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1. Brain‐age prediction: Systematic evaluation of site effects, and sample age range and size

Author

Yu, Yuetong, Cui, Hao‐Qi, Haas, Shalaila S, New, Faye, Sanford, Nicole, Yu, Kevin, Zhan, Denghuang, Yang, Guoyuan, Gao, Jia‐Hong, Wei, Dongtao, Qiu, Jiang, Banaj, Nerisa, Boomsma, Dorret I, Breier, Alan, Brodaty, Henry, Buckner, Randy L, Buitelaar, Jan K, Cannon, Dara M, Caseras, Xavier, Clark, Vincent P, Conrod, Patricia J, Crivello, Fabrice, Crone, Eveline A, Dannlowski, Udo, Davey, Christopher G, de Haan, Lieuwe, de Zubicaray, Greig I, Di Giorgio, Annabella, Fisch, Lukas, Fisher, Simon E, Franke, Barbara, Glahn, David C, Grotegerd, Dominik, Gruber, Oliver, Gur, Raquel E, Gur, Ruben C, Hahn, Tim, Harrison, Ben J, Hatton, Sean, Hickie, Ian B, Pol, Hilleke E Hulshoff, Jamieson, Alec J, Jernigan, Terry L, Jiang, Jiyang, Kalnin, Andrew J, Kang, Sim, Kochan, Nicole A, Kraus, Anna, Lagopoulos, Jim, Lazaro, Luisa, McDonald, Brenna C, McDonald, Colm, McMahon, Katie L, Mwangi, Benson, Piras, Fabrizio, Rodriguez‐Cruces, Raul, Royer, Jessica, Sachdev, Perminder S, Satterthwaite, Theodore D, Saykin, Andrew J, Schumann, Gunter, Sevaggi, Pierluigi, Smoller, Jordan W, Soares, Jair C, Spalletta, Gianfranco, Tamnes, Christian K, Trollor, Julian N, Ent, Dennis Van't, Vecchio, Daniela, Walter, Henrik, Wang, Yang, Weber, Bernd, Wen, Wei, Wierenga, Lara M, Williams, Steven CR, Wu, Mon‐Ju, Zunta‐Soares, Giovana B, Bernhardt, Boris, Thompson, Paul, Frangou, Sophia, Ge, Ruiyang, and Group, ENIGMA‐Lifespan Working

Subjects
Biological Psychology, Psychology, Neurosciences, Clinical Research, Aging, Neurological, Mental health, Humans, Adolescent, Female, Aged, Adult, Child, Young Adult, Male, Brain, Aged, 80 and over, Child, Preschool, Middle Aged, Magnetic Resonance Imaging, Neuroimaging, Sample Size, benchmarking, brain aging, brainAGE, ENIGMA‐Lifespan Working Group, Cognitive Sciences, Experimental Psychology, Biological psychology, Cognitive and computational psychology
Abstract

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.

Published
2024

2. Rasmussen’s encephalitis: structural, functional, and clinical correlates of contralesional epileptiform activity

Author

Bauer, Tobias, von Wrede, Randi D., Pujar, Suresh, Rácz, Attila, Hoppe, Christian, Baumgartner, Tobias, Varadkar, Sophia, Held, Nina R., Reiter, Johannes T., Enders, Selma, David, Bastian, Prillwitz, Conrad C., Brugues, Mar, Keil, Vera C. W., Jeub, Monika, Borger, Valeri, Sander, Josemir W., Kunz, Wolfram S., Radbruch, Alexander, Weber, Bernd, Helmstaedter, Christoph, Vatter, Hartmut, Baldeweg, Torsten, Becker, Albert J., Cross, J. Helen, Surges, Rainer, and Rüber, Theodor

Published
2024
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5. Event‐based modeling in temporal lobe epilepsy demonstrates progressive atrophy from cross‐sectional data

Author

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

Subjects
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.

Published
2022

6. Topographic divergence of atypical cortical asymmetry and atrophy patterns in temporal lobe epilepsy

Author

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

Subjects
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.

Published
2022

7. Association Between Anatomical Location of Surgically Induced Lesions and Postoperative Seizure Outcome in Temporal Lobe Epilepsy.

Author

Gleichgerrcht, Ezequiel, Drane, Daniel, Keller, Simon, Davis, Kathryn, Gross, Robert, Willie, Jon, Pedersen, Nigel, de Bezenac, Christophe, Jensen, Jens, Weber, Bernd, Kuzniecky, Ruben, and Bonilha, Leonardo

Subjects
Drug Resistant Epilepsy, Epilepsy, Temporal Lobe, Female, Humans, Magnetic Resonance Imaging, Seizures, Temporal Lobe, Treatment Outcome, White Matter
Abstract

