Neurofeedback and epilepsy: Renaissance of an old self-regulation method?

A Marchi, R Guex, M Denis, N El Youssef, F Pizzo… - Revue …, 2024 - Elsevier
Neurofeedback is a brain-computer interface tool enabling the user to self-regulate their
neuronal activity, and ultimately, induce long-term brain plasticity, making it an interesting …

Enhancing the accuracy of electroencephalogram-based emotion recognition through Long Short-Term Memory recurrent deep neural networks

MR Yousefi, A Dehghani, H Taghaavifar - Frontiers in Human …, 2023 - frontiersin.org
Introduction Emotions play a critical role in human communication, exerting a significant
influence on brain function and behavior. One effective method of observing and analyzing …

Comparing EEG-based epilepsy diagnosis using neural networks and wavelet transform

MR Yousefi, A Dehghani, S Golnejad, MM Hosseini - Applied Sciences, 2023 - mdpi.com
Epilepsy is a common neurological disorder characterized by the recurrence of seizures,
which can significantly impact the lives of patients. Electroencephalography (EEG) can …

[HTML][HTML] Utilizing Phase Locking Value to Determine Neurofeedback Treatment Responsiveness in Attention Deficit Hyperactivity Disorder

MR Yousefi, N Khanahmadi… - Journal of Integrative …, 2024 - imrpress.com
Background: Neurofeedback is a non-invasive brain training technique used to enhance
and treat hyperactivity disorder by altering the patterns of brain activity. Nonetheless, the …

Non-linear processing and reinforcement learning to predict rTMS treatment response in depression

E Ebrahimzadeh, A Dehghani, M Asgarinejad… - Psychiatry Research …, 2024 - Elsevier
Background Forecasting the efficacy of repetitive transcranial magnetic stimulation (rTMS)
therapy can lead to substantial time and cost savings by preventing futile treatments. To …

[PDF][PDF] Navigating the'Zen Zeitgeist': The Potential of Personalized Neurofeedback for Meditation

T Brandmeyer, N Reggente - 2023 - osf.io
The advancement of neurotechnological tools for meditation and mindfulness training may
help to accelerate many of the transformational states and traits that result from consistent …

[HTML][HTML] Sensori-motor neurofeedback improves inhibitory control and induces neural changes: a placebo-controlled, double-blind, event-related potentials study

C Dousset, F Wyckmans, T Monseigne… - International journal of …, 2024 - Elsevier
Abstract Background/Objective Inhibition is crucial for controlling behavior and is impaired in
various psychopathologies. Neurofeedback holds promise in addressing cognitive deficits …

[HTML][HTML] Assessing robustness to adversarial attacks in attention-based networks: Case of EEG-based motor imagery classification

NEHSB Aissa, A Korichi, A Lakas, CA Kerrache… - SLAS technology, 2024 - Elsevier
The classification of motor imagery (MI) using Electroencephalography (EEG) plays a pivotal
role in facilitating communication for individuals with physical limitations through Brain …

[HTML][HTML] Multimodal transformer graph convolution attention isomorphism network (MTCGAIN): a novel deep network for detection of insomnia disorder

Y Wang, Y Ren, Y Bi, F Zhao, X Bai, L Wei… - … Imaging in Medicine …, 2024 - ncbi.nlm.nih.gov
Background In clinic, the subjectivity of diagnosing insomnia disorder (ID) often leads to
misdiagnosis or missed diagnosis, as ID may have the same symptoms as those of other …

Combining VR with electroencephalography as a frontier of brain-computer interfaces

H Li, H Shin, L Sentis, KC Siu, JR Millán, N Lu - Device, 2024 - cell.com
This review presents an overview of the integration of virtual reality (VR) and
electroencephalography (EEG), known as VR-EEG systems, and their promising …