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Magnetoencephalography (MEG) and electroencephalogra-phy (EEG) are non-invasive modalities that measure the weak electromagnetic fields generated by neural activity. Inferring the location of the current sources that generated these…

Machine Learning · Statistics 2019-02-14 Hicham Janati , Thomas Bazeille , Bertrand Thirion , Marco Cuturi , Alexandre Gramfort

Epilepsy is a neurological condition such that it affects the brain and the nervous system. It is characterized by recurrent seizures, which are physical reactions to sudden, usually brief, excessive electrical discharges in a group of…

Signal Processing · Electrical Eng. & Systems 2018-07-30 Asmaa Hamad , Aboul Ella Hassanien , Aly A. Fahmy , Essam H. Houssein

Epilepsy is the second most common brain disorder after migraine. Automatic detection of epileptic seizures can considerably improve the patients' quality of life. Current Electroencephalogram (EEG)-based seizure detection systems encounter…

Signal Processing · Electrical Eng. & Systems 2018-03-28 Ramy Hussein , Hamid Palangi , Rabab Ward , Z. Jane Wang

Accurate electroencephalography (EEG) and magnetoencephalography (MEG) source localization and reconstruction are essential for understanding brain function, yet remain challenging because the underlying EEG/MEG inverse problem is…

Optimization and Control · Mathematics 2026-04-29 Julia Jurkowska , Joanna Dreszer , Monika Lewandowska , Krzysztof Tołpa , Tomasz Piotrowski

Epilepsy is a neurological disorder that affects normal neural activity. These electrical activities can be recorded as signals containing information about the brain known as Electroencephalography (EEG) signals. Analysis of the EEG…

Signal Processing · Electrical Eng. & Systems 2025-07-10 Fatemeh Valipour , Zahra Valipour , Mani Garousi , Ali Khadem

This report introduces a new hierarchical Bayesian model for the EEG source localization problem. This model promotes structured sparsity to search for focal brain activity. This sparsity is obtained via a multivariate Bernoulli Laplacian…

Methodology · Statistics 2015-09-16 Facundo Costa , Hadj Batatia , Thomas Oberlin , Jean-Yves Tourneret

The problem of reconstructing brain activity from electric potential measurements performed on the surface of a human head is not an easy task: not just because the solution of the related inverse problem is fundamentally ill-posed (not…

Numerical Analysis · Mathematics 2023-08-11 Santtu Söderholm , Joonas Lahtinen , Carsten H. Wolters , Sampsa Pursiainen

Brain source imaging is an important method for noninvasively characterizing brain activity using Electroencephalogram (EEG) or Magnetoencephalography (MEG) recordings. Traditional EEG/MEG Source Imaging (ESI) methods usually assume that…

Applications · Statistics 2019-06-07 Feng Liu , Li Wang , Yifei Lou , Rencang Li , Patrick Purdon

Magnetoencephalography and electroencephalography (M/EEG) are non-invasive modalities that measure the weak electromagnetic fields generated by neural activity. Estimating the location and magnitude of the current sources that generated…

Machine Learning · Statistics 2019-10-16 Hicham Janati , Thomas Bazeille , Bertrand Thirion , Marco Cuturi , Alexandre Gramfort

We provide an overview of the state-of-the-art for mathematical methods that are used to reconstruct brain activity from neurophysiological data. After a brief introduction on the mathematics of the forward problem, we discuss standard and…

Quantitative Methods · Quantitative Biology 2017-05-09 Alberto Sorrentino , Michele Piana

Invasive electroencephalograph (EEG) recordings of ten patients suffering from focal epilepsy were analyzed using the method of renormalized entropy. Introduced as a complexity measure for the different regimes of a dynamical system, the…

Medical Physics · Physics 2009-10-31 K. Kopitzki , P. C. Warnke , J. Timmer

Diagnosing epilepsy is a problem of crucial importance. So analysing EEG data is of much importance to help this diagnosis. Assembling the Feigenbaum graphs for EEG signals. And calculating their average clustering, average degree, and…

Neurons and Cognition · Quantitative Biology 2019-02-08 Gabriel Guarneros B. , Cristian Pérez A. , Andrea Montiel P. , J. F. Rojas

Current non-invasive neuroimaging techniques trade off between spatial resolution and temporal resolution. While magnetoencephalography (MEG) can capture rapid neural dynamics and functional magnetic resonance imaging (fMRI) can spatially…

Neurons and Cognition · Quantitative Biology 2025-10-13 Beige Jerry Jin , Leila Wehbe

The electroencephalographic (EEG) data intracerebrally recorded from 20 epileptic humans with different brain origins of focal epilepsies or types of seizures, ages and sexes are investigated (nearly 700 million data). Multi channel…

Biological Physics · Physics 2010-02-19 Caglar Tuncay

Detecting where and when brain regions activate in a cognitive task or in a given clinical condition is the promise of non-invasive techniques like magnetoencephalography (MEG) or electroencephalography (EEG). This problem, referred to as…

Machine Learning · Statistics 2020-11-26 Jérôme-Alexis Chevalier , Alexandre Gramfort , Joseph Salmon , Bertrand Thirion

Inferring strength and direction of interactions from electroencephalographic (EEG) recordings is of crucial importance to improve our understanding of dynamical interdependencies underlying various physiologic and pathophysiologic…

Neurons and Cognition · Quantitative Biology 2016-10-07 Klaus Lehnertz , Henning Dickten

A normative electrographic activity map could be a powerful resource to understand normal brain function and identify abnormal activity. Here, we present a normative brain map using scalp EEG in terms of relative band power. In this…

Neurons and Cognition · Quantitative Biology 2023-04-07 Vytene Janiukstyte , Thomas W Owen , Umair J Chaudhary , Beate Diehl , Louis Lemieux , John S Duncan , Jane de Tisi , Yujiang Wang , Peter N Taylor

The EEG source localization is an ill-posed problem. It involves estimation of the sources which outnumbers the number of measurements. For a given measurement at given time all sources are not active which makes the problem as sparse…

Signal Processing · Electrical Eng. & Systems 2022-02-02 Teja Mannepalli , Aurobinda Routray

Epilepsy is the fourth most common neurological disorder, affecting about 1% of the population at all ages. As many as 60% of people with epilepsy experience focal seizures which originate in a certain brain area and are limited to part of…

Machine Learning · Computer Science 2019-03-20 Diyuan Lu , Jochen Triesch

Source imaging based on magnetoencephalography (MEG) and electroencephalography (EEG) allows for the non-invasive analysis of brain activity with high temporal and good spatial resolution. As the bioelectromagnetic inverse problem is…

Applications · Statistics 2016-07-29 Daniel Strohmeier , Yousra Bekhti , Jens Haueisen , Alexandre Gramfort