A review of critical challenges in MI-BCI: From conventional to deep learning methods

Z Khademi, F Ebrahimi, HM Kordy - Journal of Neuroscience Methods, 2023‏ - Elsevier
Brain-computer interfaces (BCIs) have achieved significant success in controlling external
devices through the Electroencephalogram (EEG) signal processing. BCI-based Motor …

[HTML][HTML] Repetitive transcranial magnetic stimulation (rtms) in mild cognitive impairment: effects on cognitive functions—a systematic review

M Sharbafshaaer, I Gigi, L Lavorgna… - Journal of Clinical …, 2023‏ - mdpi.com
Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive brain stimulation
technique also used as a non-pharmacological intervention against cognitive impairment …

Differentiation of schizophrenia by combining the spatial EEG brain network patterns of rest and task P300

F Li, J Wang, Y Liao, C Yi, Y Jiang, Y Si… - IEEE transactions on …, 2019‏ - ieeexplore.ieee.org
The P300 is regarded as a psychosis endophenotype of schizophrenia and a putative
biomarker of risk for schizophrenia. However, the brain activity (ie, P300 amplitude) during …

A hybrid-domain deep learning-based BCI for discriminating hand motion planning from EEG sources

C Ieracitano, FC Morabito, A Hussain… - International journal of …, 2021‏ - World Scientific
In this paper, a hybrid-domain deep learning (DL)-based neural system is proposed to
decode hand movement preparation phases from electroencephalographic (EEG) …

A survey of brain network analysis by electroencephalographic signals

C Luo, F Li, P Li, C Yi, C Li, Q Tao, X Zhang, Y Si… - Cognitive …, 2022‏ - Springer
Brain network analysis is one efficient tool in exploring human brain diseases and can
differentiate the alterations from comparative networks. The alterations account for time …

Long-term kinesthetic motor imagery practice with a BCI: impacts on user experience, motor cortex oscillations and BCI performances

S Rimbert, S Fleck - Computers in Human Behavior, 2023‏ - Elsevier
Kinesthetic motor imagery (KMI) generates specific brain patterns in sensorimotor rhythm
over the motor cortex (called event-related (de)-synchronization, ERD/ERS), allowing KMI to …

A long short-term memory network for sparse spatiotemporal EEG source imaging

JC Bore, P Li, L Jiang, WMA Ayedh… - … on Medical Imaging, 2021‏ - ieeexplore.ieee.org
EEG inverse problem is underdetermined, which poses a long standing challenge in
Neuroimaging. The combination of source-imaging and analysis of cortical directional …

A new dispersion entropy and fuzzy logic system methodology for automated classification of dementia stages using electroencephalograms

JP Amezquita-Sanchez, N Mammone… - Clinical Neurology and …, 2021‏ - Elsevier
A new EEG-based methodology is presented for differential diagnosis of the Alzheimer's
disease (AD), Mild Cognitive Impairment (MCI), and healthy subjects employing the discrete …

Granger causal inference based on dual laplacian distribution and its application to MI-BCI classification

P Li, X Gao, C Li, C Yi, W Huang, Y Si… - … on Neural Networks …, 2023‏ - ieeexplore.ieee.org
Granger causality-based effective brain connectivity provides a powerful tool to probe the
neural mechanism for information processing and the potential features for brain computer …

Functional connectivity analysis in motor-imagery brain computer interfaces

N Leeuwis, S Yoon, M Alimardani - Frontiers in Human Neuroscience, 2021‏ - frontiersin.org
Motor Imagery BCI systems have a high rate of users that are not capable of modulating their
brain activity accurately enough to communicate with the system. Several studies have …