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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

Background: Transcranial magnetic stimulation (TMS) is a powerful tool to investigate neurophysiology of the human brain and treat brain disorders. Traditionally, therapeutic TMS has been applied in a one-size-fits-all approach,…

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

Electroencephalography (EEG) recordings are analyzed using battery-powered wearable devices to monitor brain activities and neurological disorders. These applications require long and continuous processing to generate feasible results.…

Signal Processing · Electrical Eng. & Systems 2024-02-16 Zain Taufique , Muhammad Awais Bin Altaf , Antonio Miele , Pasi Liljeberg , Anil Kanduri

Chronobiological rhythms, such as the circadian rhythm, have long been linked to neurological disorders, but it is currently unknown how pathological processes affect the expression of biological rhythms in the brain. Here, we use the…

The term gestalt has been widely used in the field of psychology which defined the perception of human mind to group any object not in part but as a unified whole. Music in general is polytonic i.e. a combination of a number of pure tones…

Electroencephalography (EEG) signals, known for convenient non-invasive acquisition but low signal-to-noise ratio, have recently gained substantial attention due to the potential to decode natural images. This paper presents a…

Human-Computer Interaction · Computer Science 2024-04-05 Yonghao Song , Bingchuan Liu , Xiang Li , Nanlin Shi , Yijun Wang , Xiaorong Gao

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

Electroencephalography (EEG) is an invaluable tool in neuroscience, offering insights into brain activity with high temporal resolution. Recent advancements in machine learning and generative modeling have catalyzed the application of EEG…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Yashvir Sabharwal , Balaji Rama

The extent of intra-individual and inter-individual variability is an important factor in determining the statistical, and hence possibly clinical, significance of observed differences in the EEG. This study investigates the changes in…

Neurons and Cognition · Quantitative Biology 2018-01-08 Sacha Jennifer van Albada , Christopher J. Rennie , Peter A. Robinson

The cognitive functions of human and non-human primates rely on the dynamic interplay of distributed neural assemblies. As such, it seems unlikely that cognition can be supported by macroscopic brain dynamics at the proximity of…

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

Brain function as measured by multichannel EEG recordings can be described to a high level of accuracy by microstates, characterized as a sequence of time intervals within which the sign invariant normalized scalp electric potential field…

Neurons and Cognition · Quantitative Biology 2022-08-08 Roberto D. Pascual-Marqui , Kieko Kochi , Toshihiko Kinoshita

Subcortical structures play a critical role in brain function. However, options for assessing electrophysiological activity in these structures are limited. Electromagnetic fields generated by neuronal activity in subcortical structures can…

Stroke-induced disturbances of large-scale cortical networks are known to be associated with the extent of motor deficits. We argue that identifying brain networks representative of motor behavior in the resting brain would provide…

Neurons and Cognition · Quantitative Biology 2019-07-24 Ozan Özdenizci , Timm Meyer , Felix Wichmann , Jan Peters , Bernhard Schölkopf , Müjdat Çetin , Moritz Grosse-Wentrup

Epileptic seizures detection and forecasting is nowadays widely recognized as a problem of great significance and social resonance, and still remains an open, grand challenge. Furthermore, the development of mobile warning systems and…

Quantitative Methods · Quantitative Biology 2018-12-10 Roberto Zingone , Chiara Mocenni , Dario Madeo

Electroencephalography (EEG) is a generally used neuroimaging approach in brain-computer interfaces due to its non-invasive characteristics and convenience, making it an effective tool for understanding human intentions. Therefore, recent…

Signal Processing · Electrical Eng. & Systems 2024-11-19 Sung-Jin Kim , Dae-Hyeok Lee , Hyeon-Taek Han

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

Electroencephalography (EEG) and magnetoencephalography (MEG) play important and complementary roles in non-invasive brain-computer interface (BCI) decoding. However, compared to the low cost and portability of EEG, MEG is more expensive…

Signal Processing · Electrical Eng. & Systems 2026-02-10 Zhuo Li , Shuqiang Wang

Periodic and nonperiodic components of electrophysiological signals are modelled in terms of syncronized sequences of closed loops of firing neurons correlated in Markov chains. Single closed loops of firing neurons reproduce fundamental…

Neurons and Cognition · Quantitative Biology 2022-09-19 P. Mazzetti , A. Carbone