BACKGROUND AND OBJECTIVES: To determine the association between surgical lesions of distinct gray and white structures and connections with favorable postoperative seizure outcomes. METHODS: Patients with drug-resistant temporal lobe epilepsy (TLE) from 3 epilepsy centers were included. We employed a voxel-based and connectome-based mapping approach to determine the association between favorable outcomes and surgery-induced temporal lesions. Analyses were conducted controlling for multiple confounders, including total surgical resection/ablation volume, hippocampal volumes, side of surgery, and site where the patient was treated. RESULTS: The cohort included 113 patients with TLE (54 women; 86 right-handed; mean age at seizure onset 16.5 years [SD 11.9]; 54.9% left) who were 61.1% free of disabling seizures (Engel Class 1) at follow-up. Postoperative seizure freedom in TLE was associated with (1) surgical lesions that targeted the hippocampus as well as the amygdala-piriform cortex complex and entorhinal cortices; (2) disconnection of temporal, frontal, and limbic regions through loss of white matter tracts within the uncinate fasciculus, anterior commissure, and fornix; and (3) functional disconnection of the frontal (superior and middle frontal gyri, orbitofrontal region) and temporal (superior and middle pole) lobes. DISCUSSION: Better postoperative seizure freedom is associated with surgical lesions of specific structures and connections throughout the temporal lobes. These findings shed light on the key components of epileptogenic networks in TLE and constitute a promising source of new evidence for future improvements in surgical interventions. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that for patients with TLE, postoperative seizure freedom is associated with surgical lesions of specific temporal lobe structures and connections.

Published
2022

8. Radiological identification of temporal lobe epilepsy using artificial intelligence: a feasibility study.

Author

Gleichgerrcht, Ezequiel, Munsell, Brent, Keller, Simon, Drane, Daniel, Jensen, Jens, Spampinato, M, Pedersen, Nigel, Weber, Bernd, Kuzniecky, Ruben, McDonald, Carrie, and Bonilha, Leonardo

Subjects
artificial intelligence, convoluted neural network, structural neuroimaging, temporal lobe epilepsy
Abstract

Temporal lobe epilepsy is associated with MRI findings reflecting underlying mesial temporal sclerosis. Identifying these MRI features is critical for the diagnosis and management of temporal lobe epilepsy. To date, this process relies on visual assessment by highly trained human experts (e.g. neuroradiologists, epileptologists). Artificial intelligence is increasingly recognized as a promising aid in the radiological evaluation of neurological diseases, yet its applications in temporal lobe epilepsy have been limited. Here, we applied a convolutional neural network to assess the classification accuracy of temporal lobe epilepsy based on structural MRI. We demonstrate that convoluted neural networks can achieve high accuracy in the identification of unilateral temporal lobe epilepsy cases even when the MRI had been originally interpreted as normal by experts. We show that accuracy can be potentiated by employing smoothed grey matter maps and a direct acyclic graphs approach. We further discuss the foundations for the development of computer-aided tools to assist with the diagnosis of epilepsy.

Published
2022

9. The ENIGMA‐Epilepsy working group: Mapping disease from large data sets

Author

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

Subjects
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.

Published
2022

10. Structural network alterations in focal and generalized epilepsy assessed in a worldwide ENIGMA study follow axes of epilepsy risk gene expression

Author

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

Subjects
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.

Published
2022

11. Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation

Author

Agartz, Ingrid, Asherson, Philip, Ayesa-Arriola, Rosa, Banaj, Nerisa, Banaschewski, Tobias, Baumeister, Sarah, Bertolino, Alessandro, Borgwardt, Stefan, Bourque, Josiane, Brandeis, Daniel, Breier, Alan, Buitelaar, Jan K, Cannon, Dara M, Cervenka, Simon, Conrod, Patricia J, Crespo-Facorro, Benedicto, Davey, Christopher G, de Haan, Lieuwe, de Zubicaray, Greig I, Di Giorgio, Annabella, Frodl, Thomas, Gruner, Patricia, Gur, Raquel E, Gur, Ruben C, Harrison, Ben J, Hatton, Sean N, Hickie, Ian, Howells, Fleur M, Huyser, Chaim, Jernigan, Terry L, Jiang, Jiyang, Joska, John A, Kahn, René S, Kalnin, Andrew J, Kochan, Nicole A, Koops, Sanne, Kuntsi, Jonna, Lagopoulos, Jim, Lazaro, Luisa, Lebedeva, Irina S, Lochner, Christine, Martin, Nicholas G, Mazoyer, Bernard, McDonald, Brenna C, McDonald, Colm, McMahon, Katie L, Medland, Sarah, Modabbernia, Amirhossein, Mwangi, Benson, Nakao, Tomohiro, Nyberg, Lars, Piras, Fabrizio, Portella, Maria J, Qiu, Jiang, Roffman, Joshua L, Sachdev, Perminder S, Sanford, Nicole, Satterthwaite, Theodore D, Saykin, Andrew J, Sellgren, Carl M, Sim, Kang, Smoller, Jordan W, Soares, Jair C, Sommer, Iris E, Spalletta, Gianfranco, Stein, Dan J, Thomopoulos, Sophia I, Tomyshev, Alexander S, Tordesillas-Gutiérrez, Diana, Trollor, Julian N, van 't Ent, Dennis, van den Heuvel, Odile A, van Erp, Theo GM, van Haren, Neeltje EM, Vecchio, Daniela, Veltman, Dick J, Wang, Yang, Weber, Bernd, Wei, Dongtao, Wen, Wei, Westlye, Lars T, Williams, Steven CR, Wright, Margaret J, Wu, Mon-Ju, Yu, Kevin, Ge, Ruiyang, Yu, Yuetong, Qi, Yi Xuan, Fan, Yu-nan, Chen, Shiyu, Gao, Chuntong, Haas, Shalaila S, New, Faye, Boomsma, Dorret I, Brodaty, Henry, Brouwer, Rachel M, Buckner, Randy, Caseras, Xavier, Crivello, Fabrice, Crone, Eveline A, Erk, Susanne, Fisher, Simon E, Franke, Barbara, Glahn, David C, Dannlowski, Udo, Grotegerd, Dominik, Gruber, Oliver, Hulshoff Pol, Hilleke E, Schumann, Gunter, Tamnes, Christian K, Walter, Henrik, Wierenga, Lara M, Jahanshad, Neda, Thompson, Paul M, and Frangou, Sophia

