Seizure Onset Zone Lateralization Using a Non-linear Analysis of Micro vs. Macro Electroencephalographic Recordings During Seizure-Free Stages of the Sleep-Wake Cycle From Epilepsy Patients

Abstract

The application of non-linear signal analysis techniques to biomedical data is key to improve our knowledge about complex physiological and pathological processes. In particular, the use of non-linear techniques to study electroencephalographic (EEG) recordings can provide an advanced characterization of brain dynamics. In epilepsy these dynamics are altered at different spatial scales of neuronal organization. We therefore apply non-linear signal analysis to EEG recordings from epilepsy patients derived with intracranial hybrid electrodes, which are composed of classical macro contacts and micro wires. Thereby, these electrodes record EEG at two different spatial scales. Our aim is to test the degree to which the analysis of the EEG recorded at these different scales allows us to characterize the neuronal dynamics affected by epilepsy. For this purpose, we retrospectively analyzed long-term recordings performed during five nights in three patients during which no seizures took place. As a benchmark we used the accuracy with which this analysis allows determining the hemisphere that contains the seizure onset zone, which is the brain area where clinical seizures originate. We applied the surrogate-corrected non-linear predictability score (ψ), a non-linear signal analysis technique which was shown previously to be useful for the lateralization of the seizure onset zone from classical intracranial EEG macro contact recordings. Higher values of ψ were found predominantly for signals recorded from the hemisphere containing the seizure onset zone as compared to signals recorded from the opposite hemisphere. These differences were found not only for the EEG signals recorded with macro contacts, but also for those recorded with micro wires. In conclusion, the information obtained from the analysis of classical macro EEG contacts can be complemented by the one of micro wire EEG recordings. This combined approach may therefore help to further improve the degree to which quantitative EEG analysis can contribute to the diagnostics in epilepsy patients.

PreEpiSeizures: description and outcomes of physiological data acquisition using wearable devices during video-EEG monitoring in people with epilepsy

“…Three of the public databases (Bern-Barcelona ( Andrzejak et al, 2012 ), New Delhi EEG ( Swami et al, 2016 ) and Epilepsy Seizure Recognition ( Andrzejak et al, 2001 )) only presented segments of a few seconds duration. Bonn-Barcelona micro- and macro-EEG database ( Martínez et al, 2020 ), comprises data from epileptic patients without epileptic seizures.…”

Prevalence and localization of nocturnal epileptiform discharges in mild cognitive impairment

“…Beyond epileptiform discharges, there are even micro or subclinical seizures without clear clinical manifestation that are common with invasive EEG recordings from the hippocampus. 8 , 28 , 29 Low-amplitude EEG spikes without a history of clinical seizures are sometimes referred to as subclinical. 24 , 30 , 31 These discharges are not ‘subclinical’ as they may cause disruptions in memory and executive functioning as they are known to do in patients with epilepsy, especially in light of the recent results of the Vossel et al study, 14 with both short-term and long-term impacts.…”

Modular pipeline for reconstruction and localization of implanted intracranial ECoG and sEEG electrodes

“…Across one data set (N = 27), the location of electrodes in white matter versus cortical grey matter varies depending on the depth electrode trajectory (Fig 4E). This information may be useful for designing novel electrodes for localizing grey matter along common trajectories [78][79][80]. Further, this localization information and measures of electrode location is instrumental for examining how anatomical features alter neural responses to stimulation or for seizure localization (Fig 5) [6,14].…”