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1. Automatic rating of incomplete hippocampal inversions evaluated across multiple cohorts

Author

Hemforth, Lisa, Couvy-Duchesne, Baptiste, De Matos, Kevin, Brianceau, Camille, Joulot, Matthieu, Banaschewski, Tobias, Bokde, Arun L. W., Desrivières, Sylvane, Flor, Herta, Grigis, Antoine, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Brühl, Rüdiger, Martinot, Jean-Luc, Martinot, Marie-Laure Paillère, Artiges, Eric, Papadopoulos, Dimitri, Lemaitre, Herve, Paus, Tomas, Poustka, Luise, Hohmann, Sarah, Holz, Nathalie, Fröhner, Juliane H., Smolka, Michael N., Vaidya, Nilakshi, Walter, Henrik, Whelan, Robert, Schumann, Gunter, Büchel, Christian, Poline, JB, Itterman, Bernd, Frouin, Vincent, Martin, Alexandre, group, IMAGEN study, Cury, Claire, and Colliot, Olivier

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Quantitative Biology - Neurons and Cognition
Abstract

Incomplete Hippocampal Inversion (IHI), sometimes called hippocampal malrotation, is an atypical anatomical pattern of the hippocampus found in about 20% of the general population. IHI can be visually assessed on coronal slices of T1 weighted MR images, using a composite score that combines four anatomical criteria. IHI has been associated with several brain disorders (epilepsy, schizophrenia). However, these studies were based on small samples. Furthermore, the factors (genetic or environmental) that contribute to the genesis of IHI are largely unknown. Large-scale studies are thus needed to further understand IHI and their potential relationships to neurological and psychiatric disorders. However, visual evaluation is long and tedious, justifying the need for an automatic method. In this paper, we propose, for the first time, to automatically rate IHI. We proceed by predicting four anatomical criteria, which are then summed up to form the IHI score, providing the advantage of an interpretable score. We provided an extensive experimental investigation of different machine learning methods and training strategies. We performed automatic rating using a variety of deep learning models (conv5-FC3, ResNet and SECNN) as well as a ridge regression. We studied the generalization of our models using different cohorts and performed multi-cohort learning. We relied on a large population of 2,008 participants from the IMAGEN study, 993 and 403 participants from the QTIM/QTAB studies as well as 985 subjects from the UKBiobank. We showed that deep learning models outperformed a ridge regression. We demonstrated that the performances of the conv5-FC3 network were at least as good as more complex networks while maintaining a low complexity and computation time. We showed that training on a single cohort may lack in variability while training on several cohorts improves generalization., Comment: Accepted for publication at the Journal of Machine Learning for Biomedical Imaging (MELBA) https://melba-journal.org/2024:016

Published
2024
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2. Regional patterns of human cortex development correlate with underlying neurobiology

Author

Lotter, Leon D., Saberi, Amin, Hansen, Justine Y., Misic, Bratislav, Paquola, Casey, Barker, Gareth J., Bokde, Arun L. W., Desrivières, Sylvane, Flor, Herta, Grigis, Antoine, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Brühl, Rüdiger, Martinot, Jean-Luc, Paillère, Marie-Laure, Artiges, Eric, Papadopoulos Orfanos, Dimitri, Paus, Tomáš, Poustka, Luise, Hohmann, Sarah, Fröhner, Juliane H., Smolka, Michael N., Vaidya, Nilakshi, Walter, Henrik, Whelan, Robert, Schumann, Gunter, Nees, Frauke, Banaschewski, Tobias, Eickhoff, Simon B., and Dukart, Juergen

Published
2024
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3. Investigating grey matter volumetric trajectories through the lifespan at the individual level

Author

Shi, Runye, Xiang, Shitong, Jia, Tianye, Robbins, Trevor W., Kang, Jujiao, Banaschewski, Tobias, Barker, Gareth J., Bokde, Arun L. W., Desrivières, Sylvane, Flor, Herta, Grigis, Antoine, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Brühl, Rüdiger, Martinot, Jean-Luc, Martinot, Marie-Laure Paillère, Artiges, Eric, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Paus, Tomáš, Poustka, Luise, Hohmann, Sarah, Millenet, Sabina, Fröhner, Juliane H., Smolka, Michael N., Vaidya, Nilakshi, Walter, Henrik, Whelan, Robert, Schumann, Gunter, Lin, Xiaolei, Sahakian, Barbara J., and Feng, Jianfeng

Published
2024
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4. Assessing general versus specific liability for externalizing problems in adolescence: Concurrent and prospective prediction of symptoms of conduct disorder, ADHD, and substance use.

Author

Perkins, Emily, Foell, Jens, Drislane, Laura, Brislin, Sarah, Frick, Paul, Yancey, James, Soto, Elia, Ganley, Colleen, Keel, Pamela, Sica, Claudio, Flor, Herta, Nees, Frauke, Banaschewski, Tobias, Bokde, Arun, Desrivières, Sylvane, Grigis, Antoine, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Ittermann, Bernd, Martinot, Jean-Luc, Paillère Martinot, Marie-Laure, Artiges, Eric, Papadopoulos Orfanos, Dimitri, Poustka, Luise, Hohmann, Sarah, Fröhner, Juliane, Smolka, Michael, Walter, Henrik, Whelan, Robert, Schumann, Gunter, Patrick, Christopher, and Joyner, Keanan

Subjects
Adolescent, Alcoholism, Attention Deficit Disorder with Hyperactivity, Conduct Disorder, Female, Humans, Male, Prospective Studies, Substance-Related Disorders
Abstract

This study explored the generality versus specificity of two trait-liability factors for externalizing problems-disinhibition and callousness-in the concurrent and prospective prediction of symptoms of conduct disorder, attention-deficit/hyperactivity disorder (ADHD), and substance use (i.e., alcohol use disorder and history of illicit substance use). Disinhibition involves an impulsive, unrestrained cognitive-behavioral style; callousness entails a dispositional lack of social-emotional sensitivity. Participants were European adolescents from the multisite IMAGEN project who completed questionnaires and clinical interviews at ages 14 (N = 1,504, Mage = 14.41, 51.13% female) and 16 (N = 1,407, Mage = 16.46, 51.88% female). Disinhibition was related concurrently and prospectively to greater symptoms of conduct disorder, ADHD, and alcohol use disorder; higher scores on a general externalizing factor; and greater likelihood of having tried an illicit substance. Callousness was selectively related to greater conduct disorder symptoms. These findings indicate disinhibition confers broad liability for externalizing spectrum disorders, perhaps due to its affiliated deficits in executive function. In contrast, callousness appears to represent more specific liability for antagonistic (aggressive/exploitative) forms of externalizing, as exemplified by antisocial behavior. Results support the utility of developmental-ontogenetic and hierarchical-dimensional models of psychopathology and have important implications for early assessment of risk for externalizing problems. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Published
2022

5. Multi-feature computational framework for combined signatures of dementia in underrepresented settings.

Author

Moguilner, Sebastian, Birba, Agustina, Fittipaldi, Sol, Gonzalez-Campo, Cecilia, Tagliazucchi, Enzo, Reyes, Pablo, Matallana, Diana, Parra, Mario, Slachevsky, Andrea, Farías, Gonzalo, Cruzat, Josefina, García, Adolfo, Eyre, Harris, La Joie, Renaud, Rabinovici, Gil, Whelan, Robert, and Ibáñez, Agustín

Subjects
feature selection, harmonization, machine learning, multimodal neuroimaging, neurodegeneration, Alzheimer Disease, Bayes Theorem, Biomarkers, Brain, Frontotemporal Dementia, Humans, Magnetic Resonance Imaging, Neuropsychological Tests
Abstract

Objective.The differential diagnosis of behavioral variant frontotemporal dementia (bvFTD) and Alzheimers disease (AD) remains challenging in underrepresented, underdiagnosed groups, including Latinos, as advanced biomarkers are rarely available. Recent guidelines for the study of dementia highlight the critical role of biomarkers. Thus, novel cost-effective complementary approaches are required in clinical settings.Approach. We developed a novel framework based on a gradient boosting machine learning classifier, tuned by Bayesian optimization, on a multi-feature multimodal approach (combining demographic, neuropsychological, magnetic resonance imaging (MRI), and electroencephalography/functional MRI connectivity data) to characterize neurodegeneration using site harmonization and sequential feature selection. We assessed 54 bvFTD and 76 AD patients and 152 healthy controls (HCs) from a Latin American consortium (ReDLat).Main results. The multimodal model yielded high area under the curve classification values (bvFTD patients vs HCs: 0.93 (±0.01); AD patients vs HCs: 0.95 (±0.01); bvFTD vs AD patients: 0.92 (±0.01)). The feature selection approach successfully filtered non-informative multimodal markers (from thousands to dozens).Results. Proved robust against multimodal heterogeneity, sociodemographic variability, and missing data.Significance. The model accurately identified dementia subtypes using measures readily available in underrepresented settings, with a similar performance than advanced biomarkers. This approach, if confirmed and replicated, may potentially complement clinical assessments in developing countries.

