More Than Spikes: On the Added Value of Non-linear Intracranial EEG Analysis for Surgery Planning in Temporal Lobe Epilepsy

Epilepsy surgery can be a very effective therapy in medication refractory patients. During patient evaluation intracranial EEG is analyzed by clinical experts to identify the brain tissue generating epileptiform events. Quantitative EEG analysis increasingly complements this approach in research settings, but not yet in clinical routine. We investigate the correspondence between epileptiform events and a specific quantitative EEG marker. We analyzed 99 preictal epochs of multichannel intracranial EEG of 40 patients with mixed etiologies. Time and channel of occurrence of epileptiform events (spikes, slow waves, sharp waves, fast oscillations) were annotated by a human expert and non-linear excess interrelations were calculated as a quantitative EEG marker. We assessed whether the visually identified preictal events predicted channels that belonged to the seizure onset zone, that were later resected or that showed strong non-linear interrelations. We also investigated whether the seizure onset zone or the resection were predicted by channels with strong non-linear interrelations. In patients with temporal lobe epilepsy (32 of 40), epileptic spikes and the seizure onset zone predicted the resected brain tissue much better in patients with favorable seizure control after surgery than in unfavorable outcomes. Beyond that, our analysis did not reveal any significant associations with epileptiform EEG events. Specifically, none of the epileptiform event types did predict non-linear interrelations. In contrast, channels with strong non-linear excess EEG interrelations predicted the resected channels better in patients with temporal lobe epilepsy and favorable outcome. Also in the small number of patients with seizure onset in the frontal and parietal lobes, no association between epileptiform events and channels with strong non-linear excess EEG interrelations was detectable. In contrast to patients with temporal seizure onset, EEG channels with strong non-linear excess interrelations did neither predict the seizure onset zone nor the resection of these patients or allow separation between patients with favorable and unfavorable seizure control. Our study indicates that non-linear excess EEG interrelations are not strictly associated with epileptiform events, which are one key concept of current clinical EEG assessment. Rather, they may provide information relevant for surgery planning in temporal lobe epilepsy. Our study suggests to incorporate quantitative EEG analysis in the workup of clinical cases. We make the EEG epochs and expert annotations publicly available in anonymized form to foster similar analyses for other quantitative EEG methods.

P023 Quantitative EEG analysis of polysomnography in a case of Fatal Familial Insomnia

Purpose To report on quantitative electroencephalograph (EEG) activity during polysomnography (PSG) in a rare case of confirmed Fatal Familial Insomnia (FFI). Methods Sleep/wake characteristics of a 32-year-old male patient were quantitatively analysed using central EEG recordings during two PSGs (FFI-1 and FFI-2) first, for investigation of insomnia and PLMS but with no suspicion of FFI and second, 120 days later with suspected but unconfirmed FFI at the time; 89 days prior to death. PSG metrics; absolute EEG power in specified frequency bands; EEG slowing ratio of slow-to-fast frequencies ((delta + theta)/ (alpha + sigma + beta)); and sleep spindle density were calculated. Results were compared with gender and age-matched insomnia and healthy controls (two of each). Results FFI-1 and FFI-2 PSGs revealed total time in bed of 413.5 and 392 minutes, total sleep times of 208.5 and 7.5 minute, including NREM 153.0 and 2.5 minutes, and REM 55.5 and 5.0 minutes, respectively. FFI-1 had approximately 1.5 times lower slow wave activity (SWA, 0.5–4.5Hz) during N3 than insomnia and controls.​ FFI-1 had 2 times and 1.8 times higher slowing ratio during REM than insomnia and controls, respectively. Spindle density (per minute of NREM sleep) for FFI-1 was 0.9, compared to pair-averages of 1.2 for insomnia disorder and 4.7 for healthy controls. Conclusions PSG in FFI revealed poor sleep efficiency that severely deteriorated with disease progression. Quantitative analysis of EEG revealed lower spindle density, lower SWA in N3, and higher slowing ratio in REM, when compared to insomnia patients and healthy sleepers.

