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In this paper we present a new localization method SMS-LORETA (Simultaneous Multiple Sources- Low Resolution Brain Electromagnetic Tomography), capable to locate efficiently multiple simultaneous sources. The new method overcomes some of…

Quantitative Methods · Quantitative Biology 2011-01-07 Avni Pllana , Herbert Bauer

We study source localization from high dimensional M/EEG data by extending a multiscale method based on Entropic inference devised to increase the spatial resolution of inverse problems. This method is used to construct informative prior…

Quantitative Methods · Quantitative Biology 2015-02-13 Leonardo S. Barbosa , Nestor Caticha

The brain-computer interface (BCI) establishes a non-muscle channel that enables direct communication between the human body and an external device. Electroencephalography (EEG) is a popular non-invasive technique for recording brain…

Machine Learning · Computer Science 2026-02-23 Jamal Hwaidi , Mohamed Chahine Ghanem

Scattered Light Imaging (SLI) is a novel approach for microscopically revealing the fibre architecture of unstained brain sections. The measurements are obtained by illuminating brain sections from different angles and measuring the…

Image and Video Processing · Electrical Eng. & Systems 2022-04-13 Esteban Vaca , Miriam Menzel , Katrin Amunts , Markus Axer , Timo Dickscheid

Magnetoencephalography (MEG) is an advanced imaging technique used to measure the magnetic fields outside the human head produced by the electrical activity inside the brain. Various source localization methods in MEG require the knowledge…

Methodology · Statistics 2017-07-06 Zhigang Yao , Ye Zhang , Zhidong Bai , William F. Eddy

We consider the problem of localization of sources of brain electrical activity from electroencephalographic (EEG) and magnetoencephalographic (MEG) measurements using spatial filtering techniques. We propose novel reduced-rank activity…

Signal Processing · Electrical Eng. & Systems 2024-08-02 Tomasz Piotrowski , Jan Nikadon , Alexander Moiseev

This paper is concerned with variational and Bayesian approaches to neuro-electromagnetic inverse problems (EEG and MEG). The strong indeterminacy of these problems is tackled by introducing sparsity inducing regularization/priors in a…

Signal Processing · Electrical Eng. & Systems 2023-06-28 Samy Mokhtari , Jean-Michel Badier , Christian G. Bénar , Bruno Torrésani

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

Electroencephalography (EEG) is a widely used, non-invasive method for capturing brain activity, and is particularly relevant for applications in Brain-Computer Interfaces (BCI). However, collecting high-quality EEG data remains a major…

Signal Processing · Electrical Eng. & Systems 2025-10-22 Henrique de Lima Alexandre , Clodoaldo Aparecido de Moraes Lima

MEG and EEG are noninvasive functional neuroimaging techniques that provide recordings of brain activity with high temporal resolution, and thus provide a unique window to study fast time-scale neural dynamics in humans. However, the…

Applications · Statistics 2015-11-13 Camilo Lamus , Matti S. Hamalainen , Emery N. Brown , Patrick L. Purdon

The curtain of technical limitations impeding rat multichannel non-invasive electroencephalography (EEG) has risen. Given the importance of this preclinical model, development and validation of EEG source imaging (ESI) is essential. We…

Neurons and Cognition · Quantitative Biology 2016-01-26 Pedro A. Valdes-Hernandez , Jihye Bae , Yinchen Song , Akira Sumiyoshi , Eduardo Aubert-Vazquez , Jorge J. Riera

Timely diagnosis is important for saving the life of epileptic patients. In past few years, a lot of treatments are available for epilepsy. These treatments require use of anti-seizure drugs but are not effective in controlling frequency of…

Machine Learning · Computer Science 2021-11-08 Shivam Gupta , Jyoti Meena , O. P Gupta

Region-based methods have proven necessary for improving segmentation accuracy of neuronal structures in electron microscopy (EM) images. Most region-based segmentation methods use a scoring function to determine region merging. Such…

Computer Vision and Pattern Recognition · Computer Science 2018-04-04 Ting Liu , Miaomiao Zhang , Mehran Javanmardi , Nisha Ramesh , Tolga Tasdizen

Medical image segmentation has become an essential technique in clinical and research-oriented applications. Because manual segmentation methods are tedious, and fully automatic segmentation lacks the flexibility of human intervention or…

Image and Video Processing · Electrical Eng. & Systems 2019-04-24 Kevin Karsch , Qing He , Ye Duan

Electroencephalography (EEG) source imaging aims to reconstruct the spatial distribution of neural activity within the brain from non-invasive scalp measurements. This inverse problem is severely ill-posed due to the low spatial resolution…

Numerical Analysis · Mathematics 2026-04-08 Joonas Lahtinen , Alexandra Koulouri

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

Human brain activity is based on electrochemical processes, which can only be measured invasively. Therefore, quantities such as magnetic flux density (MEG) or electric potential differences (EEG) are measured non-invasively in medicine and…

Numerical Analysis · Mathematics 2022-07-27 Sarah Leweke , Olaf Hauk , Volker Michel

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

Source localization using EEG is important in diagnosing various physiological and psychiatric diseases related to the brain. The high temporal resolution of EEG helps medical professionals assess the internal physiology of the brain in a…

Signal Processing · Electrical Eng. & Systems 2022-10-28 Teja Mannepalli , Aurobinda Routray

Electroencephalography (EEG) data present unique modeling challenges because recordings vary in length, exhibit very low signal to noise ratios, differ significantly across participants, drift over time within sessions, and are rarely…

Signal Processing · Electrical Eng. & Systems 2026-01-05 Shahar Ain Kedem , Itamar Zimerman , Eliya Nachmani