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Recording from deep neural structures such as hippocampus non-invasively and yet with high temporal resolution remains a major challenge for human neuroscience. Although it has been proposed that deep neuronal activity might be recordable during cognitive tasks using magnetoencephalography (MEG), this remains to be demonstrated as the contribution of deep structures to MEG recordings may be too small to be detected or might be eclipsed by the activity of large-scale neocortical networks. In the present study, we disentangled mesial activity and large-scale networks from the MEG signals thanks to blind source separation (BSS). We then validated the MEG BSS components using intracerebral EEG signals recorded simultaneously in patients during their presurgical evaluation of epilepsy. In the MEG signals obtained during a memory task involving the recognition of old and new images, we identified with BSS a putative mesial component, which was present in all patients and all control subjects. The time course of the component selectively correlated with SEEG signals recorded from hippocampus and rhinal cortex, thus confirming its mesial origin. This finding complements previous studies with epileptic activity and opens new possibilities for using MEG to study deep brain structures in cognition and in brain disorders.

OBJECTIVE This study aims to evaluate the utility of magnetoencephalography in presurgical planning and in predicting post-surgical seizure outcome. METHODS This study included a cohort of 231 children (1-18 years) with focal drug-resistant epilepsy who underwent MEG as a part of their presurgical workup. Characteristics of MEG observations were described in all children. The concordance and agreement of Magnetic Source Imaging (MSI) of interictal discharges (IED) was estimated with either of the 3 subgroups - MRI lesion; presumed epileptogenic zone (EZ); or resection cavity. In operated children group, MEG dipole characteristics between good and poor outcome groups were assessed. RESULTS A total of 153 cases (66.2%) showed frequent IEDs (60 spikes/60 min). Of the 173 cases where MSI showed clusters (74.9%), 151 had lesions and 22 were non-lesional. amongst patients with lesional epilepsy and MEG clusters, class I concordance (MEG localization either completely included or overlapped at least 60% with the MRI lesion) was seen in 60.92% with a Cohen's kappa of 0.608. In non-lesional epilepsy, class I concordance of MEG with presumed EZ was found in (81.81%) with an agreement of 0.317. Fifty-three children underwent surgery of whom 39 (73.58%) showed a good outcome (Engel I). In operated children, concordance between MEG focus and resection cavity was observed in 23 (58.97%) with good outcome and in 12 (86.72%) with poor outcome with no significant difference (p>0.05). However, MEG cluster regular organization and clusterectomy are associated with good seizure outcome postoperatively (p< 0.05). Presence of scatters were associated with poor outcome (p

Objective The purpose of this study is to localize the sources of epileptiform discharges (EDs), in juvenile myoclonic epilepsy (JME) using Magnetoencephalography (MEG), at three different time instances and analyze the propagation of EDs, from onset to offset, for inferring the cortical and subcortical region of involvement. Methods Twenty patients (age 23.5±6.3years old) with JME were recruited in this prospective study. MEG source analysis was performed on the independently collected EDs of each patient. The distributed source model was employed for source localization using low resolution electromagnetic brain tomography (LORETA). In each EDs, the onset (leading edge of the spike from baseline), peak and offset (trailing edge of the spike), with time window of 8ms, were subjected for source localization in order to study the propagation of the EDs. The obtained source location coordinates, from each individual MRI, were transformed in Talairach space and the distribution of region of source involvement was analysed. Results The frequency pattern of lobar distribution at onset, peak and offset respectively suggest that discharges most commonly localized at onset from sublobar region, at peak from frontal lobe and at offset from the sublobar region. It was observed that the maximum involvement of sources from the sublobar, limbic and frontal lobes at different time instances. It indicates that the restricted cortical-subcortical involvement during the generation and propagation of EDs in JME. Significance This MEG study supported the cortical-subcortical region of involvement and provided further insights in our understanding the network involvement in generation and propagation of EDs in JME.

Introduction Accurate delineation of epileptogenic zone(EZ) is crucial in patients with medically refractory epilepsy (MRE) warranting surgery and at least 33% will have seizure recurrence post-surgery. Intracranial EEG studies had showed that high frequency oscillations (HFO; 80–200 Hz) can accurately localize the EZ and patients had better post-surgical seizure freedom, if brain regions generating HFOs were resected out. However, none of the noninvasive studies evaluated the clinical utility of HFOs. So, we investigated epileptic HFOs source imaging to delineate the presurgical EZ and predict the seizure freedom. Methods Fifty-two patients (M: F = 37:15; age = 23 ± 8.9 years; disease duration 11.4 ± 7.7 years) with MRE were longitudinally recruited and studied with MEG. Each interictal epileptic discharge were marked by assessing spatial topography. Subject specific semi-realistic head model and a 3D grid voxels of 10 mm resolution was constructed. Source reconstruction was performed with frequency beamformer, by attenuating the source power at a specified location, subject to unit-gain constraint. Gain matrix was determined and cross-spectral density matrix on a Fourier transformed data was calculated at 7 distinct frequency bands; 8–14 Hz, 14–30 Hz, 1–30 Hz, 30–54 Hz, 55–80 Hz, 30–80 Hz, and 80–200 Hz. From the available clinical data, EZ was defined, respective surgery was performed and surgical outcome was assessed. The congruency of source construction with the EZ and surgically resected cortex was established at four levels, for each band & strength was quantified by kappa statistic. Sensitivity, positive predictive value (PPV) and accuracy was evaluated. Source localization error (SLE) was determined on the basis of minimum euclidean distance between the margin of reconstructed sources with the volume of the resected cortex. Results With surgery, 44 (84.6%) patients had good (Engel-I) and 8 (15.4%) patients had poor (Engel-II-IV) clinical outcome at 22.1 ± 10 months follow up. Compared to other frequency bands, interictal HFO imaging accurately delineated the epileptogenic cortex in 80.3% (k = 0.44 ± 0.12) of the patients, with 80.8% sensitivity, 100% PPV, and 80.32% accuracy. The highest possible concordance rate of 78.8% (k = 0.46 ± 0.1) with the surgically resected cortical volume, was observed for the reconstructed HFO sources. HFO source reconstruction did correlate with the seizure freedom (p Conclusion To date, this is the first ever largest prospective & noninvasive (MEG) study to investigate the clinical role of the HFOs, where HFOs precisely delineated the EZ & predicted the patients who might achieve seizure freedom with surgery, emerging as a key noninvasive epilepsy biomarker.

Introduction 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) for each subgroup and at each source montage. HFO source localization was consistent between algorithms (k = 0.8570 ± 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 Conclusion HFOs could reliably be detected in the MEG periictal state, and its sources were accurately localized in almost 95% of the patients with medically refractory epilepsy. During preictal to ictal transition, HFOs exhibited dynamic augmentation in intrinsic epileptogenicity. Spatial overlap of ictal HFO sources was consistent with EZ determinants including the presumed EZ and the surgical resection area.