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Related papers: Non-Invasive Functional-Brain-Imaging with a Novel…

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The electroencephalogram, a type of non-invasive-based brain signal that has a user intention-related feature provides an efficient bidirectional pathway between user and computer. In this work, we proposed a deep learning framework based…

Human-Computer Interaction · Computer Science 2020-12-08 Byoung-Hee Kwon , Byeong-Hoo Lee , Ji-Hoon Jeong

Magnetoencephalography (MEG) and magnetic resonance imaging at ultra-low fields (ULF MRI) are two methods based on the ability of SQUID (superconducting quantum interference device) sensors to detect femtotesla magnetic fields. Combination…

In this paper, we propose a method to estimate the position, orientation and gain of a magnetic field sensor using a set of (large) electromagnetic coils. We apply the method for calibrating an array of optically pumped magnetometers (OPMs)…

Electroencephalography (EEG) and magnetoencephalography (MEG) measure neural activity non-invasively by capturing electromagnetic fields generated by dendritic currents. Although rooted in the same biophysics, EEG and MEG exhibit distinct…

Signal Processing · Electrical Eng. & Systems 2025-10-16 Qinfan Xiao , Ziyun Cui , Chi Zhang , Siqi Chen , Wen Wu , Andrew Thwaites , Alexandra Woolgar , Bowen Zhou , Chao Zhang

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

Magnetoencephalography (MEG) is a cutting-edge neuroimaging technique that measures the intricate brain dynamics underlying cognitive processes with an unparalleled combination of high temporal and spatial precision. MEG data analytics has…

Neurons and Cognition · Quantitative Biology 2025-05-20 Arthur Dehgan , Hamza Abdelhedi , Vanessa Hadid , Irina Rish , Karim Jerbi

In this paper, we analyze spatial sampling of electro- (EEG) magnetoencephalography (MEG), where the electric or magnetic field is typically sampled on a curved surface such as the scalp. Using simulated measurements, we study the…

One of the challenges in functional brain imaging is integration of complementary imaging modalities, such as magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI). MEG, which uses highly sensitive superconducting…

Classification of electroencephalogram (EEG) and electrocorticogram (ECoG) signals obtained during motor imagery (MI) has substantial application potential, including for communication assistance and rehabilitation support for patients with…

Computer Vision and Pattern Recognition · Computer Science 2025-10-20 Shuntaro Suzuki , Shunya Nagashima , Masayuki Hirata , Komei Sugiura

The human brain constitutes 2% of the total body mass, but consumes 20% of the oxygen. The rate of the brain's oxygen utilization can be determined from the knowledge of cerebral blood flow and oxygen extraction fraction (OEF). Therefore,…

Medical Physics · Physics 2022-02-04 Dengrong Jiang , Hanzhang Lu

Electroencephalography (EEG) and Magnetoencephalography (MEG) are pivotal in understanding brain activity but are limited by their poor spatial resolution. EEG/MEG source imaging (ESI) infers the high-resolution electric field distribution…

Signal Processing · Electrical Eng. & Systems 2024-02-01 Song Wang , Chen Wei , Kexin Lou , Dongfeng Gu , Quanying Liu

Non-invasive decoding of imagined speech remains challenging due to weak, distributed signals and limited labeled data. Our paper introduces an image-based approach that transforms magnetoencephalography (MEG) signals into time-frequency…

Computation and Language · Computer Science 2026-01-23 Soufiane Jhilal , Stéphanie Martin , Anne-Lise Giraud

Scalar optically-pumped magnetometers (OPMs) are being developed in small packages with high sensitivities. The high common-mode rejection ratio of these sensors allows for detection of very small signals in the presence of large background…

Instrumentation and Detectors · Physics 2021-09-17 Richard J. Clancy , Vladislav Gerginov , Orang Alem , Stephen Becker , Svenja Knappe

A brain--machine interface (BMI) based on motor imagery (MI) enables the control of devices using brain signals while the subject imagines performing a movement. It plays a vital role in prosthesis control and motor rehabilitation. To…

Signal Processing · Electrical Eng. & Systems 2024-09-20 Xiaying Wang , Michael Hersche , Michele Magno , Luca Benini

Characterizing functional brain networks in humans during magnetophosphene perception. Dense electroencephalography (EEG, 128 channels) was performed in N=3 volunteers during high-level (50 mT) magnetic field (MF) exposure. Functional brain…

Neurons and Cognition · Quantitative Biology 2018-03-02 Julien Modolo , Mahmoud Hassan , Alexandre Legros

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

The neuromagnetic activity (magnetoencephalogram, MEG) from healthy human brain and from an epileptic patient against chromatic flickering stimuli has been earlier analyzed on the basis of a memory functions formalism (MFF). Information…

Medical Physics · Physics 2010-06-29 O. Yu. Panischev , S. A. Demin , J. Bhattacharya

Human brain activity generates scalp potentials (electroencephalography EEG), intracranial potentials (iEEG), and external magnetic fields (magnetoencephalography MEG), all capable of being recorded, often simultaneously, for use in…

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

Decoding linguistically meaningful representations from non-invasive neural recordings remains a central challenge in neural speech decoding. Among available neuroimaging modalities, magnetoencephalography (MEG) provides a safe and…

Neurons and Cognition · Quantitative Biology 2025-12-23 Shuntaro Suzuki , Chia-Chun Dan Hsu , Yu Tsao , Komei Sugiura