Slow modulations of high-frequency activity (40–140 Hz) discriminate preictal changes in human focal epilepsy

Abstract

Recent evidence suggests that some seizures are preceded by preictal changes that start from minutes to hours before an ictal event. Nevertheless an adequate statistical evaluation in a large database of continuous multiday recordings is still missing. Here, we investigated the existence of preictal changes in long-term intracranial recordings from 53 patients with intractable partial epilepsy (in total 531 days and 558 clinical seizures). We describe a measure of brain excitability based on the slow modulation of high-frequency gamma activities (40–140 Hz) in ensembles of intracranial contacts. In prospective tests, we found that this index identified preictal changes at levels above chance in 13.2% of the patients (7/53), suggesting that results may be significant for the whole group (p < 0.05). These results provide a demonstration that preictal states can be detected prospectively from EEG data. They advance understanding of the network dynamics leading to seizure and may help develop novel seizure prediction algorithms.

Multivariate regression methods for estimating velocity of ictal discharges from human microelectrode recordings

“…High gamma band signal has been established as a useful index of population firing [27, 34–37]. However, because of its fast oscillations, it is difficult to specify a consistent single time point for each discharge.…”

On the proper selection of preictal period for seizure prediction

“…The spectral power features are computationally very cost-effective, which makes them suitable candidates for implantable and portable warning systems. Furthermore, these features recently have demonstrated promising results for seizure prediction [15,35,39,[43][44][45][46], specifically in the high gamma frequency bands [15,[43][44][45][46]. Therefore, we investigated high-quality iEEG and sEEG recordings (with the sampling rates of 1024 Hz and 2500 Hz) and divided the gamma band into several narrower subbands to study the spectral behavior more precisely.…”

“…Therefore, we investigated high-quality iEEG and sEEG recordings (with the sampling rates of 1024 Hz and 2500 Hz) and divided the gamma band into several narrower subbands to study the spectral behavior more precisely. Instead of using the well-known frequency bands, the subbands were selected as (0.5-4], (4)(5)(6)(7)(8), (8)(9)(10)(11)(12)(13)(14)(15), (15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30), (30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45)(46)(47)(48) The spectral powers were obtained using power spectral density (PSD) estimated through Welch's method [47]. The PSD ...…”

Interictal high-frequency oscillations in focal human epilepsy

“…In addition, increased HFOs are reported to correlate with disease severity, seizure frequency [19,21], and resection of their generators with seizure-free outcome [20,22,23 ▪ ]. In addition, recent studies have demonstrated the feasibility of seizure forecasting [24,25], and HFO show promise as a biomarker of the preictal state [26,27]. …”