Article
Engineering, Biomedical
Boxuan Wei, Xiaohui Zhao, Lijuan Shi, Lu Xu, Tao Liu, Jicong Zhang
Summary: The study proposed a deep learning-based IED detection method with high accuracy and excellent performance in precision, sensitivity, specificity, and other metrics, maintaining outstanding results across multiple datasets. This method is significant in assisting clinical EEG interpretation for patients with epilepsy and provides new ideas for epileptic biomarker detection in scalp EEG, utilizing multi-level output and correlation among EEG sensors.
JOURNAL OF NEURAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
John Thomas, Prasanth Thangavel, Wei Yan Peh, Jin Jing, Rajamanickam Yuvaraj, Sydney S. Cash, Rima Chaudhari, Sagar Karia, Rahul Rathakrishnan, Vinay Saini, Nilesh Shah, Rohit Srivastava, Yee-Leng Tan, Brandon Westover, Justin Dauwels
Summary: This study proposes a diagnostic system for epilepsy based on multiple modalities extracted from EEG, achieving high accuracy in cross-validation results. The system, consisting of components like Convolutional Neural Network and spectral feature classifier, shows potential in aiding clinicians to diagnose epilepsy efficiently.
INTERNATIONAL JOURNAL OF NEURAL SYSTEMS
(2021)
Article
Engineering, Biomedical
Ana Maria Amaro de Sousa, Michel J. A. M. van Putten, Stephanie van den Berg, Maryam Amir Haeri
Summary: Interictal discharges are important signatures of epilepsy and their detection can assist in epilepsy diagnostics. This study explored unsupervised and semi-supervised deep learning approaches for the automatic detection of these discharges in EEG recordings. The best performance was achieved using a semi-supervised approach, with a sensitivity of 81.9% and specificity of 91.7%.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Review
Clinical Neurology
Catarina da Silva Lourenco, Marleen C. Tjepkema-Cloostermans, Michel J. A. M. van Putten
Summary: This article discusses the importance of EEG in the diagnosis and classification of epilepsy, with a focus on the detection of Interictal Epileptiform Discharges (IEDs), the development of automated methods, and their limitations. Traditional machine learning and deep learning methods have shown the best results in IED detection so far, but the standardization of datasets and outcome measures is needed for a more objective comparison of models.
CLINICAL NEUROPHYSIOLOGY
(2021)
Article
Biology
Elliot H. Smith, Jyun-You Liou, Edward M. Merricks, Tyler Davis, Kyle Thomson, Bradley Greger, Paul House, Ronald G. Emerson, Robert Goodman, Guy M. McKhann, Sameer Sheth, Catherine Schevon, John D. Rolston
Summary: This study investigates the relationship between interictal epileptiform discharges (IEDs) and seizures. The findings demonstrate a spatiotemporal similarity between IEDs and ictal discharges, suggesting that the propagation of IEDs can provide useful information for localizing the seizure focus.
Article
Clinical Neurology
Simon Henin, Anita Shankar, Helen Borges, Adeen Flinker, Werner Doyle, Daniel Friedman, Orrin Devinsky, Gyorgy Buzsaki, Anli Liu
Summary: The spatiotemporal characteristics of cortical high-gamma activity, hippocampal ripple activity, and interictal epileptiform discharges have a significant impact on memory performance during an associative memory task, particularly in the hippocampal region. Interictal epileptiform discharges may impair associative memory by disrupting physiological activity, making them a promising therapeutic target for memory remediation in patients with epilepsy.
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
Clinical Neurology
Robert J. Quon, Stephen Meisenhelter, Edward J. Camp, Markus E. Testorf, Yinchen Song, Qingyuan Song, George W. Culler, Payam Moein, Barbara C. Jobst
Summary: The study utilized an automated method combining template-matching algorithm and CNN to successfully detect intracranial IEDs with high F1 score and AUC. On the external test set, it was able to identify 100% of high-amplitude IED complexes, 96.23% of high amplitude isolated IEDs, and 66.15% of IEDs with atypical morphology.
CLINICAL NEUROPHYSIOLOGY
(2022)
Article
Clinical Neurology
Anca A. Arbune, Pirgit Meritam Larsen, Stephan Wustenhagen, Daniella Terney, Elena Gardella, Sandor Beniczky
Summary: The study found that more than one third of epileptiform EEG discharges showed a decrease in spiking patterns during seizures, suggesting a potential anticonvulsive function, while the majority of discharges increased in association with seizures.
CLINICAL NEUROPHYSIOLOGY
(2021)
Article
Biochemical Research Methods
Audrey Laurence, Denahin H. Toffa, Ke Peng, Manon Robert, Alain Bouthillier, Dang K. Nguyen, Frederic Leblond
Summary: This study evaluated the possibility of using an intraoperative multispectral imaging system combined with electrocorticography (ECoG) to measure the average hemodynamic response function (HRF) associated with interictal epileptiform discharges (IEDs) in patients with epilepsy. The study found inter-patient variability of the HRF and identified a sub-region that corresponded to the most active area identified by ECoG.
