beamformer IC sources against SEEG-derived ground truth in a simultaneous MEG-SEEG framework. Observations from the present study suggest that non-invasive MEG source components may potentially provide additional information, comparable to SEEG in a number of instances.

EEG-based P300 in mesial temporal lobe epilepsy and its correlation with cognitive functions: A case-control study.

OBJECTIVE: P300 is an event-related potential, being explored as an objective tool to assess cognition. This study aimed to investigate the characteristics of auditory and visual P300 in patients with TLE having unilateral HS using electroencephalography (EEG) and to study its correlation with cognition. METHODS: This is a cross-sectional case-control study, where P300 characteristics in thirty patients with unilateral hippocampal sclerosis with refractory epilepsy were compared with fifteen age-, gender-, and years of education-matched healthy controls (M: F-10:5, mean age-28 ±â€¯4.76 years). Among patients, 15 belonged to the right HS group (M: F-9:6, age at onset-12.92 ±â€¯10.22 years, duration of epilepsy-16.67 ±â€¯9.38 years) and 15 to the left HS group (M: F-8:7, age at onset-10.62 ±â€¯7.18 years, duration of epilepsy-15.53 ±â€¯10.14 years). All subjects underwent EEG-based auditory and visual oddball tasks and cognitive assessment. The P300 latencies (in milliseconds) as well as amplitudes (in microvolts) were predicted in EEG and were correlated with cognitive scores. Source localization of P300 was performed with the CLARA algorithm. RESULTS: The auditory P300 latencies in controls, right HS, and left HS were 323.93 ±â€¯40.28, 351.06 ±â€¯47.23, and 328.80 ±â€¯36.03, respectively (p = 0.18) and its amplitudes were 2.3040 ±â€¯1.46, 2.77 ±â€¯1.19, and 2.68 ±â€¯1.78, respectively (p = 0.48). Visual P300 latencies in controls, right HS, and left HS were 365.87 ±â€¯47.37, 359.67 ±â€¯64.45, and 376.00 ±â€¯60.06, respectively (p = 0.51) and its amplitudes were 3.93 ±â€¯2.28, 2.09 ±â€¯1.45, and 3.56 ±â€¯1.74, respectively (p = 0.014). Further, when compared to the control group the cognitive scores were lower in the patient group (p < 0.05). SIGNIFICANCE: In comparison to the controls, patients with right HS recorded lesser amplitude on visual P300 and lower scores on cognitive tests. P300 and cognitive parameters exhibited varied relationship. P300 could be a complementary objective tool to assess cognition in patients with TLE.

P300 in mesial temporal lobe epilepsy and its correlation with cognition - A MEG based prospective case-control study.

PURPOSE: To assess the role of P300 in patients with temporal lobe epilepsy (TLE) with unilateral hippocampal sclerosis (HS) using magnetoencephalography (MEG) based auditory and visual oddball tasks, and to assess its correlation with neuropsychological tests. METHODS: Thirty-patients (M:F-17:13, onset-11.77 ±â€¯8.75 years, duration-16.10 ±â€¯9.61 years) with TLE-HS (Left:15, Right:15) and fifteen-healthy age, gender and years of education matched controls (M:F-10:5, age-28.13 ±â€¯4.76 years) underwent auditory and visual oddball tasks in MEG and cognition assessment using Indian Council of Medical Research (ICMR)-cognitive test battery. Independent component analysis (ICA) was applied to the magnetic evoked field responses for the detection of the P300 component. Source localization of P300 was performed with Classical LORETA Analysis Recursively Applied (CLARA). The latency and amplitude of P300 were estimated and subsequently correlated with cognitive scores. RESULTS: The visual P300 amplitude in the TLE group was lower when compared to the control group. In subgroup comparison (controls vs. right HS vs. left HS), visual P300 amplitudes were lower in the right HS group compared to both left HS and control groups (p-value = 0.014). On the other hand, no significant difference for auditory P300 latency or amplitude was noted between patients and controls as well as between subgroups. A negative correlation found between the MEG visual P300 amplitude and Indian Trial Making Test (TMT)-B duration in the patient group. CONCLUSION: Patients with TLE-HS have decreased visual-P300 amplitude. A significant correlation found between visual P300 amplitude and cognitive tests of visuospatial attention and working memory. Overall, MEG based visual P300 amplitude can be further explored with large sample size studies to establish as a complementary objective test for cognitive assessment in TLE.

Magnetoencephalography imaging of high frequency oscillations strengthens presurgical localization and outcome prediction.