Published
2024
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12. An open presurgery MRI dataset of people with epilepsy and focal cortical dysplasia type II

Author

Schuch, Fabiane, Walger, Lennart, Schmitz, Matthias, David, Bastian, Bauer, Tobias, Harms, Antonia, Fischbach, Laura, Schulte, Freya, Schidlowski, Martin, Reiter, Johannes, Bitzer, Felix, von Wrede, Randi, Rácz, Atilla, Baumgartner, Tobias, Borger, Valeri, Schneider, Matthias, Flender, Achim, Becker, Albert, Vatter, Hartmut, Weber, Bernd, Specht-Riemenschneider, Louisa, Radbruch, Alexander, Surges, Rainer, and Rüber, Theodor

Published
2023
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14. Artificial intelligence for classification of temporal lobe epilepsy with ROI-level MRI data: A worldwide ENIGMA-Epilepsy study

Author

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

Subjects
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.

Published
2021

15. Network-based atrophy modeling in the common epilepsies: A worldwide ENIGMA study

Author

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

Subjects
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.

Published
2020

16. White matter abnormalities across different epilepsy syndromes in adults: an ENIGMA-Epilepsy study

Author

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

Subjects
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

Published
2020

17. REPLY TO NIELSEN ET AL. : Social mindfulness is associated with countries’ environmental performance and individual environmental concern

Author

Van Doesum, Niels J., Murphy, Ryan O., Gallucci, Marcello, Aharonov-Majar, Efrat, Athenstaedt, Ursula, Au, Wing Tung, Bai, Liying, Böhm, Robert, Bovina, Inna, Buchan, Nancy R., Chen, Xiao-Ping, Dumont, Kitty B., Engelmann, Jan B., Eriksson, Kimmo, Euh, Hyun, Fiedler, Susann, Friesen, Justin, Gächter, Simon, Garcia, Camilo, González, Roberto, Graf, Sylvie, Growiec, Katarzyna, Guimond, Serge, Hřebíčková, Martina, Immer-Bernold, Elizabeth, Joireman, Jeff, Karagonlar, Gokhan, Kawakami, Kerry, Kiyonari, Toko, Kou, Yu, Kyrtsis, Alexandros-Andreas, Lay, Siugmin, Leonardelli, Geoffrey J., Li, Norman P., Li, Yang, Maciejovsky, Boris, Manesi, Zoi, Mashuri, Ali, Mok, Aurelia, Moser, Karin S., Moták, Ladislav, Netedu, Adrian, Platow, Michael J., Raczka-Winkler, Karolina, Folmer, Christopher P. Reinders, Reyna, Cecilia, Romano, Angelo, Shalvi, Shaul, Simão, Cláudia, Stivers, Adam W., Strimling, Pontus, Tsirbas, Yannis, Utz, Sonja, van der Meij, Leander, Waldzus, Sven, Wang, Yiwen, Weber, Bernd, Weisel, Ori, Wildschut, Tim, Winter, Fabian, Wu, Junhui, Yong, Jose C., and Van Lange, Paul A. M.

Published
2022

19. REPLY TO KOMATSU ET AL. : From local social mindfulness to global sustainability efforts?

Author

Van Doesum, Niels J., Murphy, Ryan O., Galluccie, Marcello, Aharonov-Majar, Efrat, Athenstaedt, Ursula, Au, Wing Tung, Baii, Liying, Böhm, Robert, Bovina, Inna, Buchan, Nancy R., Chen, Xiao-Ping, Dumont, Kitty B., Engelmann, Jan B., Eriksson, Kimmo, Euh, Hyun, Fiedler, Susann, Friesen, Justin, Gächter, Simon, Garcia, Camilo, González, Roberto, Graf, Sylvie, Growieca, Katarzyna, Guimond, Serge, Hřebíčková, Martina, Immer-Bernold, Elizabeth, Joireman, Jeff, Karagonlar, Gokhan, Kawakami, Kerry, Kiyonari, Toko, Kou, Yu, Kyrtsis, Alexandros-Andreas, Lay, Siugmin, Leonardelli, Geoffrey J., Li, Norman P., Lin, Yang, Maciejovsky, Boris, Manesi, Zoi, Mashuri, Ali, Mok, Aurelia, Moser, Karin S., Moták, Ladislav, Netedu, Adrian, Platow, Michael J., Raczka-Winkler, Karolina, Folmer, Christopher P. Reinders, Reynab, Cecilia, Romano, Angelo, Shalvi, Shaul, Simão, Cláudia, Stivers, Adam W., Strimling, Pontus, Tsirbas, Yannis, Utz, Sonja, van der Meijh, Leander, Waldzus, Sven, Wang, Yiwen, Weber, Bernd, Weisel, Ori, Wildschut, Tim, Winter, Fabian, Wu, Junhui, Yong, Jose C., and Van Lange, Paul A. M.

