Deep learning convolutional neural networks discriminate adult ADHD from healthy individuals on the basis of event-related spectral EEG

L Dubreuil-Vall, G Ruffini, JA Camprodon - Frontiers in neuroscience, 2020 - frontiersin.org
Attention deficit hyperactivity disorder (ADHD) is a heterogeneous neurodevelopmental
disorder that affects 5% of the pediatric and adult population worldwide. The diagnosis …

Deep learning with EEG spectrograms in rapid eye movement behavior disorder

G Ruffini, D Ibañez, M Castellano… - Frontiers in …, 2019 - frontiersin.org
REM Behavior Disorder (RBD) is now recognized as the prodromal stage of α-
synucleinopathies such as Parkinson's disease (PD). In this paper, we describe deep …

Power spectrum and spectrogram of EEG analysis during general anesthesia: Python-based computer programming analysis

T Sawa, T Yamada, Y Obata - Journal of clinical monitoring and computing, 2022 - Springer
The commonly used principle for measuring the depth of anesthesia involves changes in the
frequency components of the electroencephalogram (EEG) under general anesthesia …

[HTML][HTML] Electroencephalographic markers of brain development during sevoflurane anaesthesia in children up to 3 years old

L Cornelissen, SE Kim, JM Lee, EN Brown… - British journal of …, 2018 - Elsevier
Background General anaesthetics generate spatially defined brain oscillations in the EEG
that relate fundamentally to neural-circuit architecture. Few studies detailing the neural …

A state space modeling approach to real-time phase estimation

A Wodeyar, M Schatza, AS Widge, UT Eden… - Elife, 2021 - elifesciences.org
Brain rhythms have been proposed to facilitate brain function, with an especially important
role attributed to the phase of low-frequency rhythms. Understanding the role of phase in …

[HTML][HTML] From bench to bedside: Overview of magnetoencephalography in basic principle, signal processing, source localization and clinical applications

Y Yang, S Luo, W Wang, X Gao, X Yao, T Wu - NeuroImage: Clinical, 2024 - Elsevier
Magnetoencephalography (MEG) is a non-invasive technique that can precisely capture the
dynamic spatiotemporal patterns of the brain by measuring the magnetic fields arising from …

Spectral and time-frequency analysis

Z Zhang - EEG Signal Processing and feature extraction, 2019 - Springer
EEG signals are typically characterized by oscillatory patterns at certain frequency bands.
Normally, the EEG data, especially spontaneous EEG data, are analyzed in the frequency …

A hidden Markov model reliably characterizes ketamine-induced spectral dynamics in macaque local field potentials and human electroencephalograms

IC Garwood, S Chakravarty, J Donoghue… - PLoS Computational …, 2021 - journals.plos.org
Ketamine is an NMDA receptor antagonist commonly used to maintain general anesthesia.
At anesthetic doses, ketamine causes high power gamma (25-50 Hz) oscillations alternating …

Differential effects of sevoflurane and desflurane on frontal intraoperative electroencephalogram dynamics associated with postoperative delirium

YS Kim, J Kim, S Park, KN Kim, Y Ha, S Yi… - Journal of Clinical …, 2024 - Elsevier
Study objective Intraoperative electroencephalogram (EEG) patterns associated with
postoperative delirium (POD) development have been studied, but the differences in EEG …

Spectrally and temporally resolved estimation of neural signal diversity

PAM Mediano, FE Rosas, AI Luppi, V Noreika, AK Seth… - bioRxiv, 2023 - biorxiv.org
Quantifying the complexity of neural activity has provided fundamental insights into
cognition, consciousness, and clinical conditions. However, the most widely used approach …