Published
2022

6. Brain health in diverse settings: How age, demographics and cognition shape brain function

Author

Hernandez, Hernan, Baez, Sandra, Medel, Vicente, Moguilner, Sebastian, Cuadros, Jhosmary, Santamaria-Garcia, Hernando, Tagliazucchi, Enzo, Valdes-Sosa, Pedro A., Lopera, Francisco, OchoaGómez, John Fredy, González-Hernández, Alfredis, Bonilla-Santos, Jasmin, Gonzalez-Montealegre, Rodrigo A., Aktürk, Tuba, Yıldırım, Ebru, Anghinah, Renato, Legaz, Agustina, Fittipaldi, Sol, Yener, Görsev G., Escudero, Javier, Babiloni, Claudio, Lopez, Susanna, Whelan, Robert, Lucas, Alberto A Fernández, García, Adolfo M., Huepe, David, Caterina, Gaetano Di, Soto-Añari, Marcio, Birba, Agustina, Sainz-Ballesteros, Agustin, Coronel, Carlos, Herrera, Eduar, Abasolo, Daniel, Kilborn, Kerry, Rubido, Nicolás, Clark, Ruaridh, Herzog, Ruben, Yerlikaya, Deniz, Güntekin, Bahar, Parra, Mario A., Prado, Pavel, and Ibanez, Agustin

Published
2024
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7. The relationship between negative life events and cortical structural connectivity in adolescents

Author

Sibilia, Francesca, Jost-Mousseau, Coline, Banaschewski, Tobias, Barker, Gareth J., Büchel, Christian, Desrivières, Sylvane, Flor, Herta, Grigis, Antoine, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Ittermann, Bernd, Martinot, Jean-Luc, Martinot, Marie-Laure Paillère, Artiges, Eric, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Poustka, Luise, Millenet, Sabina, Fröhner, Juliane H., Smolka, Michael N., Walter, Henrik, Whelan, Robert, Schumann, Gunter, and Bokde, Arun L.W.

Published
2024
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8. Association between vmPFC gray matter volume and smoking initiation in adolescents

Author

Xiang, Shitong, Jia, Tianye, Xie, Chao, Cheng, Wei, Chaarani, Bader, Banaschewski, Tobias, Barker, Gareth J., Bokde, Arun L. W., Büchel, Christian, Desrivières, Sylvane, Flor, Herta, Grigis, Antoine, Gowland, Penny A., Brühl, Rüdiger, Martinot, Jean-Luc, Martinot, Marie-Laure Paillère, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Poustka, Luise, Hohmann, Sarah, Fröhner, Juliane H., Smolka, Michael N., Vaidya, Nilakshi, Walter, Henrik, Whelan, Robert, Garavan, Hugh, Schumann, Gunter, Sahakian, Barbara J., Robbins, Trevor W., and Feng, Jianfeng

Published
2023
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9. Reward Processing in Novelty Seekers: A Transdiagnostic Psychiatric Imaging Biomarker.

Author

Qi, Shile, Schumann, Gunter, Bustillo, Juan, Turner, Jessica A, Jiang, Rongtao, Zhi, Dongmei, Fu, Zening, Mayer, Andrew R, Vergara, Victor M, Silva, Rogers F, Iraji, Armin, Chen, Jiayu, Damaraju, Eswar, Ma, Xiaohong, Yang, Xiao, Stevens, Michael, Mathalon, Daniel H, Ford, Judith M, Voyvodic, James, Mueller, Bryon A, Belger, Aysenil, Potkin, Steven G, Preda, Adrian, Zhuo, Chuanjun, Xu, Yong, Chu, Congying, Banaschewski, Tobias, Barker, Gareth J, Bokde, Arun LW, Quinlan, Erin Burke, Desrivières, Sylvane, Flor, Herta, Grigis, Antoine, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Martinot, Jean-Luc, Paillère Martinot, Marie-Laure, Artiges, Eric, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Paus, Tomáš, Poustka, Luise, Hohmann, Sarah, Fröhner, Juliane H, Smolka, Michael N, Walter, Henrik, Whelan, Robert, Calhoun, Vince D, Sui, Jing, and IMAGEN Consortium

Subjects
IMAGEN Consortium, Humans, Magnetic Resonance Imaging, Reward, Attention Deficit Disorder with Hyperactivity, Depressive Disorder, Major, Adolescent, Adult, Young Adult, Biomarkers, ADHD, Attention-deficit/hyperactivity disorder, MDD, Major depressive disorders, Novelty seeking, Reward processing, Schizophrenia, Substance use, Prevention, Serious Mental Illness, Pediatric, Mental Health, Neurosciences, Brain Disorders, Substance Misuse, Behavioral and Social Science, Depression, Alcoholism, Alcohol Use and Health, Clinical Research, 2.1 Biological and endogenous factors, Aetiology, Mental health, Good Health and Well Being, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

BackgroundDysfunctional reward processing is implicated in multiple mental disorders. Novelty seeking (NS) assesses preference for seeking novel experiences, which is linked to sensitivity to reward environmental cues.MethodsA subset of 14-year-old adolescents (IMAGEN) with the top 20% ranked high-NS scores was used to identify high-NS-associated multimodal components by supervised fusion. These features were then used to longitudinally predict five different risk scales for the same and unseen subjects (an independent dataset of subjects at 19 years of age that was not used in predictive modeling training at 14 years of age) (within IMAGEN, n ≈1100) and even for the corresponding symptom scores of five types of patient cohorts (non-IMAGEN), including drinking (n = 313), smoking (n = 104), attention-deficit/hyperactivity disorder (n = 320), major depressive disorder (n = 81), and schizophrenia (n = 147), as well as to classify different patient groups with diagnostic labels.ResultsMultimodal biomarkers, including the prefrontal cortex, striatum, amygdala, and hippocampus, associated with high NS in 14-year-old adolescents were identified. The prediction models built on these features are able to longitudinally predict five different risk scales, including alcohol drinking, smoking, hyperactivity, depression, and psychosis for the same and unseen 19-year-old adolescents and even predict the corresponding symptom scores of five types of patient cohorts. Furthermore, the identified reward-related multimodal features can classify among attention-deficit/hyperactivity disorder, major depressive disorder, and schizophrenia with an accuracy of 87.2%.ConclusionsAdolescents with higher NS scores can be used to reveal brain alterations in the reward-related system, implicating potential higher risk for subsequent development of multiple disorders. The identified high-NS-associated multimodal reward-related signatures may serve as a transdiagnostic neuroimaging biomarker to predict disease risks or severity.

Published
2021

10. Adolescents’ pain-related ontogeny shares a neural basis with adults’ chronic pain in basothalamo-cortical organization

Author

Heukamp, Nils Jannik, Banaschewski, Tobias, Bokde, Arun L.W., Desrivières, Sylvane, Grigis, Antoine, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Kandić, Mina, Brühl, Rüdiger, Martinot, Jean-Luc, Paillère Martinot, Marie-Laure, Artiges, Eric, Papadopoulos Orfanos, Dimitri, Lemaitre, Herve, Löffler, Martin, Poustka, Luise, Hohmann, Sarah, Millenet, Sabina, Fröhner, Juliane H., Smolka, Michael N., Usai, Katrin, Vaidya, Nilakshi, Walter, Henrik, Whelan, Robert, Schumann, Gunter, Flor, Herta, and Nees, Frauke

Published
2024
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13. A shared neural basis underlying psychiatric comorbidity

Author

Xie, Chao, Xiang, Shitong, Shen, Chun, Peng, Xuerui, Kang, Jujiao, Li, Yuzhu, Cheng, Wei, He, Shiqi, Banaschewski, Tobias, Barker, Gareth J., Bokde, Arun L. W., Bromberg, Uli, Büchel, Christian, Desrivières, Sylvane, Flor, Herta, Grigis, Antoine, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Ittermann, Bernd, Martinot, Jean-Luc, Martinot, Marie-Laure Paillère, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Paus, Tomáš, Poustka, Luise, Fröhner, Juliane H., Smolka, Michael N., Walter, Henrik, Whelan, Robert, Sahakian, Barbara J., Robbins, Trevor W., Schumann, Gunter, Jia, Tianye, and Feng, Jianfeng