Published
2022

21. Social mindfulness and prosociality vary across the globe

Author

Van Doesum, Niels J., Murphy, Ryan O., Gallucci, Marcello, Aharonov-Majar, Efrat, Athenstaedt, Ursula, Au, Wing Tung, Bai, Liying, Böhm, Robert, Bovina, Inna, Buchan, Nancy R., Chen, Xiao-Ping, Dumont, Kitty B., Engelmann, Jan B., Eriksson, Kimmo, Euh, Hyun, Fiedler, Susann, Friesen, Justin, Gächter, Simon, Garcia, Camilo, González, Roberto, Graf, Sylvie, Growiec, Katarzyna, Guimond, Serge, Hřebíčková, Martina, Immer-Bernold, Elizabeth, Joireman, Jeff, Karagonlar, Gokhan, Kawakami, Kerry, Kiyonari, Toko, Kou, Yu, Kuhlman, D. Michael, Kyrtsis, Alexandros-Andreas, Lay, Siugmin, Leonardelli, Geoffrey J., Li, Norman P., Li, Yang, Maciejovsky, Boris, Manesi, Zoi, Mashuri, Ali, Mok, Aurelia, Moser, Karin S., Moták, Ladislav, Netedu, Adrian, Pammi, Chandrasekhar, Platow, Michael J., Raczka-Winkler, Karolina, Folmer, Christopher P. Reinders, Reyna, Cecilia, Romano, Angelo, Shalvi, Shaul, Simão, Cláudia, Stivers, Adam W., Strimling, Pontus, Tsirbas, Yannis, Utz, Sonja, van der Meij, Leander, Waldzus, Sven, Wang, Yiwen, Weber, Bernd, Weisel, Ori, Wildschut, Tim, Winter, Fabian, Wu, Junhui, Yong, Jose C., and Van Lange, Paul A. M.

Published
2021

22. Sistemas de cogeneración: aplicaciones y posible obsolescencia frente a otras alternativas.

Author

Weber, Bernd, Ayala Mercado, Isis Dafne, and Bernhardt, Heinz

Subjects
*RENEWABLE energy transition (Government policy), *SECOND law of thermodynamics, *HEAT pumps, *ENERGY consumption, *CLEAN energy
Abstract

Technologies used to meet the heat demands of the residential and industrial sectors are evaluated. An analysis based on the second law of thermodynamics using the heating coefficient, showed that cogeneration systems, considered to be clean energy, are becoming obsolete. Heat pumps, though currently not popular, could potentially be good alternatives for heating while complementing the transition to renewable energy. Traditional energy systems have been developed to meet the needs of the consumer, prioritizing the cost savings. A thorough analysis of primary energy consumption is required because burning fossil fuels contributes to additional costs of climate change. [ABSTRACT FROM AUTHOR]

Published
2025
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23. Higher Validity, Lower Radiation: A New Ictal Single‐Photon Emission Computed Tomography Framework.

Author

Bitzer, Felix, Walger, Lennart, Bauer, Tobias, Schulte, Freya, Gaertner, Florian C., Schmitz, Matthias, Schidlowski, Martin, von Wrede, Randi, Rácz, Attila, Baumgartner, Tobias, Gnatkovsky, Vadym, Paech, Daniel, Borger, Valeri, Vatter, Hartmut, Weber, Bernd, Michels, Dominik L., Stöcker, Tony, Essler, Markus, Sander, Josemir W., and Radbruch, Alexander

Subjects
SPIN labels, IMAGE analysis, EPILEPSY surgery, PERFUSION imaging, EUCLIDEAN distance
Abstract

Objective: To assess whether arterial spin labeling perfusion images of healthy controls can enhance ictal single‐photon emission computed tomography analysis and whether the acquisition of the interictal image can be omitted. Methods: We developed 2 pipelines: The first uses ictal and interictal images and compares these to single‐photon emission computed tomography and arterial spin labeling of healthy controls. The second pipeline uses only the ictal image and the analogous healthy controls. Both pipelines were compared to the gold standard analysis and evaluated on data of individuals with epilepsy who underwent ictal single‐photon emission computed tomography imaging during presurgical evaluation between 2010 and 2022. Fifty healthy controls prospectively underwent arterial spin labeling imaging. The correspondence between the detected hyperperfusion and the postoperative resection cavity or the presumably affected lobe was assessed using Dice score and mean Euclidean distance. Additionally, the outcomes of the pipelines were automatically assigned to 1 of 5 concordance categories. Results: Inclusion criteria were met by 43 individuals who underwent epilepsy surgery and by 73 non‐surgical individuals with epilepsy. Compared to the gold standard analysis, both pipelines resulted in significantly higher Dice scores and lower mean distances (p < 0.05). The combination of both provided localizing results in 85/116 cases, compared to 54/116 generated by the current gold standard analysis and the ictal image alone produced localizing results in 60/116 (52%) cases. Interpretation: We propose a new ictal single‐photon emission computed tomography protocol; it finds relevantly more ictal hyperperfusion, and halves the radiation dose in about half of the individuals. ANN NEUROL 2024;96:1160–1173 [ABSTRACT FROM AUTHOR]

