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Magnetoencephalography (MEG) provides dynamic spatial-temporal insight of neural activities in the cortex. Because the number of possible sources is far greater than the number of MEG detectors, the proposition to localize sources directly…

定量方法 · 定量生物学 2009-03-06 Hung-I Pai , Chih-Yuan Tseng , H. C. Lee

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…

统计方法学 · 统计学 2017-07-06 Zhigang Yao , Ye Zhang , Zhidong Bai , William F. Eddy

We study the distribution of brain source from the most advanced brain imaging technique, Magnetoencephalography (MEG), which measures the magnetic fields outside the human head produced by the electrical activity inside the brain. Common…

应用统计 · 统计学 2019-08-13 Zhigang Yao , Zengyan Fan , Masahito Hayashi , William F. Eddy

High temporal resolution measurements of human brain activity can be performed by recording the electric potentials on the scalp surface (electroencephalography, EEG), or by recording the magnetic fields near the surface of the head…

数据分析、统计与概率 · 物理学 2015-01-22 Kevin H. Knuth

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…

统计计算 · 统计学 2014-08-01 Zhigang Yao , William F. Eddy

In this paper, we propose a novel source model for a magnetoencephalography (MEG) inverse problem that combines a conventional extended parametric approach and an imaging approach.Our aim is to separately identify a focal current source and…

信号处理 · 电气工程与系统科学 2023-02-27 Takaaki Nara , Ten-yu Yang , Kenta Kabashima

Magnetoencephalography (MEG) is a powerful technique for studying the human brain function. However, accurately estimating the number of sources that contribute to the MEG recordings remains a challenging problem due to the low…

信号处理 · 电气工程与系统科学 2023-09-22 Amita Giri , John C. Mosher , Amir Adler , Dimitrios Pantazis

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…

神经元与认知 · 定量生物学 2025-10-13 Beige Jerry Jin , Leila Wehbe

Magnetoencephalography (MEG) is a noninvasive method for measuring magnetic flux signals caused by brain activity using sensor arrays located on or above the scalp. A common strategy for monitoring brain activity is to place sensors on a…

医学物理 · 物理学 2022-05-24 Wan-Jin Yeo , Samu Taulu , J. Nathan Kutz

Magnetoencephalography (MEG) is an important noninvasive, nonhazardous technology for functional brain mapping, measuring the magnetic fields due to the intracellular neuronal current flow in the brain. However, most often, the inherent…

仪器与探测器 · 物理学 2015-03-20 A. Ukil

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…

机器学习 · 统计学 2019-10-16 Hicham Janati , Thomas Bazeille , Bertrand Thirion , Marco Cuturi , Alexandre Gramfort

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…

机器学习 · 统计学 2019-02-14 Hicham Janati , Thomas Bazeille , Bertrand Thirion , Marco Cuturi , Alexandre Gramfort

In the past five years, the use of generative and foundational AI systems has greatly improved the decoding of brain activity. Visual perception, in particular, can now be decoded from functional Magnetic Resonance Imaging (fMRI) with…

图像与视频处理 · 电气工程与系统科学 2024-03-15 Yohann Benchetrit , Hubert Banville , Jean-Rémi King

We present a deep learning solution to the problem of localization of magnetoencephalography (MEG) brain signals. The proposed deep model architectures are tuned for single and multiple time point MEG data, and can estimate varying numbers…

信号处理 · 电气工程与系统科学 2020-12-02 Dimitrios Pantazis , Amir Adler

Magnetoencephalography (MEG) is an important noninvasive, nonhazardous technology for functional brain mapping, measuring the magnetic fields due to the intracellular neuronal current flow in the brain. However, the inherent level of noise…

其他计算机科学 · 计算机科学 2015-03-24 A. Ukil

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…

信号处理 · 电气工程与系统科学 2024-02-01 Song Wang , Chen Wei , Kexin Lou , Dongfeng Gu , Quanying Liu

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…

应用统计 · 统计学 2015-11-13 Camilo Lamus , Matti S. Hamalainen , Emery N. Brown , Patrick L. Purdon

We propose a maximum entropy (ME) based approach to smooth noise not only in data but also to noise amplified by second order derivative calculation of the data especially for electroencephalography (EEG) studies. The approach includes two…

定量方法 · 定量生物学 2007-11-20 Chih-Yuan Tseng , HC Lee

Brain activity can be measured using magnetic fields located at some distance from the brain, a technique called magneto-encephalography (MEG). The origin of such magnetic fields are the ionic currents involved in neuronal activity. While…

神经元与认知 · 定量生物学 2021-12-06 Alexis Garcia-Rodriguez , Alain Destexhe

Determining the magnitude and location of neural sources within the brain that are responsible for generating magnetoencephalography (MEG) signals measured on the surface of the head is a challenging problem in functional neuroimaging. The…

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