Article
Clinical Neurology
Joshua M. Diamond, Benjamin E. Diamond, Michael S. Trotta, Kate Dembny, Sara K. Inati, Kareem A. Zaghloul
Summary: Our study suggests that ictal activity observed by intracranial EEG may reflect propagated activity from a relatively focal seizure source, even during later time points when ictal activity is more widespread. By analyzing the time differences between ictal discharges in adjacent electrodes, we were able to estimate the location of the hypothesized focal source, which was found to closely match the clinically and neurophysiologically determined brain region giving rise to seizures. Furthermore, we found that this focal source is a dynamic entity that moves and evolves over the time course of a seizure, challenging the traditional conceptualization of the seizure source.
Article
Clinical Neurology
Brandon J. Thio, Aman S. Aberra, Grace E. Dessert, Warren M. Grill
Summary: The objective of this study was to determine the appropriateness of using dipoles as a simplified representation of neural sources for stereo-EEG (sEEG). The distribution of voltages generated by dipoles, biophysically realistic cortical neuron models, and extended regions of cortex were compared to evaluate their accuracy at different spatial scales and electrode to neuron distances relevant for sEEG. The results showed that single dipoles were appropriate for representing single neurons and small regions of active cortex, while multiple dipoles were needed for larger regions of cortex.
CLINICAL NEUROPHYSIOLOGY
(2023)
Article
Clinical Neurology
Stefan Rampp, Karl Rossler, Hajo Hamer, Margit Illek, Michael Buchfelder, Arnd Doerfler, Tom Pieper, Till Hartlieb, Manfred Kudernatsch, Konrad Koelble, Jose Eduardo Peixoto-Santos, Ingmar Blumcke, Roland Coras
Summary: This study demonstrated correlations between dysmorphic neurons and neurophysiological markers, identifying their role in seizure onset, fast gamma activity, and ripples, providing a new tool for localizing epileptic activity in the human brain.
CLINICAL NEUROPHYSIOLOGY
(2021)
Article
Clinical Neurology
John M. Bernabei, Nishant Sinha, T. Campbell Arnold, Erin Conrad, Ian Ong, Akash R. Pattnaik, Joel M. Stein, Russell T. Shinohara, Timothy H. Lucas, Dani S. Bassett, Kathryn A. Davis, Brian Litt
Summary: Bernabei et al. constructed an atlas of normative interictal intracranial EEG recordings and found that brain regions generating spikes and seizures have different patterns of activity and connectivity compared to the atlas. Comparing EEG recordings to the atlas can reliably identify abnormal regions and guide invasive treatment for epilepsy.
Article
Clinical Neurology
Mariano Fernandez-Corazza, Rui Feng, Chengxin Ma, Jie Hu, Li Pan, Phan Luu, Don Tucker
Summary: The study compared the performance of MSP, sLORETA, and cMEM methods for epileptic source estimation using high-resolution electrical head models. Results showed that MSP performed similarly to sLORETA but slightly better than cMEM in terms of success rate. MSP and cMEM methods were more localized and did not require arbitrary selection of hyperparameters, making them better than sLORETA in terms of spatial dispersion. The three methods are complementary and can be used together in clinical practice.
CLINICAL NEUROPHYSIOLOGY
(2021)
Article
Chemistry, Analytical
Saina Namazifard, Kamesh Subbarao
Summary: This paper discusses the problem of accurately estimating the position and orientation of multiple dipoles using synthetic EEG signals. A proper forward model is determined, and a nonlinear constrained optimization problem with regularization is solved to compare the results with the widely used research code EEGLAB. A thorough sensitivity analysis of the estimation algorithm to the parameters in the assumed signal measurement model is conducted. The proposed source identification algorithm is tested on various types of data sets, and the numerical results show good agreement with EEGLAB, requiring minimal pre-processing of the acquired data.
Article
Clinical Neurology
Christoffer Hatlestad-Hall, Ricardo Bruna, Marte Roa Syvertsen, Aksel Erichsen, Vebjorn Andersson, Fabrizio Vecchio, Francesca Miraglia, Paolo M. Rossini, Hanna Renvall, Erik Tauboll, Fernando Maestu, Ira H. Haraldsen
Summary: This study investigated functional network alterations in focal epilepsy patients with good seizure control and high quality of life. Results showed significantly increased small world index in patients compared to controls, along with a shift towards greater alpha band hubness in two left-hemisphere regions. These findings suggest that functional network analysis could be clinically relevant for epilepsy.