Published
2023
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14. Epigenome-wide meta-analysis of blood DNA methylation and its association with subcortical volumes: findings from the ENIGMA Epigenetics Working Group

Author

Jia, Tianye, Chu, Congying, Liu, Yun, van Dongen, Jenny, Papastergios, Evangelos, Armstrong, Nicola J, Bastin, Mark E, Carrillo-Roa, Tania, den Braber, Anouk, Harris, Mathew, Jansen, Rick, Liu, Jingyu, Luciano, Michelle, Ori, Anil PS, Roiz Santiañez, Roberto, Ruggeri, Barbara, Sarkisyan, Daniil, Shin, Jean, Sungeun, Kim, Tordesillas Gutiérrez, Diana, van’t Ent, Dennis, Ames, David, Artiges, Eric, Bakalkin, Georgy, Banaschewski, Tobias, Bokde, Arun LW, Brodaty, Henry, Bromberg, Uli, Brouwer, Rachel, Büchel, Christian, Burke Quinlan, Erin, Cahn, Wiepke, de Zubicaray, Greig I, Ehrlich, Stefan, Ekström, Tomas J, Flor, Herta, Fröhner, Juliane H, Frouin, Vincent, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Hoare, Jacqueline, Ittermann, Bernd, Jahanshad, Neda, Jiang, Jiyang, Kwok, John B, Martin, Nicholas G, Martinot, Jean-Luc, Mather, Karen A, McMahon, Katie L, McRae, Allan F, Nees, Frauke, Papadopoulos Orfanos, Dimitri, Paus, Tomáš, Poustka, Luise, Sämann, Philipp G, Schofield, Peter R, Smolka, Michael N, Stein, Dan J, Strike, Lachlan T, Teeuw, Jalmar, Thalamuthu, Anbupalam, Trollor, Julian, Walter, Henrik, Wardlaw, Joanna M, Wen, Wei, Whelan, Robert, Apostolova, Liana G, Binder, Elisabeth B, Boomsma, Dorret I, Calhoun, Vince, Crespo-Facorro, Benedicto, Deary, Ian J, Hulshoff Pol, Hilleke, Ophoff, Roel A, Pausova, Zdenka, Sachdev, Perminder S, Saykin, Andrew, Wright, Margaret J, Thompson, Paul M, Schumann, Gunter, and Desrivières, Sylvane

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Mental Health, Neurosciences, Genetics, Human Genome, Diabetes, Neurodegenerative, 2.1 Biological and endogenous factors, Aetiology, Neurological, Mental health, CpG Islands, DNA Methylation, Epigenesis, Genetic, Epigenome, Genome-Wide Association Study, Humans, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

DNA methylation, which is modulated by both genetic factors and environmental exposures, may offer a unique opportunity to discover novel biomarkers of disease-related brain phenotypes, even when measured in other tissues than brain, such as blood. A few studies of small sample sizes have revealed associations between blood DNA methylation and neuropsychopathology, however, large-scale epigenome-wide association studies (EWAS) are needed to investigate the utility of DNA methylation profiling as a peripheral marker for the brain. Here, in an analysis of eleven international cohorts, totalling 3337 individuals, we report epigenome-wide meta-analyses of blood DNA methylation with volumes of the hippocampus, thalamus and nucleus accumbens (NAcc)-three subcortical regions selected for their associations with disease and heritability and volumetric variability. Analyses of individual CpGs revealed genome-wide significant associations with hippocampal volume at two loci. No significant associations were found for analyses of thalamus and nucleus accumbens volumes. Cluster-based analyses revealed additional differentially methylated regions (DMRs) associated with hippocampal volume. DNA methylation at these loci affected expression of proximal genes involved in learning and memory, stem cell maintenance and differentiation, fatty acid metabolism and type-2 diabetes. These DNA methylation marks, their interaction with genetic variants and their impact on gene expression offer new insights into the relationship between epigenetic variation and brain structure and may provide the basis for biomarker discovery in neurodegeneration and neuropsychiatric conditions.

Published
2021

16. Author Correction: A shared neural basis underlying psychiatric comorbidity

Author

Xie, Chao, Xiang, Shitong, Shen, Chun, Peng, Xuerui, Kang, Jujiao, Li, Yuzhu, Cheng, Wei, He, Shiqi, Bobou, Marina, Broulidakis, M. John, van Noort, Betteke Maria, Zhang, Zuo, Robinson, Lauren, Vaidya, Nilakshi, Winterer, Jeanne, Zhang, Yuning, King, Sinead, Banaschewski, Tobias, Barker, Gareth J., Bokde, Arun L. W., Bromberg, Uli, Büchel, Christian, Flor, Herta, Grigis, Antoine, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Ittermann, Bernd, Lemaître, Hervé, Martinot, Jean-Luc, Martinot, Marie-Laure Paillère, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Paus, Tomáš, Poustka, Luise, Fröhner, Juliane H., Schmidt, Ulrike, Sinclair, Julia, Smolka, Michael N., Stringaris, Argyris, Walter, Henrik, Whelan, Robert, Desrivières, Sylvane, Sahakian, Barbara J., Robbins, Trevor W., Schumann, Gunter, Jia, Tianye, and Feng, Jianfeng

Published
2023
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17. Bayesian causal network modeling suggests adolescent cannabis use accelerates prefrontal cortical thinning

Author

Owens, Max M., Albaugh, Matthew D., Allgaier, Nicholas, Yuan, Dekang, Robert, Gabriel, Cupertino, Renata B., Spechler, Philip A., Juliano, Anthony, Hahn, Sage, Banaschewski, Tobias, Bokde, Arun L. W., Desrivières, Sylvane, Flor, Herta, Grigis, Antoine, Gowland, Penny, Heinz, Andreas, Brühl, Rüdiger, Martinot, Jean-Luc, Martinot, Marie-Laure Paillère, Artiges, Eric, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Lemaitre, Herve, Paus, Tomáš, Poustka, Luise, Millenet, Sabina, Fröhner, Juliane H., Smolka, Michael N., Walter, Henrik, Whelan, Robert, Mackey, Scott, Schumann, Gunter, and Garavan, Hugh

Published
2022
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20. Similarity and stability of face network across populations and throughout adolescence and adulthood

Author

Liao, Zhijie, Banaschewski, Tobias, Bokde, Arun L.W., Desrivières, Sylvane, Flor, Herta, Grigis, Antoine, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Ittermann, Bernd, Martinot, Jean-Luc, Martinot, Marie-Laure Paillère, Artiges, Eric, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Poustka, Luise, Hohmann, Sarah, Millenet, Sabina, Fröhner, Juliane H., Smolka, Michael N., Walter, Henrik, Whelan, Robert, Schumann, Gunter, and Paus, Tomáš

Published
2021
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21. Viscous dynamics associated with hypoexcitation and structural disintegration in neurodegeneration via generative whole‐brain modeling

Author

Coronel‐Oliveros, Carlos, primary, Gómez, Raúl Gónzalez, additional, Ranasinghe, Kamalini, additional, Sainz‐Ballesteros, Agustín, additional, Legaz, Agustina, additional, Fittipaldi, Sol, additional, Cruzat, Josephine, additional, Herzog, Rubén, additional, Yener, Gorsev, additional, Parra, Mario, additional, Aguillon, David, additional, Lopera, Francisco, additional, Santamaria‐Garcia, Hernando, additional, Moguilner, Sebastián, additional, Medel, Vicente, additional, Orio, Patricio, additional, Whelan, Robert, additional, Tagliazucchi, Enzo, additional, Prado, Pavel, additional, and Ibañez, Agustín, additional

Published
2024
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22. Examination of the association between exposure to childhood maltreatment and brain structure in young adults: a machine learning analysis

Author

Price, Matthew, Albaugh, Matthew, Hahn, Sage, Juliano, Anthony C., Fani, Negar, Brier, Zoe M. F., Legrand, Alison C., van Stolk-Cooke, Katherine, Chaarani, Bader, Potter, Alexandra, Peck, Kelly, Allgaier, Nicholas, Banaschewski, Tobias, Bokde, Arun L. W., Quinlan, Erin Burke, Desrivières, Sylvane, Flor, Herta, Grigis, Antoine, Gowland, Penny, Heinz, Andreas, Ittermann, Bernd, Martinot, Jean-Luc, Paillère, Marie-Laure, Artiges, Eric, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Poustka, Luise, Hohmann, Sarah, Fröhner, Juliane H., Smolka, Michael N., Walter, Henrik, Whelan, Robert, Schumann, Gunter, and Garavan, Hugh

