2,836 results on '"Devinsky, Orrin"'
Search Results
2. The Temporal Structure of Language Processing in the Human Brain Corresponds to The Layered Hierarchy of Deep Language Models
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Goldstein, Ariel, Ham, Eric, Schain, Mariano, Nastase, Samuel, Zada, Zaid, Dabush, Avigail, Aubrey, Bobbi, Gazula, Harshvardhan, Feder, Amir, Doyle, Werner K, Devore, Sasha, Dugan, Patricia, Friedman, Daniel, Reichart, Roi, Brenner, Michael, Hassidim, Avinatan, Devinsky, Orrin, Flinker, Adeen, Levy, Omer, and Hasson, Uri
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Computer Science - Computation and Language ,Computer Science - Artificial Intelligence ,Computer Science - Machine Learning ,Quantitative Biology - Neurons and Cognition - Abstract
Deep Language Models (DLMs) provide a novel computational paradigm for understanding the mechanisms of natural language processing in the human brain. Unlike traditional psycholinguistic models, DLMs use layered sequences of continuous numerical vectors to represent words and context, allowing a plethora of emerging applications such as human-like text generation. In this paper we show evidence that the layered hierarchy of DLMs may be used to model the temporal dynamics of language comprehension in the brain by demonstrating a strong correlation between DLM layer depth and the time at which layers are most predictive of the human brain. Our ability to temporally resolve individual layers benefits from our use of electrocorticography (ECoG) data, which has a much higher temporal resolution than noninvasive methods like fMRI. Using ECoG, we record neural activity from participants listening to a 30-minute narrative while also feeding the same narrative to a high-performing DLM (GPT2-XL). We then extract contextual embeddings from the different layers of the DLM and use linear encoding models to predict neural activity. We first focus on the Inferior Frontal Gyrus (IFG, or Broca's area) and then extend our model to track the increasing temporal receptive window along the linguistic processing hierarchy from auditory to syntactic and semantic areas. Our results reveal a connection between human language processing and DLMs, with the DLM's layer-by-layer accumulation of contextual information mirroring the timing of neural activity in high-order language areas.
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- 2023
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3. The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)
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Poldrack, Russell A., Markiewicz, Christopher J., Appelhoff, Stefan, Ashar, Yoni K., Auer, Tibor, Baillet, Sylvain, Bansal, Shashank, Beltrachini, Leandro, Benar, Christian G., Bertazzoli, Giacomo, Bhogawar, Suyash, Blair, Ross W., Bortoletto, Marta, Boudreau, Mathieu, Brooks, Teon L., Calhoun, Vince D., Castelli, Filippo Maria, Clement, Patricia, Cohen, Alexander L, Cohen-Adad, Julien, D'Ambrosio, Sasha, de Hollander, Gilles, de la iglesia-Vayá, María, de la Vega, Alejandro, Delorme, Arnaud, Devinsky, Orrin, Draschkow, Dejan, Duff, Eugene Paul, DuPre, Elizabeth, Earl, Eric, Esteban, Oscar, Feingold, Franklin W., Flandin, Guillaume, galassi, anthony, Gallitto, Giuseppe, Ganz, Melanie, Gau, Rémi, Gholam, James, Ghosh, Satrajit S., Giacomel, Alessio, Gillman, Ashley G, Gleeson, Padraig, Gramfort, Alexandre, Guay, Samuel, Guidali, Giacomo, Halchenko, Yaroslav O., Handwerker, Daniel A., Hardcastle, Nell, Herholz, Peer, Hermes, Dora, Honey, Christopher J., Innis, Robert B., Ioanas, Horea-Ioan, Jahn, Andrew, Karakuzu, Agah, Keator, David B., Kiar, Gregory, Kincses, Balint, Laird, Angela R., Lau, Jonathan C., Lazari, Alberto, Legarreta, Jon Haitz, Li, Adam, Li, Xiangrui, Love, Bradley C., Lu, Hanzhang, Maumet, Camille, Mazzamuto, Giacomo, Meisler, Steven L., Mikkelsen, Mark, Mutsaerts, Henk, Nichols, Thomas E., Nikolaidis, Aki, Nilsonne, Gustav, Niso, Guiomar, Norgaard, Martin, Okell, Thomas W, Oostenveld, Robert, Ort, Eduard, Park, Patrick J., Pawlik, Mateusz, Pernet, Cyril R., Pestilli, Franco, Petr, Jan, Phillips, Christophe, Poline, Jean-Baptiste, Pollonini, Luca, Raamana, Pradeep Reddy, Ritter, Petra, Rizzo, Gaia, Robbins, Kay A., Rockhill, Alexander P., Rogers, Christine, Rokem, Ariel, Rorden, Chris, Routier, Alexandre, Saborit-Torres, Jose Manuel, Salo, Taylor, Schirner, Michael, Smith, Robert E., Spisak, Tamas, Sprenger, Julia, Swann, Nicole C., Szinte, Martin, Takerkart, Sylvain, Thirion, Bertrand, Thomas, Adam G., Torabian, Sajjad, Varoquaux, Gael, Voytek, Bradley, Welzel, Julius, Wilson, Martin, Yarkoni, Tal, and Gorgolewski, Krzysztof J.
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Quantitative Biology - Other Quantitative Biology - Abstract
The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.
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- 2023
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4. Applying an evolutionary mismatch framework to understand disease susceptibility.
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Lea, Amanda, Clark, Andrew, Dahl, Andrew, Devinsky, Orrin, Garcia, Angela, Golden, Christopher, Kamau, Joseph, Kraft, Thomas, Lim, Yvonne, Martins, Dino, Mogoi, Donald, Pajukanta, Päivi, Perry, George, Pontzer, Herman, Trumble, Benjamin, Urlacher, Samuel, Venkataraman, Vivek, Wallace, Ian, Lieberman, Daniel, Ayroles, Julien, and Gurven, Michael
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Humans ,Disease Susceptibility ,Diabetes Mellitus ,Type 2 ,Biological Evolution ,Cardiovascular Diseases ,Genomics - Abstract
Noncommunicable diseases (NCDs) are on the rise worldwide. Obesity, cardiovascular disease, and type 2 diabetes are among a long list of lifestyle diseases that were rare throughout human history but are now common. The evolutionary mismatch hypothesis posits that humans evolved in environments that radically differ from those we currently experience; consequently, traits that were once advantageous may now be mismatched and disease causing. At the genetic level, this hypothesis predicts that loci with a history of selection will exhibit genotype by environment (GxE) interactions, with different health effects in ancestral versus modern environments. To identify such loci, we advocate for combining genomic tools in partnership with subsistence-level groups experiencing rapid lifestyle change. In these populations, comparisons of individuals falling on opposite extremes of the matched to mismatched spectrum are uniquely possible. More broadly, the work we propose will inform our understanding of environmental and genetic risk factors for NCDs across diverse ancestries and cultures.
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- 2023
5. Author Correction: Alignment of brain embeddings and artificial contextual embeddings in natural language points to common geometric patterns
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Goldstein, Ariel, Grinstein-Dabush, Avigail, Schain, Mariano, Wang, Haocheng, Hong, Zhuoqiao, Aubrey, Bobbi, Nastase, Samuel A., Zada, Zaid, Ham, Eric, Feder, Amir, Gazula, Harshvardhan, Buchnik, Eliav, Doyle, Werner, Devore, Sasha, Dugan, Patricia, Reichart, Roi, Friedman, Daniel, Brenner, Michael, Hassidim, Avinatan, Devinsky, Orrin, Flinker, Adeen, and Hasson, Uri
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- 2024
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6. Deoxyhypusine synthase deficiency syndrome zebrafish model: aberrant morphology, epileptiform activity, and reduced arborization of inhibitory interneurons
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Shojaeinia, Elham, Mastracci, Teresa L., Soliman, Remon, Devinsky, Orrin, Esguerra, Camila V., and Crawford, Alexander D.
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- 2024
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7. Alignment of brain embeddings and artificial contextual embeddings in natural language points to common geometric patterns
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Goldstein, Ariel, Grinstein-Dabush, Avigail, Schain, Mariano, Wang, Haocheng, Hong, Zhuoqiao, Aubrey, Bobbi, Nastase, Samuel A., Zada, Zaid, Ham, Eric, Feder, Amir, Gazula, Harshvardhan, Buchnik, Eliav, Doyle, Werner, Devore, Sasha, Dugan, Patricia, Reichart, Roi, Friedman, Daniel, Brenner, Michael, Hassidim, Avinatan, Devinsky, Orrin, Flinker, Adeen, and Hasson, Uri
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- 2024
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8. A neural speech decoding framework leveraging deep learning and speech synthesis
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Chen, Xupeng, Wang, Ran, Khalilian-Gourtani, Amirhossein, Yu, Leyao, Dugan, Patricia, Friedman, Daniel, Doyle, Werner, Devinsky, Orrin, Wang, Yao, and Flinker, Adeen
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- 2024
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9. Similar brain proteomic signatures in Alzheimer’s disease and epilepsy
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Leitner, Dominique, Pires, Geoffrey, Kavanagh, Tomas, Kanshin, Evgeny, Askenazi, Manor, Ueberheide, Beatrix, Devinsky, Orrin, Wisniewski, Thomas, and Drummond, Eleanor
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- 2024
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10. Evolutionary mismatch and the role of GxE interactions in human disease
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Lea, Amanda J., Clark, Andrew G., Dahl, Andrew W., Devinsky, Orrin, Garcia, Angela R., Golden, Christopher D., Kamau, Joseph, Kraft, Thomas S., Lim, Yvonne A. L., Martins, Dino, Mogoi, Donald, Pajukanta, Paivi, Perry, George, Pontzer, Herman, Trumble, Benjamin C., Urlacher, Samuel S., Venkataraman, Vivek V., Wallace, Ian J., Gurven, Michael, Lieberman, Daniel, and Ayroles, Julien F.
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Quantitative Biology - Populations and Evolution ,Quantitative Biology - Genomics - Abstract
Globally, we are witnessing the rise of complex, non-communicable diseases (NCDs) related to changes in our daily environments. Obesity, asthma, cardiovascular disease, and type 2 diabetes are part of a long list of "lifestyle" diseases that were rare throughout human history but are now common. A key idea from anthropology and evolutionary biology--the evolutionary mismatch hypothesis--seeks to explain this phenomenon. It posits that humans evolved in environments that radically differ from the ones experienced by most people today, and thus traits that were advantageous in past environments may now be "mismatched" and disease-causing. This hypothesis is, at its core, a genetic one: it predicts that loci with a history of selection will exhibit "genotype by environment" (GxE) interactions and have differential health effects in ancestral versus modern environments. Here, we discuss how this concept could be leveraged to uncover the genetic architecture of NCDs in a principled way. Specifically, we advocate for partnering with small-scale, subsistence-level groups that are currently transitioning from environments that are arguably more "matched" with their recent evolutionary history to those that are more "mismatched". These populations provide diverse genetic backgrounds as well as the needed levels and types of environmental variation necessary for mapping GxE interactions in an explicit mismatch framework. Such work would make important contributions to our understanding of environmental and genetic risk factors for NCDs across diverse ancestries and sociocultural contexts.
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- 2023
11. Mood and Anxiety Disorders and Suicidality in Patients With Newly Diagnosed Focal Epilepsy: An Analysis of a Complex Comorbidity.
