ObjectiveTo analyze the association between peri-ictal brainstem posturing semiologies with post-ictal generalized electroencephalographic suppression (PGES) and breathing dysfunction in generalized convulsive seizures (GCS).MethodsProspective, multicenter analysis of GCS. Ictal brainstem semiology was classified as (1) decerebration: bilateral symmetric tonic arm extension, (2) decortication: bilateral symmetric tonic arm flexion only, (3) hemi-decerebration: unilateral tonic arm extension with contralateral flexion and (4) absence of ictal tonic phase. Post-ictal posturing was also assessed. Respiration was monitored using thoraco-abdominal belts, video and pulse oximetry.ResultsTwo hundred ninety-five seizures (180 patients) were analyzed. Ictal decerebration was observed in 122/295 (41.4%), decortication in 47/295 (15.9%) and hemi-decerebration in 28/295 (9.5%) seizures. Tonic phase was absent in 98/295 (33.2%) seizures. Postictal posturing occurred in 18/295 (6.1%) seizures. PGES risk increased with ictal decerebration (OR 14.79, 95% CI [6.18–35.39], p < 0.001), decortication (OR 11.26, 95% CI [2.96–42.93], p < 0.001), or hemi-decerebration (OR 48.56, 95% CI [6.07–388.78], p < 0.001) Ictal decerebration was associated with longer PGES (p = 0.011). Post-ictal posturing was associated with post-convulsive central apnea (PCCA) (p = 0.004), longer hypoxemia (p < 0.001) and SpO2 recovery (p = 0.035).ConclusionsIctal brainstem semiology is associated with increased PGES risk. Ictal decerebration is associated with longer PGES. Post-ictal posturing is associated with a threefold increased risk of PCCA, longer hypoxemia and SpO2 recovery. Peri-ictal brainstem posturing may be surrogate biomarkers for GCS severity identifiable without in-hospital monitoring.Classification of evidenceThis study provides Class III evidence that peri-ictal brainstem posturing is associated with the GCS with more prolonged PGES and more severe breathing dysfunction.

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There is growing evidence for neuronal hyperexcitability in Alzheimer’s disease (AD). Hyperexcitability is associated with an increase in epileptiform activity (EA) and the disruption of inhibitory activity of interneurons. Interneurons fire at a high rate and are frequently associated with high-frequency oscillations in the gamma frequency band (30–150 Hz). It is unclear how hyperexcitability affects the organization of functional brain networks. A sample of 63 amnestic mild cognitive impairment (MCI) patients underwent a Magnetoencephalography (MEG) resting-state recording with eyes closed. Twenty (31.75%) mild cognitive impairment patients had epileptiform activity. A cluster-based analysis of the Magnetoencephalography functional connectivity revealed a region within the right temporal cortex whose global connectivity in the gamma frequency band was significantly reduced in patients with epileptiform activity relative to those without epileptiform activity. A subsequent seed-based analysis showed that this was largely due to weaker gamma-band connectivity of this region with ipsilateral frontal and medial regions, and the upper precuneus area. In addition, this reduced functional connectivity was associated with higher gray matter atrophy across several cortical regions in the patients with epileptiform activity. These functional network disruptions and changes in brain physiology and morphology have important clinical implications as they may contribute to cognitive decline in mild cognitive impairment and Alzheimer’s disease.

Rationale: Seizure clusters may be related to Sudden Unexpected Death in Epilepsy (SUDEP). Two or more generalized convulsive seizures (GCS) were captured during video electroencephalography in 7/11 (64%) patients with monitored SUDEP in the MORTEMUS study. It follows that seizure clusters may be associated with epilepsy severity and possibly with SUDEP risk. We aimed to determine if electroclinical seizure features worsen from seizure to seizure within a cluster and possible associations between GCS clusters, markers of seizure severity, and SUDEP risk.Methods: Patients were consecutive, prospectively consented participants with drug-resistant epilepsy from a multi-center study. Seizure clusters were defined as two or more GCS in a 24-h period during the recording of prolonged video-electroencephalography in the Epilepsy monitoring unit (EMU). We measured heart rate variability (HRV), pulse oximetry, plethysmography, postictal generalized electroencephalographic suppression (PGES), and electroencephalography (EEG) recovery duration. A linear mixed effects model was used to study the difference between the first and subsequent seizures, with a level of significance set at p &lt; 0.05.Results: We identified 112 GCS clusters in 105 patients with 285 seizures. GCS lasted on average 48.7 ± 19 s (mean 49, range 2–137). PGES emerged in 184 (64.6%) seizures and postconvulsive central apnea (PCCA) was present in 38 (13.3%) seizures. Changes in seizure features from seizure to seizure such as seizure and convulsive phase durations appeared random. In grouped analysis, some seizure features underwent significant deterioration, whereas others improved. Clonic phase and postconvulsive central apnea (PCCA) were significantly shorter in the fourth seizure compared to the first. By contrast, duration of decerebrate posturing and ictal central apnea were longer. Four SUDEP cases in the cluster cohort were reported on follow-up.Conclusion: Seizure clusters show variable changes from seizure to seizure. Although clusters may reflect epilepsy severity, they alone may be unrelated to SUDEP risk. We suggest a stochastic nature to SUDEP occurrence, where seizure clusters may be more likely to contribute to SUDEP if an underlying progressive tendency toward SUDEP has matured toward a critical SUDEP threshold.