Published
2021
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23. Nonlinear functional mapping of the human brain

Author

Allgaier, Nicholas, Banaschewski, Tobias, Barker, Gareth, Bokde, Arun L. W., Bongard, Josh C., Bromberg, Uli, Büchel, Christian, Cattrell, Anna, Conrod, Patricia J., Danforth, Christopher M., Desrivières, Sylvane, Dodds, Peter S., Flor, Herta, Frouin, Vincent, Gallinat, Jürgen, Gowland, Penny, Heinz, Andreas, Ittermann, Bernd, Mackey, Scott, Martinot, Jean-Luc, Murphy, Kevin, Nees, Frauke, Papadopoulos-Orfanos, Dimitri, Poustka, Luise, Smolka, Michael N., Walter, Henrik, Whelan, Robert, Schumann, Gunter, Garavan, Hugh, and Consortium, IMAGEN

Subjects
Quantitative Biology - Neurons and Cognition, Computer Science - Neural and Evolutionary Computing
Abstract

The field of neuroimaging has truly become data rich, and novel analytical methods capable of gleaning meaningful information from large stores of imaging data are in high demand. Those methods that might also be applicable on the level of individual subjects, and thus potentially useful clinically, are of special interest. In the present study, we introduce just such a method, called nonlinear functional mapping (NFM), and demonstrate its application in the analysis of resting state fMRI from a 242-subject subset of the IMAGEN project, a European study of adolescents that includes longitudinal phenotypic, behavioral, genetic, and neuroimaging data. NFM employs a computational technique inspired by biological evolution to discover and mathematically characterize interactions among ROI (regions of interest), without making linear or univariate assumptions. We show that statistics of the resulting interaction relationships comport with recent independent work, constituting a preliminary cross-validation. Furthermore, nonlinear terms are ubiquitous in the models generated by NFM, suggesting that some of the interactions characterized here are not discoverable by standard linear methods of analysis. We discuss one such nonlinear interaction in the context of a direct comparison with a procedure involving pairwise correlation, designed to be an analogous linear version of functional mapping. We find another such interaction that suggests a novel distinction in brain function between drinking and non-drinking adolescents: a tighter coupling of ROI associated with emotion, reward, and interoceptive processes such as thirst, among drinkers. Finally, we outline many improvements and extensions of the methodology to reduce computational expense, complement other analytical tools like graph-theoretic analysis, and allow for voxel level NFM to eliminate the necessity of ROI selection., Comment: 21 pages, 12 figures, and 1 table

Published
2015

24. Brain structure and habitat: Do the brains of our children tell us where they have been brought up?

Author

Kühn, Simone, Banaschewski, Tobias, Bokde, Arun L.W., Büchel, Christian, Quinlan, Erin Burke, Desrivières, Sylvane, Flor, Herta, Grigis, Antoine, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Ittermann, Bernd, Martinot, Jean-Luc, Martinot, Marie Laure Paillère, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Paus, Tomáš, Poustka, Luise, Millenet, Sabina, Fröhner, Juliane H., Smolka, Michael N., Walter, Henrik, Whelan, Robert, Schumann, Gunter, Meyer-Lindenberg, Andreas, and Gallinat, Jürgen

Published
2020
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25. The empirical replicability of task-based fMRI as a function of sample size

Author

Bossier, Han, Roels, Sanne P., Seurinck, Ruth, Banaschewski, Tobias, Barker, Gareth J., Bokde, Arun L.W., Quinlan, Erin Burke, Desrivières, Sylvane, Flor, Herta, Grigis, Antoine, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Ittermann, Bernd, Martinot, Jean-Luc, Artiges, Eric, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Poustka, Luise, Fröhner Dipl-Psych, Juliane H., Smolka, Michael N., Walter, Henrik, Whelan, Robert, Schumann, Gunter, and Moerkerke, Beatrijs

Published
2020
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26. White matter microstructure is associated with hyperactive/inattentive symptomatology and polygenic risk for attention-deficit/hyperactivity disorder in a population-based sample of adolescents

Author

Albaugh, Matthew D., Hudziak, James. J., Ing, Alex, Chaarani, Bader, Barker, Edward, Jia, Tianye, Lemaitre, Herve, Watts, Richard, Orr, Catherine, Spechler, Philip A., Lepage, Claude, Fonov, Vladimir, Collins, Louis, Rioux, Pierre, Evans, Alan C., Banaschewski, Tobias, Bokde, Arun L. W., Bromberg, Uli, Büchel, Christian, Quinlan, Erin Burke, Desrivières, Sylvane, Flor, Herta, Frouin, Vincent, Gowland, Penny, Heinz, Andreas, Ittermann, Bernd, Martinot, Jean-Luc, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Paus, Tomáš, Poustka, Luise, Fröhner, Juliane H., Smolka, Michael N., Walter, Henrik, Whelan, Robert, Schumann, Gunter, Garavan, Hugh, and Potter, Alexandra

Published
2019
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30. Predicting change trajectories of neuroticism from baseline brain structure using whole brain analyses and latent growth curve models in adolescents

Author

Kühn, Simone, Mascherek, Anna, Banaschewski, Tobias, Bokde, Arun L. W., Büchel, Christian, Quinlan, Erin Burke, Desrivières, Sylvane, Flor, Herta, Grigis, Antoine, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Ittermann, Bernd, Martinot, Jean-Luc, Martinot, Marie-Laure Paillère, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Paus, Tomáš, Poustka, Luise, Millenet, Sabina, Fröhner, Juliane H., Smolka, Michael N., Walter, Henrik, Whelan, Robert, Schumann, Gunter, Lindenberger, Ulman, and Gallinat, Jürgen

Published
2020
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35. A biologically informed polygenic score of neuronal plasticity moderates the association between cognitive aptitudes and cortical thickness in adolescents

Author

Navarri, Xavier, primary, Vosberg, Daniel E., additional, Shin, Jean, additional, Richer, Louis, additional, Leonard, Gabriel, additional, Pike, G. Bruce, additional, Banaschewski, Tobias, additional, Bokde, Arun L.W., additional, Desrivières, Sylvane, additional, Flor, Herta, additional, Grigis, Antoine, additional, Garavan, Hugh, additional, Gowland, Penny, additional, Heinz, Andreas, additional, Brühl, Rüdiger, additional, Martinot, Jean-Luc, additional, Martinot, Marie-Laure Paillère, additional, Artiges, Eric, additional, Nees, Frauke, additional, Orfanos, Dimitri Papadopoulos, additional, Poustka, Luise, additional, Hohmann, Sarah, additional, Fröhner, Juliane H., additional, Smolka, Michael N., additional, Vaidya, Nilakshi, additional, Walter, Henrik, additional, Whelan, Robert, additional, Schumann, Gunter, additional, Pausova, Zdenka, additional, and Paus, Tomáš, additional

Published
2023
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37. Drinking motives, personality traits and life stressors-identifying pathways to harmful alcohol use in adolescence using a panel network approach

Author

Freichel, René, Pfirrmann, Janine, Cousjin, Janna, de Jong, Peter, Franken, Ingmar, Banaschewski, Tobias, Bokde, Arun L W, Desrivières, Sylvane, Flor, Herta, Grigis, Antoine, Garavan, Hugh, Heinz, Andreas, Martinot, Jean-Luc, Martinot, Marie-Laure Paillère, Artiges, Eric, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Poustka, Luise, Hohmann, Sarah, Fröhner, Juliane H, Smolka, Michael N, Vaidya, Nilakshi, Whelan, Robert, Schumann, Gunter, Walter, Henrik, Veer, Ilya M, Wiers, Reinout W, Consortium, IMAGEN, Freichel, René, Pfirrmann, Janine, Cousjin, Janna, de Jong, Peter, Franken, Ingmar, Banaschewski, Tobias, Bokde, Arun L W, Desrivières, Sylvane, Flor, Herta, Grigis, Antoine, Garavan, Hugh, Heinz, Andreas, Martinot, Jean-Luc, Martinot, Marie-Laure Paillère, Artiges, Eric, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Poustka, Luise, Hohmann, Sarah, Fröhner, Juliane H, Smolka, Michael N, Vaidya, Nilakshi, Whelan, Robert, Schumann, Gunter, Walter, Henrik, Veer, Ilya M, Wiers, Reinout W, and Consortium, IMAGEN