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Kanner, Andres, Saporta, Anita, Kim, Dong, Barry, John, Altalib, Hamada, Omotola, Hope, Jette, Nathalie, OBrien, Terence, Nadkarni, Siddhartha, Winawer, Melodie, Sperling, Michael, French, Jacqueline, Abou-Khalil, Bassel, Alldredge, Brian, Bebin, Martina, Cascino, Gregory, Cole, Andrew, Cook, Mark, Detyniecki, Kamil, Devinsky, Orrin, Dlugos, Dennis, Faught, Edward, Ficker, David, Fields, Madeline, Gidal, Barry, Gelfand, Michael, Glynn, Simon, Halford, Jonathan, Haut, Sheryl, Hegde, Manu, Holmes, Manisha, Kalviainen, Reetta, Kang, Joon, Klein, Pavel, Knowlton, Robert, Krishnamurthy, Kaarkuzhali, Kuzniecky, Ruben, Kwan, Patrick, Lowenstein, Daniel, Marcuse, Lara, Meador, Kimford, Mintzer, Scott, Pardoe, Heath, Park, Kristen, Penovich, Patricia, Singh, Rani, Somerville, Ernest, Szabo, Charles, Szaflarski, Jerzy, Lin Thio, K, Trinka, Eugen, and Burneo, Jorge
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Adult ,Humans ,Suicidal Ideation ,Anxiety Disorders ,Depressive Disorder ,Major ,Suicide ,Comorbidity ,Epilepsies ,Partial ,Risk Factors - Abstract
BACKGROUND AND OBJECTIVES: Mood, anxiety disorders, and suicidality are more frequent in people with epilepsy than in the general population. Yet, their prevalence and the types of mood and anxiety disorders associated with suicidality at the time of the epilepsy diagnosis are not established. We sought to answer these questions in patients with newly diagnosed focal epilepsy and to assess their association with suicidal ideation and attempts. METHODS: The data were derived from the Human Epilepsy Project study. A total of 347 consecutive adults aged 18-60 years with newly diagnosed focal epilepsy were enrolled within 4 months of starting treatment. The types of mood and anxiety disorders were identified with the Mini International Neuropsychiatric Interview, whereas suicidal ideation (lifetime, current, active, and passive) and suicidal attempts (lifetime and current) were established with the Columbia Suicidality Severity Rating Scale (CSSRS). Statistical analyses included the t test, χ2 statistics, and logistic regression analyses. RESULTS: A total of 151 (43.5%) patients had a psychiatric diagnosis; 134 (38.6%) met the criteria for a mood and/or anxiety disorder, and 75 (21.6%) reported suicidal ideation with or without attempts. Mood (23.6%) and anxiety (27.4%) disorders had comparable prevalence rates, whereas both disorders occurred together in 43 patients (12.4%). Major depressive disorders (MDDs) had a slightly higher prevalence than bipolar disorders (BPDs) (9.5% vs 6.9%, respectively). Explanatory variables of suicidality included MDD, BPD, panic disorders, and agoraphobia, with BPD and panic disorders being the strongest variables, particularly for active suicidal ideation and suicidal attempts. DISCUSSION: In patients with newly diagnosed focal epilepsy, the prevalence of mood, anxiety disorders, and suicidality is higher than in the general population and comparable to those of patients with established epilepsy. Their recognition at the time of the initial epilepsy evaluation is of the essence.
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- 2023
12. Comprehensive multi-omic profiling of somatic mutations in malformations of cortical development
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Chung, Changuk, Yang, Xiaoxu, Bae, Taejeong, Vong, Keng Ioi, Mittal, Swapnil, Donkels, Catharina, Westley Phillips, H, Li, Zhen, Marsh, Ashley PL, Breuss, Martin W, Ball, Laurel L, Garcia, Camila Araújo Bernardino, George, Renee D, Gu, Jing, Xu, Mingchu, Barrows, Chelsea, James, Kiely N, Stanley, Valentina, Nidhiry, Anna S, Khoury, Sami, Howe, Gabrielle, Riley, Emily, Xu, Xin, Copeland, Brett, Wang, Yifan, Kim, Se Hoon, Kang, Hoon-Chul, Schulze-Bonhage, Andreas, Haas, Carola A, Urbach, Horst, Prinz, Marco, Limbrick, David D, Gurnett, Christina A, Smyth, Matthew D, Sattar, Shifteh, Nespeca, Mark, Gonda, David D, Imai, Katsumi, Takahashi, Yukitoshi, Chen, Hsin-Hung, Tsai, Jin-Wu, Conti, Valerio, Guerrini, Renzo, Devinsky, Orrin, Silva, Wilson A, Machado, Helio R, Mathern, Gary W, Abyzov, Alexej, Baldassari, Sara, Baulac, Stéphanie, and Gleeson, Joseph G
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Genetics ,Pediatric ,Neurodegenerative ,Epilepsy ,Neurosciences ,Human Genome ,Brain Disorders ,Biotechnology ,Clinical Research ,Stem Cell Research ,Congenital Structural Anomalies ,Underpinning research ,1.1 Normal biological development and functioning ,Aetiology ,2.1 Biological and endogenous factors ,Neurological ,Humans ,Multiomics ,Brain ,Mutation ,Malformations of Cortical Development ,Focal Cortical Dysplasia Neurogenetics Consortium ,Brain Somatic Mosaicism Network ,Biological Sciences ,Medical and Health Sciences ,Developmental Biology - Abstract
Malformations of cortical development (MCD) are neurological conditions involving focal disruptions of cortical architecture and cellular organization that arise during embryogenesis, largely from somatic mosaic mutations, and cause intractable epilepsy. Identifying the genetic causes of MCD has been a challenge, as mutations remain at low allelic fractions in brain tissue resected to treat condition-related epilepsy. Here we report a genetic landscape from 283 brain resections, identifying 69 mutated genes through intensive profiling of somatic mutations, combining whole-exome and targeted-amplicon sequencing with functional validation including in utero electroporation of mice and single-nucleus RNA sequencing. Genotype-phenotype correlation analysis elucidated specific MCD gene sets associated with distinct pathophysiological and clinical phenotypes. The unique single-cell level spatiotemporal expression patterns of mutated genes in control and patient brains indicate critical roles in excitatory neurogenic pools during brain development and in promoting neuronal hyperexcitability after birth.
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- 2023
13. Event‐based modeling in temporal lobe epilepsy demonstrates progressive atrophy from cross‐sectional data
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Lopez, Seymour M, Aksman, Leon M, Oxtoby, Neil P, Vos, Sjoerd B, Rao, Jun, Kaestner, Erik, Alhusaini, Saud, Alvim, Marina, Bender, Benjamin, Bernasconi, Andrea, Bernasconi, Neda, Bernhardt, Boris, Bonilha, Leonardo, Caciagli, Lorenzo, Caldairou, Benoit, Caligiuri, Maria Eugenia, Calvet, Angels, Cendes, Fernando, Concha, Luis, Conde‐Blanco, Estefania, Davoodi‐Bojd, Esmaeil, de Bézenac, Christophe, Delanty, Norman, Desmond, Patricia M, Devinsky, Orrin, Domin, Martin, Duncan, John S, Focke, Niels K, Foley, Sonya, Fortunato, Francesco, Galovic, Marian, Gambardella, Antonio, Gleichgerrcht, Ezequiel, Guerrini, Renzo, Hamandi, Khalid, Ives‐Deliperi, Victoria, Jackson, Graeme D, Jahanshad, Neda, Keller, Simon S, Kochunov, Peter, Kotikalapudi, Raviteja, Kreilkamp, Barbara AK, Labate, Angelo, Larivière, Sara, Lenge, Matteo, Lui, Elaine, Malpas, Charles, Martin, Pascal, Mascalchi, Mario, Medland, Sarah E, Meletti, Stefano, Morita‐Sherman, Marcia E, Owen, Thomas W, Richardson, Mark, Riva, Antonella, Rüber, Theodor, Sinclair, Ben, Soltanian‐Zadeh, Hamid, Stein, Dan J, Striano, Pasquale, Taylor, Peter N, Thomopoulos, Sophia I, Thompson, Paul M, Tondelli, Manuela, Vaudano, Anna Elisabetta, Vivash, Lucy, Wang, Yujiang, Weber, Bernd, Whelan, Christopher D, Wiest, Roland, Winston, Gavin P, Yasuda, Clarissa Lin, McDonald, Carrie R, Alexander, Daniel C, Sisodiya, Sanjay M, Altmann, Andre, Bargalló, Núria, Bartolini, Emanuele, O’Brien, Terence J, and Thomas, Rhys H
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Brain Disorders ,Epilepsy ,Neurodegenerative ,Neurosciences ,Clinical Research ,Biomedical Imaging ,Aetiology ,2.1 Biological and endogenous factors ,Neurological ,Good Health and Well Being ,Atrophy ,Biomarkers ,Cross-Sectional Studies ,Epilepsy ,Temporal Lobe ,Hippocampus ,Humans ,Magnetic Resonance Imaging ,Sclerosis ,disease progression ,duration of illness ,event-based model ,MTLE ,patient staging ,ENIGMA-Epilepsy Working Group ,Clinical Sciences ,Neurology & Neurosurgery - Abstract
ObjectiveRecent work has shown that people with common epilepsies have characteristic patterns of cortical thinning, and that these changes may be progressive over time. Leveraging a large multicenter cross-sectional cohort, we investigated whether regional morphometric changes occur in a sequential manner, and whether these changes in people with mesial temporal lobe epilepsy and hippocampal sclerosis (MTLE-HS) correlate with clinical features.MethodsWe extracted regional measures of cortical thickness, surface area, and subcortical brain volumes from T1-weighted (T1W) magnetic resonance imaging (MRI) scans collected by the ENIGMA-Epilepsy consortium, comprising 804 people with MTLE-HS and 1625 healthy controls from 25 centers. Features with a moderate case-control effect size (Cohen d ≥ .5) were used to train an event-based model (EBM), which estimates a sequence of disease-specific biomarker changes from cross-sectional data and assigns a biomarker-based fine-grained disease stage to individual patients. We tested for associations between EBM disease stage and duration of epilepsy, age at onset, and antiseizure medicine (ASM) resistance.ResultsIn MTLE-HS, decrease in ipsilateral hippocampal volume along with increased asymmetry in hippocampal volume was followed by reduced thickness in neocortical regions, reduction in ipsilateral thalamus volume, and finally, increase in ipsilateral lateral ventricle volume. EBM stage was correlated with duration of illness (Spearman ρ = .293, p = 7.03 × 10-16 ), age at onset (ρ = -.18, p = 9.82 × 10-7 ), and ASM resistance (area under the curve = .59, p = .043, Mann-Whitney U test). However, associations were driven by cases assigned to EBM Stage 0, which represents MTLE-HS with mild or nondetectable abnormality on T1W MRI.SignificanceFrom cross-sectional MRI, we reconstructed a disease progression model that highlights a sequence of MRI changes that aligns with previous longitudinal studies. This model could be used to stage MTLE-HS subjects in other cohorts and help establish connections between imaging-based progression staging and clinical features.
