Article
Computer Science, Interdisciplinary Applications
Ancor Sanz-Garcia, Miriam Perez-Romero, Guillermo J. Ortega
Summary: This study aims to characterize seizure types and phases based on electrophysiological characteristics. By analyzing intracranial EEG recordings, network and spectral measures were calculated and used to identify and classify seizure types and phases. The results showed that seizure types could be classified with high accuracy using a multidimensional feature space and a support vector machine. The study also revealed specific measures and patterns related to seizure severity during different seizure phases.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2022)
Article
Chemistry, Multidisciplinary
Zakareya Lasefr, Khaled Elleithy, Ramasani Rakesh Reddy, Eman Abdelfattah, Miad Faezipour
Summary: This paper studied epileptic seizure detection methods based on EEG signals and proposed an enhanced technique with a mobile application for monitoring the classification of EEG signals. The proposed method achieved high accuracy and outperformed previous studies. It will have significant impacts in the medical field and Human-Computer Interaction fields.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Information Systems
Aayesha, Muhammad Bilal Qureshi, Muhammad Afzaal, Muhammad Shuaib Qureshi, Muhammad Fayaz
Summary: This paper focuses on extracting distinguishing features of seizure EEG recordings to develop an approach that employs both fuzzy-based and traditional machine learning algorithms for epileptic seizure detection. The obtained results show that K-Nearest Neighbor (KNN) and Fuzzy Rough Nearest Neighbor (FRNN) give the highest classification accuracy scores, with improved sensitivity and specificity percentages.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Behavioral Sciences
Sheng Wong, Anj Simmons, Jessica Rivera-Villicana, Scott Barnett, Shobi Sivathamboo, Piero Perucca, Patrick Kwan, Levin Kuhlmann, Rajesh Vasa, Terence J. O'Brien
Summary: Diagnosing and managing seizures is challenging for clinicians, and the adoption of automated seizure detection using machine learning technology is limited. Our survey of medical professionals reveals that the main barriers for usage of seizure detection tools in clinical practice are availability, lack of training, and the blackbox nature of ML algorithms.
EPILEPSY & BEHAVIOR
(2023)
Article
Engineering, Electrical & Electronic
Joseph Mathew, N. Sivakumaran, P. A. Karthick
Summary: Accurate detection of seizure types is crucial for effective treatment and management of epilepsy. This research introduces a novel feature fusion approach based on VMD to detect different types of seizures. Experimental results show that VMD performs well in distinguishing seizure types, and RSZM can effectively recognize seizure types from the first few seconds of ictal EEG. The fusion of RSZM with other features further improves the accuracy.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Chemistry, Multidisciplinary
Marcin Kolodziej, Andrzej Majkowski, Andrzej Rysz
Summary: This article explores the possibilities, issues, and challenges associated with utilizing artificial intelligence for seizure detection using the publicly available iEEG database. It presents standard approaches for analyzing iEEG signals and discusses modern deep learning algorithms. The study shows that CNN and LSTM networks yield significantly better results, and the gradient-weighted class activation mapping algorithm can identify important iEEG signal fragments for seizure detection.
APPLIED SCIENCES-BASEL
(2023)
Article
Biochemical Research Methods
Resmi Cherian, E. Gracemary Kanaga
Summary: Epilepsy is a chronic neurological disorder with a high prevalence rate. Drug-resistant epilepsy poses challenges due to the lack of effective treatments, resulting in incomplete seizure freedom and increased risk of premature death. Accurate prediction of seizures is crucial for managing patients with uncontrollable seizures. Deep learning models offer promising methods for seizure detection and prediction in epilepsy research.
JOURNAL OF NEUROSCIENCE METHODS
(2022)
Article
Engineering, Electrical & Electronic
Sohaib Majzoub, Ahmed Fahmy, Fadi Sibai, Maha Diab, Soliman Mahmoud
Summary: This work investigates epilepsy seizure detection using machine learning. The impact of training and test dataset selection on accuracy and efficacy of CNN prediction is studied. A framework utilizing multiple channels of EEG signals and feature extraction technique is proposed to minimize information loss. Results show that the proposed framework achieves an overall accuracy of 94.44% when the training set contains samples from each patient, and 92.98% when the training set contains a subset of the patient pool.
CIRCUITS SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Engineering, Biomedical
Xuyang Zhao, Noboru Yoshida, Tetsuya Ueda, Hidenori Sugano, Toshihisa Tanaka
Summary: This study applies commonly used models such as LeNet, VGG, ResNet, and ViT to the EEG image classification task, and solves the problems of data imbalance and model interpretation through data augmentation and model explanation methods. The models achieve good performance in seizure detection and provide visual and quantitative information for clinical experts in diagnosis.