Abstract

BACKGROUND AND AIMS: Models of alcohol use risk suggest that drinking motives represent the most proximal risk factors on which more distal factors converge. However, little is known about how distinct risk factors influence each other and alcohol use on different temporal scales (within a given moment versus over time). We aimed to estimate the dynamic associations of distal (personality and life stressors) and proximal (drinking motives) risk factors, and their relationship to alcohol use in adolescence and early adulthood using a novel graphical vector autoregressive (GVAR) panel network approach. DESIGN, SETTING AND CASES: We estimated panel networks on data from the IMAGEN study, a longitudinal European cohort study following adolescents across three waves (aged 16, 19 and 22 years). Our sample consisted of 1829 adolescents (51% females) who reported alcohol use on at least one assessment wave. MEASUREMENTS: Risk factors included personality traits (NEO-FFI: neuroticism, extraversion, openness, agreeableness and conscientiousness; SURPS: impulsivity and sensation-seeking), stressful life events (LEQ: sum scores of stressful life events), and drinking motives [drinking motives questionnaire (DMQ): social, enhancement, conformity, coping anxiety and coping depression]. We assessed alcohol use [alcohol use disorders identification test (AUDIT): quantity and frequency] and alcohol-related problems (AUDIT: related problems). FINDINGS: Within a given moment, social [partial correlation (pcor) = 0.17] and enhancement motives (pcor = 0.15) co-occurred most strongly with drinking quantity and frequency, while coping depression motives (pcor = 0.13), openness (pcor = 0.05) and impulsivity (pcor = 0.09) were related to alcohol-related problems. The temporal network showed no predictive associations between distal risk factors and drinking motives. Social motives (beta = 0.21), previous alcohol use

Published
2023

38. Visual deep learning of unprocessed neuroimaging characterises dementia subtypes and generalises across non-stereotypic samples

Author

Moguilner, Sebastian, Whelan, Robert, Adams, Hieab, Valcour, Victor, Tagliazucchi, Enzo, Ibáñez, Agustín, Moguilner, Sebastian, Whelan, Robert, Adams, Hieab, Valcour, Victor, Tagliazucchi, Enzo, and Ibáñez, Agustín

Abstract

Background: Dementia's diagnostic protocols are mostly based on standardised neuroimaging data collected in the Global North from homogeneous samples. In other non-stereotypical samples (participants with diverse admixture, genetics, demographics, MRI signals, or cultural origins), classifications of disease are difficult due to demographic and region-specific sample heterogeneities, lower quality scanners, and non-harmonised pipelines. Methods: We implemented a fully automatic computer-vision classifier using deep learning neural networks. A DenseNet was applied on raw (unpreprocessed) data from 3000 participants (behavioural variant frontotemporal dementia-bvFTD, Alzheimer's disease-AD, and healthy controls; both male and female as self-reported by participants). We tested our results in demographically matched and unmatched samples to discard possible biases and performed multiple out-of-sample validations. Findings: Robust classification results across all groups were achieved from standardised 3T neuroimaging data from the Global North, which also generalised to standardised 3T neuroimaging data from Latin America. Moreover, DenseNet also generalised to non-standardised, routine 1.5T clinical images from Latin America. These generalisations were robust in samples with heterogenous MRI recordings and were not confounded by demographics (i.e., were robust in both matched and unmatched samples, and when incorporating demographic variables in a multifeatured model). Model interpretability analysis using occlusion sensitivity evidenced core pathophysiological regions for each disease (mainly the hippocampus in AD, and the insula in bvFTD) demonstrating biological specificity and plausibility. Interpretation: The generalisable approach outlined here could be used in the future to aid clinician decision-making in diverse samples. Funding: The specific funding of this article is provided in the acknowledgements section.

Published
2023

39. A biologically informed polygenic score of neuronal plasticity moderates the association between cognitive aptitudes and cortical thickness in adolescents

Author

Navarri, Xavier, Vosberg, Daniel E., Shin, Jean, Richer, Louis, Leonard, Gabriel, Pike, G. Bruce, Banaschewski, Tobias, Bokde, Arun L.W., Desrivières, Sylvane, Flor, Herta, Grigis, Antoine, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Brühl, Rüdiger, Martinot, Jean-Luc, Paillère Martinot, Marie-Laure, Artiges, Eric, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Poustka, Luise, Hohmann, Sarah, Fröhner, Juliane H., Smolka, Michael N., Vaidya, Nilakshi, Walter, Henrik, Whelan, Robert, Schumann, Gunter, Pausova, Zdenka, Paus, Tomáš, Navarri, Xavier, Vosberg, Daniel E., Shin, Jean, Richer, Louis, Leonard, Gabriel, Pike, G. Bruce, Banaschewski, Tobias, Bokde, Arun L.W., Desrivières, Sylvane, Flor, Herta, Grigis, Antoine, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Brühl, Rüdiger, Martinot, Jean-Luc, Paillère Martinot, Marie-Laure, Artiges, Eric, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Poustka, Luise, Hohmann, Sarah, Fröhner, Juliane H., Smolka, Michael N., Vaidya, Nilakshi, Walter, Henrik, Whelan, Robert, Schumann, Gunter, Pausova, Zdenka, and Paus, Tomáš

Abstract

Although many studies of the adolescent brain identified positive associations between cognitive abilities and cortical thickness, little is known about mechanisms underlying such brain-behavior relationships. With experience-induced plasticity playing an important role in shaping the cerebral cortex throughout life, it is likely that some of the inter-individual variations in cortical thickness could be explained by genetic variations in relevant molecular processes, as indexed by a polygenic score of neuronal plasticity (PGS-NP). Here, we studied associations between PGS-NP, cognitive abilities, and thickness of the cerebral cortex, estimated from magnetic resonance images, in the Saguenay Youth Study (SYS, 533 females, 496 males: age=15.0 ± 1.8 years of age; cross-sectional), and the IMAGEN Study (566 females, 556 males; between 14 and 19 years; longitudinal). Using Gene Ontology, we first identified 199 genes implicated in neuronal plasticity, which mapped to 155,600 single nucleotide polymorphisms (SNPs). Second, we estimated their effect sizes from an educational attainment meta-GWAS to build a PGS-NP. Third, we examined a possible moderating role of PGS-NP in the relationship between performance intelligence quotient (PIQ), and its subtests, and the thickness of 34 cortical regions. In SYS, we observed a significant interaction between PGS-NP and object assembly vis-à-vis thickness in male adolescents (p = 0.026). A median-split analysis showed that, in males with a ‘high’ PGS-NP, stronger associations between object assembly and thickness were found in regions with larger age-related changes in thickness (r = 0.55, p = 0.00075). Although the interaction between PIQ and PGS-NP was non-significant (p = 0.064), we performed a similar median-split analysis. Again, in the high PGS-NP males, positive associations between PIQ and thickness were observed in regions with larger age-related changes in thickness (r = 0.40, p = 0.018). In the IMAGEN cohort, we did not r

Published
2023
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40. Independent contribution of polygenic risk for schizophrenia and cannabis use in predicting psychotic-like experiences in young adulthood: Testing gene × environment moderation and mediation

Author

Hersenen-Medisch 1, TN groep Adan, Onderzoeksgroep 2, Onderzoek, Brain, Neurogenetica, Elkrief, Laurent, Lin, Bochao, Marchi, Mattia, Afzali, Mohammad H., Banaschewski, Tobias, Bokde, Arun L.W., Quinlan, Erin Burke, Desrivières, Sylvane, Flor, Herta, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Ittermann, Bernd, Martinot, Jean Luc, Martinot, Marie Laure Paillère, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Paus, Tomáš, Poustka, Luise, Hohmann, Sarah, Fröhner, Juliane H., Smolka, Michael N., Walter, Henrik, Whelan, Robert, Schumann, Gunter, Luykx, Jurjen, Boks, Marco P., Conrod, Patricia J., Hersenen-Medisch 1, TN groep Adan, Onderzoeksgroep 2, Onderzoek, Brain, Neurogenetica, Elkrief, Laurent, Lin, Bochao, Marchi, Mattia, Afzali, Mohammad H., Banaschewski, Tobias, Bokde, Arun L.W., Quinlan, Erin Burke, Desrivières, Sylvane, Flor, Herta, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Ittermann, Bernd, Martinot, Jean Luc, Martinot, Marie Laure Paillère, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Paus, Tomáš, Poustka, Luise, Hohmann, Sarah, Fröhner, Juliane H., Smolka, Michael N., Walter, Henrik, Whelan, Robert, Schumann, Gunter, Luykx, Jurjen, Boks, Marco P., and Conrod, Patricia J.