BIOMEDICAL OPTICS EXPRESS
(2022)
Article
Clinical Neurology
Robert J. Quon, Edward J. Camp, Stephen Meisenhelter, Yinchen Song, Sarah A. Steimel, Markus E. Testorf, Angeline S. Andrew, Robert E. Gross, Bradley C. Lega, Michael R. Sperling, Michael J. Kahana, Barbara C. Jobst
Summary: The study investigated the impact of interictal epileptiform discharges (IEDs) on memory performance, finding that increased IED rate, white matter propagation, and localization in the left middle temporal region were associated with poorer memory performance. Specifically for lateral temporal IEDs, there was a significant interaction between IED white matter classification and amplitude, where higher amplitude and white matter propagation were linked to reduced memory performance. Additionally, changes in alpha power after an IED were positively correlated with memory performance.
Article
Clinical Neurology
Noa Cohen, Yoram Ebrahimi, Mordekhay Medvedovsky, Guy Gurevitch, Orna Aizenstein, Talma Hendler, Firas Fahoum, Tomer Gazit
Summary: Polymicrogyria is a common brain malformation that can lead to epileptic seizures. By tracking BOLD activations over time, researchers have found that early hemodynamic activity may provide important information to help localize the source of epileptic activity in patients with PMG. The development of IEDs within a small area of the PMG lesion with subsequent wider engagement of brain structures may explain the difficulty in detecting them on scalp EEG.
FRONTIERS IN NEUROLOGY
(2021)
Article
Clinical Neurology
Robert J. Quon, Stephen Meisenhelter, Richard H. Adamovich-Zeitlin, Yinchen Song, Sarah A. Steimel, Edward J. Camp, Markus E. Testorf, Todd A. MacKenzie, Robert E. Gross, Bradley C. Lega, Michael R. Sperling, Michael J. Kahana, Barbara C. Jobst
Summary: This study evaluates the influence of subject-specific factors on intracranial interictal epileptiform discharge (IED) rates in patients with refractory epilepsy. Antiseizure medication status, time of testing, and seizure onset zone location were found to have the highest impact on IED rates. Factors like SOZ location and ASM status are crucial when analyzing IEDs for clinical or research purposes.
Article
Computer Science, Artificial Intelligence
Chenchen Cheng, Yuanfeng Zhou, Bo You, Yan Liu, Gao Fei, Liling Yang, Yakang Dai
Summary: This study developed a novel multiview feature fusion representation (MVFFR) method to detect EEG signals with/without interictal epileptiform spikes (IES). The experimental results showed that MVFFR achieved the optimal detection performance compared with other feature ranking methods, and the MVFFR-related methods were complementary and indispensable. Additionally, MVFFR maintained excellent generalization capacity in an independent test.
INTERNATIONAL JOURNAL OF NEURAL SYSTEMS
(2022)
Article
Engineering, Biomedical
Chenchen Cheng, Yan Liu, Bo You, Yuanfeng Zhou, Fei Gao, Liling Yang, Yakang Dai
Summary: A multilevel feature learning method was proposed in this study for accurate spike detection, which avoids the subjectivity and inefficiency of visual inspection and enables highly accurate detection of spikes.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2022)
Article
Clinical Neurology
William O. Tatum, Jayanti Mani, Kazutaka Jin, Jonathan J. Halford, David Gloss, Firas Fahoum, Louis Maillard, Ian Mothersill, Sandor Beniczky
Summary: The objective of this clinical practice guideline is to provide recommendations on the indications and minimum standards for inpatient long-term video-electroencephalographic monitoring (LTVEM). The review of published evidence using The Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement found limited high-level evidence. Recommendations were formulated for the indications, technical requirements, and essential practice elements of LTVEM. Further research is needed to obtain evidence about long-term outcome effects of LTVEM and establish its clinical utility.
CLINICAL NEUROPHYSIOLOGY
(2022)
Article
Clinical Neurology
Josemir W. Sander, William E. Rosenfeld, Jonathan J. Halford, Bernhard J. Steinhoff, Victor Biton, Manuel Toledo
Summary: Through pooling and analyzing data from multiple studies, it was found that long-term retention rates of adjunctive cenobamate therapy for individuals with uncontrolled focal seizures were consistently high, indicating cenobamate as a potentially effective and well-tolerated treatment option. The most common reasons for discontinuation of treatment were adverse events, withdrawal of consent, and other reasons.