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- 2022
14. Do germline genetic variants influence surgical outcomes in drug-resistant epilepsy?
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Marques, Paula, Moloney, Patrick B., Ji, Caihong, Zulfiqar Ali, Quratulain, Ramesh, Archana, Goldstein, David B., Barboza, Karen, Chandran, Ilakkiah, Rong, Marlene, Selvarajah, Arunan, Qaiser, Farah, Lira, Victor S.T., Valiante, Taufik A., Bazil, Carl W., Choi, Hyunmi, Devinsky, Orrin, Depondt, Chantal, O’Brien, Terence, Perucca, Piero, Sen, Arjune, Dugan, Patricia, Sands, Tristan T., Delanty, Norman, and Andrade, Danielle M.
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- 2024
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15. A shared model-based linguistic space for transmitting our thoughts from brain to brain in natural conversations
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Zada, Zaid, Goldstein, Ariel, Michelmann, Sebastian, Simony, Erez, Price, Amy, Hasenfratz, Liat, Barham, Emily, Zadbood, Asieh, Doyle, Werner, Friedman, Daniel, Dugan, Patricia, Melloni, Lucia, Devore, Sasha, Flinker, Adeen, Devinsky, Orrin, Nastase, Samuel A., and Hasson, Uri
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- 2024
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16. Epilepsy as a Novel Phenotype of BPTF-Related Disorders
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Ferretti, Alessandro, Furlan, Margherita, Glinton, Kevin E., Fenger, Christina D., Boschann, Felix, Amlie-Wolf, Louise, Zeidler, Shimriet, Moretti, Raffaella, Stoltenburg, Corinna, Tarquinio, Daniel C., Furia, Francesca, Parisi, Pasquale, Rubboli, Guido, Devinsky, Orrin, Mignot, Cyril, Gripp, Karen W., Møller, Rikke S., Yang, Yaping, Stankiewicz, Pawel, and Gardella, Elena
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- 2024
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17. Topographic divergence of atypical cortical asymmetry and atrophy patterns in temporal lobe epilepsy
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Park, Bo-yong, Larivière, Sara, Rodríguez-Cruces, Raul, Royer, Jessica, Tavakol, Shahin, Wang, Yezhou, Caciagli, Lorenzo, Caligiuri, Maria Eugenia, Gambardella, Antonio, Concha, Luis, Keller, Simon S, Cendes, Fernando, Alvim, Marina KM, Yasuda, Clarissa, Bonilha, Leonardo, Gleichgerrcht, Ezequiel, Focke, Niels K, Kreilkamp, Barbara AK, Domin, Martin, von Podewils, Felix, Langner, Soenke, Rummel, Christian, Rebsamen, Michael, Wiest, Roland, Martin, Pascal, Kotikalapudi, Raviteja, Bender, Benjamin, O’Brien, Terence J, Law, Meng, Sinclair, Benjamin, Vivash, Lucy, Kwan, Patrick, Desmond, Patricia M, Malpas, Charles B, Lui, Elaine, Alhusaini, Saud, Doherty, Colin P, Cavalleri, Gianpiero L, Delanty, Norman, Kälviäinen, Reetta, Jackson, Graeme D, Kowalczyk, Magdalena, Mascalchi, Mario, Semmelroch, Mira, Thomas, Rhys H, Soltanian-Zadeh, Hamid, Davoodi-Bojd, Esmaeil, Zhang, Junsong, Lenge, Matteo, Guerrini, Renzo, Bartolini, Emanuele, Hamandi, Khalid, Foley, Sonya, Weber, Bernd, Depondt, Chantal, Absil, Julie, Carr, Sarah JA, Abela, Eugenio, Richardson, Mark P, Devinsky, Orrin, Severino, Mariasavina, Striano, Pasquale, Parodi, Costanza, Tortora, Domenico, Hatton, Sean N, Vos, Sjoerd B, Duncan, John S, Galovic, Marian, Whelan, Christopher D, Bargalló, Núria, Pariente, Jose, Conde-Blanco, Estefania, Vaudano, Anna Elisabetta, Tondelli, Manuela, Meletti, Stefano, Kong, Xiang‐Zhen, Francks, Clyde, Fisher, Simon E, Caldairou, Benoit, Ryten, Mina, Labate, Angelo, Sisodiya, Sanjay M, Thompson, Paul M, McDonald, Carrie R, Bernasconi, Andrea, Bernasconi, Neda, and Bernhardt, Boris C
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Epilepsy ,Neurodegenerative ,Clinical Research ,Brain Disorders ,Neurosciences ,Aetiology ,2.1 Biological and endogenous factors ,Neurological ,Adult ,Atrophy ,Connectome ,Epilepsy ,Temporal Lobe ,Hippocampus ,Humans ,Magnetic Resonance Imaging ,temporal lobe epilepsy ,asymmetry ,cortical thickness ,multi-site ,gradients ,Medical and Health Sciences ,Psychology and Cognitive Sciences ,Neurology & Neurosurgery - Abstract
Temporal lobe epilepsy, a common drug-resistant epilepsy in adults, is primarily a limbic network disorder associated with predominant unilateral hippocampal pathology. Structural MRI has provided an in vivo window into whole-brain grey matter structural alterations in temporal lobe epilepsy relative to controls, by either mapping (i) atypical inter-hemispheric asymmetry; or (ii) regional atrophy. However, similarities and differences of both atypical asymmetry and regional atrophy measures have not been systematically investigated. Here, we addressed this gap using the multisite ENIGMA-Epilepsy dataset comprising MRI brain morphological measures in 732 temporal lobe epilepsy patients and 1418 healthy controls. We compared spatial distributions of grey matter asymmetry and atrophy in temporal lobe epilepsy, contextualized their topographies relative to spatial gradients in cortical microstructure and functional connectivity calculated using 207 healthy controls obtained from Human Connectome Project and an independent dataset containing 23 temporal lobe epilepsy patients and 53 healthy controls and examined clinical associations using machine learning. We identified a marked divergence in the spatial distribution of atypical inter-hemispheric asymmetry and regional atrophy mapping. The former revealed a temporo-limbic disease signature while the latter showed diffuse and bilateral patterns. Our findings were robust across individual sites and patients. Cortical atrophy was significantly correlated with disease duration and age at seizure onset, while degrees of asymmetry did not show a significant relationship to these clinical variables. Our findings highlight that the mapping of atypical inter-hemispheric asymmetry and regional atrophy tap into two complementary aspects of temporal lobe epilepsy-related pathology, with the former revealing primary substrates in ipsilateral limbic circuits and the latter capturing bilateral disease effects. These findings refine our notion of the neuropathology of temporal lobe epilepsy and may inform future discovery and validation of complementary MRI biomarkers in temporal lobe epilepsy.
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- 2022
18. Placebo response in patients with Dravet syndrome: Post-hoc analysis of two clinical trials
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Devinsky, Orrin, Hyland, Kerry, Loftus, Rachael, Nortvedt, Charlotte, and Nabbout, Rima
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- 2024
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19. Dravet syndrome seizure frequency and clustering: Placebo-treated patients in clinical trials
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Nabbout, Rima, Hyland, Kerry, Loftus, Rachael, Nortvedt, Charlotte, and Devinsky, Orrin
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- 2024
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20. Novelty preference assessed by eye tracking: A sensitive measure of impaired recognition memory in epilepsy
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Leeman-Markowski, Beth A., Martin, Samantha P., Hardstone, Richard, Tam, Danny M., Devinsky, Orrin, and Meador, Kimford J.
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- 2024
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21. Closed-loop brain stimulation augments fear extinction in male rats
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Sierra, Rodrigo Ordoñez, Pedraza, Lizeth Katherine, Barcsai, Lívia, Pejin, Andrea, Li, Qun, Kozák, Gábor, Takeuchi, Yuichi, Nagy, Anett J., Lőrincz, Magor L., Devinsky, Orrin, Buzsáki, György, and Berényi, Antal
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- 2023
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22. Expanding genotype–phenotype correlations in FOXG1 syndrome: results from a patient registry
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Brimble, Elise, Reyes, Kathryn G., Kuhathaas, Kopika, Devinsky, Orrin, Ruzhnikov, Maura R. Z., Ortiz-Gonzalez, Xilma R., Scheffer, Ingrid, Bahi-Buisson, Nadia, and Olson, Heather
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- 2023
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23. Acquired Pedophilia: international Delphi-method-based consensus guidelines
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Scarpazza, Cristina, Costa, Cristiano, Battaglia, Umberto, Berryessa, Colleen, Bianchetti, Maria Lucia, Caggiu, Ilenia, Devinsky, Orrin, Ferracuti, Stefano, Focquaert, Farah, Forgione, Arianna, Gilbert, Fredric, Pennati, Ambrogio, Pietrini, Pietro, Rainero, Innocenzo, Sartori, Giuseppe, Swerdlow, Russell, and Camperio Ciani, Andrea S.
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- 2023
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24. The ENIGMA‐Epilepsy working group: Mapping disease from large data sets
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Sisodiya, Sanjay M, Whelan, Christopher D, Hatton, Sean N, Huynh, Khoa, Altmann, Andre, Ryten, Mina, Vezzani, Annamaria, Caligiuri, Maria Eugenia, Labate, Angelo, Gambardella, Antonio, Ives‐Deliperi, Victoria, Meletti, Stefano, Munsell, Brent C, Bonilha, Leonardo, Tondelli, Manuela, Rebsamen, Michael, Rummel, Christian, Vaudano, Anna Elisabetta, Wiest, Roland, Balachandra, Akshara R, Bargalló, Núria, Bartolini, Emanuele, Bernasconi, Andrea, Bernasconi, Neda, Bernhardt, Boris, Caldairou, Benoit, Carr, Sarah JA, Cavalleri, Gianpiero L, Cendes, Fernando, Concha, Luis, Desmond, Patricia M, Domin, Martin, Duncan, John S, Focke, Niels K, Guerrini, Renzo, Hamandi, Khalid, Jackson, Graeme D, Jahanshad, Neda, Kälviäinen, Reetta, Keller, Simon S, Kochunov, Peter, Kowalczyk, Magdalena A, Kreilkamp, Barbara AK, Kwan, Patrick, Lariviere, Sara, Lenge, Matteo, Lopez, Seymour M, Martin, Pascal, Mascalchi, Mario, Moreira, José CV, Morita‐Sherman, Marcia E, Pardoe, Heath R, Pariente, Jose C, Raviteja, Kotikalapudi, Rocha, Cristiane S, Rodríguez‐Cruces, Raúl, Seeck, Margitta, Semmelroch, Mira KHG, Sinclair, Benjamin, Soltanian‐Zadeh, Hamid, Stein, Dan J, Striano, Pasquale, Taylor, Peter N, Thomas, Rhys H, Thomopoulos, Sophia I, Velakoulis, Dennis, Vivash, Lucy, Weber, Bernd, Yasuda, Clarissa Lin, Zhang, Junsong, Thompson, Paul M, McDonald, Carrie R, Abela, Eugenio, Absil, Julie, Adams, Sophia, Alhusaini, Saud, Alvim, Marina, Balestrini, Simona, Bender, Benjamin, Bergo, Felipe, Bernardes, Tauana, Calvo, Anna, Carreno, Mar, Cherubini, Andrea, David, Philippe, Davoodi‐Bojd, Esmaeil, Delanty, Norman, Depondt, Chantal, Devinsky, Orrin, Doherty, Colin, França, Wendy Caroline, Franceschet, Leticia, Hibar, Derrek P, Ishikawa, Akari, Kaestner, Erik, Langner, Soenke, Liu, Min, Mirandola, Laura, Naylor, Jillian, and Nazem‐Zadeh, Mohammad‐reza
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Brain Disorders ,Biomedical Imaging ,Neurosciences ,Epilepsy ,Neurodegenerative ,2.1 Biological and endogenous factors ,Aetiology ,Neurological ,covariance ,deep learning ,DTI ,event-based modeling ,gene expression ,genetics ,imaging ,MRI ,quantitative ,rsfMRI ,ENIGMA Consortium Epilepsy Working Group ,Cognitive Sciences ,Experimental Psychology - Abstract
Epilepsy is a common and serious neurological disorder, with many different constituent conditions characterized by their electro clinical, imaging, and genetic features. MRI has been fundamental in advancing our understanding of brain processes in the epilepsies. Smaller-scale studies have identified many interesting imaging phenomena, with implications both for understanding pathophysiology and improving clinical care. Through the infrastructure and concepts now well-established by the ENIGMA Consortium, ENIGMA-Epilepsy was established to strengthen epilepsy neuroscience by greatly increasing sample sizes, leveraging ideas and methods established in other ENIGMA projects, and generating a body of collaborating scientists and clinicians to drive forward robust research. Here we review published, current, and future projects, that include structural MRI, diffusion tensor imaging (DTI), and resting state functional MRI (rsfMRI), and that employ advanced methods including structural covariance, and event-based modeling analysis. We explore age of onset- and duration-related features, as well as phenomena-specific work focusing on particular epilepsy syndromes or phenotypes, multimodal analyses focused on understanding the biology of disease progression, and deep learning approaches. We encourage groups who may be interested in participating to make contact to further grow and develop ENIGMA-Epilepsy.
