ArticleScientific reports2015
Interval analysis of interictal EEG: pathology of the alpha rhythm in focal epilepsy.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Development and validation of a deep survival model to predict time to seizure from routine electroencephalography.Epilepsia · 2026Article
- PSD-LW-DCN: a generalizable power spectral density based lightweight deep convolutional neural network for seizure detection.Scientific reports · 2026Article
- Population-based spectral characteristics of normal interictal scalp EEG inform diagnosis and treatment planning in focal epilepsy.Scientific reports · 2025Article
- The Value of Normal Interictal EEGs in Epilepsy Diagnosis and Treatment Planning: A Retrospective Cohort Study using Population-level Spectral Power and Connectivity Patterns.medRxiv : the preprint server for health sciences · 2025Article
- Computer-assisted analysis of routine EEG to identify hidden biomarkers of epilepsy: A systematic review.Computational and structural biotechnology journal · 2024Review
- Alpha rhythm slowing in temporal lobe epilepsy across scalp EEG and MEG.Brain communications · 2024Article
- Machine-learning for the prediction of one-year seizure recurrence based on routine electroencephalography.Scientific reports · 2023Article
- EEG/fNIRS Based Workload Classification Using Functional Brain Connectivity and Machine Learning.Sensors (Basel, Switzerland) · 2022Article
- Entropy Measures of Electroencephalograms towards the Diagnosis of Psychogenic Non-Epileptic Seizures.Entropy (Basel, Switzerland) · 2022Article
- Quantitative analysis of visually reviewed normal scalp EEG predicts seizure freedom following anterior temporal lobectomy.Epilepsia · 2022Article
- Seizure classification with selected frequency bands and EEG montages: a Natural Language Processing approach.Brain informatics · 2022Article
- Brivaracetam Modulates Short-Term Synaptic Activity and Low-Frequency Spontaneous Brain Activity by Delaying Synaptic Vesicle Recycling in Two Distinct Rodent Models of Epileptic Seizures.Journal of molecular neuroscience : MN · 2022Article
- Heterogeneity of resting-state EEG features in juvenile myoclonic epilepsy and controls.Brain communications · 2022Article
- Dynamic coupling between the central and autonomic cardiac nervous systems in patients with refractory epilepsy: A pilot study.Frontiers in neurology · 2022Article
- Artificial intelligence as an emerging technology in the current care of neurological disorders.Journal of neurology · 2021Review
- Zero-crossing patterns reveal subtle epileptiform discharges in the scalp EEG.Scientific reports · 2021Article
- Characterizing the electrophysiological abnormalities in visually reviewed normal EEGs of drug-resistant focal epilepsy patients.Brain communications · 2021Article
- A Feature Tensor-Based Epileptic Detection Model Based on Improved Edge Removal Approach for Directed Brain Networks.Frontiers in neuroscience · 2020Article
- Thalamic arousal network disturbances in temporal lobe epilepsy and improvement after surgery.Journal of neurology, neurosurgery, and psychiatry · 2019Article
- Slower alpha rhythm associates with poorer seizure control in epilepsy.Annals of clinical and translational neurology · 2019Article
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5 authors.
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Abstract
The contemporary use of interictal scalp electroencephalography (EEG) in the context of focal epilepsy workup relies on the visual identification of interictal epileptiform discharges. The high-specificity performance of this marker comes, however, at a cost of only moderate sensitivity. Zero-crossing interval analysis is an alternative to Fourier analysis for the assessment of the rhythmic component of EEG signals. We applied this method to standard EEG recordings of 78 patients divided into 4 subgroups: temporal lobe epilepsy (TLE), frontal lobe epilepsy (FLE), psychogenic nonepileptic seizures (PNES) and nonepileptic patients with headache. Interval-analysis based markers were capable of effectively discriminating patients with epilepsy from those in control subgroups (AUC~0.8) with diagnostic sensitivity potentially exceeding that of visual analysis. The identified putative epilepsy-specific markers were sensitive to the properties of the alpha rhythm and displayed weak or non-significant dependences on the number of antiepileptic drugs (AEDs) taken by the patients. Significant AED-related effects were concentrated in the theta interval range and an associated marker allowed for identification of patients on AED polytherapy (AUC~0.9). Interval analysis may thus, in perspective, increase the diagnostic yield of interictal scalp EEG. Our findings point to the possible existence of alpha rhythm abnormalities in patients with epilepsy.
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