JOURNAL OF NEURAL ENGINEERING
(2023)
Article
Engineering, Biomedical
R. Zanetti, U. Pale, T. Teijeiro, D. Atienza
Summary: This study introduces a new feature, approximate zero-crossing (AZC), for seizure classification in EEG and iEEG. The use of AZC features in a low-complexity seizure detection method outperforms a classical literature feature-based method.
JOURNAL OF NEURAL ENGINEERING
(2022)
Article
Clinical Neurology
Hannah Spitzer, Mathilde Ripart, Kirstie Whitaker, Felice D'Arco, Kshitij Mankad, Andrew A. Chen, Antonio Napolitano, Luca De Palma, Alessandro De Benedictis, Stephen Foldes, Zachary Humphreys, Kai Zhang, Wenhan Hu, Jiajie Mo, Marcus Likeman, Shirin Davies, Christopher Guttler, Matteo Lenge, Nathan T. Cohen, Yingying Tang, Shan Wang, Aswin Chari, Martin Tisdall, Nuria Bargallo, Estefania Conde-Blanco, Jose Carlos Pariente, Saul Pascual-Diaz, Ignacio Delgado-Martinez, Carmen Perez-Enriquez, Ilaria Lagorio, Eugenio Abela, Nandini Mullatti, Jonathan O'Muircheartaigh, Katy Vecchiato, Yawu Liu, Maria Eugenia Caligiuri, Ben Sinclair, Lucy Vivash, Anna Willard, Jothy Kandasamy, Ailsa McLellan, Drahoslav Sokol, Mira Semmelroch, Ane G. Kloster, Giske Opheim, Leticia Ribeiro, Clarissa Yasuda, Camilla Rossi-Espagnet, Khalid Hamandi, Anna Tietze, Carmen Barba, Renzo Guerrini, William Davis Gaillard, Xiaozhen You, Irene Wang, Sofia Gonzalez-Ortiz, Mariasavina Severino, Pasquale Striano, Domenico Tortora, Reetta Kalviainen, Antonio Gambardella, Angelo Labate, Patricia Desmond, Elaine Lui, Terence O'Brien, Jay Shetty, Graeme Jackson, John S. Duncan, Gavin P. Winston, Lars H. Pinborg, Fernando Cendes, Fabian J. Theis, Russell T. Shinohara, J. Helen Cross, Torsten Baldeweg, Sophie Adler, Konrad Wagstyl
Summary: One of the challenges in applying machine learning to diagnostic biomedical imaging is the interpretability of algorithms. This study developed an open-source and interpretable machine-learning algorithm to automatically identify FCDs from structural MRI data, improving the confidence of physicians in identifying subtle MRI lesions in individuals with epilepsy.
Article
Engineering, Biomedical
Akash R. Pattnaik, Nina J. Ghosn, Ian Z. Ong, Andrew Y. Revell, William K. S. Ojemann, Brittany H. Scheid, Georgia Georgostathi, John M. Bernabei, Erin C. Conrad, Saurabh R. Sinha, Kathryn A. Davis, Nishant Sinha, Brian Litt
Summary: This study proposes a quantitative measure of seizure severity that incorporates EEG and clinical data, and demonstrates its application in guiding epilepsy therapy. The severity score is found to be associated with lower medication loads and better surgical outcomes. This scoring method improves the accuracy of epilepsy treatment.
JOURNAL OF NEURAL ENGINEERING
(2023)
Article
Chemistry, Analytical
Sergio E. Sanchez-Hernandez, Ricardo A. Salido-Ruiz, Sulema Torres-Ramos, Israel Roman-Godinez
Summary: This study compared the performance of a set of feature selection methods across different classification models for the detection of epileptic activity. The results showed that the performance was notably affected by the classifier, dataset, and feature set, and no feature selection method clearly outperformed the others.
Article
Neurosciences
Anna Witkowska-Wrobel, Kirill Aristovich, Abbe Crawford, Justin D. Perkins, David Holder
Summary: The study successfully reconstructed slow impedance changes evoked by cell swelling using Electrical Impedance Tomography (EIT) in a swine model of epilepsy, demonstrating the potential of combining EIT with intracranial EEG monitoring to improve diagnostic yield in epileptic patients.
Article
Engineering, Electrical & Electronic
Sandeep Singh, Harjot Kaur
Summary: This study proposes an intelligent epilepsy seizure detection system using adaptive mode decomposition methods. The experimental results show that the system achieves high accuracy, sensitivity, and specificity in detecting epilepsy seizures.
