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Simultaneous real-time fMRI and EEG neurofeedback (rtfMRI-EEG-nf) is an emerging neuromodulation approach, that enables simultaneous volitional regulation of both hemodynamic (BOLD fMRI) and electrophysiological (EEG) brain activities. Here…

Neurons and Cognition · Quantitative Biology 2020-07-06 Vadim Zotev , Ahmad Mayeli , Masaya Misaki , Jerzy Bodurka

The primary goal of any company is to increase its profits by improving both the quality of its products and how they are advertised. In this context, neuromarketing seeks to enhance the promotion of products and generate a greater…

Recently, there have been several concerted international efforts - the BRAIN initiative, European Human Brain Project and the Human Connectome Project, to name a few - that hope to revolutionize our understanding of the connected brain.…

Neurons and Cognition · Quantitative Biology 2016-02-10 Adeel Razi , Karl Friston

Next generation cars embed intelligent assessment of car driving safety through innovative solutions often based on usage of artificial intelligence. The safety driving monitoring can be carried out using several methodologies widely…

Signal Processing · Electrical Eng. & Systems 2023-04-14 Francesco Rundo

Functional MRI (fMRI) is a powerful technique that has allowed us to characterize visual cortex responses to stimuli, yet such experiments are by nature constructed based on a priori hypotheses, limited to the set of images presented to the…

Neurons and Cognition · Quantitative Biology 2021-05-18 Zijin Gu , Keith W. Jamison , Meenakshi Khosla , Emily J. Allen , Yihan Wu , Thomas Naselaris , Kendrick Kay , Mert R. Sabuncu , Amy Kuceyeski

The application of psychophysiology in human-computer interaction is a growing field with significant potential for future smart personalised systems. Working in this emerging field requires comprehension of an array of physiological…

Human-Computer Interaction · Computer Science 2016-09-05 Niklas Ravaja , Benjamin Cowley , Jari Torniainen

Functional magnetic resonance imaging (fMRI) is a notoriously noisy measurement of brain activity because of the large variations between individuals, signals marred by environmental differences during collection, and spatiotemporal…

Epilepsy is one of the most occurring neurological disease globally emerged back in 4000 BC. It is affecting around 50 million people of all ages these days. The trait of this disease is recurrent seizures. In the past few decades, the…

Machine Learning · Computer Science 2021-11-08 Virender Ranga , Shivam Gupta , Jyoti Meena , Priyansh Agrawal

Drowsy driving is pervasive, and also a major cause of traffic accidents. Estimating a driver's drowsiness level by monitoring the electroencephalogram (EEG) signal and taking preventative actions accordingly may improve driving safety.…

Human-Computer Interaction · Computer Science 2019-09-26 Yuqi Cuui , Yifan Xu , Dongrui Wu

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

Background: Electrocardiogram (ECG) analysis has emerged as a promising tool for detecting physiological changes linked to non-cardiac disorders. Given the close connection between cardiovascular and neurocognitive health, ECG abnormalities…

Signal Processing · Electrical Eng. & Systems 2025-11-20 Juan Miguel Lopez Alcaraz , Ebenezer Oloyede , David Taylor , Wilhelm Haverkamp , Nils Strodthoff

Functional neuroimaging can measure the brain?s response to an external stimulus. It is used to perform brain mapping: identifying from these observations the brain regions involved. This problem can be cast into a linear supervised…

Machine Learning · Computer Science 2012-07-03 Gael Varoquaux , Alexandre Gramfort , Bertrand Thirion

Driver drowsiness is identified as a critical factor in road accidents, necessitating robust detection systems to enhance road safety. This study proposes a driver drowsiness detection system, DrowzEE-G-Mamba, that combines…

Human-Computer Interaction · Computer Science 2025-06-11 Gourav Siddhad , Sayantan Dey , Partha Pratim Roy

Distracted driving continues to be a significant cause of road traffic injuries and fatalities worldwide, even with advancements in driver monitoring technologies. Recent developments in machine learning (ML) and deep learning (DL) have…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Anthony Dontoh , Stephanie Ivey , Logan Sirbaugh , Andrews Danyo , Armstrong Aboah

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

One debatable issue in traffic safety research is that cognitive load from sec-ondary tasks reduces primary task performance, such as driving. Although physiological signals have been extensively used in driving-related research to assess…

Human-Computer Interaction · Computer Science 2024-08-14 Mehshan Ahmed Khan , Houshyar Asadi , Mohammad Reza Chalak Qazani , Adetokunbo Arogbonlo , Saeid Nahavandi , Chee Peng Lim

There are many important regression problems in real-world brain-computer interface (BCI) applications, e.g., driver drowsiness estimation from EEG signals. This paper considers offline analysis: given a pool of unlabeled EEG epochs…

Machine Learning · Computer Science 2020-03-31 Dongrui Wu , Vernon J. Lawhern , Stephen Gordon , Brent J. Lance , Chin-Teng Lin

About 30% of all traffic crash fatalities in the United States involve drunk drivers, making the prevention of drunk driving paramount to vehicle safety in the US and other locations which have a high prevalence of driving while under the…

Computer Vision and Pattern Recognition · Computer Science 2023-10-11 Ross Greer , Akshay Gopalkrishnan , Sumega Mandadi , Pujitha Gunaratne , Mohan M. Trivedi , Thomas D. Marcotte

Cognitive neuroscience explores the mechanisms of cognition by studying its structural and functional brain correlates. Here, we report the first systematic review that assesses how information from structural and functional neuroimaging…

Neurons and Cognition · Quantitative Biology 2022-02-07 Marta Czime Litwińczuk , Nelson Trujillo-Barreto , Nils Muhlert , Lauren Cloutman , Anna Woollams

A micro-sleep is a short sleep that lasts from 1 to 30 secs. Its detection during driving is crucial to prevent accidents that could claim a lot of people's lives. Electroencephalogram (EEG) is suitable to detect micro-sleep because EEG was…

Machine Learning · Computer Science 2020-12-11 Young-Seok Kweon , Gi-Hwan Shin , Heon-Gyu Kwak , Minji Lee