Article
Neurosciences
Odile Feys, Pierre Corvilain, Etienne Labyt, Mahdi Mahmoudzadeh, Laura Routier, Claudine Sculier, Niall Holmes, Matthew Brookes, Serge Goldman, Rudy Romain, Sergey Mitryukovskiy, Agustin Palacios-Laloy, Denis Schwartz, Nacim Betrouni, Philippe Derambure, Fabrice Wallois, Vincent Wens, Xavier De Tiege
Summary: This study investigates the application of tri-axial optically pumped magnetometers (OPMs) in detecting interictal epileptiform discharges (IEDs). The results show that both Rb-OPMs and He-OPMs have comparable ability to detect IEDs, with higher amplitude observed in Rb-OPM recordings due to differences in sensor locations. Tri-axial OPMs allow for maximum spatial brain sampling for IED detection with a limited number of sensors.
FRONTIERS IN NEUROSCIENCE
(2023)
Article
Chemistry, Physical
Pengfei Zhai, Xiuwei Xuan, Hongji Li, Cuiping Li, Penghai Li, Mingji Li
Summary: The study demonstrates that B and N co-doped vertical graphene (BNVG) electrodes can improve the contact issue of graphene in monitoring scalp electroencephalogram (EEG) signals. By analyzing the effects of different B and N atom contents, the optimal BNVG electrode is determined and successfully applied in an EEG cap for recording EEG signals, which has important implications for clinical and brain-computer interface systems.
Article
Chemistry, Multidisciplinary
Jianzhuo Yan, Jinnan Li, Hongxia Xu, Yongchuan Yu, Tianyu Xu
Summary: This study presents a transformer-based seizure prediction model that extracts time-frequency characteristics of EEG signals and solves the length limitations in deep learning models by fusing and classifying the features. Experimental results show that the model improves the accuracy of seizure prediction.
APPLIED SCIENCES-BASEL
(2022)
Article
Clinical Neurology
Zachary Fitzgerald, Marcia Morita-Sherman, Olivia Hogue, Boney Joseph, Marina K. M. Alvim, Clarissa L. Yasuda, Deborah Vegh, Dileep Nair, Richard Burgess, William Bingaman, Imad Najm, Michael W. Kattan, Ingmar Blumcke, Gregory Worrell, Benjamin H. Brinkmann, Fernando Cendes, Lara Jehi
Summary: This study evaluates the role of scalp EEG in predicting resective epilepsy surgery outcomes, finding the significance of IEDs. The nomogram provides an individualized prediction of postoperative outcome, assessing the relationship between preoperative findings and outcomes.
Article
Multidisciplinary Sciences
Jeff Craley, Christophe Jouny, Emily Johnson, David Hsu, Raheel Ahmed, Archana Venkataraman
Summary: SZTrack is a neural network architecture that detects and tracks seizure activity in multichannel EEG. It captures the evolution of seizures and provides localization information. Experimental results on clinical and additional datasets demonstrate the effectiveness and generalization capabilities of this network.
Article
Clinical Neurology
Lorenzo Ricci, Margherita Matarrese, Jurriaan M. Peters, Eleonora Tamilia, Joseph R. Madsen, Phillip L. Pearl, Christos Papadelis
Summary: This study examined the utility of virtual implantation with electrical source imaging (ESI) on ictal scalp EEG for mapping the seizure onset zone (SOZ) and predicting surgical outcome in children with drug resistant epilepsy. The results showed that virtual implantation can approximate the SOZ and predict the outcome of the surgery.
CLINICAL NEUROPHYSIOLOGY
(2022)
Review
Clinical Neurology
Zulfi Haneef, Kaiyuan Yang, Sameer A. Sheth, Fuad Z. Aloor, Behnaam Aazhang, Vaishnav Krishnan, Cemal Karakas
Summary: Sub-scalp electroencephalography (ssEEG) is a promising technology for ultra-long-term EEG recordings. This review examines the potential utility of ssEEG devices in epilepsy evaluation, including seizure quantification, characterization, localization, alarms, forecasting, biomarker discovery, sleep medicine, and responsive stimulation. The review also discusses the different ssEEG devices in development and suggests a roadmap for ideal ssEEG designs.