CLINICAL NEUROPHYSIOLOGY
(2021)
Article
Clinical Neurology
Jacopo Lanzone, Lorenzo Ricci, Mario Tombini, Marilisa Boscarino, Oriano Mecarelli, Patrizia Pulitano, Vincenzo Di Lazzaro, Giovanni Assenza
Summary: This study examined qEEG changes in patients with epilepsy receiving Perampanel (PER) as add-on therapy, revealing increased theta power but no significant alteration in EEG connectivity. Compared to healthy controls, patients showed differences in beta power and connectivity in delta and theta ranges. Alpha power may serve as a predictor of treatment response.
CLINICAL NEUROPHYSIOLOGY
(2021)
Article
Neurosciences
Oshrit Arviv, Yuval Harpaz, Evgeny Tsizin, Tal Benoliel, Dana Ekstein, Mordekhay Medvedovsky
Summary: The aim of this study was to investigate whether a virtual MEG helmet (VMH) can improve the accuracy of source estimation. Controlled simulations were conducted and a series of VMHs were constructed using translations and rotations. The results showed that VMHs can significantly improve source estimation accuracy, especially at low noise levels. Additionally, tailoring the VMHs based on a priori information can further enhance accuracy, even for proximate locations.
FRONTIERS IN NEUROSCIENCE
(2022)
Review
Clinical Neurology
Benjamin C. Cox, Omar A. Danoun, Brian Nils Lundstrom, Terrence D. Lagerlund, Lily C. Wong-Kisiel, Benjamin H. Brinkmann
Summary: EEG source imaging is highly concordant with intracranial EEG in evaluating medically refractory focal epilepsy. Higher concordance is observed in temporal lobe discharges and ictal spiking. Source imaging shows improved concordance and reliability compared to epileptologist localization in a subset of high-density EEG patients.
BRAIN COMMUNICATIONS
(2021)
Article
Clinical Neurology
Graham W. Johnson, Derek J. Doss, Victoria L. Morgan, Danika L. Paulo, Leon Y. Cai, Jared S. Shless, Aarushi S. Negi, Abhijeet Gummadavelli, Hakmook Kang, Shilpa B. Reddy, Robert P. Naftel, Sarah K. Bick, Shawniqua Williams Roberson, Benoit M. Dawant, Mark T. Wallace, Dario J. Englot
Summary: Why are people with epilepsy not continuously having seizures? Johnson et al. use intracranial electrical recordings to analyse brain network interactions in people with epilepsy, and provide evidence that the seizure-onset network is actively suppressed by the rest of the brain during interictal states.
Article
Clinical Neurology
Rupesh Kumar Chikara, Saeed Jahromi, Eleonora Tamilia, Joseph R. Madsen, Steve M. Stufflebeam, Phillip L. Pearl, Christos Papadelis
Summary: The study aims to evaluate the diagnostic accuracy of electromagnetic source imaging (EMSI) in localizing spikes and predicting surgical outcome in children with drug resistant epilepsy (DRE) due to focal cortical dysplasia (FCD). We analyzed MEG and HD-EEG data from 23 children and compared the localization accuracy and predictive performance of EMSI, ESI, and MSI. The results showed that EMSI had superior localization accuracy and predictive performance compared to individual modalities.
CLINICAL NEUROPHYSIOLOGY
(2023)
Article
Clinical Neurology
Shuai Ye, Lin Yang, Yunfeng Lu, Michal T. Kucewicz, Benjamin Brinkmann, Cindy Nelson, Abbas Sohrabpour, Gregory A. Worrell, Bin He
Summary: Noninvasive ictal source imaging with high-density EEG recording can accurately localize seizure onset zone prior to surgical planning in focal epilepsy patients, providing valuable guidance for clinical decisions, especially in cases with complex interictal activity patterns.
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
Clinical Neurology
Michael Scherg, Reinhard Schulz, Patrick Berg, Jae-Hyun Cho, Harald Bornfleth, Mustafa A. Kural, Friedrich G. Woermann, Christian G. Bien, Sandor Beniczky
Summary: The study validated the accuracy of relative source power imaging of extratemporal interictal epileptiform discharges in patients, showing that RSP maps provide a faster, more intuitive, and more accurate source estimation compared to conventional methods. In surgical cases, the results demonstrated high sensitivity and moderate specificity, with no significant differences between the three source imaging methods.
