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Related papers: Discrepancies in Mental Workload Estimation: Self-…

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Mind-wandering (MW), which usually defined as a lapse of attention, occurs between 20%-40% of the time, has negative effects on our daily life. Therefore, detecting when MW occurs can prevent us from those negative outcomes resulting from…

Signal Processing · Electrical Eng. & Systems 2020-11-30 Yi-Ta Chen , Hsing-Hao Lee , Ching-Yen Shih , Zih-Ling Chen , Win-Ken Beh , Su-Ling Yeh , An-Yeu Wu

Visual decoding from brain signals is a key challenge at the intersection of computer vision and neuroscience, requiring methods that bridge neural representations and computational models of vision. We introduce a tri-modal contrastive…

Machine Learning · Computer Science 2026-05-26 Zexuan Chen , Sichao Liu , Runhao Lu , Huichao Qi , Alexandra Woolgar , Xi Vincent Wang , Lihui Wang

Cognitive load, the amount of mental effort required for task completion, plays an important role in performance and decision-making outcomes, making its classification and analysis essential in various sensitive domains. In this paper, we…

Machine Learning · Computer Science 2023-08-02 Dustin Pulver , Prithila Angkan , Paul Hungler , Ali Etemad

With the increasing prevalence of 3D videos, investigating the differences of viewing experiences between 2D and 3D videos has become an important issue. In this study, we explored the cognitive load induced by 2D and 3D video stimuli under…

Neurons and Cognition · Quantitative Biology 2024-05-14 Yu Liu , Chen Song , Yunpeng Yin , Herui Shi , Jinglin Sun , Han Wang , Peiguang Jing

Working Memory (WM) load is an important cognitive feature that is highly correlated with mental effort. Several neurological biomarkers such as theta power and mid-frontal activity show increased activity with increasing WM load. Such…

Neurons and Cognition · Quantitative Biology 2020-08-13 Neta B. Maimon , Lior Molcho , Nathan Intrator , Dominique Lamy

Accurate and continuous estimation of cognitive workload is fundamental to creating adaptive human-machine systems. However, designing architectures that balance representational capacity with computational efficiency has been challenging…

Signal Processing · Electrical Eng. & Systems 2026-05-20 Stefanos Gkikas , Christian Arzate Cruz , Thomas Kassiotis , Giorgos Giannakakis , Raul Fernandez Rojas , Randy Gomez

Recent self-supervised pre-training methods for electroencephalogram (EEG) have shown promising results. However, the pre-trained models typically require full fine-tuning on each downstream task individually to achieve good performance. In…

Machine Learning · Computer Science 2026-04-30 Sicheng Dai , Kai Chen , Hongwang Xiao , Shan Yu , Qiwei Ye

This article summarizes a systematic review of the electroencephalography (EEG)-based cognitive workload (CWL) estimation. The focus of the article is twofold: identify the disparate experimental paradigms used for reliably eliciting…

Signal Processing · Electrical Eng. & Systems 2024-10-24 Vishnu KN , Cota Navin Gupta

Clinical electroencephalography is routinely used to evaluate patients with diverse and often overlapping neurological conditions, yet interpretation remains manual, time-intensive, and variable across experts. While automated EEG analysis…

Human-Computer Interaction · Computer Science 2025-12-30 Argha Kamal Samanta , Deepak Mewada , Monalisa Sarma , Debasis Samanta

Motivated behaviour relies on the brain's capacity to evaluate effort and reward. Dysregulation within these processes contributes to a spectrum of conditions, from hyperactivity in attention-deficit/hyperactivity disorder (ADHD) to…

Neurons and Cognition · Quantitative Biology 2026-04-20 Nam Trinh

Cognitive effort, defined as the relationship between cognitive load and task performance, provides insight into how individuals allocate mental resources during demanding tasks. This construct is particularly important in high-stakes…

Human-Computer Interaction · Computer Science 2026-04-13 Shayla Sharmin , Mohammad Fahim Abrar , Gael Lucero-Palacios , Aditya Raikwar , Roghayeh Leila Barmaki

Normalization is a critical yet often overlooked component in the preprocessing pipeline for EEG deep learning applications. The rise of large-scale pretraining paradigms such as self-supervised learning (SSL) introduces a new set of tasks…

Signal Processing · Electrical Eng. & Systems 2025-07-01 Dung Truong , Arnaud Delorme

Brain connectivity can be estimated through a wide number of analyses applied to electroencephalographic (EEG) data. However, substantial heterogeneity in the implementation of connectivity methods exist. Heterogeneity in conceptualization…

Neurons and Cognition · Quantitative Biology 2021-09-01 Aleksandra Miljevic , Neil W. Bailey , Fidel Vila-Rodriguez , Sally E. Herring , Paul B. Fitzgerald

The classification of harmful brain activities, such as seizures and periodic discharges, play a vital role in neurocritical care, enabling timely diagnosis and intervention. Electroencephalography (EEG) provides a non-invasive method for…

Machine Learning · Computer Science 2025-10-21 Shivraj Singh Bhatti , Aryan Yadav , Mitali Monga , Neeraj Kumar

Electroencephalography (EEG) has been widely used to study the relationship between naps and working memory, yet the effects of naps on distinct working memory tasks remain unclear. Here, participants performed word-pair and visuospatial…

Neurons and Cognition · Quantitative Biology 2023-11-16 Gi-Hwan Shin , Young-Seok Kweon , Heon-Gyu Kwak , Ha-Na Jo , Seong-Whan Lee

In the status quo, dementia is yet to be cured. Precise diagnosis prior to the onset of the symptoms can prevent the rapid progression of the emerging cognitive impairment. Recent progress has shown that Electroencephalography (EEG) is the…

When using Head-Mounted Displays (HMDs), users may not always notice or report visual discomfort by blurred vision through unadjusted lenses, motion sickness, and increased eye strain. Current measures for visual discomfort rely on users'…

Human-Computer Interaction · Computer Science 2024-07-29 Francesco Chiossi , Yannick Weiss , Thomas Steinbrecher , Christian Mai , Thomas Kosch

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

The idea to estimate the statistical interdependence among (interacting) brain regions has motivated numerous researchers to investigate how the resulting connectivity patterns and networks may organize themselves under any conceivable…

Neurons and Cognition · Quantitative Biology 2021-02-03 Matteo Fraschini , Simone Maurizio La Cava , Luca Didaci , Luigi Barberini

Working memory (WM), denoting the information temporally stored in the mind, is a fundamental research topic in the field of human cognition. Electroencephalograph (EEG), which can monitor the electrical activity of the brain, has been…

Machine Learning · Computer Science 2024-12-03 Junfu Chen , Sirui Li , Dechang Pi