Article
Clinical Neurology
Nishant Sinha, John S. Duncan, Beate Diehl, Fahmida A. Chowdhury, Jane de Tisi, Anna Miserocchi, Andrew William Mcevoy, Kathryn A. Davis, Sjoerd B. Vos, Gavin P. Winston, Yujiang Wang, Peter Neal Taylor
Summary: This study aimed to investigate the impact of the relationship between brain structure and function on the success of epilepsy surgery. The results showed that patients with stronger structure-function coupling in brain areas implanted with EEG electrodes had better control of seizure activity.
Article
Clinical Neurology
Mickael Ferrand, Cedric Baumann, Olivier Aron, Jean-Pierre Vignal, Jacques Jonas, Louise Tyvaert, Sophie Colnat-Coulbois, Laurent Koessler, Louis Maillard
Summary: In this study, 6 different seizure patterns were identified based on the first abnormality on scalp EEG. However, none of these patterns were specific to a single intracerebral localization, indicating that scalp EEG alone may not accurately predict the onset location of seizures.
Article
Clinical Neurology
Camelia Lentoiu, Irina Oane, Andrei Barborica, Cristian Donos, Constantin Pistol, Andrei Daneasa, Flavius Bratu, Ioana Mindruta
Summary: This study highlights the brain structures and networks involved in ictal grimacing in parietal lobe epilepsy. Two patients with drug-resistant epilepsy and ictal grimacing were analyzed using intracranial electrodes. The results showed that different networks were responsible for different facial expressions, such as disgust and smiling/laughter.
EPILEPTIC DISORDERS
(2022)
Article
Multidisciplinary Sciences
Somin Lee, Julia Henry, Andrew K. Tryba, Yasar Esengul, Peter Warnke, Shasha Wu, Wim van Drongelen
Summary: Infraslow activity (ISA) has become an interesting biomarker for characterizing seizures. However, studying low frequency activity in clinical seizure recordings has been challenging due to technical limitations. This study presents a digital inverse filter that can recover attenuated low frequency activity in intracranial recordings and demonstrates its application in identifying and assessing the seizure onset zone.
SCIENTIFIC REPORTS
(2022)
Article
Engineering, Biomedical
Chunsheng Li, Abbas Sohrabpour, Haiteng Jiang, Bin He
Summary: Seizure generation is thought to be driven by epileptogenic networks, and high-frequency hubs play a more critical role in determining treatment outcomes. HF hubs show increased activity in the early and middle stages of seizures, while LF hubs show increased activity in the late stages. HF hubs can more accurately predict treatment outcomes, providing more precise targets for surgical interventions or neuromodulation therapies.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2021)
Article
Clinical Neurology
Saramati Narasimhan, Hernan F. J. Gonzalez, Graham W. Johnson, Kristin E. Wills, Danika L. Paulo, Victoria L. Morgan, Dario J. Englot
Summary: Evaluating fMRI connectivity between mesial temporal structures and default mode network may aid in lateralization of mesial temporal lobe epilepsy, reduce the need for intracranial monitoring, and guide surgical planning.
JOURNAL OF NEUROSURGERY
(2022)
Article
Neurosciences
Nadja Birk, Jan Schoenberger, Karin Helene Somerlik-Fuchs, Andreas Schulze-Bonhage, Julia Jacobs
Summary: High-frequency oscillations (HFOs) can serve as biomarkers for evaluating seizure severity in epilepsy. The occurrence of HFOs during seizures in a chronic focal epilepsy rat model was found to correlate with the severity of seizures, with higher rates of HFOs observed during severe seizures. Postictal decrease in HFOs may reflect inhibition of epileptic activity.
FRONTIERS IN HUMAN NEUROSCIENCE
(2021)
Article
Neurosciences
Kaijia Sun, Haixiang Wang, Yunxian Bai, Wenjing Zhou, Liang Wang
Summary: The MRIES toolbox is developed to automatically process CCEP data and visualize connectivity results, providing researchers and clinicians with a user-friendly interface for displaying and comparing connectivity measurements. The toolbox aims to improve the reproducibility of CCEP findings and facilitate clinical translation.
FRONTIERS IN NEUROSCIENCE
(2021)
Article
Clinical Neurology
Cristina Filipescu, Elisabeth Landre, Baris Turak, Bertrand Devaux, Francine Chassoux
Summary: This study describes pure insular ictal semiology and patterns of extra-insular spread using SEEG based on the classification of insular cytoarchitecture. The findings suggest that the classification and corresponding ictal features can help in grading insular seizures and optimizing SEEG planning for presumed insular epilepsy.
CLINICAL NEUROPHYSIOLOGY
(2023)
Article
Clinical Neurology
Sara Simula, Elodie Garnier, Margherita Contento, Francesca Pizzo, Julia Makhalova, Stanislas Lagarde, Christian-George Benar, Fabrice Bartolomei
Summary: Stereoelectroencephalography-guided radiofrequency thermocoagulation (SEEG-guided RF-TC) aims to reduce seizure frequency by modifying epileptogenic networks through local thermocoagulative lesions. This study evaluated the changes in brain activity after RF-TC using SEEG recordings and found significant differences in both local and network-related (FC) changes between responders and nonresponders.
