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

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Microscopy has been key to tremendous advances in science, technology, and medicine, revealing structure and dynamics across time and length scales. However, combining high spatial and temporal resolution in a non-invasive, label-free…

Fourier ptychographic microscopy (FPM) is a promising quantitative phase imaging technique that enables high-resolution, label-free imaging over a large field-of-view. Here, we present the first application of FPM for the quantitative…

We present the concept and the results of an investigation of an all-optical vector magnetic field sensor scheme developed for biological applications such as non-zero field magnetoencephalography and magnetocardiography. The scheme differs…

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

While functional magnetic resonance imaging (fMRI) offers valuable insights into brain activity, it is limited by high operational costs and significant infrastructural demands. In contrast, electroencephalography (EEG) provides…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Kristofer Grover Roos , Atsushi Fukuda , Quan Huu Cap

Understanding the neural mechanisms behind auditory and linguistic processing is key to advancing cognitive neuroscience. In this study, we use Magnetoencephalography (MEG) data to analyze brain responses to spoken language stimuli. We…

Neurons and Cognition · Quantitative Biology 2025-01-08 Matteo Ciferri , Matteo Ferrante , Nicola Toschi

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

Machine learning techniques have enabled researchers to leverage neuroimaging data to decode speech from brain activity, with some amazing recent successes achieved by applications built using invasive devices. However, research requiring…

Machine Learning · Computer Science 2024-10-29 Jeremiah Ridge , Oiwi Parker Jones

Electroencephalogram (EEG) decoding models for brain-computer interfaces (BCIs) struggle with cross-dataset learning and generalization due to channel layout inconsistencies, non-stationary signal distributions, and limited…

Human-Computer Interaction · Computer Science 2025-07-17 Xiaoqing Chen , Siyang Li , Dongrui Wu

A Brain Computer Interface (BCI) connects the human brain to the outside world, providing a direct communication channel. Electroencephalography (EEG) signals are commonly used in BCIs to reflect cognitive patterns related to motor function…

Machine Learning · Computer Science 2025-11-19 Abdullah Al Shiam , Md. Khademul Islam Molla , Abu Saleh Musa Miah , Md. Abdus Samad Kamal

Magnetic field imaging is a valuable resource for signal source localization and characterization. This work reports an optically pumped magnetometer (OPM) based on the free-induction-decay (FID) protocol, that implements microfabricated…

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

Electroencephalography (EEG) is a critical, non-invasive method to monitor electrical brain activity. EEGs can span anywhere from a couple seconds to multiple hours, posing a major hurdle for existing deep learning methods due to two major…

Artificial Intelligence · Computer Science 2026-05-28 Abhilash Durgam , Nyle Siddiqui , Jeffrey A. Chan-Santiago , Qiushi Fu , Elakkat D. Gireesh , Mubarak Shah

Simultaneously recorded electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) can be used to non-invasively measure the spatiotemporal dynamics of the human brain. One challenge is dealing with the artifacts that…

Neurons and Cognition · Quantitative Biology 2017-07-26 Josef Faller , Linbi Hong , Jennifer Cummings , Paul Sajda

To minimize functional morbidity associated with brain surgery, new preventive approaches (also referred to as "prehabilitation") by using motor-imagery-based computer interfaces (MI-BCIs) can be utilized. To achieve successful MI-BCI…

Neurons and Cognition · Quantitative Biology 2017-08-03 Milena Korostenskaja , Christoph Kapeller , Ki H Lee , Christoph Guger , James Baumgartner , Eduardo M. Castillo

Combining low cost wireless EEG sensors with smartphones offers novel opportunities for mobile brain imaging in an everyday context. We present a framework for building multi-platform, portable EEG applications with real-time 3D source…

Human-Computer Interaction · Computer Science 2014-03-05 Arkadiusz Stopczynski , Carsten Stahlhut , Jakob Eg Larsen , Michael Kai Petersen , Lars Kai Hansen

Electroencephalography (EEG) is a non-invasive method for measuring brain activity with high temporal resolution; however, EEG signals often exhibit low signal-to-noise ratios because of contamination from physiological and environmental…

Machine Learning · Computer Science 2025-09-03 Yuhong Zhang , Xusheng Zhu , Yuchen Xu , ChiaEn Lu , Hsinyu Shih , Gert Cauwenberghs , Tzyy-Ping Jung

Single-channel SQUID system technology, operating at a noise level of 100s of aT/$\sqrt{\textrm{Hz}}$, enables the non-invasive detection of synchronized spiking activity at the single-trial level via magnetoencephalography (MEG). However,…

Regeneration of the nervous system after injury remains an important therapeutic objective, especially in the central nervous system (CNS), in which regeneration is restricted by both neuronal limitations as well as adverse extracellular…

Neurons and Cognition · Quantitative Biology 2026-05-05 Maryam Kheyrollah , Reza Khanbabaie , Chris Ullrich , Mohammad Moulaeifard

Neuronal electrical activity underlies human cognition including perception, attention, memory, language, and decision-making. Yet its direct, noninvasive measurement in the living human brain remains a fundamental challenge. Existing…