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Representation and classification of Electroencephalography (EEG) brain signals are critical processes for their analysis in cognitive tasks. Particularly, extraction of discriminative features from raw EEG signals, without any…

Machine Learning · Computer Science 2019-05-01 Emad-ul-Haq Qazi , Muhammad Hussain , Hatim Aboalsamh

Accurately monitoring cognitive load in real time is critical for Brain-Computer Interfaces (BCIs) that adapt to user engagement and support personalized learning. Electroencephalography (EEG) offers a non-invasive, cost-effective modality…

Human-Computer Interaction · Computer Science 2026-05-04 Deeksha M. Shama , Dimitra Emmanouilidou , Ivan J. Tashev

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

For neurological disorders and diseases, functional and anatomical connectomes of the human brain can be used to better inform targeted interventions and treatment strategies. Functional magnetic resonance imaging (fMRI) is a non-invasive…

Methodology · Statistics 2023-07-03 Matt Ryan , Gary Glonek , Jono Tuke , Melissa Humphries

Global brain activity self-organizes into discrete patterns characterized by distinct behavioral observables and modes of information processing. The human thalamocortical system is a densely connected network where local neural activation…

The extraction of brain functioning features is a crucial step in the definition of brain-computer interfaces (BCIs). In the last decade, functional connectivity (FC) estimators have been increasingly explored based on their ability to…

Neurons and Cognition · Quantitative Biology 2019-12-06 Tiziana Cattai , Stefania Colonnese , Marie-Constance Corsi , Danielle S. Bassett , Gaetano Scarano , Fabrizio De Vico Fallani

In this paper, we analyze electroencephalograms (EEG) which are recordings of brain electrical activity. We develop new clustering methods for identifying synchronized brain regions, where the EEGs show similar oscillations or waveforms…

Methodology · Statistics 2020-07-29 Tianbo Chen , Ying Sun , Carolina Euan , Hernando Ombao

Functional magnetic resonance imaging (fMRI) is a non-invasive and in-vivo imaging technique essential for measuring brain activity. Functional connectivity is used to study associations between brain regions, either while study subjects…

Applications · Statistics 2024-03-26 Kun Meng , Ani Eloyan

This article is devoted to EEG studying of connectivity cortical areas involved in keeping vision information in working memory. VAR-modeling was used for describing signals got from connected with working memory brain zones. Brain…

Signal Processing · Electrical Eng. & Systems 2020-07-01 A. V. Erofeeva , T. V. Zakharova

Coherence and phase synchronization between time series corresponding to different spatial locations are usually interpreted as indicators of the connectivity between locations. In neurophysiology, time series of electric neuronal activity…

Methodology · Statistics 2007-07-12 Roberto D. Pascual-Marqui

Background: Real-time functional magnetic resonance imaging neurofeedback (rtfMRI-nf) has proven to be a powerful technique to help subjects to gauge and enhance emotional control. Traditionally, rtfMRI-nf has focused on emotional…

This study examines the utility of functional connectivity (FC) and graph-based (GB) measures with a support vector machine classifier for use in electroencephalogram (EEG) based biometrics. Although FC-based features have been used in…

Signal Processing · Electrical Eng. & Systems 2022-06-06 Pradeep Kumar G , Utsav Dutta , Kanishka Sharma , Ramakrishnan Angarai Ganesan

Estimating brain effective connectivity (EC) from functional magnetic resonance imaging (fMRI) data can aid in comprehending the neural mechanisms underlying human behavior and cognition, providing a foundation for disease diagnosis.…

Machine Learning · Computer Science 2025-03-17 Wen Xiong , Jinduo Liu , Junzhong Ji , Fenglong Ma

Cognition refers to the function of information perception and processing, which is the fundamental psychological essence of human beings. It is responsible for reasoning and decision-making, while its evaluation is significant for the…

Human-Computer Interaction · Computer Science 2024-08-28 Jun Chen , Anqi Chen , Bingkun Jiang , Mohammad S. Obaidat , Ni Li , Xinyu Zhang

Near-infrared spectroscopy (NIRS) can measure neural activity through blood oxygenation changes in the brain in a wearable form factor, enabling unique applications for research in and outside the lab. NIRS has proven capable of measuring…

Signal Processing · Electrical Eng. & Systems 2023-12-14 Christian Kothe , Grant Hanada , Sean Mullen , Tim Mullen

Accurately assessing mental workload is crucial in cognitive neuroscience, human-computer interaction, and real-time monitoring, as cognitive load fluctuations affect performance and decision-making. While Electroencephalography (EEG) based…

Neural and Evolutionary Computing · Computer Science 2025-09-29 Jiahui An , Sara Irina Fabrikant , Giacomo Indiveri , Elisa Donati

An important field of research in functional neuroimaging is the discovery of integrated, distributed brain systems and networks, whose different regions need to work in unison for normal functioning. The EEG is a non-invasive technique…

The analysis of EEG/MEG functional connectivity has become an important tool in neural research. Especially the high time resolution of EEG/MEG enables important insight into the functioning of the human brain. To date, functional…

Signal Processing · Electrical Eng. & Systems 2023-03-07 Lorenz Esch , Jinlong Dong , Matti Hämäläinen , Daniel Baumgarten , Jens Haueisen , Johannes Vorwerk

Measuring brain activity with electroencephalography (EEG) is mature enough to assess mental states. Combined with existing methods, such tool can be used to strengthen the understanding of user experience. We contribute a set of methods to…

Human-Computer Interaction · Computer Science 2016-01-13 Jérémy Frey , Maxime Daniel , Julien Castet , Martin Hachet , Fabien Lotte

This study employs cutting-edge wearable monitoring technology to conduct high-precision, high-temporal-resolution (1-second interval) cognitive load assessment on electroencephalogram (EEG) data from the FP1 channel and heart rate…

Human-Computer Interaction · Computer Science 2024-07-04 Ling He , Yanxin Chen , Wenqi Wang , Shuting He , Xiaoqiang Hu