Intracranial EEG seizure onset and termination patterns and their association

Seizure onset and offset pattern determine the entrainment of the cortex and substantia nigra in the nonhuman primate model of focal temporal lobe seizures

Temporal lobe epilepsy (TLE) is the most common form of drug-resistant epilepsy. A major focus of human and animal studies on TLE network has been the limbic circuit. However, there is also evidence suggesting an active role of the basal ganglia in the propagation and control of temporal lobe seizures. Here, we characterize the involvement of the substantia nigra (SN) and somatosensory cortex (SI) during temporal lobe (TL) seizures induced by penicillin injection in the hippocampus (HPC) of two nonhuman primates. The seizure onset and offset patterns were manually classified and spectral power and coherence were calculated. We then compared the 3-second segments recorded in pre-ictal, onset, offset and post-ictal periods based on the seizure onset and offset patterns. Our results demonstrated an involvement of the SN and SI dependent on the seizure onset and offset pattern. We found that low amplitude fast activity (LAF) and high amplitude slow activity (HAS) onset patterns were associated with an increase in activity of the SN while the change in activity was limited to LAF seizures in the SI. However, the increase in HPC/SN coherence was specific to the farther-spreading LAF onset pattern. As for the role of the SN in seizure cessation, we observed that the coherence between the HPC/SN was reduced during burst suppression (BS) compared to other termination phases. Additionally, we found that this coherence returned to normal levels after the seizure ended, with no significant difference in post-ictal periods among the three types of seizure offsets. This study constitutes the first demonstration of TL seizures entraining the SN in the primate brain. Moreover, these findings provide evidence that this entrainment is dependent on the onset and offset pattern and support the hypothesis that the SN might play a role in the maintenance and termination of some specific temporal lobe seizure.

Quantifying seizure termination patterns reveals limited pathways to seizure end

OBJECTIVE

Despite their possible importance in the design of novel neuromodulatory approaches and in understanding status epilepticus, the dynamics and mechanisms of seizure termination are not well studied. We examined intracranial recordings from patients with epilepsy to differentiate seizure termination patterns and investigated whether these patterns are indicative of different underlying mechanisms.

METHODS

Seizures were classified into one of two termination patterns: (a) those that end simultaneously across the brain (synchronous), and (b) those whose termination is piecemeal across the cortex (asynchronous). Both types ended with either a burst suppression pattern, or continuous seizure activity. These patterns were quantified and compared using burst suppression ratio, absolute energy, and network connectivity.

RESULTS

Seizures with electrographic generalization showed burst suppression patterns in 90% of cases, compared with only 60% of seizures which remained focal. Interestingly, we found similar absolute energy and burst suppression ratios in seizures with synchronous and asynchronous termination, while seizures with continuous seizure activity were found to be different from seizures with burst suppression, showing lower energy during seizure and lower burst suppression ratio at the start and end of seizure. Finally, network density was observed to increase with seizure progression, with significantly lower densities in seizures with continuous seizure activity compared to seizures with burst suppression.

SIGNIFICANCE

Based on this spatiotemporal classification scheme, we suggest that there are a limited number of seizure termination patterns and dynamics. If this bears out, it would imply that the number of mechanisms underlying seizure termination is also constrained. Seizures with different termination patterns exhibit different dynamics even before their start. This may provide useful clues about how seizures may be managed, which in turn may lead to more targeted modes of therapy for seizure control.