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- 2022
25. Structural network alterations in focal and generalized epilepsy assessed in a worldwide ENIGMA study follow axes of epilepsy risk gene expression
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Larivière, Sara, Royer, Jessica, Rodríguez-Cruces, Raúl, Paquola, Casey, Caligiuri, Maria Eugenia, Gambardella, Antonio, Concha, Luis, Keller, Simon S, Cendes, Fernando, Yasuda, Clarissa L, Bonilha, Leonardo, Gleichgerrcht, Ezequiel, Focke, Niels K, Domin, Martin, von Podewills, Felix, Langner, Soenke, Rummel, Christian, Wiest, Roland, Martin, Pascal, Kotikalapudi, Raviteja, O’Brien, Terence J, Sinclair, Benjamin, Vivash, Lucy, Desmond, Patricia M, Lui, Elaine, Vaudano, Anna Elisabetta, Meletti, Stefano, Tondelli, Manuela, Alhusaini, Saud, Doherty, Colin P, Cavalleri, Gianpiero L, Delanty, Norman, Kälviäinen, Reetta, Jackson, Graeme D, Kowalczyk, Magdalena, Mascalchi, Mario, Semmelroch, Mira, Thomas, Rhys H, Soltanian-Zadeh, Hamid, Davoodi-Bojd, Esmaeil, Zhang, Junsong, Winston, Gavin P, Griffin, Aoife, Singh, Aditi, Tiwari, Vijay K, Kreilkamp, Barbara AK, Lenge, Matteo, Guerrini, Renzo, Hamandi, Khalid, Foley, Sonya, Rüber, Theodor, Weber, Bernd, Depondt, Chantal, Absil, Julie, Carr, Sarah JA, Abela, Eugenio, Richardson, Mark P, Devinsky, Orrin, Severino, Mariasavina, Striano, Pasquale, Tortora, Domenico, Kaestner, Erik, Hatton, Sean N, Vos, Sjoerd B, Caciagli, Lorenzo, Duncan, John S, Whelan, Christopher D, Thompson, Paul M, Sisodiya, Sanjay M, Bernasconi, Andrea, Labate, Angelo, McDonald, Carrie R, Bernasconi, Neda, and Bernhardt, Boris C
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Neurodegenerative ,Genetics ,Neurosciences ,Brain Disorders ,Epilepsy ,Aetiology ,2.1 Biological and endogenous factors ,Neurological ,Adult ,Connectome ,Epilepsy ,Generalized ,Epilepsy ,Temporal Lobe ,Gene Expression ,Humans ,Immunoglobulin E ,Magnetic Resonance Imaging ,Nerve Net - Abstract
Epilepsy is associated with genetic risk factors and cortico-subcortical network alterations, but associations between neurobiological mechanisms and macroscale connectomics remain unclear. This multisite ENIGMA-Epilepsy study examined whole-brain structural covariance networks in patients with epilepsy and related findings to postmortem epilepsy risk gene expression patterns. Brain network analysis included 578 adults with temporal lobe epilepsy (TLE), 288 adults with idiopathic generalized epilepsy (IGE), and 1328 healthy controls from 18 centres worldwide. Graph theoretical analysis of structural covariance networks revealed increased clustering and path length in orbitofrontal and temporal regions in TLE, suggesting a shift towards network regularization. Conversely, people with IGE showed decreased clustering and path length in fronto-temporo-parietal cortices, indicating a random network configuration. Syndrome-specific topological alterations reflected expression patterns of risk genes for hippocampal sclerosis in TLE and for generalized epilepsy in IGE. These imaging-transcriptomic signatures could potentially guide diagnosis or tailor therapeutic approaches to specific epilepsy syndromes.
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- 2022
26. Content Validation of Clinician-Reported Items for a Severity Measure for CDKL5 Deficiency Disorder
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Saldaris, Jacinta, Weisenberg, Judith, Pestana-Knight, Elia, Marsh, Eric D, Suter, Bernhard, Rajaraman, Rajsekar, Heidary, Gena, Olson, Heather E, Devinsky, Orrin, Price, Dana, Jacoby, Peter, Leonard, Helen, Benke, Tim A, Demarest, Scott, and Downs, Jenny
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Biomedical and Clinical Sciences ,Neurosciences ,Clinical Sciences ,Brain Disorders ,Clinical Research ,Child ,Epileptic Syndromes ,Female ,Humans ,Interviews as Topic ,Male ,Neurologists ,Outcome Assessment ,Health Care ,Patient Acuity ,Psychometrics ,Reproducibility of Results ,Spasms ,Infantile ,Surveys and Questionnaires ,CDKL5 deficiency disorder ,clinical severity ,outcome measure ,think aloud ,content validity ,Cognitive Sciences ,Neurology & Neurosurgery ,Clinical sciences - Abstract
CDKL5 deficiency disorder (CDD) results in early-onset seizures and severe developmental impairments. A CDD clinical severity assessment (CCSA) was previously developed with clinician and parent-report items to capture information on a range of domains. Consistent with US Food and Drug Administration (FDA) guidelines, content validation is the first step in evaluating the psychometric properties of an outcome measure. The aim of this study was to validate the content of the clinician-reported items in the CCSA (CCSA-Clinician). Eight neurologists leading the USA CDD Center of Excellence clinics were interviewed using the "think aloud" technique to critique 26 clinician-reported items. Common themes were aggregated, and a literature search of related assessments informed item modifications. The clinicians then participated in 2 consensus meetings to review themes and finalize the items. A consensus was achieved for the content of the CCSA-Clinician. Eight of the original items were omitted, 11 items were added, and the remaining 18 items were revised. The final 29 items were classified into 2 domains: functioning and neurologic impairments. This study enabled refinement of the CCSA-Clinician and provided evidence for its content validity. This preliminary validation is essential before field testing and further validation, in order to advance the instrument toward clinical trial readiness.
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- 2021
27. Localized Motion Artifact Reduction on Brain MRI Using Deep Learning with Effective Data Augmentation Techniques
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Zhao, Yijun, Ossowski, Jacek, Wang, Xuming, Li, Shangjin, Devinsky, Orrin, Martin, Samantha P., and Pardoe, Heath R.
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Electrical Engineering and Systems Science - Image and Video Processing ,Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Machine Learning - Abstract
In-scanner motion degrades the quality of magnetic resonance imaging (MRI) thereby reducing its utility in the detection of clinically relevant abnormalities. We introduce a deep learning-based MRI artifact reduction model (DMAR) to localize and correct head motion artifacts in brain MRI scans. Our approach integrates the latest advances in object detection and noise reduction in Computer Vision. Specifically, DMAR employs a two-stage approach: in the first, degraded regions are detected using the Single Shot Multibox Detector (SSD), and in the second, the artifacts within the found regions are reduced using a convolutional autoencoder (CAE). We further introduce a set of novel data augmentation techniques to address the high dimensionality of MRI images and the scarcity of available data. As a result, our model was trained on a large synthetic dataset of 225,000 images generated from 375 whole brain T1-weighted MRI scans. DMAR visibly reduces image artifacts when applied to both synthetic test images and 55 real-world motion-affected slices from 18 subjects from the multi-center Autism Brain Imaging Data Exchange (ABIDE) study. Quantitatively, depending on the level of degradation, our model achieves a 27.8%-48.1% reduction in RMSE and a 2.88--5.79 dB gain in PSNR on a 5000-sample set of synthetic images. For real-world artifact-affected scans from ABIDE, our model reduced the variance of image voxel intensity within artifact-affected brain regions (p = 0.014)., Comment: 11 pages, 8 figures
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- 2020
28. Shared genetic basis between genetic generalized epilepsy and background electroencephalographic oscillations
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Stevelink, Remi, Luykx, Jurjen J, Lin, Bochao D, Leu, Costin, Lal, Dennis, Smith, Alexander W, Schijven, Dick, Carpay, Johannes A, Rademaker, Koen, Baldez, Roiza A Rodrigues, Devinsky, Orrin, Braun, Kees PJ, Jansen, Floor E, Smit, Dirk JA, Koeleman, Bobby PC, Abou‐Khalil, Bassel, Auce, Pauls, Avbersek, Andreja, Bahlo, Melanie, Balding, David J, Bast, Thomas, Baum, Larry, Becker, Albert J, Becker, Felicitas, Berghuis, Bianca, Berkovic, Samuel F, Boysen, Katja E, Bradfield, Jonathan P, Brody, Lawrence C, Buono, Russell J, Campbell, Ellen, Cascino, Gregory D, Catarino, Claudia B, Cavalleri, Gianpiero L, Cherny, Stacey S, Chinthapalli, Krishna, Coffey, Alison J, Compston, Alastair, Coppola, Antonietta, Cossette, Patrick, Craig, John J, de Haan, Gerrit‐Jan, De Jonghe, Peter, de Kovel, Carolien GF, Delanty, Norman, Depondt, Chantal, Dlugos, Dennis J, Doherty, Colin P, Elger, Christian E, Eriksson, Johan G, Ferraro, Thomas N, Feucht, Martha, Francis, Ben, Franke, Andre, French, Jacqueline A, Freytag, Saskia, Gaus, Verena, Geller, Eric B, Gieger, Christian, Glauser, Tracy, Glynn, Simon, Goldstein, David B, Gui, Hongsheng, Guo, Youling, Haas, Kevin F, Hakonarson, Hakon, Hallmann, Kerstin, Haut, Sheryl, Heinzen, Erin L, Helbig, Ingo, Hengsbach, Christian, Hjalgrim, Helle, Iacomino, Michele, Ingason, Andrés, Jamnadas‐Khoda, Jennifer, Johnson, Michael R, Kälviäinen, Reetta, Kantanen, Anne‐Mari, Kasperavičiūte, Dalia, Trenite, Dorothee Kasteleijn‐Nolst, Kirsch, Heidi E, Knowlton, Robert C, Krause, Roland, Krenn, Martin, Kunz, Wolfram S, Kuzniecky, Ruben, Kwan, Patrick, Lau, Yu‐Lung, Lehesjoki, Anna‐Elina, Lerche, Holger, Lieb, Wolfgang, Lindhout, Dick, Lo, Warren D, Lopes‐Cendes, Iscia, Lowenstein, Daniel H, Malovini, Alberto, Marson, Anthony G, Mayer, Thomas, McCormack, Mark, and Mills, James L
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Biomedical and Clinical Sciences ,Neurosciences ,Clinical Sciences ,Genetics ,Brain Disorders ,Clinical Research ,Human Genome ,Neurodegenerative ,Epilepsy ,2.1 Biological and endogenous factors ,Aetiology ,Neurological ,Adult ,Algorithms ,Beta Rhythm ,Cohort Studies ,Databases ,Factual ,Electroencephalography ,Epilepsy ,Generalized ,Genome-Wide Association Study ,Humans ,Linkage Disequilibrium ,Mendelian Randomization Analysis ,Risk Assessment ,Theta Rhythm ,beta power ,EEG ,generalized epilepsy ,GGE ,oscillations ,PRS ,International League Against Epilepsy Consortium on Complex Epilepsies ,Epi25 Collaborative ,Neurology & Neurosurgery ,Clinical sciences - Abstract
ObjectiveParoxysmal epileptiform abnormalities on electroencephalography (EEG) are the hallmark of epilepsies, but it is uncertain to what extent epilepsy and background EEG oscillations share neurobiological underpinnings. Here, we aimed to assess the genetic correlation between epilepsy and background EEG oscillations.MethodsConfounding factors, including the heterogeneous etiology of epilepsies and medication effects, hamper studies on background brain activity in people with epilepsy. To overcome this limitation, we compared genetic data from a genome-wide association study (GWAS) on epilepsy (n = 12 803 people with epilepsy and 24 218 controls) with that from a GWAS on background EEG (n = 8425 subjects without epilepsy), in which background EEG oscillation power was quantified in four different frequency bands: alpha, beta, delta, and theta. We replicated our findings in an independent epilepsy replication dataset (n = 4851 people with epilepsy and 20 428 controls). To assess the genetic overlap between these phenotypes, we performed genetic correlation analyses using linkage disequilibrium score regression, polygenic risk scores, and Mendelian randomization analyses.ResultsOur analyses show strong genetic correlations of genetic generalized epilepsy (GGE) with background EEG oscillations, primarily in the beta frequency band. Furthermore, we show that subjects with higher beta and theta polygenic risk scores have a significantly higher risk of having generalized epilepsy. Mendelian randomization analyses suggest a causal effect of GGE genetic liability on beta oscillations.SignificanceOur results point to shared biological mechanisms underlying background EEG oscillations and the susceptibility for GGE, opening avenues to investigate the clinical utility of background EEG oscillations in the diagnostic workup of epilepsy.