Article
Clinical Neurology
William O. Tatum, Jayanti Mani, Kazutaka Jin, Jonathan J. Halford, David Gloss, Firas Fahoum, Louis Maillard, Ian Mothersill, Sandor Beniczky
Summary: The clinical practice guideline aims to provide recommendations on the indications and minimum standards for inpatient long-term video-electroencephalographic monitoring (LTVEM). Limited high-level evidence exists for specific aspects of diagnosis for LTVEM in patients with seizures and nonepileptic events, indicating a need for further research.
Article
Clinical Neurology
William O. Tatum, Jonathan J. Halford, Piotr Olejniczak, Olga Selioutski, Madeleine M. Grigg-Damberger, David Gloss, Jayant Acharya, Stephan Schuele, Saurabh R. Sinha, Tammy Tsuchida, Frank W. Drislane
Summary: Ambulatory EEG devices provide portable, multichannel, digital EEG recording in the patient's natural environment. However, there are technical challenges in acquiring interpretable EEG outside of the hospital setting and the lack of technical standards for ambulatory EEG. This article provides minimal technical standards for ambulatory EEG to ensure the quality of studies in clinical and research practice.
JOURNAL OF CLINICAL NEUROPHYSIOLOGY
(2022)
Article
Engineering, Biomedical
Prasanth Thangavel, John Thomas, Nishant Sinha, Wei Yan Peh, Rajamanickam Yuvaraj, Sydney S. Cash, Rima Chaudhari, Sagar Karia, Jin Jing, Rahul Rathakrishnan, Vinay Saini, Nilesh Shah, Rohit Srivastava, Yee-Leng Tan, Brandon Westover, Justin Dauwels
Summary: This study aims to automate and improve the reliable diagnosis of epilepsy by exploring the background characteristics of interictal EEG. The results show that using a combination of three features (IED rate, and Daubechies and Morlet wavelets) significantly improves the classification accuracy of EEGs with IEDs vs. normal EEGs. The inclusion of IED-independent features also enhances the classification of epileptic EEGs with and without IEDs vs. normal EEGs. These findings pave the way for automated detection of epilepsy and open up an underexplored option in epilepsy diagnosis.
JOURNAL OF NEURAL ENGINEERING
(2022)
Article
Clinical Neurology
John Thomas, Philippe Kahane, Chifaou Abdallah, Tamir Avigdor, Willemiek J. E. M. Zweiphenning, Stephan Chabardes, Kassem Jaber, Veronique Latreille, Lorella Minotti, Jeff Hall, Francois Dubeau, Jean Gotman, Birgit Frauscher
Summary: This study aims to identify specific spike features in intracranial EEG that accurately define the epileptogenic zone (EZ) and predict surgical outcomes. The study found that spike rate with preceding gamma activity in wakefulness performed better than other biomarkers in classifying surgical outcomes. Resection of brain regions with high spike-gamma rates in wakefulness is associated with a high probability of achieving seizure freedom.
ANNALS OF NEUROLOGY
(2023)
Article
Clinical Neurology
Jin Jing, Wendong Ge, Aaron F. Struck, Marta Bento Fernandes, Shenda Hong, Sungtae An, Safoora Fatima, Aline Herlopian, Ioannis Karakis, Jonathan J. Halford, Marcus C. Ng, Emily L. Johnson, Brian L. Appavu, Rani A. Sarkis, Gamaleldin Osman, Peter W. Kaplan, Monica B. Dhakar, Lakshman Arcot Jayagopal, Zubeda Sheikh, Olga Taraschenko, Sarah Schmitt, Hiba A. Haider, Jennifer A. Kim, Christa B. Swisher, Nicolas Gaspard, Mackenzie C. Cervenka, Andres Rodriguez A. Ruiz, Jong Woo Lee, Mohammad Tabaeizadeh, Emily J. Gilmore, Kristy Nordstrom, Ji Yeoun Yoo, Manisha G. Holmes, Susan T. Herman, Jennifer A. Williams, Jay Pathmanathan, Fabio A. Nascimento, Ziwei Fan, Samaneh Nasiri, Mouhsin M. Shafi, Sydney S. Cash, Daniel B. Hoch, Andrew J. Cole, Eric S. Rosenthal, Sahar F. Zafar, Jimeng Sun, M. Brandon Westover
Summary: This study assessed the reliability of experts in identifying seizures and other potentially harmful rhythmic brain activity using EEG. The results showed high agreement among experts, with differences mainly attributed to variations in decision thresholds.
