Absence seizure susceptibility correlates with pre-ictal β oscillations

Abstract

Absence seizures are generalized, cortico-thalamo-cortical (CTC) high power electroenecephalographic (EEG) or electrocorticographic (ECoG) events that initiate and terminate suddenly. ECoG recordings of absence seizures in animal models of genetic absence epilepsy show a sudden spike-wave-discharge (SWD) onset that rapidly emerges from normal ECoG activity. However, given that absence seizures occur most often during periods of drowsiness or quiet wakefulness, we wondered whether SWD onset correlates with pre-ictal changes in network activity. To address this, we analyzed ECoG recordings of both spontaneous and induced SWDs in rats with genetic absence epilepsy. We discovered that the duration and intensity of spontaneous SWDs positively correlate with pre-ictal 20–40 Hz (β) spectral power and negatively correlate with 4-7 Hz (Ø) power. In addition, the output of thalamocortical neurons decreases within the same preictal window of time. In separate experiments we found that the propensity for SWD induction was correlated with pre-ictal β power. These results argue that CTC networks undergo a pre-seizure state transition, possibly due to a functional reorganization of cortical microcircuits, which leads to the generation of absence seizures.

Changes in interictal pretreatment and posttreatment EEG in childhood absence epilepsy

“…The increased beta power may reflect propensity for epileptic spikes generationspikes that triggers absence seizures. This interpretation is corroborated by the recent work of Sorokin et al who found that in rats absence seizure susceptibility correlates with pre-ictal beta oscillations (Sorokin et al, 2018). It is worth pointing out that as we detune the parameters of the analyzing wavelet away from the values optimal for spike detection, the differences in beta power between the CAE patients and controls disappear.…”

Thalamic activity patterns unfolding over multiple time scales predict seizure onset in absence epilepsy

“…In combination with our previous study 21 , these results verify a robust change in neural dynamics a few seconds prior to absence seizure onset, which can be observed through multiple spatio-temporal scales (EEG 21 and single-neuron activity). Further, these results suggest that a pre-ictal peak (PiP) in neural activity seems to be a low-dimensional feature of thalamic multi-neuronal dynamics.…”

“…The thalamus displayed a statistically significant increase in pre-ictal firing (-3 to -0.5 seconds relative to seizure onset) compared to non-ictal (-5 to -3 seconds) activity ( Figure 1E, KS test, p < 0.05). Note the pre-ictal period is defined as the period 3 seconds or less before seizure onset, consistent with previous work 21 . We did not observe this effect in the hippocampus, nor did we observe much change in cortical activity during the pre-ictal period -a surprising result given that the cortex and thalamus are strongly mutually connected [68][69][70] and display synchronized discharges during the seizures themselves 37,43,71 .…”

“…To detect seizures, we selected a single cortical channel with prominent seizures and few artifacts, down-sampled the LFP to 500 Hz, and then used the discrete wavelet transform (DWT) with a Symelet-4 mother wavelet to extract a multi-level time-varying frequency representation of the signal 21 . We expanded upon our previous seizure detection algorithm, which relied on summing specific wavelet bands and thresholding the result 21 , by training a logistic regression classifier on relative wavelet variances derived from 250 ms segments of LFP (with 125 ms of overlap) that either did or did not contain an SWD envelope (1 or 0 class label, respectively; Figure S2 A-B). This allowed the classifier to find the appropriate weights for the various frequencies of the wavelettransformed data, rather than having the user pre-specify such weights a priori ( Figure S2 C-D).…”

“…This dogma underlying the nature of absence seizure initiation is starting to change. For instance, pre-ictal increases in both high and low (1)(2)(3)(4) Hz) frequency cortical oscillations in the ECoG, derived via wavelet-decomposition 19,20 , have been reported in different rodent models of genetic absence epilepsy [21][22][23] . Along these lines, other studies have corroborated these wavelet-based methods via non-linear analyses of single and multichannel EEG.…”