EEG-LORETA endophenotypes of the common idiopathic generalized epilepsy syndromes

Clemens, Béla; Puskás, Szilvia; Besenyei, Mónika; Emri, Miklós; Opposits, Gábor; Kis, Sándor Attila; Hollódy, Katalin; Fogarasi, András; Kondákor, István; Füle, K.; Bense, Katalin; Fekete, István

doi:10.1016/j.eplepsyres.2011.12.008

Cited by 17 publications

(19 citation statements)

References 78 publications

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“…Changes in terms of both spectral power[1112131415] (including γ-frequency band)[1415] and coherence[1216] are reported in these. Except a few studies,[1117] most studies comparing inter-ictal background power and coherence in generalized epilepsies with normal controls, have not specifically determined patients with JME as a separate group. Rather they have clubbed patients with JME, juvenile absence epilepsy, and epilepsy with exclusively generalized tonic–clonic seizures together.…”

Section: Introductionmentioning

confidence: 99%

“…Rather they have clubbed patients with JME, juvenile absence epilepsy, and epilepsy with exclusively generalized tonic–clonic seizures together. [1213141516] Limited number of studies[1117] which present separate results for JME patients have found both similar and contrasting findings compared to patients with idiopathic generalized epilepsy considered broadly.…”

Section: Introductionmentioning

confidence: 99%

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Juvenile myoclonic epilepsy: Clinical characteristics, standard and quantitative electroencephalography analyses

et al. 2013

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Objectives:Most studies comparing inter-ictal background quantitative electroencephalography (EEG) measures in generalized epilepsies with normal controls do not specifically determine patients with juvenile myoclonic epilepsy (JME) as a separate group. The study aims at comparing absolute spectral power and global field coherence in various frequency bands between patients diagnosed exclusively with JME and 10 healthy controls, and correlating significantly different quantitative EEG measures with various clinical characteristics and standard EEG abnormalities.Materials and Methods:Clinical and EEG data were collected from 10 patients with JME and 10 healthy controls. Spectral power and global field spectral coherence were calculated using Welch's averaged periodogram method. The data was analyzed using descriptive statistics, Fisher's exact test and t-test.Results:Statistically significant (or trend level) higher power (global α and θ, frontal α and θ, left temporal θ, right occipital α, δ and γ1, and central δ, θ, α, β, and γ2) and coherence (global α and γ1) was found in JME patients when compared to controls. Significant correlation of left frontal and central θ-power with presence of absence seizures (negative), central δ-, and θ-power with the presence of psychiatric comorbidity and central θ-power with frequency of myoclonic seizures was found.Conclusion:Findings on global–frontal and temporal–occipital power support mild diffuse epileptogenic state and θ-activity as an endophenotype concepts in JME patients, respectively; findings suggest future studies on JME to include psychiatric comorbidity while selecting the sample; some spectral measures (e.g., central θ-power) do relate to progression of JME while some do not.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Juvenile myoclonic epilepsy: Clinical characteristics, standard and quantitative electroencephalography analyses

et al. 2013

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“…It has also been reported that in animal models of epilepsy increased theta activity showed the seizure-gating effect [26, 27]. Clemens et al [28] also reported that increased theta activity in some brain areas can be detected as an endophenotype for idiopathic generalized epilepsy. In this study, we emphasize the importance of the pathophysiology of theta rhythms in epilepsy patients.…”

Section: Introductionmentioning

confidence: 94%

“…Particularly, their very narrow band analysis led to astonishing findings according to which activity increased as a function of frequency from 4 to 7 or 8 Hz and rapidly fell at 8 or 9 Hz in epilepsy patients. We can speculate that the traditional theta frequency band setting at 4–8 Hz might be inappropriate to detect exact theta peak or paroxysmal activity in the theta band, especially centered around 7 or 8 Hz, and the frequency band setting at 5–9 or 5–10 Hz might be appropriate for these “high” theta activities, as already mentioned in some previous studies [26-28]. …”

Section: Introductionmentioning

confidence: 97%

“…To localize the sources of scalp-recorded spontaneous theta activity in patients with partial epilepsy, Clemens et al [28] analyzed interictal EEG data using LORETA in the very narrow band of 1 Hz width. They found that EEG activity in the theta band is increased in anatomically meaningful patterns in partial epilepsy patients and differs from the anatomical distribution of theta rhythm in healthy persons.…”

Section: Introductionmentioning

confidence: 99%

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Automated Source Estimation of Scalp EEG Epileptic Activity Using eLORETA Kurtosis Analysis

et al. 2019

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Objectives: eLORETA (exact low-resolution brain electromagnetic tomography) is a technique created by Pascual-Marqui et al. [Int J Psychophysiol. 1994 Oct; 18(1): 49–65] for the 3-dimensional representation of current source density in the brain by electroencephalography (EEG) data. Kurtosis analysis allows for the identification of spiky activity in the brain. In this study, we focused on the evaluation of the reliability of eLORETA kurtosis analysis. For this purpose, the results of eLORETA kurtosis source localization of paroxysmal activity in EEG were compared with those of eLORETA current source density (CSD) analysis of EEG data in 3 epilepsy patients with partial seizures. Methods: EEG was measured using a digital EEG system with 19 channels. We set the bandpass filter at traditional frequency band settings (1–4, 4–8, 8–15, 15–30, and 30–60 Hz) and 5–10 and 20–70 Hz and performed eLORETA kurtosis to compare the source localization of paroxysmal activity with that of visual interpretation of EEG data and CSD analysis of eLORETA in focal epilepsy patients. Results: The eLORETA kurtosis analysis of EEG data preprocessed by bandpass filtering from 20 to 70 Hz and traditional frequency band settings did not show any discrete paroxysmal source activity compatible with the results of CSD analysis of eLORETA. In all 3 cases, eLORETA kurtosis analysis filtered at 5–10 Hz showed paroxysmal activities in the theta band, which were all consistent with the visual inspection results and the CSD analysis results. Discussion: Our findings suggested that eLORETA kurtosis analysis of EEG data might be useful for the identification of spiky paroxysmal activity sources in epilepsy patients. Since EEG is widely used in the clinical practice of epilepsy, eLORETA kurtosis analysis is a promising method that can be applied to epileptic activity mapping.

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Using interictal seizure-free EEG data to recognise patients with epilepsy based on machine learning of brain functional connectivity

Cao

Grajcar

Shan

et al. 2021

Biomedical Signal Processing and Control

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EEG-LORETA endophenotypes of the common idiopathic generalized epilepsy syndromes

Cited by 17 publications

References 78 publications

Juvenile myoclonic epilepsy: Clinical characteristics, standard and quantitative electroencephalography analyses

Juvenile myoclonic epilepsy: Clinical characteristics, standard and quantitative electroencephalography analyses

Automated Source Estimation of Scalp EEG Epileptic Activity Using eLORETA Kurtosis Analysis

Using interictal seizure-free EEG data to recognise patients with epilepsy based on machine learning of brain functional connectivity

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