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Recent advances in statistical theory, together with advances in the computational power of computers, provide alternative methods to do mass-univariate hypothesis testing in which a large number of univariate tests, can be properly used to…

Machine Learning · Statistics 2014-06-27 Seyed Mostafa Kia

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

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…

Neurons and Cognition · Quantitative Biology 2025-10-13 Beige Jerry Jin , Leila Wehbe

Traumatic Brain Injury (TBI) poses a significant global public health challenge, contributing to high morbidity and mortality rates and placing a substantial economic burden on healthcare systems worldwide. The diagnosis of TBI relies on…

Image and Video Processing · Electrical Eng. & Systems 2024-01-12 Hanem Ellethy , Shekhar S. Chandra , Viktor Vegh

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…

Image and Video Processing · Electrical Eng. & Systems 2024-03-15 Yohann Benchetrit , Hubert Banville , Jean-Rémi King

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

A Magnetoencephalography (MEG) time-series recording consists of multi-channel signals collected by superconducting sensors, with each signal's intensity reflecting magnetic field changes over time at the sensor location. Automating…

Signal Processing · Electrical Eng. & Systems 2025-01-22 Hanyang Dong , Shurong Sheng , Xiongfei Wang , Jiahong Gao , Yi Sun , Wanli Yang , Kuntao Xiao , Pengfei Teng , Guoming Luan , Zhao Lv

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

Brain-machine interfaces (BMIs), particularly those based on electroencephalography (EEG), offer promising solutions for assisting individuals with motor disabilities. However, challenges in reliably interpreting EEG signals for specific…

Signal Processing · Electrical Eng. & Systems 2025-04-23 Biplov Paneru , Bipul Thapa , Bishwash Paneru , Sanjog Chhetri Sapkota

Brain Electroencephalography (EEG) classification is widely applied to analyze cerebral diseases in recent years. Unfortunately, invalid/noisy EEGs degrade the diagnosis performance and most previously developed methods ignore the necessity…

Machine Learning · Computer Science 2018-02-12 Chenglong Dai , Jia Wu , Dechang Pi , Lin Cui

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…

Quantitative Methods · Quantitative Biology 2009-03-06 Hung-I Pai , Chih-Yuan Tseng , H. C. Lee

With the development of the modern society, mind control applied to both the recovery of disabled individuals and auxiliary control of normal people has obtained great attention in numerous researches. In our research, we attempt to…

Human-Computer Interaction · Computer Science 2015-09-29 Zhen Li , Jianjun Xu , Tingshao Zhu

Imaging the bio-impedance distribution of the brain can provide initial diagnosis of acute stroke. This paper presents a compact and non-radiative tomographic modality, i.e. multi-frequency Electromagnetic Tomography (mfEMT), for the…

Applied Physics · Physics 2020-07-29 Jinxi Xiang , Yonggui Dong , Yunjie Yang

Concurrency of transcranial magnetic stimulation with electroencephalography (TMS-EEG) technique is a powerful and challenging methodology for basic research and clinical applications. Aspects considered in experiments for effective TMS-EEG…

Neurons and Cognition · Quantitative Biology 2024-03-18 Hua Cheng

Current pain assessment within hospitals often relies on self-reporting or non-specific EKG vital signs. This system leaves critically ill, sedated, and cognitively impaired patients vulnerable to undertreated pain and opioid overuse.…

Machine Learning · Computer Science 2025-10-08 Aavid Mathrawala , Dhruv Kurup , Josie Lau

We present a novel solution to the problem of localizing magnetoencephalography (MEG) and electroencephalography (EEG) brain signals. The solution is sequential and iterative, and is based on minimizing the least-squares criterion by the…

Signal Processing · Electrical Eng. & Systems 2022-02-03 Amir Adler , Mati Wax , Dimitrios Pantazis

Background: Mild cognitive impairment (MCI) is often considered a precursor to Alzheimer's disease (AD) due to the high rate of progression from MCI to AD. Sensitive neural biomarkers may provide a tool for an accurate MCI diagnosis,…

Neurons and Cognition · Quantitative Biology 2022-11-02 Adi Wijaya , Noor Akhmad Setiawan , Asma Hayati Ahmad , Rahimah Zakaria , Zahiruddin Othman

Mild Traumatic Brain Injury (mTBI) is a significant public health challenge due to its high prevalence and potential for long-term health effects. Despite Computed Tomography (CT) being the standard diagnostic tool for mTBI, it often yields…

Image and Video Processing · Electrical Eng. & Systems 2024-04-09 Hanem Ellethy , Viktor Vegh , Shekhar S. Chandra

Traumatic brain injury (TBI) is a complex injury that is hard to predict and diagnose, with many studies focused on associating head kinematics to brain injury risk. Recently, there has been a push towards using computationally expensive…

Disease heterogeneity has been a critical challenge for precision diagnosis and treatment, especially in neurologic and neuropsychiatric diseases. Many diseases can display multiple distinct brain phenotypes across individuals, potentially…