Published
2024
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26. Artificial intelligence for classification of temporal lobe epilepsy with ROI-level MRI data: A worldwide ENIGMA-Epilepsy study

Author

Altmann, Andre, Depondt, Chantal, Galovic, Marian, Thomopoulos, Sophia I., Wiest, Roland, Gleichgerrcht, Ezequiel, Munsell, Brent C., Alhusaini, Saud, Alvim, Marina K.M., 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 A.K., 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., Xian Rao, Jun, Richardson, Mark P., Rodríguez-Cruces, Raúl, Rüber, Theodor, Sinclair, Ben, Soltanian-Zadeh, Hamid, Stein, Dan J., Striano, Pasquale, Taylor, Peter N., Thomas, Rhys H., Elisabetta Vaudano, Anna, Vivash, Lucy, von Podewills, Felix, Vos, Sjoerd B., Weber, Bernd, Yao, Yi, Lin Yasuda, Clarissa, Zhang, Junsong, Thompson, Paul M., Sisodiya, Sanjay M., McDonald, Carrie R., and Bonilha, Leonardo

Published
2021
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32. Impact of Synbiotic Intake on Liver Metabolism in Metabolically Healthy Participants and Its Potential Preventive Effect on Metabolic-Dysfunction-Associated Fatty Liver Disease (MAFLD): A Randomized, Placebo-Controlled, Double-Blinded Clinical Trial

Author

Mantri, Aakash, primary, Köhlmoos, Anika, additional, Schelski, Daniela Stephanie, additional, Seel, Waldemar, additional, Stoffel-Wagner, Birgit, additional, Krawitz, Peter, additional, Stehle, Peter, additional, Holst, Jens Juul, additional, Weber, Bernd, additional, Koban, Leonie, additional, Plassmann, Hilke, additional, and Simon, Marie-Christine, additional

Published
2024
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33. A worldwide ENIGMA study on epilepsy-related gray and white matter compromise across the adult lifespan

Author

Chen, Judy, primary, Ngo, Alexander, additional, Rodríguez-Cruces, Raúl, additional, Royer, Jessica, additional, Caligiuri, Maria Eugenia, additional, Gambardella, Antonio, additional, Concha, Luis, additional, Keller, Simon S., additional, Cendes, Fernando, additional, Yasuda, Clarissa L., additional, Alvim, Marina K. M., additional, Bonilha, Leonardo, additional, Gleichgerrcht, Ezequiel, additional, Focke, Niels K., additional, Kreilkamp, Barbara, additional, Domin, Martin, additional, von Podewils, Felix, additional, Langner, Soenke, additional, Rummel, Christian, additional, Wiest, Roland, additional, Martin, Pascal, additional, Kotikalapudi, Raviteja, additional, Bender, Benjamin, additional, O’Brien, Terence J., additional, Sinclair, Benjamin, additional, Vivash, Lucy, additional, Kwan, Patrick, additional, Desmond, Patricia M., additional, Lui, Elaine, additional, Duma, Gian Marco, additional, Bonanni, Paolo, additional, Ballerini, Alice, additional, Vaudano, Anna Elisabetta, additional, Meletti, Stefano, additional, Tondelli, Manuela, additional, Alhusaini, Saud, additional, Doherty, Colin P., additional, Cavalleri, Gianpiero L., additional, Delanty, Norman, additional, Kälviäinen, Reetta, additional, Jackson, Graeme D., additional, Kowalczyk, Magdalena, additional, Mascalchi, Mario, additional, Semmelroch, Mira, additional, Thomas, Rhys H., additional, Soltanian-Zadeh, Hamid, additional, Davoodi-Bojd, Esmaeil, additional, Zhang, Junsong, additional, Lenge, Matteo, additional, Guerrini, Renzo, additional, Bartolini, Emanuele, additional, Hamandi, Khalid, additional, Foley, Sonya, additional, Rüber, Theodor, additional, Bauer, Tobias, additional, Weber, Bernd, additional, Caldairou, Benoit, additional, Depondt, Chantal, additional, Absil, Julie, additional, Carr, Sarah J. A., additional, Abela, Eugenio, additional, Richardson, Mark P., additional, Devinsky, Orrin, additional, Pardoe, Heath, additional, Severino, Mariasavina, additional, Striano, Pasquale, additional, Tortora, Domenico, additional, Kaestner, Erik, additional, Hatton, Sean N., additional, Arienzo, Donatello, additional, Vos, Sjoerd B., additional, Ryten, Mina, additional, Taylor, Peter N., additional, Duncan, John S., additional, Whelan, Christopher D., additional, Galovic, Marian, additional, Winston, Gavin P., additional, Thomopoulos, Sophia I., additional, Thompson, Paul M., additional, Sisodiya, Sanjay M., additional, Labate, Angelo, additional, McDonald, Carrie R., additional, Caciagli, Lorenzo, additional, Bernasconi, Neda, additional, Bernasconi, Andrea, additional, Larivière, Sara, additional, Schrader, Dewi, additional, and Bernhardt, Boris C., additional

Published
2024
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34. Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation