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- 2021
29. Comparing measured dietary variation within and between tropical hunter-gatherer groups to the Paleo Diet
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Lieberman, Daniel E., Worthington, Steven, Schell, Laura D., Parkent, Christine M., Devinsky, Orrin, and Carmody, Rachel N.
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- 2023
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30. Abstract 19166: Activity Level and Causes of Sudden Death: From the San Francisco Postmortem Systematic Investigation of Sudden Cardiac Death (POST SCD) Study
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Kinkead, Brielle, Eik, David, Yee, Matthew, Refaat, Marwan M, Devinsky, Orrin, Nakasuka, Kosuke, Connolly, Andrew, Moffatt, Ellen, and Tseng, Zian H
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- 2023
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31. Artificial intelligence for classification of temporal lobe epilepsy with ROI-level MRI data: A worldwide ENIGMA-Epilepsy study
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Gleichgerrcht, Ezequiel, Munsell, Brent C, Alhusaini, Saud, Alvim, Marina KM, Bargalló, Núria, Bender, Benjamin, Bernasconi, Andrea, Bernasconi, Neda, Bernhardt, Boris, Blackmon, Karen, Caligiuri, Maria Eugenia, Cendes, Fernando, Concha, Luis, Desmond, Patricia M, Devinsky, Orrin, Doherty, Colin P, Domin, Martin, Duncan, John S, Focke, Niels K, Gambardella, Antonio, Gong, Bo, Guerrini, Renzo, Hatton, Sean N, Kälviäinen, Reetta, Keller, Simon S, Kochunov, Peter, Kotikalapudi, Raviteja, Kreilkamp, Barbara AK, Labate, Angelo, Langner, Soenke, Larivière, Sara, Lenge, Matteo, Lui, Elaine, Martin, Pascal, Mascalchi, Mario, Meletti, Stefano, O'Brien, Terence J, Pardoe, Heath R, Pariente, Jose C, Rao, Jun Xian, Richardson, Mark P, Rodríguez-Cruces, Raúl, Rüber, Theodor, Sinclair, Ben, Soltanian-Zadeh, Hamid, Stein, Dan J, Striano, Pasquale, Taylor, Peter N, Thomas, Rhys H, Vaudano, Anna Elisabetta, Vivash, Lucy, von Podewills, Felix, Vos, Sjoerd B, Weber, Bernd, Yao, Yi, Yasuda, Clarissa Lin, Zhang, Junsong, Thompson, Paul M, Sisodiya, Sanjay M, McDonald, Carrie R, Bonilha, Leonardo, Group, ENIGMA-Epilepsy Working, Altmann, Andre, Depondt, Chantal, Galovic, Marian, Thomopoulos, Sophia I, and Wiest, Roland
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Biomedical Imaging ,Neurodegenerative ,Neurosciences ,Brain Disorders ,Prevention ,Epilepsy ,2.1 Biological and endogenous factors ,Aetiology ,Neurological ,Artificial Intelligence ,Brain ,Epilepsy ,Temporal Lobe ,Hippocampus ,Humans ,Magnetic Resonance Imaging ,Sclerosis ,Support Vector Machine ,Temporal lobe epilepsy ,Machine learning ,Artificial inteligence ,ENIGMA-Epilepsy Working Group - Abstract
Artificial intelligence has recently gained popularity across different medical fields to aid in the detection of diseases based on pathology samples or medical imaging findings. Brain magnetic resonance imaging (MRI) is a key assessment tool for patients with temporal lobe epilepsy (TLE). The role of machine learning and artificial intelligence to increase detection of brain abnormalities in TLE remains inconclusive. We used support vector machine (SV) and deep learning (DL) models based on region of interest (ROI-based) structural (n = 336) and diffusion (n = 863) brain MRI data from patients with TLE with ("lesional") and without ("non-lesional") radiographic features suggestive of underlying hippocampal sclerosis from the multinational (multi-center) ENIGMA-Epilepsy consortium. Our data showed that models to identify TLE performed better or similar (68-75%) compared to models to lateralize the side of TLE (56-73%, except structural-based) based on diffusion data with the opposite pattern seen for structural data (67-75% to diagnose vs. 83% to lateralize). In other aspects, structural and diffusion-based models showed similar classification accuracies. Our classification models for patients with hippocampal sclerosis were more accurate (68-76%) than models that stratified non-lesional patients (53-62%). Overall, SV and DL models performed similarly with several instances in which SV mildly outperformed DL. We discuss the relative performance of these models with ROI-level data and the implications for future applications of machine learning and artificial intelligence in epilepsy care.
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- 2021
32. Network-based atrophy modeling in the common epilepsies: A worldwide ENIGMA study
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Larivière, Sara, Rodríguez-Cruces, Raúl, Royer, Jessica, Caligiuri, Maria Eugenia, Gambardella, Antonio, Concha, Luis, Keller, Simon S, Cendes, Fernando, Yasuda, Clarissa, Bonilha, Leonardo, Gleichgerrcht, Ezequiel, Focke, Niels K, Domin, Martin, von Podewills, Felix, Langner, Soenke, Rummel, Christian, Wiest, Roland, Martin, Pascal, Kotikalapudi, Raviteja, O’Brien, Terence J, Sinclair, Benjamin, Vivash, Lucy, Desmond, Patricia M, Alhusaini, Saud, Doherty, Colin P, Cavalleri, Gianpiero L, Delanty, Norman, Kälviäinen, Reetta, Jackson, Graeme D, Kowalczyk, Magdalena, Mascalchi, Mario, Semmelroch, Mira, Thomas, Rhys H, Soltanian-Zadeh, Hamid, Davoodi-Bojd, Esmaeil, Zhang, Junsong, Lenge, Matteo, Guerrini, Renzo, Bartolini, Emanuele, Hamandi, Khalid, Foley, Sonya, Weber, Bernd, Depondt, Chantal, Absil, Julie, Carr, Sarah JA, Abela, Eugenio, Richardson, Mark P, Devinsky, Orrin, Severino, Mariasavina, Striano, Pasquale, Tortora, Domenico, Hatton, Sean N, Vos, Sjoerd B, Duncan, John S, Whelan, Christopher D, Thompson, Paul M, Sisodiya, Sanjay M, Bernasconi, Andrea, Labate, Angelo, McDonald, Carrie R, Bernasconi, Neda, and Bernhardt, Boris C
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Mental Health ,Brain Disorders ,Epilepsy ,Clinical Research ,Neurosciences ,Neurodegenerative ,Aetiology ,2.1 Biological and endogenous factors ,Neurological - Abstract
Epilepsy is increasingly conceptualized as a network disorder. In this cross-sectional mega-analysis, we integrated neuroimaging and connectome analysis to identify network associations with atrophy patterns in 1021 adults with epilepsy compared to 1564 healthy controls from 19 international sites. In temporal lobe epilepsy, areas of atrophy colocalized with highly interconnected cortical hub regions, whereas idiopathic generalized epilepsy showed preferential subcortical hub involvement. These morphological abnormalities were anchored to the connectivity profiles of distinct disease epicenters, pointing to temporo-limbic cortices in temporal lobe epilepsy and fronto-central cortices in idiopathic generalized epilepsy. Negative effects of age on atrophy further revealed a strong influence of connectome architecture in temporal lobe, but not idiopathic generalized, epilepsy. Our findings were reproduced across individual sites and single patients and were robust across different analytical methods. Through worldwide collaboration in ENIGMA-Epilepsy, we provided deeper insights into the macroscale features that shape the pathophysiology of common epilepsies.