CIRCUITS SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Behavioral Sciences
Larissa Altoe Reboli, Renato Marciano Maciel, Jasiara Carla de Oliveira, Marcio Flavio Dutra Moraes, Cristiane Queixa Tilelli, Vinicius Rosa Cota
Summary: This study investigated the effects of nonperiodic stimulation (NPS) on neural function in animals. Results from behavioral tests and electrophysiological recordings showed that NPS did not impair neural function and may be safe for clinical studies. Additionally, the study found that NPS may have a desynchronization effect by competing with epileptic activity, which has implications for understanding neuropsychological phenomena and developing rehabilitation neurotechnology.
BEHAVIOURAL BRAIN RESEARCH
(2022)
Article
Clinical Neurology
Toshiya Nishi, Cameron S. Metcalf, Shinji Fujimoto, Shigeo Hasegawa, Maki Miyamoto, Eiji Sunahara, Sayuri Watanabe, Shinichi Kondo, H. Steve White
Summary: The study characterizes the anticonvulsive property of soticlestat in rodent models of epilepsy and suggests that it may be a novel class of antiseizure medications for the treatment of intractable epilepsy disorders.
Article
Neurosciences
Peter J. West, Kyle Thomson, Peggy Billingsley, Timothy Pruess, Carlos Rueda, Gerald W. Saunders, Misty D. Smith, Cameron S. Metcalf, Karen S. Wilcox
Summary: The study demonstrates that in this MTLE IAK model, pharmacoresistant seizures are resistant to two representative sodium channel-inhibiting ASDs (phenytoin and carbamazepine) and partially sensitive to GABA receptor modulating ASDs (diazepam and phenobarbital) or a mixed-mechanism ASD (valproate). This model is being incorporated into the NINDS-funded ETSP testing platform for treatment resistant epilepsy.
EXPERIMENTAL NEUROLOGY
(2022)
Article
Neurosciences
Daniel B. Rubin, Tommy Hosman, Jessica N. Kelemen, Anastasia Kapitonava, Francis R. Willett, Brian F. Coughlin, Eric Halgren, Eyal Y. Kimchi, Ziv M. Williams, John D. Simeral, Leigh R. Hochberg, Sydney S. Cash
Summary: Replay of motor cortex neural activity may occur during sleep following motor learning in humans.
JOURNAL OF NEUROSCIENCE
(2022)
Article
Neurosciences
Flavio Afonso Goncalves Mourao, Leonardo de Oliveira Guarnieri, Paulo Aparecido Amaral Junior, Vinicius Rezende Carvalho, Eduardo Mazoni Andrade Marcal Mendes, Marcio Flavio Dutra Moraes
Summary: In this study, a new method for implanting multiple tungsten electrode arrays in the brain was described. The researchers also developed a low-cost headstage system that allows high-quality multichannel recording. This method provides a valuable alternative for small laboratories and developing countries.
FRONTIERS IN NEUROSCIENCE
(2022)
Article
Critical Care Medicine
Leon Naar, Lydia R. Maurer, Ander Dorken Gallastegi, Majed W. El Hechi, Sowmya R. Rao, Catherine Coughlin, Senan Ebrahim, Adesh Kadambi, April E. Mendoza, Noelle N. Saillant, B. Christian B. Renne, George C. Velmahos, Haytham M. A. Kaafarani, Jarone Lee
Summary: This study found that the outcomes of postoperative patients admitted directly to an ICU were not affected by the academic status of the institution, but were associated with the operative volume of the unit.
JOURNAL OF INTENSIVE CARE MEDICINE
(2022)
Article
Clinical Neurology
Abigail A. Bucklin, Wolfgang Ganglberger, Syed A. Quadri, Ryan A. Tesh, Noor Adra, Madalena Da Silva Cardoso, Michael J. Leone, Parimala Velpula Krishnamurthy, Aashritha Hemmige, Subapriya Rajan, Ezhil Panneerselvam, Luis Paixao, Jasmine Higgins, Muhammad Abubakar Ayub, Yu-Ping Shao, Elissa M. Ye, Brian Coughlin, Haoqi Sun, Sydney S. Cash, B. Taylor Thompson, Oluwaseun Akeju, David Kuller, Robert J. Thomas, M. Brandon Westover
Summary: This study investigated the prevalence, severity, and risk factors of sleep-disordered breathing in ICU patients. The results showed that sleep-disordered breathing and sleep apnea events are common in ICU and are associated with hypoxia and periodic breathing. Limited bio-signals can be used for detection, but risk factors are insufficient for predicting the severity of AHI.