Author

Ge, Ruiyang, primary, Yu, Yuetong, additional, Qi, Yi Xuan, additional, Fan, Yu-nan, additional, Chen, Shiyu, additional, Gao, Chuntong, additional, Haas, Shalaila S, additional, New, Faye, additional, Boomsma, Dorret I, additional, Brodaty, Henry, additional, Brouwer, Rachel M, additional, Buckner, Randy, additional, Caseras, Xavier, additional, Crivello, Fabrice, additional, Crone, Eveline A, additional, Erk, Susanne, additional, Fisher, Simon E, additional, Franke, Barbara, additional, Glahn, David C, additional, Dannlowski, Udo, additional, Grotegerd, Dominik, additional, Gruber, Oliver, additional, Hulshoff Pol, Hilleke E, additional, Schumann, Gunter, additional, Tamnes, Christian K, additional, Walter, Henrik, additional, Wierenga, Lara M, additional, Jahanshad, Neda, additional, Thompson, Paul M, additional, Frangou, Sophia, additional, Agartz, Ingrid, additional, Asherson, Philip, additional, Ayesa-Arriola, Rosa, additional, Banaj, Nerisa, additional, Banaschewski, Tobias, additional, Baumeister, Sarah, additional, Bertolino, Alessandro, additional, Borgwardt, Stefan, additional, Bourque, Josiane, additional, Brandeis, Daniel, additional, Breier, Alan, additional, Buitelaar, Jan K, additional, Cannon, Dara M, additional, Cervenka, Simon, additional, Conrod, Patricia J, additional, Crespo-Facorro, Benedicto, additional, Davey, Christopher G, additional, de Haan, Lieuwe, additional, de Zubicaray, Greig I, additional, Di Giorgio, Annabella, additional, Frodl, Thomas, additional, Gruner, Patricia, additional, Gur, Raquel E, additional, Gur, Ruben C, additional, Harrison, Ben J, additional, Hatton, Sean N, additional, Hickie, Ian, additional, Howells, Fleur M, additional, Huyser, Chaim, additional, Jernigan, Terry L, additional, Jiang, Jiyang, additional, Joska, John A, additional, Kahn, René S, additional, Kalnin, Andrew J, additional, Kochan, Nicole A, additional, Koops, Sanne, additional, Kuntsi, Jonna, additional, Lagopoulos, Jim, additional, Lazaro, Luisa, additional, Lebedeva, Irina S, additional, Lochner, Christine, additional, Martin, Nicholas G, additional, Mazoyer, Bernard, additional, McDonald, Brenna C, additional, McDonald, Colm, additional, McMahon, Katie L, additional, Medland, Sarah, additional, Modabbernia, Amirhossein, additional, Mwangi, Benson, additional, Nakao, Tomohiro, additional, Nyberg, Lars, additional, Piras, Fabrizio, additional, Portella, Maria J, additional, Qiu, Jiang, additional, Roffman, Joshua L, additional, Sachdev, Perminder S, additional, Sanford, Nicole, additional, Satterthwaite, Theodore D, additional, Saykin, Andrew J, additional, Sellgren, Carl M, additional, Sim, Kang, additional, Smoller, Jordan W, additional, Soares, Jair C, additional, Sommer, Iris E, additional, Spalletta, Gianfranco, additional, Stein, Dan J, additional, Thomopoulos, Sophia I, additional, Tomyshev, Alexander S, additional, Tordesillas-Gutiérrez, Diana, additional, Trollor, Julian N, additional, van 't Ent, Dennis, additional, van den Heuvel, Odile A, additional, van Erp, Theo GM, additional, van Haren, Neeltje EM, additional, Vecchio, Daniela, additional, Veltman, Dick J, additional, Wang, Yang, additional, Weber, Bernd, additional, Wei, Dongtao, additional, Wen, Wei, additional, Westlye, Lars T, additional, Williams, Steven CR, additional, Wright, Margaret J, additional, Wu, Mon-Ju, additional, and Yu, Kevin, additional

Published
2024
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35. Patterns of subregional cerebellar atrophy across epilepsy syndromes: An ENIGMA‐Epilepsy study

Author

Kerestes, Rebecca, primary, Perry, Andrew, additional, Vivash, Lucy, additional, O'Brien, Terence J., additional, Alvim, Marina K. M., additional, Arienzo, Donatello, additional, Aventurato, Ítalo K., additional, Ballerini, Alice, additional, Baltazar, Gabriel F., additional, Bargalló, Núria, additional, Bender, Benjamin, additional, Brioschi, Ricardo, additional, Bürkle, Eva, additional, Caligiuri, Maria Eugenia, additional, Cendes, Fernando, additional, de Tisi, Jane, additional, Duncan, John S., additional, Engel, Jerome P., additional, Foley, Sonya, additional, Fortunato, Francesco, additional, Gambardella, Antonio, additional, Giacomini, Thea, additional, Guerrini, Renzo, additional, Hall, Gerard, additional, Hamandi, Khalid, additional, Ives‐Deliperi, Victoria, additional, João, Rafael B., additional, Keller, Simon S., additional, Kleiser, Benedict, additional, Labate, Angelo, additional, Lenge, Matteo, additional, Marotta, Cassandra, additional, Martin, Pascal, additional, Mascalchi, Mario, additional, Meletti, Stefano, additional, Owens‐Walton, Conor, additional, Parodi, Costanza B., additional, Pascual‐Diaz, Saül, additional, Powell, David, additional, Rao, Jun, additional, Rebsamen, Michael, additional, Reiter, Johannes, additional, Riva, Antonella, additional, Rüber, Theodor, additional, Rummel, Christian, additional, Scheffler, Freda, additional, Severino, Mariasavina, additional, Silva, Lucas S., additional, Staba, Richard J., additional, Stein, Dan J., additional, Striano, Pasquale, additional, Taylor, Peter N., additional, Thomopoulos, Sophia I., additional, Thompson, Paul M., additional, Tortora, Domenico, additional, Vaudano, Anna Elisabetta, additional, Weber, Bernd, additional, Wiest, Roland, additional, Winston, Gavin P., additional, Yasuda, Clarissa L., additional, Zheng, Hong, additional, McDonald, Carrie R., additional, Sisodiya, Sanjay M., additional, and Harding, Ian H., additional

