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Autism spectrum disorder (ASD) is one of the major developmental disorders affecting children. Recently, it has been hypothesized that ASD is associated with atypical brain connectivities. A substantial body of researches use Pearson's…

Neurons and Cognition · Quantitative Biology 2019-03-06 Biwei Huang , Kun Zhang , Ruben Sanchez-Romero , Joseph Ramsey , Madelyn Glymour , Clark Glymour

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

This article is motivated by studying multisensory effects on brain activities in intracranial electroencephalography (iEEG) experiments. Differential brain activities to multisensory stimulus presentations are zero in most regions and…

Methodology · Statistics 2022-06-01 Zhengjia Wang , John Magnotti , Michael S. Beauchamp , Meng Li

Evaluating foundation models under appropriate adaptation settings is essential for understanding the quality and transferability of the learned representations. Recent EEG foundation models have demonstrated promising transfer capabilities…

Machine Learning · Computer Science 2026-05-28 Aditya Kommineni , Emily Zhou , Kleanthis Avramidis , Tiantian Feng , Shrikanth Narayanan

Among the different modalities to assess emotion, electroencephalogram (EEG), representing the electrical brain activity, achieved motivating results over the last decade. Emotion estimation from EEG could help in the diagnosis or…

Computer Vision and Pattern Recognition · Computer Science 2022-04-05 Victor Delvigne , Antoine Facchini , Hazem Wannous , Thierry Dutoit , Laurence Ris , Jean-Philippe Vandeborre

The electroencephalography (EEG) source imaging problem is very sensitive to the electrical modelling of the skull of the patient under examination. Unfortunately, the currently available EEG devices and their embedded software do not take…

Machine Learning · Computer Science 2020-02-04 Alexandra Koulouri , Ville Rimpilainen

We propose a new representation learning solution for the classification of cognitive load based on Electroencephalogram (EEG). Our method integrates both time and frequency domains by first passing the raw EEG signals through the…

Human-Computer Interaction · Computer Science 2025-11-18 Prithila Angkan , Amin Jalali , Paul Hungler , Ali Etemad

Electroencephalogram (EEG) is a non-invasive tool for real-time neural monitoring,widely used in depression detection via deep learning. However, existing models primarily focus on binary classification (depression/normal), lacking…

Signal Processing · Electrical Eng. & Systems 2025-03-19 ZhongYi Zhang , ChenYang Xu , LiXuan Zhao , HuiRang Hou , QingHao Meng

Major depressive disorder (MDD) is a prevalent mental disorder associated with complex neurobiological changes that cannot be fully captured using a single imaging modality. The use of multimodal magnetic resonance imaging (MRI) provides a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Nojod M. Alotaibi , Areej M. Alhothali

Detecting where and when brain regions activate in a cognitive task or in a given clinical condition is the promise of non-invasive techniques like magnetoencephalography (MEG) or electroencephalography (EEG). This problem, referred to as…

Machine Learning · Statistics 2020-11-26 Jérôme-Alexis Chevalier , Alexandre Gramfort , Joseph Salmon , Bertrand Thirion

This article provides a theoretical basis for relating macroscopic electrical signals recorded from biological tissue, such as electroencephalogram (EEG) and local field potential (LFP), to the electrophysiological processes at the cellular…

Neurons and Cognition · Quantitative Biology 2012-09-24 Hiroyoshi Miyakawa , Toru Aonishi

Major depressive disorder (MDD) is one of the most common mental health conditions that has been intensively investigated for its association with brain atrophy and mortality. Recent studies reveal that the deviation between the predicted…

Neurons and Cognition · Quantitative Biology 2022-10-18 Yunsong Luo , Wenyu Chen , Jiang Qiu , Tao Jia

The link between different psychophysiological measures during emotion episodes is not well understood. To analyse the functional relationship between electroencephalography (EEG) and facial electromyography (EMG), we apply historical…

Applications · Statistics 2017-05-16 David Rügamer , Sarah Brockhaus , Kornelia Gentsch , Klaus Scherer , Sonja Greven

The assessment of Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) associated with brain changes remains a challenging task. Recent studies have demonstrated that combination of multi-modality imaging techniques can better…

Machine Learning · Computer Science 2022-09-26 Jun Yu , Zhaoming Kong , Liang Zhan , Li Shen , Lifang He

In universal environment, a patient-friendly inexpensive method is needed to realize the early diagnosis of depression, which is believed to be an effective way to reduce the mortality of depression. The purpose of this study is only to…

Signal Processing · Electrical Eng. & Systems 2020-02-28 Qiuxia Shi , Ang Liu , Rongyan Chen , Jian Shen , Qinglin Zhao , Bin Hu

Depression disorder is a serious health condition that has affected the lives of millions of people around the world. Diagnosis of depression is a challenging practice that relies heavily on subjective studies and, in most cases, suffers…

Signal Processing · Electrical Eng. & Systems 2025-03-26 Amir Nassibi , Christos Papavassiliou , Ildar Rakhmatulin , Danilo Mandic , S. Farokh Atashzar

Continuous electroencephalography (EEG) is routinely used in neurocritical care to monitor seizures and other harmful brain activity, including rhythmic and periodic patterns that are clinically significant. Although deep learning methods…

Human-Computer Interaction · Computer Science 2026-01-05 Argha Kamal Samanta , Deepak Mewada , Monalisa Sarma , Debasis Samanta

The process of integration of inputs from several sensory modalities in the human brain is referred to as multisensory integration. Age-related cognitive decline leads to a loss in the ability of the brain to conceive multisensory inputs.…

Signal Processing · Electrical Eng. & Systems 2023-05-02 Prerna Singh , Ayush Tripathi , Lalan Kumar , Tapan Kumar Gandhi

Neuropsychiatric disorders, such as Alzheimer's disease (AD), depression, and autism spectrum disorder (ASD), are characterized by linguistic and acoustic abnormalities, offering potential biomarkers for early detection. Despite the promise…

Computation and Language · Computer Science 2025-12-25 Zhongren Dong , Haotian Guo , Weixiang Xu , Huan Zhao , Zixing Zhang

Major depressive disorder (MDD) is one of the most common mental disorders, with significant impacts on many daily activities and quality of life. It stands as one of the most common mental disorders globally and ranks as the second leading…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Nojod M. Alotaibi , Areej M. Alhothali , Manar S. Ali