ReviewFrontiers in neurology2021
Localization of Epileptic Foci Based on Simultaneous EEG-fMRI Data.
Review in Frontiers in neurology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Complementary predictive value of electromagnetic source imaging and hemodynamic responses in epilepsy surgery: A quantitative spatial analysis.Epilepsia · 2026Article
- Integrating multivariate resting-state fMRI features to localize epileptic networks in common childhood epilepsy.Epilepsia · 2026Article
- Mapping EEG Metrics to Human Affective and Cognitive Models: An Interdisciplinary Scoping Review from a Cognitive Neuroscience Perspective.Biomimetics (Basel, Switzerland) · 2025Review
- Precision Neuro-Oncology in Glioblastoma: AI-Guided CRISPR Editing and Real-Time Multi-Omics for Genomic Brain Surgery.International journal of molecular sciences · 2025Review
- Impact of visual distractors in virtual reality environments on sustained attention behavioral performance and EEG characteristics.Frontiers in human neuroscience · 2025Article
- Spatio-temporal independent component classification for localization of seizure onset zone.Frontiers in neurology · 2025Article
- EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.Frontiers in human neuroscience · 2025Article
- Investigating the role of auditory cues in modulating motor timing: insights from EEG and deep learning.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
- Exploring Aesthetic Perception in Impaired Aging: A Multimodal Brain-Computer Interface Study.Sensors (Basel, Switzerland) · 2024Article
- From bench to bedside: Overview of magnetoencephalography in basic principle, signal processing, source localization and clinical applications.NeuroImage. Clinical · 2024Review
- Enhancing the accuracy of electroencephalogram-based emotion recognition through Long Short-Term Memory recurrent deep neural networks.Frontiers in human neuroscience · 2023Article
- Machine learning approaches and non-linear processing of extracted components in frontal region to predict rTMS treatment response in major depressive disorder.Frontiers in systems neuroscience · 2023Article
- Simultaneous EEG-fMRI: What Have We Learned and What Does the Future Hold?Sensors (Basel, Switzerland) · 2022Review
- An Explainable Statistical Method for Seizure Prediction Using Brain Functional Connectivity from EEG.Computational intelligence and neuroscience · 2022Article
- An improved saliency model of visual attention dependent on image content.Frontiers in human neuroscience · 2022Article
- A Spherical Phase Space Partitioning Based Symbolic Time Series Analysis (SPSP-STSA) for Emotion Recognition Using EEG Signals.Frontiers in human neuroscience · 2022Article
- Identifying the neural network for neuromodulation in epilepsy through connectomics and graphs.Brain communications · 2022Article
- Simultaneous electroencephalography-functional magnetic resonance imaging for assessment of human brain function.Frontiers in systems neuroscience · 2022Review
- Detection of epileptic seizures through EEG signals using entropy features and ensemble learning.Frontiers in human neuroscience · 2022Article
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Authors and funding
5 authors.
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Abstract
Combining functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) enables a non-invasive investigation of the human brain function and evaluation of the correlation of these two important modalities of brain activity. This paper explores recent reports on using advanced simultaneous EEG-fMRI methods proposed to map the regions and networks involved in focal epileptic seizure generation. One of the applications of EEG and fMRI combination as a valuable clinical approach is the pre-surgical evaluation of patients with epilepsy to map and localize the precise brain regions associated with epileptiform activity. In the process of conventional analysis using EEG-fMRI data, the interictal epileptiform discharges (IEDs) are visually extracted from the EEG data to be convolved as binary events with a predefined hemodynamic response function (HRF) to provide a model of epileptiform BOLD activity and use as a regressor for general linear model (GLM) analysis of the fMRI data. This review examines the methodologies involved in performing such studies, including techniques used for the recording of EEG inside the scanner, artifact removal, and statistical analysis of the fMRI signal. It then discusses the results reported for patients with primary generalized epilepsy and patients with different types of focal epileptic disorders. An important matter that these results have brought to light is that the brain regions affected by interictal epileptic discharges might not be limited to the ones where they have been generated. The developed methods can help reveal the regions involved in or affected by a seizure onset zone (SOZ). As confirmed by the reviewed literature, EEG-fMRI provides information that comes particularly useful when evaluating patients with refractory epilepsy for surgery.
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