CLINICAL NEUROPHYSIOLOGY
(2022)
Article
Clinical Neurology
Rui Li, Chris Plummer, Simon J. Vogrin, William P. Woods, Levin Kuhlmann, Ray Boston, David T. J. Liley, Mark J. Cook, David B. Grayden
Summary: A study aimed at localizing epileptic foci through automated methods showed success in localizing spikes in 12 out of 13 epilepsy surgery patients. The research demonstrates good performance of automated beamforming in predicting postoperative seizure freedom for patients.
CLINICAL NEUROPHYSIOLOGY
(2021)
Article
Behavioral Sciences
Oshi Swarup, Alexandra Waxmann, Jocelyn Chu, Simon Vogrin, Alan Lai, Joshua Laing, James Barker, Linda Seiderer, Sophia Ignatiadis, Chris Plummer, Ross Carne, Udaya Seneviratne, Mark Cook, Michael Murphy, Wendyl D'Souza
Summary: Long-term outcomes of patients undergoing intracranial EEG (iEEG) evaluation for epilepsy surgery at St. Vincent's Hospital, Melbourne showed that most patients achieved seizure freedom and good quality of life at last follow-up. While some patients may experience depressive episodes, overall mood was not significantly associated with seizure freedom.
EPILEPSY & BEHAVIOR
(2021)
Review
Radiology, Nuclear Medicine & Medical Imaging
Yi-En Quek, Yi Leng Fung, Mike W-L Cheung, Simon J. Vogrin, Steven J. Collins, Stephen C. Bowden
Summary: The study compared automated methods and manual segmentation in measuring regional brain volumes on MRI across healthy controls, patients with mild cognitive impairment, and patients with dementia due to AD. The results showed that automated methods are generally comparable to manual segmentation for measuring hippocampal, lateral ventricle, and parahippocampal gyrus volumes, but with substantial uncontrolled variance. Therefore, caution should be used when utilizing automated methods in measuring these regions in AD patients.
JOURNAL OF MAGNETIC RESONANCE IMAGING
(2022)
Article
Multidisciplinary Sciences
Miao Cao, Daniel Galvis, Simon J. Vogrin, William P. Woods, Sara Vogrin, Fan Wang, Wessel Woldman, John R. Terry, Andre Peterson, Chris Plummer, Mark J. Cook
Summary: Dynamic network models provide insights into brain networks affected by epileptic seizures. In this study, the authors derive ViEEG (virtual intracranial EEG) from non-invasive MEG recordings to identify brain areas involved in seizure generation in patients with epilepsy. The proposed ViEEG approach combines non-invasive MEG, dynamical network models, and a virtual resection technique, and shows promise in preserving critical temporospatial characteristics for identifying brain areas involved in seizure generation. The non-invasive ViEEG approach may have advantages over invasive iEEG and could potentially be used in surgical management of epilepsy.
NATURE COMMUNICATIONS
(2022)
Review
Clinical Neurology
Miao Cao, Simon J. Vogrin, Andre D. H. Peterson, William Woods, Mark J. Cook, Chris Plummer
Summary: More informative quantitative techniques are urgently needed to assess strategies for epilepsy surgery objectively and non-invasively. Recent advances in network analysis and dynamical network modeling provide a novel and data-driven approach for a more objective assessment of the epileptogenic zone (EZ). However, further research is required to validate the effectiveness of these methods when applied to non-invasive neuroimaging data and neurophysiological data.
FRONTIERS IN NEUROLOGY
(2022)
Article
Clinical Neurology
James Allebone, Sarah J. Wilson, Richard C. J. Bradlow, Jerome Maller, Terry O' Brien, Saul A. Mullen, Mark Cook, Sophia J. Adams, Simon Vogrin, David N. Vaughan, Alan Connelly, Patrick Kwan, Samuel F. Berkovic, Wendyl J. DSouza, Graeme Jackson, Dennis Velakoulis, Richard A. Kanaan
Summary: The study explores the cortical morphological associations of psychoses of epilepsy. The results show cortical thickening in psychoses of epilepsy, mainly occurring in nodes of the cognitive control and default mode networks. Patients with interictal psychosis also displayed cortical thickening in the temporal and occipital regions. The findings provide new insights into the cortical morphology of psychoses of epilepsy.