Review
Neurosciences
Stanislas Lagarde, Christian-G Benar, Fabrice Wendling, Fabrice Bartolomei
Summary: This article reviews the concept of the epileptogenic network, explains the basic notions of functional connectivity, and reports the current body of published data using intracranial EEG. The data show that there are differential changes in functional connectivity between epileptic and non-epileptic areas even at temporal distance from seizures. These findings may help locate epileptic areas and predict surgical outcomes.
BRAIN CONNECTIVITY
(2022)
Article
Multidisciplinary Sciences
Sakar Rijal, Ludovica Corona, M. Scott Perry, Eleonora Tamilia, Joseph R. Madsen, Scellig S. D. Stone, Jeffrey Bolton, Phillip L. Pearl, Christos Papadelis
Summary: Normal brain functioning relies on complex interactions among different regions forming networks. This study investigates the use of functional connectivity in quantifying epileptogenicity and predicting surgical outcome in children with drug resistant epilepsy (DRE). The findings suggest that functional connectivity can distinguish epileptogenic states and predict outcome in patients with DRE.
SCIENTIFIC REPORTS
(2023)
Article
Neurosciences
Zahraa Sabra, Ali Alawieh, Leonardo Bonilha, Thomas Naselaris, Nicholas AuYong
Summary: This study investigated the regional and cross-regional cortical activities underlying the cognition of visual narrative using intracranial stereotactic electroencephalograms recordings. The results showed that the frontal and temporal lobes encode the difference between visual narrative and random image set. Additionally, the frontal lobe is more engaged when contextually novel stimuli are presented.
FRONTIERS IN HUMAN NEUROSCIENCE
(2022)
Article
Biochemical Research Methods
Vinicius Rezende Carvalho, Marcio Flavio Dutra Moraes, Sydney S. Cash, Eduardo Mazoni Andrade Marcal Mendes
Summary: The study evaluates the use of active probing paradigms to forecast seizures by analyzing underlying neural model parameter changes. The results show that responses to stimuli can predict seizures regardless of the parameters shifting towards ictal states. This approach may assist in early-warning systems for seizure forecasting.
PLOS COMPUTATIONAL BIOLOGY
(2021)
Article
Psychiatry
Juan P. Ramirez-Mahaluf, Angeles Tepper, Luz Maria Alliende, Carlos Mena, Carmen Paz Castaneda, Barbara Iruretagoyena, Ruben Nachar, Francisco Reyes-Madrigal, Pablo Leon-Ortiz, Ricardo Mora-Duran, Tomas Ossandon, Alfonso Gonzalez-Valderrama, Juan Undurraga, Camilo De la Fuente-Sandoval, Nicolas A. Crossley
Summary: This study analyzed the temporal changes in functional connectivity in patients with a first episode of psychosis and compared them with healthy controls. The results showed that patients had a temporal disorganization of the brain's dynamic functional connectivity, which was associated with antipsychotic medication use.
SCHIZOPHRENIA BULLETIN
(2023)
Article
Clinical Neurology
Z. I. Wang, B. Krishnan, D. W. Shattuck, R. M. Leahy, A. N. V. Moosa, E. Wyllie, R. C. Burgess, N. B. Al-Sharif, A. A. Josh, A. V. Alexopoulos, J. C. Mosher, U. Udayasankar, S. E. Jones
AMERICAN JOURNAL OF NEURORADIOLOGY
(2016)
Article
Engineering, Biomedical
George Dassios, Athanassios S. Fokas, Parham Hashemzadeh, Richard M. Leahy
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
(2018)
Article
Engineering, Biomedical
Jian Li, Justin P. Haldar, John C. Mosher, Dileep R. Nair, Jorge A. Gonzalez-Martinez, Richard M. Leahy
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
(2019)
Article
Neurosciences
Jian Li, Olesya Grinenko, John C. Mosher, Jorge Gonzalez-Martinez, Richard M. Leahy, Patrick Chauvel
HUMAN BRAIN MAPPING
(2020)
Article
Computer Science, Artificial Intelligence
Haleh Akrami, Anand A. Joshi, Jian Li, Sergul Aydore, Richard M. Leahy
Summary: The presence of outliers can significantly affect the performance and training process of deep learning methods, particularly in anomaly detection tasks using variational autoencoders (VAEs). In this paper, the authors propose a robust VAE model that incorporates the concept of robust statistics to control the robustness to outliers in the training data. The model maintains the same computational complexity as the standard VAE and includes a single tuning parameter for controlling the degree of robustness. The authors show the improved robustness of the proposed model using various datasets and demonstrate its application in detecting brain lesions in medical images. They also present a method for unsupervised hyperparameter tuning.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Clinical Neurology
H. Akrami, R. M. Leahy, A. Irimia, P. E. Kim, C. N. Heck, A. A. Joshi
Summary: This study used an MR imaging data set to identify imaging biomarkers that predict posttraumatic epilepsy. The findings suggest that lesions in the temporal lobes, occipital lobe, and cerebellum are associated with an increased incidence of posttraumatic epilepsy.
AMERICAN JOURNAL OF NEURORADIOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Rodrigo A. Lobos, Muhammad Usman Ghani, W. Clem Karl, Richard M. Leahy, Justin P. Haldar
Summary: This study presents a novel theory suggesting that sinograms often possess substantial redundancies that can be used for linear prediction of missing/degraded samples. Additionally, when sinogram samples are assembled into a structured Hankel/Toeplitz matrix, the matrix is expected to have low-rank characteristics.
IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING
(2021)