Network alterations in temporal lobe epilepsy during non-rapid eye movement sleep and wakefulness.

OBJECTIVE: Investigate sleep and temporal lobe epilepsy (TLE) effects on brain networks derived from electroencephalography (EEG). METHODS: High-density EEG was recorded during non-rapid eye movement (NREM) sleep stage 2 (N2) and wakefulness in 23 patients and healthy controls (HC). Epochs without epileptic discharges were source-reconstructed in 72 brain regions and connectivity was estimated. We calculated network integration and segregation at global (global efficiency, GE; average clustering coefficient, avgCC) and hemispheric level. These were compared between groups across frequency bands and correlated with the individual proportion of wakefulness- or sleep-related seizures. RESULTS: At the global level, patients had higher delta GE, delta avgCC and theta avgCC than controls, irrespective of the vigilance state. During wakefulness, theta GE of patients was higher than controls and, for patients, theta GE during wakefulness was higher than during N2. Wake-to-sleep differences in TLE were notable only in the ipsilateral hemisphere. Only measures from wakefulness recordings correlated with the proportion of wakefulness- or sleep-related seizures. CONCLUSIONS: TLE network alterations are more prominent during wakefulness and at lower frequencies. Increased integration and segregation suggest a pathological 'small world' configuration with a possible inhibitory role. SIGNIFICANCE: Network alterations in TLE occur and are easier to detect during wakefulness.

Structure-function coupling increases during interictal spikes in temporal lobe epilepsy: A graph signal processing study.

OBJECTIVE: Structure-function coupling remains largely unknown in brain disorders. We studied this coupling during interictal epileptic discharges (IEDs), using graph signal processing in temporal lobe epilepsy (TLE). METHODS: We decomposed IEDs of 17 patients on spatial maps, i.e. network harmonics, extracted from a structural connectome. Harmonics were split in smooth maps (long-range interactions reflecting integration) and coarse maps (short-range interactions reflecting segregation) and were used to reconstruct the part of the signal coupled (Xc) and decoupled (Xd) from the structure, respectively. We analysed how Xc and Xd embed the IED energy over time, at global and regional level. RESULTS: For Xc, the energy was smaller than for Xd before the IED onset (p < .001), but became larger around the first IED peak (p < .05, cluster 2, C2). Locally, the ipsilateral mesial regions were significantly coupled to the structure over the whole epoch. The ipsilateral hippocampus increased its coupling during C2 (p < .01). CONCLUSIONS: At whole-brain level, segregation gives way to integrative processes during the IED. Locally, brain regions commonly involved in the TLE epileptogenic network increase their reliance on long-range couplings during IED (C2). SIGNIFICANCE: In TLE, integration mechanisms prevail during the IED and are localized in the ipsilateral mesial temporal regions.

Deep brain activities can be detected with magnetoencephalography.

The hippocampus and amygdala are key brain structures of the medial temporal lobe, involved in cognitive and emotional processes as well as pathological states such as epilepsy. Despite their importance, it is still unclear whether their  neural activity can be recorded non-invasively. Here, using simultaneous intracerebral and magnetoencephalography (MEG) recordings in patients with focal drug-resistant epilepsy, we demonstrate a direct contribution of amygdala and hippocampal activity to surface MEG recordings. In particular, a method of blind source separation, independent component analysis, enabled activity arising from large neocortical networks to be disentangled from that of deeper structures, whose amplitude at the surface was small but significant. This finding is highly relevant for our understanding of hippocampal and amygdala brain activity as it implies that their activity could potentially be measured non-invasively.

EpiTools, A software suite for presurgical brain mapping in epilepsy: Intracerebral EEG.

BACKGROUND: In pharmacoresistant epilepsy, exploration with depth electrodes can be needed to precisely define the epileptogenic zone. Accurate location of these electrodes is thus essential for the interpretation of Stereotaxic EEG (SEEG) signals. As SEEG analysis increasingly relies on signal processing, it is crucial to make a link between these results and patient's anatomy. Our aims were thus to develop a suite of software tools, called "EpiTools", able to i) precisely and automatically localize the position of each SEEG contact and ii) display the results of signal analysis in each patient's anatomy. NEW METHOD: The first tool, GARDEL (GUI for Automatic Registration and Depth Electrode Localization), is able to automatically localize SEEG contacts and to label each contact according to a pre-specified nomenclature (for instance that of FreeSurfer or MarsAtlas). The second tool, 3Dviewer, enables to visualize in the 3D anatomy of the patient the origin of signal processing results such as rate of biomarkers, connectivity graphs or Epileptogenicity Index. RESULTS: GARDEL was validated in 30 patients by clinicians and proved to be highly reliable to determine within the patient's individual anatomy the actual location of contacts. COMPARISON WITH EXISTING METHODS: GARDEL is a fully automatic electrode localization tool needing limited user interaction (only for electrode naming or contact correction). The 3Dviewer is able to read signal processing results and to display them in link with patient's anatomy. CONCLUSION: EpiTools can help speeding up the interpretation of SEEG data and improving its precision.