Linear and Nonlinear Quantitative EEG Analysis during Neutral Hypnosis Following an Opened/Closed Eye Paradigm

Hypnotic susceptibility is a major factor influencing the study of the neural correlates of hypnosis using EEG. In this context, while its effects on the response to hypnotic suggestions are undisputed, less attention has been paid to “neutral hypnosis” (i.e., the hypnotic condition in absence of suggestions). Furthermore, although an influence of opened and closed eye condition onto hypnotizability has been reported, a systematic investigation is still missing. Here, we analyzed EEG signals from 34 healthy subjects with low (LS), medium (MS), and (HS) hypnotic susceptibility using power spectral measures (i.e., TPSD, PSD) and Lempel-Ziv-Complexity (i.e., LZC, fLZC). Indeed, LZC was found to be more suitable than other complexity measures for EEG analysis, while it has been never used in the study of hypnosis. Accordingly, for each measure, we investigated within-group differences between rest and neutral hypnosis, and between opened-eye/closed-eye conditions under both rest and neutral hypnosis. Then, we evaluated between-group differences for each experimental condition. We observed that, while power estimates did not reveal notable differences between groups, LZC and fLZC were able to distinguish between HS, MS, and LS. In particular, we found a left frontal difference between HS and LS during closed-eye rest. Moreover, we observed a symmetric pattern distinguishing HS and LS during closed-eye hypnosis. Our results suggest that LZC is better capable of discriminating subjects with different hypnotic susceptibility, as compared to standard power analysis.

796 Quantitative EEG Analysis in Angelman Syndrome

Introduction Angelman syndrome (AS) is a neurodevelopmental disorder resulting from decreased expression of the maternal copy of the imprinted UBE3A gene on chromosome 15. This disorder is characterized by intellectual disability, impaired speech and motor skills, and sleep abnormalities but currently lacks any treatment. However, mouse models have shown that un-silencing the dormant paternal copy of UBE3A has been an effective mechanism to restore the functionality of the UBE3A protein, thus clinical trials using this approach are on the near horizon. Developing biomarkers is essential for assessing responses to treatment when clinical trials begin, and quantitative EEG analysis has shown great promise as a biomarker for AS. Methods Here, we sought to define EEG biomarkers directly linked to sleep impairments seen in up to 90% of individuals with AS (Trickett). We analyzed nine overnight sleep studies from patients with AS with age and sex matched Down syndrome and neurotypical controls. We specifically examined low-frequency delta rhythms and sleep spindles during NREM sleep. Results We confirmed that low- delta rhythms are increased during overnight sleep in AS, and that this biomarker appears more reliable than possible changes in sleep spindles. Conclusion Our results suggest that quantitative measurement of delta rhythms during sleep can be used as a potential biomarker for treatments in Angelman syndrome clinical trials. Support (if any):

Early detection of cognitive impairment in patients with hypertension and evaluation of treatment effectiveness according to EEG data

Objective: to establish the relationship between the presence of cognitive disorders in patients with arterial hypertension and changes in EEG, to assess the dynamics of these changes against the background of various modes of cerebroprotective therapy.Materials and methods: the study involved 92 people with arterial hypertension, whose average age was 63 ± 8.2 years. The research was carried out on the device “Encephalan-EEGR-19/26”. To assess cognitive functions, patients were tested using the MoСA test. Patients with cognitive impairment were divided into three groups of dynamic monitoring with diff erent modes of cerebroprotective therapy.Results: non-specifi c patterns in the slow-wave range were registered in patients with cognitive impairment during visual EEG analysis. In the quantitative analysis of the EEG revealed changes in the frequency and amplitude of the alpha rhythm, the power variation on the basic rhythms, the reduction of the total strength of the rhythms, the increase in relative power of slow rhythms in the frontal leads to the total power of the rhythms. After the treatment, most patients showed an increase in scores on the “Montreal scale”, a decrease in anxiety and depression on the” Hospital scale”, and an increase in the SF-36 index. Quantitative EEG analysis revealed positive dynamics comparable to the clinic and test data. The most favorable EEG dynamics was registered in groups of patients receiving neuroprotective and combined therapy.Conclusions: the results obtained indicate the diagnostic value of quantitative EEG analysis and the feasibility of adding drugs that improve the metabolism and blood supply to the brain to standard antihypertensive therapy.