Published
2024
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37. Combining baseline characteristics to disentangle response differences to disorder-specific versus supportive psychotherapy in patients with persistent depressive disorder

Author

Serbanescu, Ilinca, Walter, Henrik, Schnell, Knut, Kessler, Henrik, Weber, Bernd, Drost, Sarah, Groß, Magdalena, Neudeck, Peter, Klein, Jan Philipp, Assmann, Nele, Zobel, Ingo, Backenstrass, Matthias, Hautzinger, Martin, Meister, Ramona, Härter, Martin, Schramm, Elisabeth, and Schoepf, Dieter

Published
2020
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38. Impaired cognitive performance under psychosocial stress in cannabis-dependent men is associated with attenuated precuneus activity

Author

Zhao, Weihua, Zimmermann, Kaeli, Zhou, Xinqi, Zhou, Feng, Fu, Meina, Dernbach, Christian, Scheele, Dirk, Weber, Bernd, Eckstein, Monika, Hurlemann, Rene, Kendrick, Keith M., and Becker, Benjamin

Subjects
Neural circuitry -- Laws, regulations and rules -- Psychological aspects, Substance abuse -- Laws, regulations and rules -- Psychological aspects, Marijuana -- Laws, regulations and rules -- Psychological aspects, Addiction, Government regulation, Health, Psychology and mental health
Abstract

Background: Deficient regulation of stress plays an important role in the escalation of substance use, addiction and relapse. Accumulating evidence suggests dysregulations in cognitive and reward-related processes and the underlying neural circuitry in cannabis dependence. However, despite the important regulatory role of the endocannabinoid system in the stress response, associations between chronic cannabis use and altered stress processing at the neural level have not been systematically examined. Methods: Against this background, the present functional MRI study examined psychosocial stress processing in cannabis-dependent men (n = 28) and matched controls (n = 23) using an established stress-induction paradigm (Montreal Imaging Stress Task) that combines computerized (adaptive) mental arithmetic challenges with social evaluative threat. Results: During psychosocial stress exposure, but not the no-stress condition, cannabis users demonstrated impaired performance relative to controls. In contrast, levels of experienced stress and cardiovascular stress responsivity did not differ from controls. Functional MRI data revealed that stress-induced performance deteriorations in cannabis users was accompanied by decreased precuneus activity and increased connectivity of this region with the superior frontal gyrus. Limitations: Only male cannabis-dependent users were examined; the generalizability in female users remains to be determined. Conclusion: Together, the present findings provide first evidence for exaggerated stress-induced cognitive performance deteriorations in cannabis users. The neural data suggest that deficient stress-related recruitment of the precuneus may be associated with the deterioration of performance at the behavioural level., Introduction Drug addiction has been conceptualized as a chronic and relapsing brain disorder. At the symptomatic level, the condition is characterized by escalating drug intake, progressive loss of behavioural control, [...]

Published
2020
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39. Brain-age prediction:Systematic evaluation of site effects, and sample age range and size

