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Electroencephalography (EEG) monitors ---by either intrusive or noninvasive electrodes--- time and frequency variations and spectral content of voltage fluctuations or waves, known as brain rhythms, which in some way uncover activity during…

Neurons and Cognition · Quantitative Biology 2019-03-13 Javier A. Galadí , Joaquín J. Torres , J. Marro

We study the coherence in time and space of electromagnetic fields propagated through complex media. Whether for localization, imaging or telecommunication, the development of dedicated numerical techniques is generally based on the…

Computational Physics · Physics 2022-04-21 Thomas Fromenteze , Matthieu Davy , Okan Yurduseven , Yann Marie-Joseph , Cyril Decroze

Electroencephalography (EEG) signals, known for convenient non-invasive acquisition but low signal-to-noise ratio, have recently gained substantial attention due to the potential to decode natural images. This paper presents a…

Human-Computer Interaction · Computer Science 2024-04-05 Yonghao Song , Bingchuan Liu , Xiang Li , Nanlin Shi , Yijun Wang , Xiaorong Gao

Electrophysiological signals (electroencephalography, EEG, and magnetoencephalography , MEG), as many natural processes, exhibit scale-invariance properties resulting in a power-law (1/f) spectrum. Interestingly, EEG and MEG differ in their…

Neurons and Cognition · Quantitative Biology 2019-10-25 Christian-G. Bénar , C. Grova , V. Jirsa , J. Lina

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

Over recent decades, neuroimaging tools, particularly electroencephalography (EEG), have revolutionized our understanding of the brain and its functions. EEG is extensively used in traditional brain-computer interface (BCI) systems due to…

Neurons and Cognition · Quantitative Biology 2026-05-12 Zaineb Ajra , Binbin Xu , Gérard Dray , Jacky Montmain , Stéphane Perrey

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

We propose a novel technique to assess functional brain connectivity in EEG/MEG signals. Our method, called Sparsely-Connected Sources Analysis (SCSA), can overcome the problem of volume conduction by modeling neural data innovatively with…

Methodology · Statistics 2010-08-05 Stefan Haufe , Ryota Tomioka , Guido Nolte , Klaus-Robert Mueller , Motoaki Kawanabe

The dynamic behavior of scalp potentials (EEG) is apparently due to some combination of global and local processes with important top-down and bottom-up interactions across spatial scales. In treating global mechanisms, we stress the…

Neurons and Cognition · Quantitative Biology 2010-04-27 Lester Ingber , Paul L. Nunez

Several methods have been developed to extract information from electroencephalograms (EEG). One of them is Phase-Amplitude Coupling (PAC) which is a type of Cross-Frequency Coupling (CFC) method, consisting in measure the synchronization…

Neurons and Cognition · Quantitative Biology 2021-04-13 Marco A. Formoso , Andrés Ortiz , Francisco J. Martínez-Murcia , Nicolás Gallego-Molina , Juan L. Luque

The aim of this study is to investigate bursts- related EEG signals in a focal hand dystonia patient. Despite of considering time domain and frequency domain techniques as mutually exclusive analysis, in this contribution we have taken…

Medical Physics · Physics 2018-02-08 Giulia Cisotto , Umberto Michieli , Leonardo Badia

Inferring patterns of synchronous brain activity from a heterogeneous sample of electroencephalograms (EEG) is scientifically and methodologically challenging. While it is intuitively and statistically appealing to rely on readings from…

Electroencephalography (EEG) signals reflect activities on certain brain areas. Effective classification of time-varying EEG signals is still challenging. First, EEG signal processing and feature engineering are time-consuming and highly…

Human-Computer Interaction · Computer Science 2019-08-27 Xiang Zhang , Lina Yao , Xianzhi Wang , Wenjie Zhang , Shuai Zhang , Yunhao Liu

Electroencephalography provides a non-invasive window into brain activity, offering valuable insights for neurological research, brain-computer interfaces, and clinical diagnostics. However, the development of robust machine learning models…

Signal Processing · Electrical Eng. & Systems 2025-02-26 Chi-Sheng Chen , Ying-Jung Chen , Aidan Hung-Wen Tsai

In this paper, we analyze electroencephalograms (EEG) which are recordings of brain electrical activity. We develop new clustering methods for identifying synchronized brain regions, where the EEGs show similar oscillations or waveforms…

Methodology · Statistics 2020-07-29 Tianbo Chen , Ying Sun , Carolina Euan , Hernando Ombao

Visual decoding from electroencephalography (EEG) has emerged as a highly promising avenue for non-invasive brain-computer interfaces (BCIs). Existing EEG-based decoding methods predominantly align brain signals with the final-layer…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Jingyi Tang , Shuai Jiang , Fei Su , Zhicheng Zhao

Contemporary neuroimaging methods can shed light on the basis of human neural and cognitive specializations, with important implications for neuroscience and medicine. Different MRI acquisitions provide different brain networks at the…

Neurons and Cognition · Quantitative Biology 2016-02-23 C. Alonso-Montes , I. Diez , L. Remaki , I. Escudero , B. Mateos , Y. Rosseel , D. Marinazzo , S. Stramaglia , J. Cortes

A new model of physically realizable electromagnetic source is proposed. The source is partially coherent and non-uniformly totally polarized. The coherence and polarization characteristics of this new source are analyzed. The spatial…

An inhomogeneous anisotropic physical model of the brain cortex is presented that predicts the emergence of non--evanescent (weakly damped) wave--like modes propagating in the thin cortex layers transverse to both the mean neural fiber…

Biological Physics · Physics 2020-04-29 Vitaly L. Galinsky , Lawrence R. Frank

Humans constantly interact with digital devices that disregard their feelings. However, the synergy between human and technology can be strengthened if the technology is able to distinguish and react to human emotions. Models that rely on…

Human-Computer Interaction · Computer Science 2020-05-07 Andrea Kuijt , Maryam Alimardani