SEIZURE-EUROPEAN JOURNAL OF EPILEPSY
(2022)
Article
Behavioral Sciences
Ewan S. Nurse, Linda J. Dalic, Shannon Clarke, Mark Cook, John Archer
Summary: This study investigates a deep learning model for the detection of generalized paroxysmal fast activity (GPFA) events and estimation of their overall burden from scalp EEG. The model achieved a high correlation coefficient with manual estimates and showed good detection sensitivity. There was no significant difference found in patients with different treatments.
EPILEPSY & BEHAVIOR
(2023)
Article
Engineering, Biomedical
Kevin Meng, Farhad Goodarzy, EuiYoung Kim, Ye Jin Park, June Sic Kim, Mark J. Cook, Chun Kee Chung, David B. Grayden
Summary: This study aimed to demonstrate the feasibility of synthesizing artificial speech sounds from human cortical surface recordings during silent speech production. Ten participants with intractable epilepsy were temporarily implanted with intracranial electrode arrays. A decoding model predicted audible outputs directly from patient-specific neural feature inputs, and the synthesized sounds were objectively and subjectively assessed.
JOURNAL OF NEURAL ENGINEERING
(2023)
Article
Clinical Neurology
Gabrielle M. Schroeder, Philippa J. Karoly, Matias Maturana, Mariella Panagiotopoulou, Peter N. Taylor, Mark J. Cook, Yujiang Wang
Summary: In this observational study, researchers analyzed the variability of seizures in patients with chronic intracranial EEG recordings and found that the variability is modulated by different factors on multiple timescales. These findings have important implications for the treatment of epilepsy.
BRAIN COMMUNICATIONS
(2023)
Article
Engineering, Biomedical
Wenjuan Xiong, Ewan S. Nurse, Elisabeth Lambert, Mark J. Cook, Tatiana Kameneva
Summary: This study investigates the use of machine learning techniques for classification of psychogenic non-epileptic seizures (PNES) and epileptic seizures (ES) based on electroencephalography (EEG) and electrocardiography (ECG) data. The highest classification accuracy achieved was 87.83%, using the 15-0 minute preictal period of EEG and ECG data. Combining ECG data with EEG data improved the classification accuracy from 86.37% to 87.83%.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2023)
Proceedings Paper
Acoustics
Kevin Meng, Seo-Hyun Lee, Farhad Goodarzy, Simon Vogrin, Mark J. Cook, Seong-Whan Lee, David B. Grayden
Summary: We developed a voice-based cursor control task and collected intracranial neural data during isolated utterances of phonemes. Our findings provide evidence for tracking voice activity and classifying individual utterances using intracranial electrodes, which is important for the development of speech brain-computer interfaces.
Proceedings Paper
Computer Science, Artificial Intelligence
Kevin Meng, EuiYoung Kim, Simon Vogrin, Mark J. Cook, Farhad Goodarzy, David B. Grayden, Chun Kee Chung
Summary: This study introduces a BCI speech synthesis system that can be trained with limited overt speech to generate continuous audio outputs for subsequent speech imagery tasks. The feasibility of the system is confirmed through simulations using recorded datasets from epilepsy patients, showing that it can be used to synthesize different types of speech under specific clinical constraints.
10TH INTERNATIONAL WINTER CONFERENCE ON BRAIN-COMPUTER INTERFACE (BCI2022)
(2022)
Article
Clinical Neurology
Jaakko Vallinoja, Timo Nurmi, Julia Jaatela, Vincent Wens, Mathieu Bourguignon, Helena Maenpaa, Harri Piitulainen
Summary: The study aimed to assess the effects of lesions related to spastic diplegic cerebral palsy on functional connectivity. Using multiple imaging modalities, the researchers found enhanced functional connectivity in the sensorimotor network of individuals with spastic diplegic cerebral palsy, which was not correlated with hand coordination performance.
CLINICAL NEUROPHYSIOLOGY
(2024)
Article
Clinical Neurology
Francesca Ginatempo, Nicola Loi, John C. Rothwell, Franca Deriu
Summary: This study comprehensively investigated sensorimotor integration in the cranial-cervical muscles of healthy adults and found that the integration of sensory inputs with motor output is profoundly influenced by the type of sensory afferent involved and the functional role played by the target muscle.
CLINICAL NEUROPHYSIOLOGY
(2024)