Author

Yu, Yuetong, Cui, Hao‐Qi, Haas, Shalaila S., New, Faye, Sanford, Nicole, Yu, Kevin, Zhan, Denghuang, Yang, Guoyuan, Gao, Jia‐Hong, Wei, Dongtao, Qiu, Jiang, Banaj, Nerisa, Boomsma, Dorret I., Breier, Alan, Brodaty, Henry, Buckner, Randy L., Buitelaar, Jan K., Cannon, Dara M., Caseras, Xavier, Clark, Vincent P., Conrod, Patricia J., Crivello, Fabrice, Crone, Eveline A., Dannlowski, Udo, Davey, Christopher G., de Haan, Lieuwe, de Zubicaray, Greig I., Di Giorgio, Annabella, Fisch, Lukas, Fisher, Simon E., Franke, Barbara, Glahn, David C., Grotegerd, Dominik, Gruber, Oliver, Gur, Raquel E., Gur, Ruben C., Hahn, Tim, Harrison, Ben J., Hatton, Sean, Hickie, Ian B., Hulshoff Pol, Hilleke E., Jamieson, Alec J., Jernigan, Terry L., Jiang, Jiyang, Kalnin, Andrew J., Kang, Sim, Kochan, Nicole A., Kraus, Anna, Lagopoulos, Jim, Lazaro, Luisa, McDonald, Brenna C., McDonald, Colm, McMahon, Katie L., Mwangi, Benson, Piras, Fabrizio, Rodriguez‐Cruces, Raul, Royer, Jessica, Sachdev, Perminder S., Satterthwaite, Theodore D., Saykin, Andrew J., Schumann, Gunter, Sevaggi, Pierluigi, Smoller, Jordan W., Soares, Jair C., Spalletta, Gianfranco, Tamnes, Christian K., Trollor, Julian N., Van't Ent, Dennis, Vecchio, Daniela, Walter, Henrik, Wang, Yang, Weber, Bernd, Wen, Wei, Wierenga, Lara M., Williams, Steven C. R., Wu, Mon‐Ju, Zunta‐Soares, Giovana B., Bernhardt, Boris, Thompson, Paul, Frangou, Sophia, Ge, Ruiyang, Yu, Yuetong, Cui, Hao‐Qi, Haas, Shalaila S., New, Faye, Sanford, Nicole, Yu, Kevin, Zhan, Denghuang, Yang, Guoyuan, Gao, Jia‐Hong, Wei, Dongtao, Qiu, Jiang, Banaj, Nerisa, Boomsma, Dorret I., Breier, Alan, Brodaty, Henry, Buckner, Randy L., Buitelaar, Jan K., Cannon, Dara M., Caseras, Xavier, Clark, Vincent P., Conrod, Patricia J., Crivello, Fabrice, Crone, Eveline A., Dannlowski, Udo, Davey, Christopher G., de Haan, Lieuwe, de Zubicaray, Greig I., Di Giorgio, Annabella, Fisch, Lukas, Fisher, Simon E., Franke, Barbara, Glahn, David C., Grotegerd, Dominik, Gruber, Oliver, Gur, Raquel E., Gur, Ruben C., Hahn, Tim, Harrison, Ben J., Hatton, Sean, Hickie, Ian B., Hulshoff Pol, Hilleke E., Jamieson, Alec J., Jernigan, Terry L., Jiang, Jiyang, Kalnin, Andrew J., Kang, Sim, Kochan, Nicole A., Kraus, Anna, Lagopoulos, Jim, Lazaro, Luisa, McDonald, Brenna C., McDonald, Colm, McMahon, Katie L., Mwangi, Benson, Piras, Fabrizio, Rodriguez‐Cruces, Raul, Royer, Jessica, Sachdev, Perminder S., Satterthwaite, Theodore D., Saykin, Andrew J., Schumann, Gunter, Sevaggi, Pierluigi, Smoller, Jordan W., Soares, Jair C., Spalletta, Gianfranco, Tamnes, Christian K., Trollor, Julian N., Van't Ent, Dennis, Vecchio, Daniela, Walter, Henrik, Wang, Yang, Weber, Bernd, Wen, Wei, Wierenga, Lara M., Williams, Steven C. R., Wu, Mon‐Ju, Zunta‐Soares, Giovana B., Bernhardt, Boris, Thompson, Paul, Frangou, Sophia, and Ge, Ruiyang

Abstract

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5–90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8–80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9–25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5–40 and 40–90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.

Published
2024

40. Impact of Synbiotic Intake on Liver Metabolism in Metabolically Healthy Participants and Its Potential Preventive Effect on Metabolic-Dysfunction-Associated Fatty Liver Disease (MAFLD):A Randomized, Placebo-Controlled, Double-Blinded Clinical Trial

Author

Mantri, Aakash, Köhlmoos, Anika, Schelski, Daniela Stephanie, Seel, Waldemar, Stoffel-Wagner, Birgit, Krawitz, Peter, Stehle, Peter, Holst, Jens Juul, Weber, Bernd, Koban, Leonie, Plassmann, Hilke, Simon, Marie Christine, Mantri, Aakash, Köhlmoos, Anika, Schelski, Daniela Stephanie, Seel, Waldemar, Stoffel-Wagner, Birgit, Krawitz, Peter, Stehle, Peter, Holst, Jens Juul, Weber, Bernd, Koban, Leonie, Plassmann, Hilke, and Simon, Marie Christine

Abstract

Synbiotics modulate the gut microbiome and contribute to the prevention of liver diseases such as metabolic-dysfunction-associated fatty liver disease (MAFLD). This study aimed to evaluate the effect of a randomized, placebo-controlled, double-blinded seven-week intervention trial on the liver metabolism in 117 metabolically healthy male participants. Anthropometric data, blood parameters, and stool samples were analyzed using linear mixed models. After seven weeks of intervention, there was a significant reduction in alanine aminotransferase (ALT) in the synbiotic group compared to the placebo group (-14.92%, CI: -26.60--3.23%, p = 0.013). A stratified analysis according to body fat percentage revealed a significant decrease in ALT (-20.70%, CI: -40.88--0.53%, p = 0.045) in participants with an elevated body fat percentage. Further, a significant change in microbiome composition (1.16, CI: 0.06-2.25, p = 0.039) in this group was found, while the microbial composition remained stable upon intervention in the group with physiological body fat. The 7-week synbiotic intervention reduced ALT levels, especially in participants with an elevated body fat percentage, possibly due to modulation of the gut microbiome. Synbiotic intake may be helpful in delaying the progression of MAFLD and could be used in addition to the recommended lifestyle modification therapy.

Published
2024

45. Neuroeconomics

Author

Fiedler, Susann, Ettinger, Ulrich, Weber, Bernd, Reuter, Martin, Series Editor, Montag, Christian, Series Editor, Klein, Christoph, editor, and Ettinger, Ulrich, editor

Published
2019
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