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Related papers: EEG source localization using a sparsity prior bas…

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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

State-space models are widely employed across various research disciplines to study unobserved dynamics. Conventional estimation techniques, such as Kalman filtering and expectation maximisation, offer valuable insights but incur high…

Computation · Statistics 2023-11-28 Jose M. Sanchez-Bornot , Roberto C. Sotero , Scott Kelso , Damien Coyle

Reconstructing brain sources is a fundamental challenge in neuroscience, crucial for understanding brain function and dysfunction. Electroencephalography (EEG) signals have a high temporal resolution. However, identifying the correct…

Image and Video Processing · Electrical Eng. & Systems 2026-03-12 Marco Morik , Ali Hashemi , Klaus-Robert Müller , Stefan Haufe , Shinichi Nakajima

The use of EEG biometrics, for the purpose of automatic people recognition, has received increasing attention in the recent years. Most of current analysis rely on the extraction of features characterizing the activity of single brain…

Neurons and Cognition · Quantitative Biology 2014-09-10 Daria La Rocca , Patrizio Campisi , Balazs Vegso , Peter Cserti , Gyorgy Kozmann , Fabio Babiloni , Fabrizio De Vico Fallani

Magnetoencephalographic (MEG) measurements record magnetic fields generated from neurons while information is being processed in the brain. The inverse problem of identifying sources of biomagnetic fields and deducing their intensities from…

Neurons and Cognition · Quantitative Biology 2009-11-11 Hung-I Pai , Chih-Yuan Tseng , HC Lee

This paper deals with the EEG/MEG neuroimaging problem: given measurements of scalp electric potential differences (EEG: electroencephalogram) and extracranial magnetic fields (MEG: magnetoencephalogram), find the 3D distribution of the…

Mathematical Physics · Physics 2007-10-18 Roberto D. Pascual-Marqui

This work considers the optimization of electrode positions in head imaging by electrical impedance tomography. The study is motivated by maximizing the sensitivity of electrode measurements to conductivity changes when monitoring the…

Numerical Analysis · Mathematics 2023-12-19 N. Hyvönen , A. Jääskeläinen , R. Maity , A. Vavilov

In this paper, we explore the multiple source localisation problem in the cerebral cortex using magnetoencephalography (MEG) data. We model neural currents as point-wise dipolar sources which dynamically evolve over time, then model dipole…

Applications · Statistics 2015-06-18 Xi Chen , Simo Särkkä , Simon Godsill

The idea to estimate the statistical interdependence among (interacting) brain regions has motivated numerous researchers to investigate how the resulting connectivity patterns and networks may organize themselves under any conceivable…

Neurons and Cognition · Quantitative Biology 2021-02-03 Matteo Fraschini , Simone Maurizio La Cava , Luca Didaci , Luigi Barberini

Different functional areas of the human brain play different roles in brain activity, which has not been paid sufficient research attention in the brain-computer interface (BCI) field. This paper presents a new approach for…

Signal Processing · Electrical Eng. & Systems 2019-04-29 Chuanqi Tan , Fuchun Sun , Tao Kong , Bin Fang , Wenchang Zhang

Electroencephalography (EEG) signals have been promising for long-term braking intensity prediction but are prone to various artifacts that limit their reliability. Here, we propose a novel framework that models EEG signals as mixtures of…

Human-Computer Interaction · Computer Science 2026-04-21 Zikun Zhou , Wenshuo Wang , Wenzhuo Liu , Hui Yao , Chaopeng Zhang , Yichen Liu , Xiaonan Yang , Junqiang Xi

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

A major challenge in cognitive neuroscience is to evaluate the ability of the human brain to categorize or group visual stimuli based on common features. This categorization process is very fast and occurs in few hundreds of millisecond…

Neurons and Cognition · Quantitative Biology 2016-06-06 Ahmad Mheich , Mahmoud Hassan , Olivier Dufor , Mohamad Khalil , Fabrice Wendling

Transcranial electric stimulation (TES) can modulate intrinsic neural activity in the brain by injecting weak currents through electrodes attached to the scalp. TES has been widely used as a neuroscience tool to investigate how behavioural…

Magnetoencephalography (MEG) is an imaging technique used to measure the magnetic field outside the human head produced by the electrical activity inside the brain. The MEG inverse problem, identifying the location of the electrical sources…

Computation · Statistics 2014-08-01 Zhigang Yao , William F. Eddy

The M/EEG inverse problem is ill-posed. Thus additional hypotheses are needed to constrain the solution space. In this work, we consider that brain activity which generates an M/EEG signal is a connected cortical region. We study the case…

Signal Processing · Electrical Eng. & Systems 2018-12-12 Kostiantyn Maksymenko , Maureen Clerc , Théodore Papadopoulo

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

Invasive intracranial electroencephalography (iEEG) or electrocorticography (ECoG) measures electric potential directly on the surface of the brain and can be used to inform treatment planning for epilepsy surgery. Combined with numerical…

Two techniques are proposed to alleviate the computational burden of MUltiple SIgnal Classification (MUSIC) algorithm applied to Electroencephalogram (EEG) source localization. A significant reduction was achieved by parsing the cortex…

Neurons and Cognition · Quantitative Biology 2017-07-27 Seyede Mahya Safavi , Beth Lopour , Pai H. Chou

M/EEG source localization is an open research issue. To solve it, it is important to have good knowledge of several physical parameters to build a reliable head operator. Amongst them, the value of the conductivity of the human skull has…

Methodology · Statistics 2017-01-06 Facundo Costa , Hadj Batatia , Thomas Oberlin , Jean-Yves Tourneret