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- 2020
33. Reinstating olfactory bulb-derived limbic gamma oscillations alleviates depression-like behavioral deficits in rodents
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Li, Qun, Takeuchi, Yuichi, Wang, Jiale, Gellért, Levente, Barcsai, Livia, Pedraza, Lizeth K., Nagy, Anett J., Kozák, Gábor, Nakai, Shinya, Kato, Shigeki, Kobayashi, Kazuto, Ohsawa, Masahiro, Horváth, Gyöngyi, Kékesi, Gabriella, Lőrincz, Magor L., Devinsky, Orrin, Buzsáki, György, and Berényi, Antal
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- 2023
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34. POLR1A variants underlie phenotypic heterogeneity in craniofacial, neural, and cardiac anomalies
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Smallwood, Kelly, Watt, Kristin E.N., Ide, Satoru, Baltrunaite, Kristina, Brunswick, Chad, Inskeep, Katherine, Capannari, Corrine, Adam, Margaret P., Begtrup, Amber, Bertola, Debora R., Demmer, Laurie, Demo, Erin, Devinsky, Orrin, Gallagher, Emily R., Guillen Sacoto, Maria J., Jech, Robert, Keren, Boris, Kussmann, Jennifer, Ladda, Roger, Lansdon, Lisa A., Lunke, Sebastian, Mardy, Anne, McWalters, Kirsty, Person, Richard, Raiti, Laura, Saitoh, Noriko, Saunders, Carol J., Schnur, Rhonda, Skorvanek, Matej, Sell, Susan L., Slavotinek, Anne, Sullivan, Bonnie R., Stark, Zornitza, Symonds, Joseph D., Wenger, Tara, Weber, Sacha, Whalen, Sandra, White, Susan M., Winkelmann, Juliane, Zech, Michael, Zeidler, Shimriet, Maeshima, Kazuhiro, Stottmann, Rolf W., Trainor, Paul A., and Weaver, K. Nicole
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- 2023
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35. White matter abnormalities across different epilepsy syndromes in adults: an ENIGMA-Epilepsy study
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Hatton, Sean N, Huynh, Khoa H, Bonilha, Leonardo, Abela, Eugenio, Alhusaini, Saud, Altmann, Andre, Alvim, Marina KM, Balachandra, Akshara R, Bartolini, Emanuele, Bender, Benjamin, Bernasconi, Neda, Bernasconi, Andrea, Bernhardt, Boris, Bargallo, Núria, Caldairou, Benoit, Caligiuri, Maria E, Carr, Sarah JA, Cavalleri, Gianpiero L, Cendes, Fernando, Concha, Luis, Davoodi-bojd, Esmaeil, Desmond, Patricia M, Devinsky, Orrin, Doherty, Colin P, Domin, Martin, Duncan, John S, Focke, Niels K, Foley, Sonya F, Gambardella, Antonio, Gleichgerrcht, Ezequiel, Guerrini, Renzo, Hamandi, Khalid, Ishikawa, Akari, Keller, Simon S, Kochunov, Peter V, Kotikalapudi, Raviteja, Kreilkamp, Barbara AK, Kwan, Patrick, Labate, Angelo, Langner, Soenke, Lenge, Matteo, Liu, Min, Lui, Elaine, Martin, Pascal, Mascalchi, Mario, Moreira, José CV, Morita-Sherman, Marcia E, O’Brien, Terence J, Pardoe, Heath R, Pariente, José C, Ribeiro, Letícia F, Richardson, Mark P, Rocha, Cristiane S, Rodríguez-Cruces, Raúl, Rosenow, Felix, Severino, Mariasavina, Sinclair, Benjamin, Soltanian-Zadeh, Hamid, Striano, Pasquale, Taylor, Peter N, Thomas, Rhys H, Tortora, Domenico, Velakoulis, Dennis, Vezzani, Annamaria, Vivash, Lucy, von Podewils, Felix, Vos, Sjoerd B, Weber, Bernd, Winston, Gavin P, Yasuda, Clarissa L, Zhu, Alyssa H, Thompson, Paul M, Whelan, Christopher D, Jahanshad, Neda, Sisodiya, Sanjay M, and McDonald, Carrie R
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Genetics ,Neurodegenerative ,Epilepsy ,Clinical Research ,Brain Disorders ,Neurosciences ,Biomedical Imaging ,Aetiology ,2.1 Biological and endogenous factors ,Neurological ,Adult ,Brain ,Diffusion Magnetic Resonance Imaging ,Epileptic Syndromes ,Female ,Humans ,Image Interpretation ,Computer-Assisted ,Male ,Middle Aged ,White Matter ,epilepsy ,diffusion tensor imaging ,multisite analysis ,white matter ,Medical and Health Sciences ,Psychology and Cognitive Sciences ,Neurology & Neurosurgery - Abstract
The epilepsies are commonly accompanied by widespread abnormalities in cerebral white matter. ENIGMA-Epilepsy is a large quantitative brain imaging consortium, aggregating data to investigate patterns of neuroimaging abnormalities in common epilepsy syndromes, including temporal lobe epilepsy, extratemporal epilepsy, and genetic generalized epilepsy. Our goal was to rank the most robust white matter microstructural differences across and within syndromes in a multicentre sample of adult epilepsy patients. Diffusion-weighted MRI data were analysed from 1069 healthy controls and 1249 patients: temporal lobe epilepsy with hippocampal sclerosis (n = 599), temporal lobe epilepsy with normal MRI (n = 275), genetic generalized epilepsy (n = 182) and non-lesional extratemporal epilepsy (n = 193). A harmonized protocol using tract-based spatial statistics was used to derive skeletonized maps of fractional anisotropy and mean diffusivity for each participant, and fibre tracts were segmented using a diffusion MRI atlas. Data were harmonized to correct for scanner-specific variations in diffusion measures using a batch-effect correction tool (ComBat). Analyses of covariance, adjusting for age and sex, examined differences between each epilepsy syndrome and controls for each white matter tract (Bonferroni corrected at P
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- 2020
36. Autism risk in offspring can be assessed through quantification of male sperm mosaicism
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Breuss, Martin W, Antaki, Danny, George, Renee D, Kleiber, Morgan, James, Kiely N, Ball, Laurel L, Hong, Oanh, Mitra, Ileena, Yang, Xiaoxu, Wirth, Sara A, Gu, Jing, Garcia, Camila AB, Gujral, Madhusudan, Brandler, William M, Musaev, Damir, Nguyen, An, McEvoy-Venneri, Jennifer, Knox, Renatta, Sticca, Evan, Botello, Martha Cristina Cancino, Uribe Fenner, Javiera, Pérez, Maria Cárcel, Arranz, Maria, Moffitt, Andrea B, Wang, Zihua, Hervás, Amaia, Devinsky, Orrin, Gymrek, Melissa, Sebat, Jonathan, and Gleeson, Joseph G
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Biomedical and Clinical Sciences ,Mental Health ,Serious Mental Illness ,Autism ,Intellectual and Developmental Disabilities (IDD) ,Genetics ,Human Genome ,Pediatric ,Brain Disorders ,Contraception/Reproduction ,2.1 Biological and endogenous factors ,Aetiology ,Autistic Disorder ,Female ,Genetic Predisposition to Disease ,Humans ,Male ,Mosaicism ,Mutation ,Pedigree ,Polymorphism ,Single Nucleotide ,Recurrence ,Risk Factors ,Spermatozoa ,Medical and Health Sciences ,Immunology ,Biomedical and clinical sciences ,Health sciences - Abstract
De novo mutations arising on the paternal chromosome make the largest known contribution to autism risk, and correlate with paternal age at the time of conception. The recurrence risk for autism spectrum disorders is substantial, leading many families to decline future pregnancies, but the potential impact of assessing parental gonadal mosaicism has not been considered. We measured sperm mosaicism using deep-whole-genome sequencing, for variants both present in an offspring and evident only in father's sperm, and identified single-nucleotide, structural and short tandem-repeat variants. We found that mosaicism quantification can stratify autism spectrum disorders recurrence risk due to de novo mutations into a vast majority with near 0% recurrence and a small fraction with a substantially higher and quantifiable risk, and we identify novel mosaic variants at risk for transmission to a future offspring. This suggests, therefore, that genetic counseling would benefit from the addition of sperm mosaicism assessment.
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- 2020
37. Quantitative analysis of phenotypic elements augments traditional electroclinical classification of common familial epilepsies
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Abou‐Khalil, Bassel, Afawi, Zaid, Allen, Andrew S, Bautista, Jocelyn F, Bellows, Susannah T, Berkovic, Samuel F, Bluvstein, Judith, Burgess, Rosemary, Cascino, Gregory, Cossette, Patrick, Cristofaro, Sabrina, Crompton, Douglas E, Delanty, Norman, Devinsky, Orrin, Dlugos, Dennis, Ellis, Colin A, Epstein, Michael P, Fountain, Nathan B, Freyer, Catharine, Geller, Eric B, Glauser, Tracy, Glynn, Simon, Goldberg‐Stern, Hadassa, Goldstein, David B, Gravel, Micheline, Haas, Kevin, Haut, Sheryl, Heinzen, Erin L, Kirsch, Heidi E, Kivity, Sara, Knowlton, Robert, Korczyn, Amos D, Kossoff, Eric, Kuzniecky, Ruben, Loeb, Rebecca, Lowenstein, Daniel H, Marson, Anthony G, McCormack, Mark, McKenna, Kevin, Mefford, Heather C, Motika, Paul, Mullen, Saul A, J. O'Brien, Terence, Ottman, Ruth, Paolicchi, Juliann, Parent, Jack M, Paterson, Sarah, Petrou, Steven, Petrovski, Slavé, Owen Pickrell, William, Poduri, Annapurna, Rees, Mark I, Sadleir, Lynette G, Scheffer, Ingrid E, Shih, Jerry, Singh, Rani, Sirven, Joseph, Smith, Michael, Smith, Phil EM, Thio, Liu Lin, Thomas, Rhys H, Venkat, Anu, Vining, Eileen, Von Allmen, Gretchen, Weisenberg, Judith, Widdess‐Walsh, Peter, and Winawer, Melodie R
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Neurodegenerative ,Neurosciences ,Epilepsy ,Clinical Research ,Brain Disorders ,2.1 Biological and endogenous factors ,Aetiology ,Neurological ,Electroencephalography ,Epileptic Syndromes ,Female ,Humans ,Latent Class Analysis ,Male ,Pedigree ,Phenotype ,epilepsy ,genetics ,latent class analysis ,phenotype ,Epi4K Consortium ,Clinical Sciences ,Neurology & Neurosurgery - Abstract
ObjectiveClassification of epilepsy into types and subtypes is important for both clinical care and research into underlying disease mechanisms. A quantitative, data-driven approach may augment traditional electroclinical classification and shed new light on existing classification frameworks.MethodsWe used latent class analysis, a statistical method that assigns subjects into groups called latent classes based on phenotypic elements, to classify individuals with common familial epilepsies from the Epi4K Multiplex Families study. Phenotypic elements included seizure types, seizure symptoms, and other elements of the medical history. We compared class assignments to traditional electroclinical classifications and assessed familial aggregation of latent classes.ResultsA total of 1120 subjects with epilepsy were assigned to five latent classes. Classes 1 and 2 contained subjects with generalized epilepsy, largely reflecting the distinction between absence epilepsies and younger onset (class 1) versus myoclonic epilepsies and older onset (class 2). Classes 3 and 4 contained subjects with focal epilepsies, and in contrast to classes 1 and 2, these did not adhere as closely to clinically defined focal epilepsy subtypes. Class 5 contained nearly all subjects with febrile seizures plus or unknown epilepsy type, as well as a few subjects with generalized epilepsy and a few with focal epilepsy. Family concordance of latent classes was similar to or greater than concordance of clinically defined epilepsy types.SignificanceQuantitative classification of epilepsy has the potential to augment traditional electroclinical classification by (1) combining some syndromes into a single class, (2) splitting some syndromes into different classes, (3) helping to classify subjects who could not be classified clinically, and (4) defining the boundaries of clinically defined classifications. This approach can guide future research, including molecular genetic studies, by identifying homogeneous sets of individuals that may share underlying disease mechanisms.
