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Reconstructing brain sources is a fundamental challenge in neuroscience, crucial for understanding brain function and dysfunction. Electroencephalography (EEG) signals have a high temporal resolution. However, identifying the correct…

Image and Video Processing · Electrical Eng. & Systems 2026-03-12 Marco Morik , Ali Hashemi , Klaus-Robert Müller , Stefan Haufe , Shinichi Nakajima

A non-invasive functional-brain-imaging system based on optically-pumped-magnetometers (OPM) is presented. The OPM-based magnetoencephalography (MEG) system features 20 OPM channels conforming to the subject's scalp. Due to proximity (12…

Brain-computer interface systems and the recording of brain activity has garnered significant attention across a diverse spectrum of applications. EEG signals have emerged as a modality for recording neural electrical activity. Among the…

Signal Processing · Electrical Eng. & Systems 2024-05-03 M. Moein Esfahani , Hossein Sadati , Vince D Calhoun

Electroencephalogram (EEG) signals play a pivotal role in clinical medicine, brain research, and neurological disease studies. However, susceptibility to various physiological and environmental artifacts introduces noise in recorded EEG…

Signal Processing · Electrical Eng. & Systems 2024-05-24 Bin Wang , Fei Deng , Peifan Jiang

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

Skull stripping magnetic resonance images (MRI) of the human brain is an important process in many image processing techniques, such as automatic segmentation of brain structures. Numerous methods have been developed to perform this task,…

Image and Video Processing · Electrical Eng. & Systems 2026-04-16 Hjalti Thrastarson , Lotta M. Ellingsen

Affordable upper-limb prostheses often lack intuitive control systems, limiting functionality and accessibility for amputees in low-resource settings. This project presents a low-cost, dual-mode neuro-muscular control system integrating…

Machine Learning · Computer Science 2025-12-22 Pranesh Sathish Kumar

Intraoperative ultrasound imaging is used to facilitate safe brain tumour resection. However, due to challenges with image interpretation and the physical scanning, this tool has yet to achieve widespread adoption in neurosurgery. In this…

Decoding visual information from electroencephalography (EEG) has recently achieved promising results, primarily focusing on reconstructing two-dimensional (2D) images from brain activity. However, the reconstruction of three-dimensional…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Emanuele Balloni , Emanuele Frontoni , Chiara Matti , Marina Paolanti , Roberto Pierdicca , Emiliano Santarnecchi

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

Integrating Brain-Machine Interfaces into non-clinical applications like robot motion control remains difficult - despite remarkable advancements in clinical settings. Specifically, EEG-based motor imagery systems are still error-prone,…

The electroencephalogram (EEG) has been the gold standard for quantifying mental workload; however, due to its complexity and non-portability, it can be constraining. ECG signals, which are feasible on wearable equipment pieces such as…

Machine Learning · Computer Science 2026-01-13 Malavika Pradeep , Akshay Sasi , Nusaibah Farrukh , Rahul Venugopal , Elizabeth Sherly

This paper presents a novel single-channel decomposition approach to facilitate the decomposition of electroencephalography (EEG) signals recorded with limited channels. Our model posits that an EEG signal comprises short, shift-invariant…

Signal Processing · Electrical Eng. & Systems 2024-11-15 Hiroshi Higashi

Translating imagined speech from human brain activity into voice is a challenging and absorbing research issue that can provide new means of human communication via brain signals. Endeavors toward reconstructing speech from brain activity…

Audio and Speech Processing · Electrical Eng. & Systems 2023-01-19 Young-Eun Lee , Seo-Hyun Lee , Sang-Ho Kim , Seong-Whan Lee

Electroencephalography (EEG) is a non-invasive technique for recording brain electrical activity, widely used in brain-computer interface (BCI) and healthcare. Recent EEG foundation models trained on large-scale datasets have shown improved…

Machine Learning · Computer Science 2025-09-29 Yi Ding , Muyun Jiang , Weibang Jiang , Shuailei Zhang , Xinliang Zhou , Chenyu Liu , Shanglin Li , Yong Li , Cuntai Guan

Non-invasive brainwave decoding is usually done using Magneto/Electroencephalography (MEG/EEG) sensor measurements as inputs. This makes combining datasets and building models with inductive biases difficult as most datasets use different…

Signal Processing · Electrical Eng. & Systems 2024-10-29 Yonatan Gideoni , Ryan Charles Timms , Oiwi Parker Jones

Current methodologies typically integrate biophysical brain models with functional magnetic resonance imaging(fMRI) data - while offering millimeter-scale spatial resolution (0.5-2 mm^3 voxels), these approaches suffer from limited temporal…

Neurons and Cognition · Quantitative Biology 2025-07-17 Yubo Hou , Zhengxin Zhang , Ziyi Wang , Wenlian Lu , Jianfeng Feng , Taiping Zeng

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

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

Current techniques of neuroimaging, including electrical devices, are either of low spatiotemporal resolution or invasive, impeding multiscale monitoring of brain activity at both single cell and network levels. Overcoming this issue is of…