Published
2023

41. A stable and replicable neural signature of lifespan adversity in the adult brain

Author

Holz, Nathalie E; https://orcid.org/0000-0002-6225-9267, Zabihi, Mariam; https://orcid.org/0000-0002-7083-2318, Kia, Seyed Mostafa; https://orcid.org/0000-0002-7128-814X, Monninger, Maximillian, Aggensteiner, Pascal-M; https://orcid.org/0000-0002-1048-9044, Siehl, Sebastian; https://orcid.org/0000-0002-8933-7552, Floris, Dorothea L, Bokde, Arun L W; https://orcid.org/0000-0003-0114-4914, Desrivières, Sylvane; https://orcid.org/0000-0002-9120-7060, Flor, Herta; https://orcid.org/0000-0003-4809-5398, Grigis, Antoine, Garavan, Hugh, Gowland, Penny; https://orcid.org/0000-0002-4900-4817, Heinz, Andreas; https://orcid.org/0000-0001-5405-9065, Brühl, Rüdiger; https://orcid.org/0000-0003-0111-5996, Martinot, Jean-Luc, Martinot, Marie-Laure Paillère; https://orcid.org/0000-0002-0452-2450, Orfanos, Dimitri Papadopoulos; https://orcid.org/0000-0002-1242-8990, Paus, Tomáš, Poustka, Luise; https://orcid.org/0000-0002-7738-4394, Fröhner, Juliane H; https://orcid.org/0000-0002-8493-6396, Smolka, Michael N; https://orcid.org/0000-0001-5398-5569, Vaidya, Nilakshi, Walter, Henrik; https://orcid.org/0000-0002-9403-6121, Whelan, Robert; https://orcid.org/0000-0002-2790-7281, Schumann, Gunter; https://orcid.org/0000-0002-7740-6469, Meyer-Lindenberg, Andreas; https://orcid.org/0000-0001-5619-1123, Brandeis, Daniel, Buitelaar, Jan K; https://orcid.org/0000-0001-8288-7757, Nees, Frauke, et al, Holz, Nathalie E; https://orcid.org/0000-0002-6225-9267, Zabihi, Mariam; https://orcid.org/0000-0002-7083-2318, Kia, Seyed Mostafa; https://orcid.org/0000-0002-7128-814X, Monninger, Maximillian, Aggensteiner, Pascal-M; https://orcid.org/0000-0002-1048-9044, Siehl, Sebastian; https://orcid.org/0000-0002-8933-7552, Floris, Dorothea L, Bokde, Arun L W; https://orcid.org/0000-0003-0114-4914, Desrivières, Sylvane; https://orcid.org/0000-0002-9120-7060, Flor, Herta; https://orcid.org/0000-0003-4809-5398, Grigis, Antoine, Garavan, Hugh, Gowland, Penny; https://orcid.org/0000-0002-4900-4817, Heinz, Andreas; https://orcid.org/0000-0001-5405-9065, Brühl, Rüdiger; https://orcid.org/0000-0003-0111-5996, Martinot, Jean-Luc, Martinot, Marie-Laure Paillère; https://orcid.org/0000-0002-0452-2450, Orfanos, Dimitri Papadopoulos; https://orcid.org/0000-0002-1242-8990, Paus, Tomáš, Poustka, Luise; https://orcid.org/0000-0002-7738-4394, Fröhner, Juliane H; https://orcid.org/0000-0002-8493-6396, Smolka, Michael N; https://orcid.org/0000-0001-5398-5569, Vaidya, Nilakshi, Walter, Henrik; https://orcid.org/0000-0002-9403-6121, Whelan, Robert; https://orcid.org/0000-0002-2790-7281, Schumann, Gunter; https://orcid.org/0000-0002-7740-6469, Meyer-Lindenberg, Andreas; https://orcid.org/0000-0001-5619-1123, Brandeis, Daniel, Buitelaar, Jan K; https://orcid.org/0000-0001-8288-7757, Nees, Frauke, and et al

Abstract

Environmental adversities constitute potent risk factors for psychiatric disorders. Evidence suggests the brain adapts to adversity, possibly in an adversity-type and region-specific manner. However, the long-term effects of adversity on brain structure and the association of individual neurobiological heterogeneity with behavior have yet to be elucidated. Here we estimated normative models of structural brain development based on a lifespan adversity profile in a longitudinal at-risk cohort aged 25 years (n = 169). This revealed widespread morphometric changes in the brain, with partially adversity-specific features. This pattern was replicated at the age of 33 years (n = 114) and in an independent sample at 22 years (n = 115). At the individual level, greater volume contractions relative to the model were predictive of future anxiety. We show a stable neurobiological signature of adversity that persists into adulthood and emphasize the importance of considering individual-level rather than group-level predictions to explain emerging psychopathology.

Published
2023

42. Human cortex development is shaped by molecular and cellular brain systems

Author

Lotter, Leon D., Saberi, Amin, Hansen, Justine Y., Misic, Bratislav, Barker, Gareth J., Bokde, Arun L. W., Desrivières, Sylvane, Flor, Herta, Grigis, Antoine, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Brühl, Rüdiger, Martinot, Jean-Luc, Paillère, Marie-Laure, Artiges, Eric, Orfanos, Dimitri Papadopoulos, Paus, Tomáš, Poustka, Luise, Hohmann, Sarah, Fröhner, Juliane H., Smolka, Michael N., Vaidya, Nilakshi, Walter, Henrik, Whelan, Robert, Schumann, Gunter, Nees, Frauke, Banaschewski, Tobias, Eickhoff, Simon B., Dukart, Juergen, and IMAGEN Consortium

Subjects
Article
Abstract

Human brain morphology undergoes complex developmental changes with diverse regional trajectories. Various biological factors influence cortical thickness development, but human data are scarce. Building on methodological advances in neuroimaging of large cohorts, we show that population-based developmental trajectories of cortical thickness unfold along patterns of molecular and cellular brain organization. During childhood and adolescence, distributions of dopaminergic receptors, inhibitory neurons, glial cell populations as well as features of brain metabolism explain up to 50% of variance associated with regional cortical thickness trajectories. Cortical maturation patterns in later life are best explained by distributions of cholinergic and glutamatergic systems. These observations are validated in longitudinal data from over 8,000 adolescents, explaining up to 59% of developmental change at population- and 18% at single-subject level. Integrating multilevel brain atlases with normative modeling and population neuroimaging provides a biologically and clinically meaningful path to understand typical and atypical brain development in living humans.