In patients with medically refractory epilepsy, resective surgery is the mainstay of therapy to achieve seizure freedom. However, ∼20-50% of cases have intractable seizures post-surgery due to the imprecise determination of epileptogenic zone. Recent intracranial studies suggest that high frequency oscillations between 80 and 200 Hz could serve as one of the consistent epileptogenicity biomarkers for localization of the epileptogenic zone. However, these high frequency oscillations are not adopted in the clinical setting because of difficult non-invasive detection. Here, we investigated non-invasive detection and localization of high frequency oscillations and its clinical utility in accurate pre-surgical assessment and post-surgical outcome prediction. We prospectively recruited 52 patients with medically refractory epilepsy who underwent standard pre-surgical workup including magnetoencephalography (MEG) followed by resective surgery after determination of the epileptogenic zone. The post-surgical outcome was assessed after 22.14 ± 10.05 months. Interictal epileptic spikes were expertly identified, and interictal epileptic oscillations across the neural activity frequency spectrum from 8 to 200 Hz were localized using adaptive spatial filtering methods. Localization results were compared with epileptogenic zone and resected cortex for congruence assessment and validated against the clinical outcome. The concordance rate of high frequency oscillations sources (80-200 Hz) with the presumed epileptogenic zone and the resected cortex were 75.0% and 78.8%, respectively, which is superior to that of other frequency bands and standard dipole fitting methods. High frequency oscillation sources corresponding with the resected cortex, had the best sensitivity of 78.0%, positive predictive value of 100% and an accuracy of 78.84% to predict the patient's surgical outcome, among all other frequency bands. If high frequency oscillation sources were spatially congruent with resected cortex, patients had an odds ratio of 5.67 and 82.4% probability of achieving a favourable surgical outcome. If high frequency oscillations sources were discordant with the epileptogenic zone or resection area, patient has an odds ratio of 0.18 and only 14.3% probability of achieving good outcome, and mostly tended to have an unfavourable outcome (χ2 = 5.22; P = 0.02; φ = -0.317). In receiver operating characteristic curve analyses, only sources of high-frequency oscillations demonstrated the best sensitivity and specificity profile in determining the patient's surgical outcome with area under the curve of 0.76, whereas other frequency bands indicate a poor predictive performance. Our study is the first non-invasive study to detect high frequency oscillations, address the efficacy of high frequency oscillations over the different neural oscillatory frequencies, localize them and clinically validate them with the post-surgical outcome in patients with medically refractory epilepsy. The evidence presented in the current study supports the fact that HFOs might significantly improve the presurgical assessment, and post-surgical outcome prediction, where it could widely be used in a clinical setting as a non-invasive biomarker.

Evaluation of a dual signal subspace projection algorithm in magnetoencephalographic recordings from patients with intractable epilepsy and vagus nerve stimulators.

Magnetoencephalography (MEG) data is subject to many sources of environmental noise, and interference rejection is a necessary step in the processing of MEG data. Large amplitude interference caused by sources near the brain have been common in clinical settings and are difficult to reject. Artifact from vagal nerve stimulators (VNS) is a prototypical example. In this study, we describe a novel MEG interference rejection algorithm called dual signal subspace projection (DSSP), and evaluate its performance in clinical MEG data from people with epilepsy and implanted VNS. The performance of DSSP was evaluated in a retrospective cohort study of patients with epilepsy and VNS who had MEG scans for source localization of interictal epileptiform discharges. DSSP was applied to the MEG data and compared with benchmark for performance. We evaluated the clinical impact of interference rejection based on human expert detection and estimation of the location and time-course of interictal spikes, using an empirical Bayesian source reconstruction algorithm (Champagne). Clinical recordings, after DSSP processing, became more readable and a greater number of interictal epileptic spikes could be clearly identified. Source localization results of interictal spikes also significantly improved from those achieved before DSSP processing, including meaningful estimates of activity time courses. Therefore, DSSP is a valuable novel interference rejection algorithm that can be successfully deployed for the removal of strong artifacts and interferences in MEG.

Magnetoencephalographic imaging of ictal high-frequency oscillations (80-200 Hz) in pharmacologically resistant focal epilepsy.

OBJECTIVE: Specificity of ictal high-frequency oscillations (HFOs) in identifying epileptogenic abnormality is significant, compared to the spikes and interictal HFOs. The objectives of the study were to detect and to localize ictal HFOs by magnetoencephalography (MEG) for identifying the seizure onset zone (SOZ), evaluate the cortical excitability from preictal to ictal transition, and establish HFO concordance rates with other modalities and postsurgical resection. METHODS: Sixty-seven patients with drug-resistant epilepsy had at least 1 spontaneous seizure each during MEG acquisition, and analysis was carried out on 20 seizures from 20 patients. Ictal MEG data were bandpass filtered (80-200 Hz) to visualize, review, and analyze the HFOs co-occurring with ictal spikes. Source montages were generated on both hemispheres, mean fast Fourier transform was computed on virtual time series for determining the preictal to ictal spectral power transition, and source reconstruction was performed with sLORETA and beamformers. The concordance rates of ictal MEG HFOs (SOZ) was estimated with 4 reference epileptogenic regions. RESULTS: In each subject, transient bursts of high-frequency oscillatory cycles, distinct from the background activity, were observed in the periictal continuum. Time-frequency analysis showed significant spectral power surge (85-160 Hz) during ictal state (P < .05) compared to preictal state, but there was no variation in the peak HFO frequencies (P > .05) for each subgroup and at each source montage. HFO source localization was consistent between algorithms (k = 0.857 ± 0.138), with presumed epileptogenic zone (EZ) comparable to other modalities. In patients who underwent surgery (n = 6), MEG HFO SOZ was concordant with the presumed EZ and the surgical resection site (100%), and all were seizure-free during follow-up. SIGNIFICANCE: HFOs could be detected in the MEG periictal state, and its sources were accurately localized. During preictal to ictal transition, HFOs exhibited dynamic augmentation in intrinsic epileptogenicity. Spatial overlap of ictal HFO sources was consistent with EZ determinants and the surgical resection area.

