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Seizure pathways change on circadian and slower timescales in individual patients with focal epilepsy.

ABSTRACT: Personalized medicine requires that treatments adapt to not only the patient but also changing factors within each individual. Although epilepsy is a dynamic disorder characterized by pathological fluctuations in brain state, surprisingly little is known about whether and how seizures vary in the same patient. We quantitatively compared within-patient seizure network evolutions using intracranial electroencephalographic (iEEG) recordings of over 500 seizures from 31 patients with focal epilepsy (mean 16.5 seizures per patient). In all patients, we found variability in seizure paths through the space of possible network dynamics. Seizures with similar pathways tended to occur closer together in time, and a simple model suggested that seizure pathways change on circadian and/or slower timescales in the majority of patients. These temporal relationships occurred independent of whether the patient underwent antiepileptic medication reduction. Our results suggest that various modulatory processes, operating at different timescales, shape within-patient seizure evolutions, leading to variable seizure pathways that may require tailored treatment approaches.

SUBMITTER: Schroeder GM

PROVIDER: S-EPMC7245106 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Seizure pathways change on circadian and slower timescales in individual patients with focal epilepsy.

Schroeder Gabrielle M GM Diehl Beate B Chowdhury Fahmida A FA Duncan John S JS de Tisi Jane J Trevelyan Andrew J AJ Forsyth Rob R Jackson Andrew A Taylor Peter N PN Wang Yujiang Y

Proceedings of the National Academy of Sciences of the United States of America 20200504 20

Personalized medicine requires that treatments adapt to not only the patient but also changing factors within each individual. Although epilepsy is a dynamic disorder characterized by pathological fluctuations in brain state, surprisingly little is known about whether and how seizures vary in the same patient. We quantitatively compared within-patient seizure network evolutions using intracranial electroencephalographic (iEEG) recordings of over 500 seizures from 31 patients with focal epilepsy ...[more]

PMID: 32366665

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Project description:OBJECTIVE:Differentiating pathologic and physiologic high-frequency oscillations (HFOs) is challenging. In patients with focal epilepsy, HFOs occur during the transitional periods between the up and down state of slow waves. The preferred phase angles of this form of phase-event amplitude coupling are bimodally distributed, and the ripples (80-150 Hz) that occur during the up-down transition more often occur in the seizure-onset zone (SOZ). We investigated if bimodal ripple coupling was also evident for faster sleep oscillations, and could identify the SOZ. METHODS:Using an automated ripple detector, we identified ripple events in 40-60 min intracranial electroencephalography (iEEG) recordings from 23 patients with medically refractory mesial temporal lobe or neocortical epilepsy. The detector quantified epochs of sleep oscillations and computed instantaneous phase. We utilized a ripple phasor transform, ripple-triggered averaging, and circular statistics to investigate phase event-amplitude coupling. RESULTS:We found that at some individual recording sites, ripple event amplitude was coupled with the sleep oscillatory phase and the preferred phase angles exhibited two distinct clusters (p < 0.05). The distribution of the pooled mean preferred phase angle, defined by combining the means from each cluster at each individual recording site, also exhibited two distinct clusters (p < 0.05). Based on the range of preferred phase angles defined by these two clusters, we partitioned each ripple event at each recording site into two groups: depth iEEG peak-trough and trough-peak. The mean ripple rates of the two groups in the SOZ and non-SOZ (NSOZ) were compared. We found that in the frontal (spindle, p = 0.009; theta, p = 0.006, slow, p = 0.004) and parietal lobe (theta, p = 0.007, delta, p = 0.002, slow, p = 0.001) the SOZ incidence rate for the ripples occurring during the trough-peak transition was significantly increased. SIGNIFICANCE:Phase-event amplitude coupling between ripples and sleep oscillations may be useful to distinguish pathologic and physiologic events in patients with frontal and parietal SOZ.

Project description:ImportanceA bidirectional brain-computer interface that performs neurostimulation has been shown to improve seizure control in patients with refractory epilepsy, but the therapeutic mechanism is unknown.ObjectiveTo investigate whether electrographic effects of responsive neurostimulation (RNS), identified in electrocorticographic (ECOG) recordings from the device, are associated with patient outcomes.Design, setting, and participantsRetrospective review of ECOG recordings and accompanying clinical meta-data from 11 consecutive patients with focal epilepsy who were implanted with a neurostimulation system between January 28, 2015, and June 6, 2017, with 22 to 112 weeks of follow-up. Recorded ECOG data were obtained from the manufacturer; additional system-generated meta-data, including recording and detection settings, were collected directly from the manufacturer's management system using an in-house, custom-built platform. Electrographic seizure patterns were identified in RNS recordings and evaluated in the time-frequency domain, which was locked to the onset of the seizure pattern.Main outcomes and measuresPatterns of electrophysiological modulation were identified and then classified according to their latency of onset in relation to triggered stimulation events. Seizure control after RNS implantation was assessed by 3 main variables: mean frequency of seizure occurrence, estimated mean severity of seizures, and mean duration of seizures. Overall seizure outcomes were evaluated by the extended Personal Impact of Epilepsy Scale questionnaires, a patient-reported outcome measure of 3 domains (seizure characteristics, medication adverse effects, and quality of life), with a range of possible scores from 0 to 300 in which lower scores indicate worse status, and the Engel scale, which comprises 4 classes (I-IV) in which lower numbers indicate greater improvement.ResultsElectrocorticographic data from 11 patients (8 female; mean [range] age, 35 [19-65] years; mean [range] duration of epilepsy, 19 [5-37] years) were analyzed. Two main categories of electrophysiological signatures of stimulation-induced modulation of the seizure network were discovered: direct and indirect effects. Direct effects included ictal inhibition and early frequency modulation but were not associated with improved clinical outcomes (odds ratio [OR], 0.67; 95% CI, 0.06-7.35; P > .99). Only indirect effects-those occurring remote from triggered stimulation-were associated with improved clinical outcomes (OR, infinity; 95% CI, -infinity to infinity; P = .02). These indirect effects included spontaneous ictal inhibition, frequency modulation, fragmentation, and ictal duration modulation.Conclusions and relevanceThese findings suggest that RNS effectiveness may be explained by long-term, stimulation-induced modulation of seizure network activity rather than by direct effects on each detected seizure.

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Seizure pathways change on circadian and slower timescales in individual patients with focal epilepsy.

Publications

Seizure pathways change on circadian and slower timescales in individual patients with focal epilepsy.

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