Enhanced phase and amplitude synchronization toward focal seizure offset

Enhanced gamma band mutual information is associated with impaired consciousness during temporal lobe seizures

Background

Epileptic seizures are characterized by aberrant synchronization. We hypothesized that higher synchronization across the seizure onset zone (SOZ) channels during a temporal lobe seizure contributes to impaired consciousness.

New method

All symmetric bivariate synchronization measures were extended to multivariate measure by a principal component analysis (PCA) based technique. A novel nonparametric method has been proposed to test the statistical significance between increased synchronization across the seizure onset zone (SOZ) channels and reduced consciousness.

Results

Increased synchronization in the gamma band towards seizure termination significantly contributes to impaired consciousness (p < 0.1). Synchronization reaches its peak in the extratemporal region (frontal lobe) ahead of the temporal region (p < 0.05). Synchronization is prominent in beta and gamma bands by most methods and it is more in the second half of seizure duration than in the first (p < 0.05).

Conclusions

Mutual information is the only synchronization measure out of the six that we studied, whose increase can be associated with the loss of consciousness in a statistically significant way.

NREM Sleep and Antiepileptic Medications Modulate Epileptiform Activity by Altering Cortical Synchrony

INTRODUCTION

The activating role of non-rapid eye movement (NREM) sleep on epileptic cortex and conversely, the seizure remission brought about by antiepileptic medications, has been attributed to their effects on neuronal synchrony. This study aims to understand the role of neural synchrony of NREM sleep in promoting interictal epileptiform discharges (IEDs) in patients with epilepsy (PWE) by assessing the peri-IED phase synchrony during awake and sleep states. It also studies the role played by antiepileptic drugs (AEDs) on EEG desynchronization in the above cohort.

METHODS

A total of 120 PWE divided into 3 groups (each n = 40; juvenile myoclonic epilepsy [JME], temporal lobe epilepsy [TLE]. and extratemporal lobe epilepsy [Ex-TLE]) were subjected to overnight polysomnography. Each patient group was subdivided into drug-naive and on treatment (Each n = 20). EEG phase synchronization analysis was performed to compare peri-IED phase synchronization indices (SI) during awake and sleep stages and between drug naïve and on treatment groups in 4 frequency bands, namely delta, theta, alpha, and beta. The mean ± SD of peri-IED SI among various subgroups was compared employing a multilevel mixed effects modeling approach.

RESULTS

Patients with JME had increased peri-IED cortical synchrony in N3 sleep stage, whereas patients with partial epilepsy had increased IED cortical synchrony in N1 sleep stage. On the other hand, peri-IED synchrony was lower during wake and REM sleep. We also found that peri-IED synchronization in patients with JME was higher in drug-naive patients compared with those on sodium valproate monotherapy in theta, alpha, and beta bands.

CONCLUSION

The findings of this study suggest that sleep stages can alter cortical synchrony in patients with JME and focal epilepsy, with NREM IEDs being more synchronized and wake/REM IEDs being less synchronized. Furthermore, it also suggests that AEDs alleviate seizures in PWE by inhibiting cortical synchrony.

Global Synchronization of Multichannel EEG in Patients With Electrical Status Epilepticus in Sleep

In the research field of epilepsy, it is a challenge to understand the transition of brain activity to electrical status epilepticus in sleep (ESES). In this study, an S-estimator method is proposed to describe the course of global synchronization in multichannel electroencephalograph (EEG) from awake to sleep in 11 patients with ESES. The study confirms that there is a significant increase in spikes and global synchronization from awake to sleep. It is also found that global synchronization is strongly correlated with spikes. The proposed method has the potential of revealing the intrinsic features of EEG signals and the underlying brain dynamics in ESES.