Delta-gamma phase-amplitude coupling as a biomarker of postictal generalized EEG suppression

Abstract

Phase-amplitude coupling analysis shows that a state of postictal generalized EEG suppression has increased delta-gamma coupling. These coupling features, used with an unsupervised hidden Markov model, reliably differentiated four substates in seizure episodes. A sudden unexpected death in epilepsy case study showed coupling activity similar to a postictal state. Postictal generalized EEG suppression is the state of suppression of electrical activity at the end of a seizure. Prolongation of this state has been associated with increased risk of sudden unexpected death in epilepsy, making characterization of underlying electrical rhythmic activity during postictal suppression an important step in improving epilepsy treatment. Phase-amplitude coupling in EEG reflects cognitive coding within brain networks and some of those codes highlight epileptic activity; therefore, we hypothesized that there are distinct phase-amplitude coupling features in the postictal suppression state that can provide an improved estimate of this state in the context of patient risk for sudden unexpected death in epilepsy. We used both intracranial and scalp EEG data from eleven patients (six male, five female; age range 21–41 years) containing 25 seizures, to identify frequency dynamics, both in the ictal and postictal EEG suppression states. Cross-frequency coupling analysis identified that during seizures there was a gradual decrease of phase frequency in the coupling between delta (0.5-4 Hz) and gamma (30+ Hz), which was followed by an increased coupling between the phase of 0.5-1.5 Hz signal and amplitude of 30-50 Hz signal in the postictal state as compared to the pre-seizure baseline. This marker was consistent across patients. Then, using these postictal-specific features, an unsupervised state classifier – a hidden Markov model – was able to reliably classify four distinct states of seizure episodes, including a postictal suppression state. Furthermore, a connectome analysis of the postictal suppression states showed increased information flow within the network during postictal suppression states as compared to the pre-seizure baseline, suggesting enhanced network communication. When the same tools were applied to the EEG of an epilepsy patient who died unexpectedly, ictal coupling dynamics disappeared and postictal phase-amplitude coupling remained constant throughout. Overall, our findings suggest that there are active postictal networks, as defined through coupling dynamics, that can be used to objectively classify the postictal suppression state; furthermore, in a case study of sudden unexpected death in epilepsy, the network does not show ictal-like phase-amplitude coupling features despite the presence of convulsive seizures, and instead demonstrates activity similar to postictal. The postictal suppression state is a period of elevated network activity as compared to the baseline activity which can provide key insights into the epileptic pathology.

Relationship between Delta Rhythm, Seizure Occurrence and Allopregnanolone Hippocampal Levels in Epileptic Rats Exposed to the Rebound Effect

“…In general, these changes in neuronal oscillations were consistent in the postictal suppression state, regardless of whether the suppression was generalized or not across channels. Then, it was also suggested that very high frequency oscillations (600–2000 Hz) could be combined with low delta as an additional biomarker for postictal states [ 41 ].…”

“…Using the same test, we also compared the percentage of animals with seizures during the treatment period in LEV-and saline-treated groups. After having tested for normality of distribution (Shapiro-Wilk test), data on seizure duration were analyzed by a 2-way (Treatments: LEV, SALINE) × 21 (Time Intervals expressed in days: 36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56) repeated measures ANOVA. Post hoc comparisons, when appropriated, were done using a multiple comparison test (Holm-Šidák).…”

Effects of Transcranial Ultrasound Stimulation Pulsed at 40 Hz on Aβ Plaques and Brain Rhythms in 5XFAD Mice

“…After 2 weeks of tUS stimulation, the theta-gamma coupling in Tg/Stim + in day 14 increased signi cantly in comparison with Tg/Stim + at baseline. Delta-gamma coupling also considered as a biomarker for the evaluation of generalized EEG suppression as well as network activity [41]. Our results showed an exaggeration of delta-gamma coupling in Tg/Stim + day 14 in comparison with Tg/Stim + at baseline.…”

Electrographic Features of Spontaneous Recurrent Seizures in a Mouse Model of Extended Hippocampal Kindling

“…2013 ; Zhang et al. 2017 ; Grigorovsky et al. 2020 ) that matched pre- and postdischarge signals as well as the onset, middle, and offset epochs of regional discharges ( Grigorovsky et al.…”

“…PAC strength was assessed using the algorithm by Tort et al. (2010) where phase and amplitude of different frequency bands were obtained via the complex wavelet Morlet wavelet transform using a mother wavelet with a central frequency of 0.8125 Hz and bandwidth of 5 Hz previously used on human EEG data ( Grigorovsky et al. 2020 ).…”