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- 2019
38. Time-Dependent Transformations of Memory Representations Differ along the Long Axis of the Hippocampus
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Cowan, Emily T., Liu, Anli A., Henin, Simon, Kothare, Sanjeev, Devinsky, Orrin, and Davachi, Lila
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Research has shown that sleep is beneficial for the long-term retention of memories. According to theories of memory consolidation, memories are gradually reorganized, becoming supported by widespread, distributed cortical networks, particularly during postencoding periods of sleep. However, the effects of sleep on the organization of memories in the hippocampus itself remains less clear. In a 3-d study, participants encoded separate lists of word-image pairs differing in their opportunity for sleep-dependent consolidation. Pairs were initially studied either before or after an overnight sleep period, and were then restudied in a functional magnetic resonance imaging (fMRI) scan session. We used multivariate pattern similarity analyses to examine fine-grained effects of consolidation on memory representations in the hippocampus. We provide evidence for a dissociation along the long axis of the hippocampus that emerges with consolidation, such that representational patterns for object-word memories initially formed prior to sleep become differentiated in anterior hippocampus and more similar, or overlapping, in posterior hippocampus. Differentiation in anterior hippocampal representations correlated with subsequent behavioral performance. Furthermore, representational overlap in posterior hippocampus correlated with the duration of intervening slow wave sleep. Together, these results demonstrate that sleep-dependent consolidation promotes the reorganization of memory traces along the long axis of the hippocampus.
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- 2021
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39. De novo mutations in childhood cases of sudden unexplained death that disrupt intracellular Ca 2+ regulation
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Halvorsen, Matthew, Gould, Laura, Wang, Xiaohan, Grant, Gariel, Moya, Raquel, Rabin, Rachel, Ackerman, Michael J., Tester, David J., Lin, Peter T., Pappas, John G., Maurano, Matthew T., Goldstein, David B., Tsien, Richard W., and Devinsky, Orrin
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- 2021
40. Association between postictal EEG suppression, postictal autonomic dysfunction, and sudden unexpected death in epilepsy: Evidence from intracranial EEG
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Esmaeili, Behnaz, Weisholtz, Daniel, Tobochnik, Steven, Dworetzky, Barbara, Friedman, Daniel, Kaffashi, Farhad, Cash, Sydney, Cha, Brannon, Laze, Juliana, Reich, Dustine, Farooque, Pue, Gholipour, Taha, Singleton, Michael, Loparo, Kenneth, Koubeissi, Mohamad, Devinsky, Orrin, and Lee, Jong Woo
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- 2023
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41. The influence of risk factors, biomarkers and care settings on SUDEP counseling
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Valdrighi, Alexandria, primary, Laze, Juliana, additional, Farooque, Pue, additional, Friedman, Daniel, additional, Devinsky, Orrin, additional, Singhal, Nilika, additional, and Hegde, Manu, additional
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- 2024
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42. ALIGNING BRAINS INTO A SHARED SPACE IMPROVES THEIR ALIGNMENT TO LARGE LANGUAGE MODELS
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Bhattacharjee, Arnab, primary, Zada, Zaid, additional, Wang, Haocheng, additional, Aubrey, Bobbi, additional, Doyle, Werner, additional, Dugan, Patricia, additional, Friedman, Daniel, additional, Devinsky, Orrin, additional, Flinker, Adeen, additional, Ramadge, Peter J., additional, Hasson, Uri, additional, Goldstein, Ariel, additional, and Nastase, Samuel A., additional
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- 2024
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43. Proteomic differences in hippocampus and cortex of sudden unexplained death in childhood
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Leitner, Dominique F., William, Christopher, Faustin, Arline, Askenazi, Manor, Kanshin, Evgeny, Snuderl, Matija, McGuone, Declan, Wisniewski, Thomas, Ueberheide, Beatrix, Gould, Laura, and Devinsky, Orrin
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- 2022
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44. Postictal serotonin levels are associated with peri-ictal apnea.
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Murugesan, Arun, Rani, M, Vilella, Laura, Lacuey, Nuria, Hampson, Johnson, Faingold, Carl, Friedman, Daniel, Devinsky, Orrin, Sainju, Rup, Schuele, Stephan, Diehl, Beate, Nei, Maromi, Harper, Ronald, Bateman, Lisa, Richerson, George, and Lhatoo, Samden
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Adolescent ,Adult ,Aged ,Apnea ,Death ,Sudden ,Electroencephalography ,Epilepsy ,Female ,Humans ,Male ,Middle Aged ,Seizures ,Serotonin - Abstract
OBJECTIVE: To determine the relationship between serum serotonin (5-HT) levels, ictal central apnea (ICA), and postconvulsive central apnea (PCCA) in epileptic seizures. METHODS: We prospectively evaluated video EEG, plethysmography, capillary oxygen saturation (SpO2), and ECG for 49 patients (49 seizures) enrolled in a multicenter study of sudden unexpected death in epilepsy (SUDEP). Postictal and interictal venous blood samples were collected after a clinical seizure for measurement of serum 5-HT levels. Seizures were classified according to the International League Against Epilepsy 2017 seizure classification. We analyzed seizures with and without ICA (n = 49) and generalized convulsive seizures (GCS) with and without PCCA (n = 27). RESULTS: Postictal serum 5-HT levels were increased over interictal levels for seizures without ICA (p = 0.01), compared to seizures with ICA (p = 0.21). In patients with GCS without PCCA, serum 5-HT levels were increased postictally compared to interictal levels (p < 0.001), but not in patients with seizures with PCCA (p = 0.22). Postictal minus interictal 5-HT levels also differed between the 2 groups with and without PCCA (p = 0.03). Increased heart rate was accompanied by increased serum 5-HT levels (postictal minus interictal) after seizures without PCCA (p = 0.03) compared to those with PCCA (p = 0.42). CONCLUSIONS: The data suggest that significant seizure-related increases in serum 5-HT levels are associated with a lower incidence of seizure-related breathing dysfunction, and may reflect physiologic changes that confer a protective effect against deleterious phenomena leading to SUDEP. These results need to be confirmed with a larger sample size study.
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- 2019
45. The association of serotonin reuptake inhibitors and benzodiazepines with ictal central apnea
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Lacuey, Nuria, Martins, Rita, Vilella, Laura, Hampson, Johnson P, Rani, MR Sandhya, Strohl, Kingman, Zaremba, Anita, Hampson, Jaison S, Sainju, Rup K, Friedman, Daniel, Nei, Maromi, Scott, Catherine, Gehlbach, Brian K, Hupp, Norma J, Schuele, Stephan, Ogren, Jennifer, Harper, Ronald M, Allen, Luke, Diehl, Beate, Bateman, Lisa M, Devinsky, Orrin, Richerson, George B, and Lhatoo, Samden
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Biomedical and Clinical Sciences ,Cardiovascular Medicine and Haematology ,Brain Disorders ,Neurosciences ,Clinical Research ,Lung ,Neurodegenerative ,Epilepsy ,Neurological ,Good Health and Well Being ,Adolescent ,Adult ,Aged ,Benzodiazepines ,Cohort Studies ,Electroencephalography ,Female ,Humans ,Hypoxia ,Male ,Middle Aged ,Oximetry ,Prospective Studies ,Seizures ,Selective Serotonin Reuptake Inhibitors ,Sleep Apnea ,Central ,Sudden Unexpected Death in Epilepsy ,Young Adult ,SUDEP ,Ictal central apnea ,Serotonin reuptake inhibitors ,Clinical Sciences ,Neurology & Neurosurgery ,Biological psychology ,Clinical and health psychology - Abstract
ObjectiveIctal (ICA) and postconvulsive central apnea (PCCA) have been implicated in sudden unexpected death in epilepsy (SUDEP) pathomechanisms. Previous studies suggest that serotonin reuptake inhibitors (SRIs) and benzodiazepines (BZDs) may influence breathing. The aim of this study was to investigate if chronic use of these drugs alters central apnea occurrence in patients with epilepsy.MethodsPatients with epilepsy admitted to epilepsy monitoring units (EMUs) in nine centers participating in a SUDEP study were consented. Polygraphic physiological parameters were analyzed, including video-electroencephalography (VEEG), thoracoabdominal excursions, and pulse oximetry. Outpatient medication details were collected. Patients and seizures were divided into SRI, BZD, and control (no SRI or BZD) groups. Ictal central apnea and PCCA, hypoxemia, and electroclinical features were assessed for each group.ResultsFour hundred and seventy-six seizures were analyzed (204 patients). The relative risk (RR) for ICA in the SRI group was half that of the control group (p = 0.02). In the BZD group, ICA duration was significantly shorter than in the control group (p = 0.02), as was postictal generalized EEG suppression (PGES) duration (p = 0.021). Both SRI and BZD groups were associated with smaller seizure-associated oxygen desaturation (p = 0.009; p ≪ 0.001). Neither presence nor duration of PCCA was significantly associated with SRI or BZD (p ≫ 0.05).ConclusionsSeizures in patients taking SRIs have lower occurrence of ICA, and patients on chronic treatment with BZDs have shorter ICA and PGES durations. Preventing or shortening ICA duration by using SRIs and/or BZD in patients with epilepsy may play a possible role in SUDEP risk reduction.
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- 2019
46. Understanding perirhinal contributions to perception and memory: Evidence through the lens of selective perirhinal damage
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Inhoff, Marika C, Heusser, Andrew C, Tambini, Arielle, Martin, Chris B, O'Neil, Edward B, Köhler, Stefan, Meager, Michael R, Blackmon, Karen, Vazquez, Blanca, Devinsky, Orrin, and Davachi, Lila
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Biological Psychology ,Cognitive and Computational Psychology ,Psychology ,Applied and Developmental Psychology ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Alzheimer's Disease ,Neurosciences ,Mind and Body ,Dementia ,Clinical Research ,Acquired Cognitive Impairment ,Behavioral and Social Science ,Basic Behavioral and Social Science ,Aging ,Neurodegenerative ,Brain Disorders ,Mental Health ,Underpinning research ,1.2 Psychological and socioeconomic processes ,1.1 Normal biological development and functioning ,Mental health ,Adolescent ,Adult ,Facial Recognition ,Female ,Hippocampus ,Humans ,Judgment ,Male ,Memory ,Neuropsychological Tests ,Perirhinal Cortex ,Recognition ,Psychology ,Young Adult ,Perirhinal cortex ,Perception ,Medial temporal lobe ,Cognitive Sciences ,Experimental Psychology ,Biological psychology ,Cognitive and computational psychology - Abstract
Although a memory systems view of the medial temporal lobe (MTL) has been widely influential in understanding how memory processes are implemented, a large body of work across humans and animals has converged on the idea that the MTL can support various other decisions, beyond those involving memory. Specifically, recent work suggests that perception of and memory for visual representations may interact in order to support ongoing cognition. However, given considerations involving lesion profiles in neuropsychological investigations and the correlational nature of fMRI, the precise nature of representations supported by the MTL are not well understood in humans. In the present investigation, three patients with highly specific lesions to MTL were administered a task that taxed perceptual and mnemonic judgments with highly similar face stimuli. A striking double dissociation was observed such that I.R., a patient with a cyst localized to right posterior PRc, displayed a significant impairment in perceptual discriminations, whereas patient A.N., an individual with a lesion in right posterior parahippocampal cortex and the tail of the right hippocampus, and S.D., an individual with bilateral hippocampal damage, did not display impaired performance on the perceptual task. A.N. and S.D. did, however, show impairments in memory performance, whereas patient I.R. did not. These results causally implicate right PRc in successful perceptual oddity judgments, however they suggest that representations supported by PRc are not necessary for correct mnemonic judgments, even in situations of high featural overlap.