Source analysis of epileptiform discharges in absence epilepsy using Magnetoencephalography (MEG).

PURPOSE: Magnetoencephalography (MEG) was used to record and localize the sources of the epileptiform discharges, in absence epilepsy, at three different time intervals to infer the sources of involvement during generation and propagation. METHODS: Twenty patients with absence epilepsy (M:F=1:1; age: 10.2±3.4years), which included 12 patients with childhood absence epilepsy (CAE) and 8 patients with juvenile absence epilepsy (JAE), were recruited in this prospective MEG based study. MEG epileptiform discharges were divided into three sub-groups based on the duration viz., 1s (very short),>1-9.9s (short) and ≥10s (long) and the discharges of each group were averaged independently in each patient. MEG source analysis was performed on these averaged discharges, of each of the subgroups, at the onset, during middle and offset. RESULTS: The source locations obtained, in lobar and gyri levels, were compared across these three groups of varying duration of discharges and in the CAE and JAE subjects. It was observed that the most frequent location of sources from the sublobar, limbic and frontal lobes in all the discharge groups at different time intervals. Also, it was noted that there were only subtle and variable degree of the differences of source localization of epileptic discharges among CAE and JAE subgroups. CONCLUSION: The study provided novel findings regarding origin and propagation of sources of epileptiform discharges in patients with childhood and juvenile absence epilepsies. Such analysis further improves the understanding of network involvement of subcortical and cortical regions in these patients.

Ictal Generalized EEG Attenuation (IGEA) and hypopnea in a child with occipital type 1 cortical dysplasia - Is it a biomarker for SUDEP?

An interesting association of ictal hypopnea and ictal generalized EEG attenuation (IGEA) as possible marker of sudden unexpected death in epilepsy (SUDEP) is reported. We describe a 5-years-old girl with left focal seizures with secondary generalization due to right occipital cortical dysplasia presenting with ictal hypopnea and IGEA. She had repeated episodes of the ictal apnoea in the past requiring ventilator support and intensive care unit (ICU) admission during episodes of status epilepticus. The IGEA lasted for 0.26-4.68 seconds coinciding with the ictal hypopnea during which both clinical seizure and electrical epileptic activity stopped. Review of literature showed correlation between post-ictal apnoea and post ictal generalized EEG suppression and increased risk for SUDEP. The report adds to the growing body of literature on peri-ictal apnea, about its association with IGEA might be considered as a marker for SUDEP. She is seizure free for 4 months following surgery.

Magnetoencephalography recording and analysis.

Magnetoencephalography (MEG) non-invasively measures the magnetic field generated due to the excitatory postsynaptic electrical activity of the apical dendritic pyramidal cells. Such a tiny magnetic field is measured with the help of the biomagnetometer sensors coupled with the Super Conducting Quantum Interference Device (SQUID) inside the magnetically shielded room (MSR). The subjects are usually screened for the presence of ferromagnetic materials, and then the head position indicator coils, electroencephalography (EEG) electrodes (if measured simultaneously), and fiducials are digitized using a 3D digitizer, which aids in movement correction and also in transferring the MEG data from the head coordinates to the device and voxel coordinates, thereby enabling more accurate co-registration and localization. MEG data pre-processing involves filtering the data for environmental and subject interferences, artefact identification, and rejection. Magnetic resonance Imaging (MRI) is processed for correction and identifying fiducials. After choosing and computing for the appropriate head models (spherical or realistic; boundary/finite element model), the interictal/ictal epileptiform discharges are selected and modeled by an appropriate source modeling technique (clinically and commonly used - single equivalent current dipole - ECD model). The equivalent current dipole (ECD) source localization of the modeled interictal epileptiform discharge (IED) is considered physiologically valid or acceptable based on waveform morphology, isofield pattern, and dipole parameters (localization, dipole moment, confidence volume, goodness of fit). Thus, MEG source localization can aid clinicians in sublobar localization, lateralization, and grid placement, by evoking the irritative/seizure onset zone. It also accurately localizes the eloquent cortex-like visual, language areas. MEG also aids in diagnosing and delineating multiple novel findings in other neuropsychiatric disorders, including Alzheimer's disease, Parkinsonism, Traumatic brain injury, autistic disorders, and so oon.