Article
Clinical Neurology
Andres M. Kanner, Anita S. Saporta, Dong H. Kim, John J. Barry, Hamada Altalib, Hope Omotola, Nathalie Jette, Terence J. O'Brien, Siddhartha Nadkarni, Melodie R. Winawer, Michael Sperling, Jacqueline A. French, Bassel Abou-Khalil, Brian Alldredge, Martina Bebin, Gregory D. Cascino, Andrew J. Cole, Mark J. Cook, Kamil Detyniecki, Orrin Devinsky, Dennis Dlugos, Edward Faught, David Ficker, Madeline Fields, Barry Gidal, Michael Gelfand, Simon Glynn, Jonathan J. Halford, Sheryl Haut, Manu Hegde, Manisha G. Holmes, Reetta Kalviainen, Joon Kang, Pavel Klein, Robert C. Knowlton, Kaarkuzhali Krishnamurthy, Ruben Kuzniecky, Patrick Kwan, Daniel H. Lowenstein, Lara Marcuse, Kimford J. Meador, Scott Mintzer, Heath R. Pardoe, Kristen Park, Patricia Penovich, Rani K. Singh, Ernest Somerville, Charles A. Szabo, Jerzy P. Szaflarski, K. Liu Lin Thio, Eugen Trinka, Jorge G. Burneo
Summary: This study investigated the prevalence of mood, anxiety disorders, and suicidality in patients with newly diagnosed focal epilepsy. The results showed that 43.5% of patients had a psychiatric diagnosis, with 38.6% meeting the criteria for mood and/or anxiety disorders, and 21.6% reporting suicidal ideation. Major depressive disorders, bipolar disorders, panic disorders, and agoraphobia were associated with suicidality.
Article
Chemistry, Analytical
Rajamanickam Yuvaraj, Prasanth Thagavel, John Thomas, Jack Fogarty, Farhan Ali
Summary: Advances in signal processing and machine learning have accelerated EEG-based emotion recognition research. This study compared the classification accuracy of various sets of EEG features to identify emotional states. By evaluating the performance on five independent datasets, it was found that the FD-CART feature-classification method achieved the highest accuracy for valence and arousal. These findings suggest the reliability of the FD features derived from EEG data for emotion recognition, and may contribute to the development of a real-time EEG-based emotion recognition system.
Editorial Material
Clinical Neurology
Jonathan J. Halford, Benjamin H. Brinkmann, David A. Clunie, Jean Gotman, Sandor Beniczky, Stefan Rampp, Jan Remi, Aatif Husain, J. Andrew Ehrenberg, Silvia Winkler
CLINICAL NEUROPHYSIOLOGY
(2023)
Article
Clinical Neurology
Maria E. Peltola, Markus Leitinger, Jonathan J. Halford, Kollencheri Puthenveettil Vinayan, Katsuhiro Kobayashi, Ronit M. Pressler, Ioana Mindruta, Luis Carlos Mayor, Leena Lauronen, Sandor Beniczky
Summary: This article provides recommendations on minimum standards for recording routine and sleep electroencephalography (EEG) based on the joint working group of IFCN and ILAE. The evidence was reviewed using PRISMA statement and the quality was assessed by GRADE method and QUADAS-2 tool. Consensus-based recommendations were formulated using modified Delphi technique and the GRADE system. 16 recommendations covering indications, technical standards, recording duration, sleep induction, and provocative methods were formulated.
Article
Clinical Neurology
Sana Hannan, John Thomas, Kassem Jaber, Charbel El Kosseifi, Alyssa Ho, Chifaou Abdallah, Tamir Avigdor, Jean Gotman, Birgit Frauscher
Summary: Objective sleep has significant influences on focal interictal epileptiform discharges (IEDs), with increased rates and spatial extent in non-rapid eye movement (NREM) sleep. However, the effects of sleep on seizures are unclear, and its impact on seizure topography is poorly documented. This study evaluates the influences of NREM sleep on ictal spatiotemporal dynamics, finding that NREM sleep does not significantly affect these dynamics.
ANNALS OF NEUROLOGY
(2023)
Article
Clinical Neurology
Alyssa Ho, Sana Hannan, John Thomas, Tamir Avigdor, Chifaou Abdallah, Francois Dubeau, Jean Gotman, Birgit Frauscher
Summary: This study investigates the suppressive effect of rapid eye movement (REM) sleep on interictal epileptiform discharges (IEDs) and finds that REM sleep suppresses IEDs in the neocortical regions while increasing IEDs in the mesiotemporal regions. Furthermore, late sleep shows a stronger suppression of IEDs compared to early sleep. Therefore, the influences of sleep stage interactions and anatomical locations should be considered when studying the epileptic focus.
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
Neurosciences
Jaden D. Barfuss, Fabio A. Nascimento, Erik Duhaime, Srishti Kapur, Ioannis Karakis, Marcus Ng, Aline Herlopian, Alice Lam, Douglas Maus, Jonathan J. Halford, Sydney Cash, M. Brandon Westover, Jin Jing
Summary: This study evaluated a novel educational tool to trainees how to identify interictal epileptiform discharges (IEDs) on EEG.
CLINICAL NEUROPHYSIOLOGY PRACTICE
(2023)