CLINICAL NEUROPHYSIOLOGY
(2022)
Article
Clinical Neurology
Philipp Franz Windhager, Adrian V. Marcu, Eugen Trinka, Arne Bathke, Yvonne Hoeller
Summary: This study investigated the relationship between age and high-frequency oscillations (HFOs), and found that the age effect on HFO rates could not be replicated in scalp-EEG recordings. This lack of replicability may be due to the local propagation patterns of age-related HFOs occurring only in deep structures. Limitations such as small sample size, decreased signal-to-noise ratio compared to invasive recordings, and HFO-mimicking artifacts should be considered.
FRONTIERS IN NEUROLOGY
(2022)
Article
Multidisciplinary Sciences
Yoon Gi Chung, Woo-Jin Lee, Sung Min Na, Hunmin Kim, Hee Hwang, Chang-Ho Yun, Ki Joong Kim
Summary: This study proposes deep learning-based models to detect and classify interictal epileptiform discharges (IEDs) in the frontal, temporal, and occipital scalp regions. The models achieved high accuracies in detecting and categorizing IEDs, but improvements are still needed.
SCIENTIFIC REPORTS
(2023)
Article
Computer Science, Artificial Intelligence
Runze Zheng, Yuanmeng Feng, Tianlei Wang, Jiuwen Cao, Duanpo Wu, Tiejia Jiang, Feng Gao
Summary: In this paper, the scalp EEG based functional connectivity and network topology parameters are comprehensively studied for the prognostic analysis of West syndrome. The study reveals that West seizures weaken connections between brain regions responsible for cognition and intelligence, while brain regions responsible for information synergy and visual reception have greater variability in connectivity during seizures.
Article
Clinical Neurology
Veronique Latreille, Tamir Avigdor, John Thomas, Joelle Crane, Viviane Sziklas, Marilyn Jones-Gotman, Birgit Frauscher
Summary: This study investigated the role of sleep oscillations in memory consolidation and found that scalp spindles play an important role in memory processes in patients with drug-resistant temporal lobe epilepsy. However, the role of sleep ripples in memory abilities in epilepsy is still unclear.
Article
Psychology, Experimental
Thalia D. M. Stalmeier, Jelle Lubbers, Mira B. Cladder-Micus, Imke Hanssen, Marloes J. Huijbers, Anne E. M. Speckens, Dirk E. M. Geurts
Summary: This exploratory study found that negative self-referential memory bias is related to depressive symptoms in patients with bipolar disorder (BD). Furthermore, the study suggests that mindfulness-based cognitive therapy (MBCT) may reduce this negative memory bias over time.
COGNITION & EMOTION
(2022)
Article
Clinical Neurology
Lars Vedel Kessing, Simon Christoffer Ziersen, Thomas Gerds, Esben Budtz-Jorgensen
Summary: This nationwide population-based longitudinal register linkage study aimed to investigate the long-term response to lithium in patients with bipolar disorder with and without comorbid epilepsy. The study also aimed to compare differences in responses between lithium, valproate, and lamotrigine within patients with comorbid bipolar disorder and epilepsy. The findings suggest that valproate and lamotrigine should be given priority in these patients.
JOURNAL OF AFFECTIVE DISORDERS
(2022)
Review
Engineering, Biomedical
Duong Nhu, Mubeen Janmohamed, Ana Antonic-Baker, Piero Perucca, Terence J. O'Brien, Amanda K. Gilligan, Patrick Kwan, Chang Wei Tan, Levin Kuhlmann
Summary: Automated interictal epileptiform discharge (IED) detection has been extensively studied using machine learning methods, particularly deep learning (DL). While DL shows promising results in IED detection, there are limitations in standardizing data collection, multi-center testing, and reporting of clinically relevant metrics.
JOURNAL OF NEURAL ENGINEERING
(2022)
Article
Engineering, Biomedical
Antoine Ghestem, Marco N. Pompili, Matthias Dipper-Wawra, Pascale P. Quilichini, Christophe Bernard, Maeva Ferraris
Summary: Researchers have developed a new prosthesis for long-term electrophysiological recordings in rats, including those with epilepsy. The new design successfully protected the probes from strong mechanical stress and allowed for the safe retrieval of probes, with a retrieval and reuse success rate of 91%.
JOURNAL OF NEURAL ENGINEERING
(2023)