Published
2023

43. Genetic variants associated with longitudinal changes in brain structure across the lifespan

Author

Brouwer, Rachel M, Klein, Marieke, Kremen, William S, Guimaraes, Joao P O F T, Homuth, Georg, Hottenga, Jouke-Jan, Knol, Maria J, Kwok, John B J, Le Hellard, Stephanie, Mather, Karen A, Milaneschi, Yuri, Morris, Derek W, Nöthen, Markus M., Panizzon, Matthew S, Papiol, Sergi, Rietschel, Marcella, Santoro, Marcos L, Steen, Vidar M, Stein, Jason L, Streit, Fabian, Tankard, Rick M, Teumer, Alexander, van 't Ent, Dennis, van der Meer, Dennis, Olde Loohuis, Loes M, van Eijk, Kristel R, Vassos, Evangelos, Vázquez-Bourgon, Javier, Witt, Stephanie H, Consortium, IMAGEN, Adams, Hieab H H, Agartz, Ingrid, Ames, David, Amunts, Katrin, Andreassen, Ole A, Whelan, Christopher D, Arango, Celso, Banaschewski, Tobias, Baune, Bernhard T, Belangero, Sintia I, Bokde, Arun L W, Boomsma, Dorret I, Bressan, Rodrigo A, Brodaty, Henry, Buitelaar, Jan K, Cahn, Wiepke, Aghajani, Moji, Caspers, Svenja, Cichon, Sven, Crespo-Facorro, Benedicto, Cox, Simon R, Dannlowski, Udo, Elvsåshagen, Torbjørn, Espeseth, Thomas, Falkai, Peter, Fisher, Simon E, Flor, Herta, Alloza, Clara, Fullerton, Janice M, Garavan, Hugh, Gowland, Penny A, Grabe, Hans, Hahn, Tim, Heinz, Andreas, Hillegers, Manon, Hoare, Jacqueline, Hoekstra, Pieter J, Ikram, Mohammad A, Alnæs, Dag, Jackowski, Andrea P, Jansen, Andreas, Jönsson, Erik G, Kahn, Rene S, Kircher, Tilo, Korgaonkar, Mayuresh S, Krug, Axel, Lemaitre, Herve, Malt, Ulrik F, Martinot, Jean-Luc, Artiges, Eric, McDonald, Colm, Mitchell, Philip B, Muetzel, Ryan L, Murray, Robin M, Nees, Frauke, Nenadić, Igor, Oosterlaan, Jaap, Ophoff, Roel A, Pan, Pedro M, Penninx, Brenda W J H, Ayesa-Arriola, Rosa, Poustka, Luise, Sachdev, Perminder S, Salum, Giovanni A, Schofield, Peter R, Schumann, Gunter, Shaw, Philip, Sim, Kang, Smolka, Michael N, Stein, Dan J, Trollor, Julian N, Barker, Gareth J, van den Berg, Leonard H, Veldink, Jan H, Walter, Henrik, Westlye, Lars T, Whelan, Robert, White, Tonya, Wright, Margaret J, Medland, Sarah E, Franke, Barbara, Thompson, Paul M, Grasby, Katrina L, Bastin, Mark E, Hulshoff Pol, Hilleke E, Brühl, Rüdiger, Papadopoulos Orfanos, Dimitri, Paus, Tomáš, Millenet, Sabina, Blok, Elisabet, Bøen, Erlend, Breukelaar, Isabella A, Bright, Joanna K, Buimer, Elizabeth E L, Bülow, Robin, Cannon, Dara M, Ciufolini, Simone, Crossley, Nicolas A, Schnack, Hugo G, Damatac, Christienne G, Dazzan, Paola, de Mol, Casper L, de Zwarte, Sonja M C, Desrivières, Sylvane, Díaz-Caneja, Covadonga M, Doan, Nhat Trung, Dohm, Katharina, Fröhner, Juliane H, Goltermann, Janik, Jahanshad, Neda, Grigis, Antoine, Grotegerd, Dominik, Han, Laura K M, Harris, Mathew, Hartman, Catharina A, Heany, Sarah J, Heindel, Walter, Heslenfeld, Dirk J., Hohmann, Sarah, Ittermann, Bernd, Teeuw, Jalmar, Jansen, Philip R, Janssen, Joost, Jia, Tianye, Jiang, Jiyang, Jockwitz, Christiane, Karali, Temmuz, Keeser, Daniel, Koevoets, Martijn G J C, Lenroot, Rhoshel K, Malchow, Berend, Thomopoulos, Sophia I, Mandl, René C W, Medel, Vicente, Meinert, Susanne, Morgan, Catherine A, Mühleisen, Thomas W, Nabulsi, Leila, Opel, Nils, de la Foz, Víctor Ortiz-García, Overs, Bronwyn J, Paillère Martinot, Marie-Laure, Sprooten, Emma, Redlich, Ronny, Marques, Tiago Reis, Repple, Jonathan, Roberts, Gloria, Roshchupkin, Gennady V, Setiaman, Nikita, Shumskaya, Elena, Stein, Frederike, Sudre, Gustavo, Takahashi, Shun, Franz, Carol E, Thalamuthu, Anbupalam, Tordesillas-Gutiérrez, Diana, van der Lugt, Aad, van Haren, Neeltje E M, Wardlaw, Joanna M, Wen, Wei, Westeneng, Henk-Jan, Wittfeld, Katharina, Zhu, Alyssa H, Zugman, Andre, Gogtay, Nitin, Armstrong, Nicola J, Bonfiglio, Gaia, Bralten, Janita, Dalvie, Shareefa, Davies, Gail, Di Forti, Marta, Ding, Linda, Donohoe, Gary, Forstner, Andreas J, Gonzalez-Peñas, Javier, Child and Adolescent Psychiatry / Psychology, Erasmus MC other, Anesthesiology, Epidemiology, Radiology & Nuclear Medicine, Clinical Genetics, Psychiatry, the IMAGEN Consortium, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Human genetics, Amsterdam Neuroscience - Complex Trait Genetics, Pediatric surgery, APH - Aging & Later Life, APH - Mental Health, APH - Digital Health, European Commission, European Research Council, Comunidad de Madrid, Instituto de Salud Carlos III, Fundación Mutua Madrileña, Fundación Alicia Koplowitz, Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Clinical Cognitive Neuropsychiatry Research Program (CCNP), Psychiatry 2, RS: MHeNs - R2 - Mental Health, Psychiatrie & Neuropsychologie, Complex Trait Genetics, Cognitive Psychology, Biological Psychology, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, APH - Methodology, Clinical Neuropsychology, IBBA, General Paediatrics, ARD - Amsterdam Reproduction and Development, and Paediatrics

Subjects
Neuroinformatics, EXPRESSION, Aging, SUSCEPTIBILITY LOCI, Longevity, SURFACE-AREA, INDIVIDUAL-DIFFERENCES, All institutes and research themes of the Radboud University Medical Center, SDG 3 - Good Health and Well-being, Aging/genetics, Humans, ddc:610, GENOME-WIDE ASSOCIATION, METAANALYSIS, RISK, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], General Neuroscience, 220 Statistical Imaging Neuroscience, Longevity/genetics, Brain, Magnetic Resonance Imaging, genetics [Aging], VOLUME, RELIABILITY, sense organs, CORTICAL THICKNESS, genetics [Longevity], Genome-Wide Association Study
Abstract

et al., Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging., The ENIGMA-Plasticity Working Group is part of the ENIGMA World Aging Center, funded by NIA grants R56 AG058854 and R01 AG058854. The ENIGMA Consortium core funding was supported by NIH Consortium Grant U54 EB020403, supported by a cross-NIH alliance that funds Big Data to Knowledge Centers of Excellence. 1000BRAINS: 1000BRAINS is a population-based cohort based on the Heinz-Nixdorf Recall Study and is supported, in part, by the German National Cohort. We thank the Heinz Nixdorf Foundation (Germany) for their generous support in terms of the Heinz Nixdorf Study. The authors are supported by the Initiative and Networking Fund of the Helmholtz Association (Svenja Caspers) and the European Union’s Horizon 2020 Research and Innovation Programme under grant agreements 785907 (Human Brain Project SGA2; Svenja Caspers, Sven Cichon and Katrin Amunts). This work was further supported by the German Federal Ministry of Education and Research (BMBF) through the Integrated Network IntegraMent (Integrated Understanding of Causes and Mechanisms in Mental Disorders) under the auspices of the e:Med Program (grant 01ZX1314A; Sven Cichon) and by the Swiss National Science Foundation (SNSF, grant 156791; Sven Cichon). The authors acknowledge grants supporting their work from the European Union’s Horizon 2020 Research and Innovation Programme (H2020/2014–2020) under grant agreements 667302 (CoCA), 728018 (Eat2beNICE), 785907 (HBP SGA2) and 772376 (EScORIAL) and the Netherlands ALS Foundation.Additional support is received from the European Community’s Seventh Framework Programme (FP7/2007—2013) under grant agreements n° 602805 (Aggressotype), n° 603016 (MATRICS), n° 602450 (IMAGEMEND) and n° 278948 (TACTICS) and from the European Community’s Horizon 2020 Programme (H2020/2014—2020) under grant agreements n° 643051 (MiND) and n° 667302 (CoCA). FP7 Ideas: the European Research Council (ERC-230374 to D.B.). This work was supported by Spanish Ministry of Science and Innovation, Instituto de Salud Carlos III (SAM16PE07CP1, PI16/02012 and PI19/024), co-financed by ERDF Funds from the European Commission, ‘A way of making Europe’, CIBERSAM; Madrid Regional Government (B2017/BMD-3740 AGES-CM-2), European Union Structural Funds; European Union Seventh Framework Program under grant agreements FP7- HEALTH-2013-2.2.1-2-603196 (Project PSYSCAN) and European Union H2020 Program under the Innovative Medicines Initiative 2 Joint Undertaking (grant agreement 115916, Project PRISM and grant agreement 777394, Project AIMS-2-TRIALS), Fundación Familia Alonso, Fundación Alicia Koplowitz and Fundación Mutua Madrileña. The Horizon 2020 funded ERC Advanced Grant ‘STRATIFY’ (Brain network based stratification of reinforcement-related disorders) (695313). The FP7 project MATRICS (603016). The research leading to these results also received support from the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement 278948 (TACTICS), 602805 (Aggressotype), 603016 (MATRICS) and 602450 (Imagemend) and the Innovation Medicine Initiative grants 115300 (EU-AIMS) and 777394 (AIMS-2-TRIALS).PAFIP: PAFIP was supported by the Instituto de Salud Carlos III (PI14/00639, PI14/00918 and PI17/01056) and Fundación Instituto de Investigación Marqués de Valdecilla (NCT0235832 and NCT025KG Jebsen Stiftelsen and H2020 CoMorMent (847776).34363). European Union Marie Curie Research Training Network (MRTN-CT-2006-035987).

