Motor imagery EEG decoding based on multi-scale hybrid networks and feature enhancement

X Tang, C Yang, X Sun, M Zou… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Motor Imagery (MI) based on Electroencephalography (EEG), a typical Brain-Computer
Interface (BCI) paradigm, can communicate with external devices according to the brain's …

Diagnosis of Alzheimer's disease via resting-state EEG: integration of spectrum, complexity, and synchronization signal features

X Zheng, B Wang, H Liu, W Wu, J Sun… - Frontiers in Aging …, 2023 - frontiersin.org
Background Alzheimer's disease (AD) is the most common neurogenerative disorder,
making up 70% of total dementia cases with a prevalence of more than 55 million people …

[HTML][HTML] Functional connectivity of EEG is subject-specific, associated with phenotype, and different from fMRI

M Nentwich, L Ai, J Madsen, QK Telesford, S Haufe… - NeuroImage, 2020 - Elsevier
A variety of psychiatric, behavioral and cognitive phenotypes have been linked to brain
''functional connectivity''--the pattern of correlation observed between different brain regions …

Frontoparietal theta-gamma interactions track working memory enhancement with training and tDCS

KT Jones, EL Johnson, ME Berryhill - Neuroimage, 2020 - Elsevier
Despite considerable interest in enhancing, preserving, and rehabilitating working memory
(WM), efforts to elicit sustained behavioral improvements have been met with limited …

EEG based automated detection of seizure using machine learning approach and traditional features

S Abhishek, S Kumar, N Mohan, KP Soman - Expert Systems with …, 2024 - Elsevier
The detection of epileptic seizures is key for neurologists to initiate the right treatment at the
earliest. However, the traditional methods are dependent on manual diagnosis which are …

Learning DenseNet features from EEG based spectrograms for subject independent emotion recognition

N Pusarla, A Singh, S Tripathi - Biomedical signal processing and control, 2022 - Elsevier
Subject-independent emotion recognition (SIER) using electroencephalogram (EEG)
signals has always been a challenge among the biomedical research community. One of the …

Neural circuits of idiopathic normal pressure hydrocephalus: a perspective review of brain connectivity and symptoms meta-analysis

A Griffa, D Van De Ville, FR Herrmann… - … & Biobehavioral Reviews, 2020 - Elsevier
Idiopathic normal pressure hydrocephalus (iNPH) is a prevalent reversible neurological
disorder characterized by impaired locomotion, cognition and urinary control with …

[HTML][HTML] The emergence of a theta social brain network during infancy

B van der Velde, T White, C Kemner - NeuroImage, 2021 - Elsevier
Infants' socio-cognitive ability develops dramatically during the first year of life. From the
perspective of ontogeny, the early development of social behavior allows for parent-child …

Functional connectivity analysis on electroencephalography signals reveals potential biomarkers for treatment response in major depression

SS Huang, YH Yu, HH Chen, CC Hung, YT Wang… - BMC psychiatry, 2023 - Springer
Background The treatment efficacy varies across individual patients with major depressive
disorder (MDD). It lacks robust electroencephalography (EEG) markers for an …

Comprehensive review of eeg-based algorithms for mental stress analysis

SA Patil, AN Paithane - 2023 7th International Conference On …, 2023 - ieeexplore.ieee.org
Electroencephalography (EEG) as a tool for analyzing mental stress has recently gained
significant attention. The field of neuroscience employs electroencephalography (EEG) to …