SLEEP AND BREATHING
(2023)
Article
Pharmacology & Pharmacy
Isabel Vieira de Assis Lima, Hyorrana Priscila Pereira Pinto, Paula Maria Quaglio Bellozi, Maria Carolina Machado da Silva, Luciano R. Vilela, Fabricio A. Moreira, Marcio Flavio Dutra Moraes, Antonio Carlos Pinheiro de Oliveira
Summary: The study suggests that the anticonvulsant effect of CBD requires the involvement of the PI3K signaling pathway. In a seizure model induced by PTZ in mice, genetic ablation of PI3K increased seizure duration and frequency, while CBD inhibited PTZ-induced seizures. Genetic deletion of PI3K or pretreatment with the selective inhibitor LY294002 prevented the anticonvulsant effects of CBD.
PHARMACOLOGICAL REPORTS
(2022)
Editorial Material
Neurosciences
Vinicius Rosa Cota, Marcio Flavio Dutra Moraes
FRONTIERS IN NEUROSCIENCE
(2022)
Article
Engineering, Biomedical
Adam Khalifa, Seyed Mahdi Abrishami, Mohsen Zaeimbashi, Alexander D. Tang, Brian Coughlin, Jennifer Rodger, Sydney S. Cash, Nian X. Sun
Summary: This study proposes a new concept of noninvasive focal stimulation of deep brain regions using temporal interference of two high-frequency magnetic fields. The experimental results show that regions affected by only one high-frequency magnetic field have low C-Fos expression, while regions affected by two fields interfering to create a low-frequency envelope display a significant increase in C-Fos expression.
JOURNAL OF NEURAL ENGINEERING
(2023)
Article
Clinical Neurology
Lisa Coles, Patrick A. Forcelli, Karine Leclercq, Anna-Maria Katsarou, Brian D. Klein, Heidrun Potschka, Rudiger Koehling, Lauren Harte-Hargrove, Aristea S. Galanopoulou, Cameron S. Metcalf
Summary: In order to address concerns over rigor and reproducibility in preclinical studies, the ILAE/AES Task Force has developed common data elements and case report forms for epilepsy research. These forms have been adapted and refined to cover various aspects of preclinical drug screening. They provide a standardized approach to collect data on general pharmacology, pharmacokinetics, pharmacodynamics, tolerability, and elements of rigor and reproducibility. The case report forms can be used widely in the epilepsy research community.
Article
Biochemical Research Methods
Brian Coughlin, William Munoz, Yoav Kfir, Michael J. Young, Domokos Meszena, Mohsen Jamali, Irene Caprara, Richard Hardstone, Arjun Khanna, Martina L. Mustroph, Eric M. Trautmann, Charlie Windolf, Erdem Varol, Dan J. Soper, Sergey D. Stavisky, Marleen Welkenhuysen, Barundeb Dutta, Krishna V. Shenoy, Leigh R. Hochberg, R. Mark Richardson, Ziv M. Williams, Sydney S. Cash, Angelique C. Paulk
Summary: Neuropixels probes are silicon-based electrophysiology-recording tools with high channel count and recording-site density. They have been successfully used in clinical surgeries to study human neurophysiology, demonstrating their potential and challenges as research devices.
Letter
Obstetrics & Gynecology
Adesh Kadambi, Isabel Fulcher, Kartik Venkatesh, Jonathan S. Schor, Mark A. Clapp, Timothy Wen
AMERICAN JOURNAL OF OBSTETRICS & GYNECOLOGY MFM
(2023)
Article
Health Care Sciences & Services
Tobias Brotherton, Samuel Brotherton, Henry Ashworth, Adesh Kadambi, Hassaan Ebrahim, Senan Ebrahim
Summary: While electronic health records have shown effectiveness in low-resource settings, there are still barriers to implementation. The Hikma Health EHR, developed through a user-centered design process, has been deployed for 26,000 patients. Clinician users have reported positive impacts including improved continuity of care, clinical data visualization, and efficiency.
FRONTIERS IN DIGITAL HEALTH
(2022)
Article
Clinical Neurology
Cameron S. Metcalf, Fabiola Vanegas, Tristan Underwood, Kristina Johnson, Peter J. West, Misty D. Smith, Karen S. Wilcox
Summary: The study evaluated the efficacy of antiseizure medications and anti-inflammatory compounds in reducing seizure burden in C57Bl/6J mice infected with Theiler's murine encephalomyelitis virus (TMEV). Several prototype ASMs and anti-inflammatory drugs showed promising results in reducing seizures, with some exhibiting mechanisms of action beyond traditional ASMs. This highlights the importance of evaluating compounds from different mechanistic classes in the TMEV model for potential treatment of infection-induced seizures.