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- 2019
47. Postconvulsive central apnea as a biomarker for sudden unexpected death in epilepsy (SUDEP).
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Vilella, Laura, Lacuey, Nuria, Hampson, Johnson P, Rani, MR Sandhya, Sainju, Rup K, Friedman, Daniel, Nei, Maromi, Strohl, Kingman, Scott, Catherine, Gehlbach, Brian K, Zonjy, Bilal, Hupp, Norma J, Zaremba, Anita, Shafiabadi, Nassim, Zhao, Xiuhe, Reick-Mitrisin, Victoria, Schuele, Stephan, Ogren, Jennifer, Harper, Ronald M, Diehl, Beate, Bateman, Lisa, Devinsky, Orrin, Richerson, George B, Ryvlin, Philippe, and Lhatoo, Samden D
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Clinical Research ,Epilepsy ,Brain Disorders ,Prevention ,Neurodegenerative ,Neurosciences ,Lung ,Adolescent ,Adult ,Aged ,Biomarkers ,Cardiopulmonary Resuscitation ,Death ,Sudden ,Electroencephalography ,Female ,Humans ,Male ,Middle Aged ,Prospective Studies ,Sleep Apnea ,Central ,Statistics ,Nonparametric ,Video Recording ,Young Adult ,Clinical Sciences ,Cognitive Sciences ,Neurology & Neurosurgery - Abstract
ObjectiveTo characterize peri-ictal apnea and postictal asystole in generalized convulsive seizures (GCS) of intractable epilepsy.MethodsThis was a prospective, multicenter epilepsy monitoring study of autonomic and breathing biomarkers of sudden unexpected death in epilepsy (SUDEP) in patients ≥18 years old with intractable epilepsy and monitored GCS. Video-EEG, thoracoabdominal excursions, nasal airflow, capillary oxygen saturation, and ECG were analyzed.ResultsWe studied 148 GCS in 87 patients. Nineteen patients had generalized epilepsy; 65 had focal epilepsy; 1 had both; and the epileptogenic zone was unknown in 2. Ictal central apnea (ICA) preceded GCS in 49 of 121 (40.4%) seizures in 23 patients, all with focal epilepsy. Postconvulsive central apnea (PCCA) occurred in 31 of 140 (22.1%) seizures in 22 patients, with generalized, focal, or unknown epileptogenic zones. In 2 patients, PCCA occurred concurrently with asystole (near-SUDEP), with an incidence rate of 10.2 per 1,000 patient-years. One patient with PCCA died of probable SUDEP during follow-up, suggesting a SUDEP incidence rate 5.1 per 1,000 patient-years. No cases of laryngospasm were detected. Rhythmic muscle artifact synchronous with breathing was present in 75 of 147 seizures and related to stertorous breathing (odds ratio 3.856, 95% confidence interval 1.395-10.663, p = 0.009).ConclusionsPCCA occurred in both focal and generalized epilepsies, suggesting a different pathophysiology from ICA, which occurred only in focal epilepsy. PCCA was seen in 2 near-SUDEP cases and 1 probable SUDEP case, suggesting that this phenomenon may serve as a clinical biomarker of SUDEP. Larger studies are needed to validate this observation. Rhythmic postictal muscle artifact is suggestive of post-GCS breathing effort rather than a specific biomarker of laryngospasm.
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- 2019
48. Incidence, Recurrence, and Risk Factors for Peri-ictal Central Apnea and Sudden Unexpected Death in Epilepsy
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Vilella, Laura, Lacuey, Nuria, Hampson, Johnson P, Rani, MR Sandhya, Loparo, Kenneth, Sainju, Rup K, Friedman, Daniel, Nei, Maromi, Strohl, Kingman, Allen, Luke, Scott, Catherine, Gehlbach, Brian K, Zonjy, Bilal, Hupp, Norma J, Zaremba, Anita, Shafiabadi, Nassim, Zhao, Xiuhe, Reick-Mitrisin, Victoria, Schuele, Stephan, Ogren, Jennifer, Harper, Ronald M, Diehl, Beate, Bateman, Lisa M, Devinsky, Orrin, Richerson, George B, Tanner, Adriana, Tatsuoka, Curtis, and Lhatoo, Samden D
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Biomedical and Clinical Sciences ,Cardiovascular Medicine and Haematology ,Clinical Research ,Epilepsy ,Prevention ,Lung ,Brain Disorders ,Neurosciences ,Neurodegenerative ,Neurological ,Good Health and Well Being ,apnea ,breathing ,epilepsy ,ictal central apnea ,seizures ,sudden unexpected death in epilepsy ,post-convulsive central apnea ,Clinical Sciences ,Psychology ,Clinical sciences ,Biological psychology - Abstract
Introduction: Peri-ictal breathing dysfunction was proposed as a potential mechanism for SUDEP. We examined the incidence and risk factors for both ictal (ICA) and post-convulsive central apnea (PCCA) and their relationship with potential seizure severity biomarkers (i. e., post-ictal generalized EEG suppression (PGES) and recurrence. Methods: Prospective, multi-center seizure monitoring study of autonomic, and breathing biomarkers of SUDEP in adults with intractable epilepsy and monitored seizures. Video EEG, thoraco-abdominal excursions, capillary oxygen saturation, and electrocardiography were analyzed. A subgroup analysis determined the incidences of recurrent ICA and PCCA in patients with ≥2 recorded seizures. We excluded status epilepticus and obscured/unavailable video. Central apnea (absence of thoracic-abdominal breathing movements) was defined as ≥1 missed breath, and ≥5 s. ICA referred to apnea preceding or occurring along with non-convulsive seizures (NCS) or apnea before generalized convulsive seizures (GCS). Results: We analyzed 558 seizures in 218 patients (130 female); 321 seizures were NCS and 237 were GCS. ICA occurred in 180/487 (36.9%) seizures in 83/192 (43.2%) patients, all with focal epilepsy. Sleep state was related to presence of ICA [RR 1.33, CI 95% (1.08-1.64), p = 0.008] whereas extratemporal epilepsy was related to lower incidence of ICA [RR 0.58, CI 95% (0.37-0.90), p = 0.015]. ICA recurred in 45/60 (75%) patients. PCCA occurred in 41/228 (18%) of GCS in 30/134 (22.4%) patients, regardless of epilepsy type. Female sex [RR 11.30, CI 95% (4.50-28.34), p < 0.001] and ICA duration [RR 1.14 CI 95% (1.05-1.25), p = 0.001] were related to PCCA presence, whereas absence of PGES was related to absence of PCCA [0.27, CI 95% (0.16-0.47), p < 0.001]. PCCA duration was longer in males [HR 1.84, CI 95% (1.06-3.19), p = 0.003]. In 9/17 (52.9%) patients, PCCA was recurrent. Conclusion: ICA incidence is almost twice the incidence of PCCA and is only seen in focal epilepsies, as opposed to PCCA, suggesting different pathophysiologies. ICA is likely to be a recurrent semiological phenomenon of cortical seizure discharge, whereas PCCA may be a reflection of brainstem dysfunction after GCS. Prolonged ICA or PCCA may, respectively, contribute to SUDEP, as evidenced by two cases we report. Further prospective cohort studies are needed to validate these hypotheses.
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- 2019
49. iEEG-BIDS, extending the Brain Imaging Data Structure specification to human intracranial electrophysiology
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Holdgraf, Christopher, Appelhoff, Stefan, Bickel, Stephan, Bouchard, Kristofer, D’Ambrosio, Sasha, David, Olivier, Devinsky, Orrin, Dichter, Benjamin, Flinker, Adeen, Foster, Brett L, Gorgolewski, Krzysztof J, Groen, Iris, Groppe, David, Gunduz, Aysegul, Hamilton, Liberty, Honey, Christopher J, Jas, Mainak, Knight, Robert, Lachaux, Jean-Philippe, Lau, Jonathan C, Lee-Messer, Christopher, Lundstrom, Brian N, Miller, Kai J, Ojemann, Jeffrey G, Oostenveld, Robert, Petridou, Natalia, Piantoni, Gio, Pigorini, Andrea, Pouratian, Nader, Ramsey, Nick F, Stolk, Arjen, Swann, Nicole C, Tadel, François, Voytek, Bradley, Wandell, Brian A, Winawer, Jonathan, Whitaker, Kirstie, Zehl, Lyuba, and Hermes, Dora
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Biological Psychology ,Physical Sciences ,Psychology ,Brain Disorders ,Neurosciences ,1.1 Normal biological development and functioning ,Underpinning research ,Neurological ,Brain ,Datasets as Topic ,Electroencephalography ,Humans ,Information Storage and Retrieval ,Neuroimaging - Abstract
The Brain Imaging Data Structure (BIDS) is a community-driven specification for organizing neuroscience data and metadata with the aim to make datasets more transparent, reusable, and reproducible. Intracranial electroencephalography (iEEG) data offer a unique combination of high spatial and temporal resolution measurements of the living human brain. To improve internal (re)use and external sharing of these unique data, we present a specification for storing and sharing iEEG data: iEEG-BIDS.
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- 2019
50. Brainstem network disruption: A pathway to sudden unexplained death in epilepsy?
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Mueller, Susanne G, Nei, Maromi, Bateman, Lisa M, Knowlton, Robert, Laxer, Kenneth D, Friedman, Daniel, Devinsky, Orrin, and Goldman, Alica M
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Biomedical and Clinical Sciences ,Clinical Sciences ,Neurosciences ,Neurodegenerative ,Brain Disorders ,Epilepsy ,Adolescent ,Adult ,Atrophy ,Autonomic Nervous System ,Brain Stem ,Child ,Child ,Preschool ,Death ,Sudden ,Epilepsies ,Partial ,Female ,Heart Rate ,Humans ,Infant ,Magnetic Resonance Imaging ,Male ,Middle Aged ,Young Adult ,autonomic control ,brainstem ,graph analysis ,network ,SUDEP ,Cognitive Sciences ,Experimental Psychology ,Biological psychology ,Cognitive and computational psychology - Abstract
Observations in witnessed Sudden Unexpected Death in Epilepsy (SUDEP) suggest that a fatal breakdown of the central autonomic control could play a major role in SUDEP. A previous MR study found volume losses in the mesencephalon in focal epilepsy that were more severe and extended into the lower brainstem in two patients who later died of SUDEP. The aims of this study were to demonstrate an association (1) between brainstem volume loss and impaired autonomic control (reduced heart rate variability [HRV]); (2) between brainstem damage and time to SUDEP in patients who later died of SUDEP. Two populations were studied: (1) Autonomic system function population (ASF, 18 patients with focal epilepsy, 11 controls) with HRV measurements and standardized 3 T MR exams. (2) SUDEP population (26 SUDEP epilepsy patients) with clinical MRI 1-10 years before SUDEP. Deformation-based morphometry of the brainstem was used to generate profile similarity maps from the resulting Jacobian determinant maps that were further characterized by graph analysis to identify regions with excessive expansion indicating significant volume loss or atrophy. The total number of regions with excessive expansion in ASF was negatively correlated with HRV (r = -.37, p = .03), excessive volume loss in periaqueductal gray/medulla oblongata autonomic nuclei explained most of the HRV associated variation (r/r2 = -.82/.67, p
- Published
- 2018
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