Published
2022

44. Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations

Author

Moguilner, Sebastian, Baez, Sandra, Hernandez, Hernan, Migeot, Joaquín, Legaz, Agustina, Gonzalez-Gomez, Raul, Farina, Francesca R., Prado, Pavel, Cuadros, Jhosmary, Tagliazucchi, Enzo, Altschuler, Florencia, Maito, Marcelo Adrián, Godoy, María E., Cruzat, Josephine, Valdes-Sosa, Pedro A., Lopera, Francisco, Ochoa-Gómez, John Fredy, Hernandez, Alfredis Gonzalez, Bonilla-Santos, Jasmin, Gonzalez-Montealegre, Rodrigo A., Anghinah, Renato, d’Almeida Manfrinati, Luís E., Fittipaldi, Sol, Medel, Vicente, Olivares, Daniela, Yener, Görsev G., Escudero, Javier, Babiloni, Claudio, Whelan, Robert, Güntekin, Bahar, Yırıkoğulları, Harun, Santamaria-Garcia, Hernando, Lucas, Alberto Fernández, Huepe, David, Di Caterina, Gaetano, Soto-Añari, Marcio, Birba, Agustina, Sainz-Ballesteros, Agustin, Coronel-Oliveros, Carlos, Yigezu, Amanuel, Herrera, Eduar, Abasolo, Daniel, Kilborn, Kerry, Rubido, Nicolás, Clark, Ruaridh A., Herzog, Ruben, Yerlikaya, Deniz, Hu, Kun, Parra, Mario A., Reyes, Pablo, García, Adolfo M., Matallana, Diana L., Avila-Funes, José Alberto, Slachevsky, Andrea, Behrens, María I., Custodio, Nilton, Cardona, Juan F., Barttfeld, Pablo, Brusco, Ignacio L., Bruno, Martín A., Sosa Ortiz, Ana L., Pina-Escudero, Stefanie D., Takada, Leonel T., Resende, Elisa, Possin, Katherine L., de Oliveira, Maira Okada, Lopez-Valdes, Alejandro, Lawlor, Brian, Robertson, Ian H., Kosik, Kenneth S., Duran-Aniotz, Claudia, Valcour, Victor, Yokoyama, Jennifer S., Miller, Bruce, and Ibanez, Agustin

Abstract

Brain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding brain health and disease. However, the impact of diversity (including geographical, socioeconomic, sociodemographic, sex and neurodegeneration) on the brain-age gap is unknown. We analyzed datasets from 5,306 participants across 15 countries (7 Latin American and Caribbean countries (LAC) and 8 non-LAC countries). Based on higher-order interactions, we developed a brain-age gap deep learning architecture for functional magnetic resonance imaging (2,953) and electroencephalography (2,353). The datasets comprised healthy controls and individuals with mild cognitive impairment, Alzheimer disease and behavioral variant frontotemporal dementia. LAC models evidenced older brain ages (functional magnetic resonance imaging: mean directional error = 5.60, root mean square error (r.m.s.e.) = 11.91; electroencephalography: mean directional error = 5.34, r.m.s.e. = 9.82) associated with frontoposterior networks compared with non-LAC models. Structural socioeconomic inequality, pollution and health disparities were influential predictors of increased brain-age gaps, especially in LAC (R² = 0.37, F² = 0.59, r.m.s.e. = 6.9). An ascending brain-age gap from healthy controls to mild cognitive impairment to Alzheimer disease was found. In LAC, we observed larger brain-age gaps in females in control and Alzheimer disease groups compared with the respective males. The results were not explained by variations in signal quality, demographics or acquisition methods. These findings provide a quantitative framework capturing the diversity of accelerated brain aging.

Published
2024
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45. Pubertal maturation and sex effects on the default-mode network connectivity implicated in mood dysregulation

Author

Ernst, Monique, Benson, Brenda, Artiges, Eric, Gorka, Adam X., Lemaitre, Herve, Lago, Tiffany, Miranda, Ruben, Banaschewski, Tobias, Bokde, Arun L. W., Bromberg, Uli, Brühl, Rüdiger, Büchel, Christian, Cattrell, Anna, Conrod, Patricia, Desrivières, Sylvane, Fadai, Tahmine, Flor, Herta, Grigis, Antoine, Gallinat, Juergen, Garavan, Hugh, Gowland, Penny, Grimmer, Yvonne, Heinz, Andreas, Kappel, Viola, Nees, Frauke, Papadopoulos-Orfanos, Dimitri, Penttilä, Jani, Poustka, Luise, Smolka, Michael N., Stringaris, Argyris, Struve, Maren, van Noort, Betteke M., Walter, Henrik, Whelan, Robert, Schumann, Gunter, Grillon, Christian, Martinot, Marie-Laure Paillère, Martinot, Jean-Luc, and for the IMAGEN Consortium

Published
2019
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46. Genuine high-order interactions in brain networks and neurodegeneration

Author

Herzog, Rubén, primary, Rosas, Fernando E., additional, Whelan, Robert, additional, Fittipaldi, Sol, additional, Santamaria-Garcia, Hernando, additional, Cruzat, Josephine, additional, Birba, Agustina, additional, Moguilner, Sebastian, additional, Tagliazucchi, Enzo, additional, Prado, Pavel, additional, and Ibanez, Agustin, additional

Published
2022
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48. The Role of Empathy in Alcohol Use of Bullying Perpetrators and Victims: Lower Personal Empathic Distress Makes Male Perpetrators of Bullying More Vulnerable to Alcohol Use.

Author

Prignitz, Maren, Banaschewski, Tobias, Bokde, Arun L. W., Desrivières, Sylvane, Grigis, Antoine, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Martinot, Jean-Luc, Paillère Martinot, Marie-Laure, Artiges, Eric, Papadopoulos Orfanos, Dimitri, Poustka, Luise, Hohmann, Sarah, Fröhner, Juliane H., Robinson, Lauren, Smolka, Michael N., Walter, Henrik, Winterer, Jeanne M., and Whelan, Robert

Published
2023
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49. Genetic risk for schizophrenia and autism, social impairment and developmental pathways to psychosis

Author

Velthorst, Eva, Froudist-Walsh, Sean, Stahl, Eli, Ruderfer, Douglas, Ivanov, Ilyan, Buxbaum, Joseph, iPSYCH-Broad ASD Group, the IMAGEN consortium, Banaschewski, Tobias, Bokde, Arun L. W., Dipl-Psych, Uli Bromberg, Büchel, Christian, Quinlan, Erin Burke, Desrivières, Sylvane, Flor, Herta, Frouin, Vincent, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Ittermann, Bernd, Martinot, Marie-Laure Paillère, Artiges, Eric, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Paus, Tomáš, Poustka, Luise, Hohmann, Sarah, Fröhner, Juliane H., Smolka, Michael N., Walter, Henrik, Whelan, Robert, Schumann, Gunter, and Reichenberg, Abraham

Published
2018
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50. Epigenetic variance in dopamine D2 receptor: a marker of IQ malleability?

Author

Kaminski, Jakob A., Schlagenhauf, Florian, Rapp, Michael, Awasthi, Swapnil, Ruggeri, Barbara, Deserno, Lorenz, Banaschewski, Tobias, Bokde, Arun L. W., Bromberg, Uli, Büchel, Christian, Quinlan, Erin Burke, Desrivières, Sylvane, Flor, Herta, Frouin, Vincent, Garavan, Hugh, Gowland, Penny, Ittermann, Bernd, Martinot, Jean-Luc, Martinot, Marie-Laure Paillère, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Paus, Tomáš, Poustka, Luise, Smolka, Michael N., Fröhner, Juliane H., Walter, Henrik, Whelan, Robert, Ripke, Stephan, Schumann, Gunter, Heinz, Andreas, and the IMAGEN consortium

Published
2018
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