Aperiodic activity reflects pathologic waveform shapes in focal epilepsy

Abstract

Epilepsy constitutes a clinically-manifest excitability disorder that is characterized by aberrant electrophysiological activity in the electroencephalogram (EEG). The correct identification of the seizure onset zone relies on the visual detection of pathological waveforms and the assessment of their morphology, rhythmicity, and density. Recent advances in quantitative EEG analyses indicated that aperiodic EEG background activity might provide complementary information to traditional qualitative methods. Importantly, aperiodic activity, and specifically the slope of the 1/ƒ^χ decay function of the power spectrum, might constitute a biomarker of the underlying population excitability dynamics. Hence, in the context of epileptic activity, an altered spectral slope is often considered as a signature of pathological excitability. To date, it remained unclear if this straightforward interpretation also applies to states of manifest seizure activity. To address this question, we recorded intracranial electroencephalography (iEEG) during focal seizures from patients diagnosed with pharmacoresistant epilepsy (18 patients, 11 females). The results demonstrate that the spectral slope successfully delineates seizure activity. However, the spectral slope was sensitive to the presence and waveform shape of distinct epileptic components. By combining iEEG recordings with simulations, we demonstrate that epileptic spiking activity and associated slow-wave components differentially impact spectral slope estimates. These results offer a more parsimonious explanation for the biophysical origins of aperiodic activity as compared to the concept of an underlying balance between excitation and inhibition.

Significance Statement It is under debate whether the non-oscillatory EEG background (aperiodic) component of electrophysiological brain activity provides diagnostic insights into clinical disorders such as epilepsy. Seizure-related changes in aperiodic activity have mostly been ascribed to pathological excitability. Yet, epileptic waveform shapes could potentially modulate spectral estimates of aperiodic activity. Heidiri et al. demonstrate that aperiodic activity tracks ictal activity, wherein the morphology and density of epileptic activity systematically distort spectral estimates and associated aperiodic estimates. These findings show that aperiodic activity is directly modulated by the presence of waveform shapes, and may not necessarily reflect pathologic aberrations in the underlying population excitability.