Search

Your search keyword '"Veer, Ilya"' showing total 494 results
Start Over Author "Veer, Ilya"
494 results on '"Veer, Ilya"'

1. Correction: The functional connectome in obsessive-compulsive disorder: resting-state mega-analysis and machine learning classification for the ENIGMA-OCD consortium

Author

Bruin, Willem B, Abe, Yoshinari, Alonso, Pino, Anticevic, Alan, Backhausen, Lea L, Balachander, Srinivas, Bargallo, Nuria, Batistuzzo, Marcelo C, Benedetti, Francesco, Bertolin Triquell, Sara, Brem, Silvia, Calesella, Federico, Couto, Beatriz, Denys, Damiaan AJP, Echevarria, Marco AN, Eng, Goi Khia, Ferreira, Sónia, Feusner, Jamie D, Grazioplene, Rachael G, Gruner, Patricia, Guo, Joyce Y, Hagen, Kristen, Hansen, Bjarne, Hirano, Yoshiyuki, Hoexter, Marcelo Q, Jahanshad, Neda, Jaspers-Fayer, Fern, Kasprzak, Selina, Kim, Minah, Koch, Kathrin, Bin Kwak, Yoo, Kwon, Jun Soo, Lazaro, Luisa, Li, Chiang-Shan R, Lochner, Christine, Marsh, Rachel, Martínez-Zalacaín, Ignacio, Menchon, Jose M, Moreira, Pedro S, Morgado, Pedro, Nakagawa, Akiko, Nakao, Tomohiro, Narayanaswamy, Janardhanan C, Nurmi, Erika L, Zorrilla, Jose C Pariente, Piacentini, John, Picó-Pérez, Maria, Piras, Fabrizio, Piras, Federica, Pittenger, Christopher, Reddy, Janardhan YC, Rodriguez-Manrique, Daniela, Sakai, Yuki, Shimizu, Eiji, Shivakumar, Venkataram, Simpson, Blair H, Soriano-Mas, Carles, Sousa, Nuno, Spalletta, Gianfranco, Stern, Emily R, Evelyn Stewart, S, Szeszko, Philip R, Tang, Jinsong, Thomopoulos, Sophia I, Thorsen, Anders L, Yoshida, Tokiko, Tomiyama, Hirofumi, Vai, Benedetta, Veer, Ilya M, Venkatasubramanian, Ganesan, Vetter, Nora C, Vriend, Chris, Walitza, Susanne, Waller, Lea, Wang, Zhen, Watanabe, Anri, Wolff, Nicole, Yun, Je-Yeon, Zhao, Qing, van Leeuwen, Wieke A, van Marle, Hein JF, van de Mortel, Laurens A, van der Straten, Anouk, van der Werf, Ysbrand D, Thompson, Paul M, Stein, Dan J, van den Heuvel, Odile A, and van Wingen, Guido A

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Clinical and Health Psychology, Clinical Sciences, Psychology, Machine Learning and Artificial Intelligence, Mental Illness, Serious Mental Illness, Brain Disorders, Anxiety Disorders, Mental Health, Good Health and Well Being, ENIGMA-OCD Working Group, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Correction to: Molecular Psychiatry, published online 2 May 2023 In this article Honami Arai, Irene Bollettini, Rosa Calvo Escalona, Ana Coelho, Federica Colombo, Leila Darwich, Martine Fontaine, Toshikazu Ikuta, Jonathan C. Ipser, Asier Juaneda-Seguí, Hitomi Kitagawa, Gerd Kvale, Mafalda Machado-Sousa, Astrid Morer, Takashi Nakamae, Jin Narumoto, Joseph O’Neill, Sho Okawa, Eva Real, Veit Roessner, Joao R. Sato, Cinto Segalàs, Roseli G. Shavitt, Dick J. Veltman, Kei Yamada were missing from the author list indexed under the ENIGMA-OCD Working Group. Additionally, there was an error regarding Tokiko Yoshida’s name, where the first name and last name were written in the wrong order. The original article has been corrected.

Published
2023

2. The functional connectome in obsessive-compulsive disorder: resting-state mega-analysis and machine learning classification for the ENIGMA-OCD consortium.

Author

Bruin, Willem, Abe, Yoshinari, Alonso, Pino, Anticevic, Alan, Backhausen, Lea, Balachander, Srinivas, Bargallo, Nuria, Batistuzzo, Marcelo, Benedetti, Francesco, Bertolin Triquell, Sara, Brem, Silvia, Calesella, Federico, Couto, Beatriz, Denys, Damiaan, Echevarria, Marco, Eng, Goi, Ferreira, Sónia, Feusner, Jamie, Grazioplene, Rachael, Gruner, Patricia, Guo, Joyce, Hagen, Kristen, Hansen, Bjarne, Hirano, Yoshiyuki, Hoexter, Marcelo, Jahanshad, Neda, Jaspers-Fayer, Fern, Kasprzak, Selina, Kim, Minah, Koch, Kathrin, Bin Kwak, Yoo, Kwon, Jun, Lazaro, Luisa, Li, Chiang-Shan, Lochner, Christine, Marsh, Rachel, Martínez-Zalacaín, Ignacio, Menchon, Jose, Moreira, Pedro, Morgado, Pedro, Nakagawa, Akiko, Nakao, Tomohiro, Narayanaswamy, Janardhanan, Nurmi, Erika, Zorrilla, Jose, Picó-Pérez, Maria, Piras, Fabrizio, Piras, Federica, Pittenger, Christopher, Reddy, Janardhan, Rodriguez-Manrique, Daniela, Sakai, Yuki, Shimizu, Eiji, Shivakumar, Venkataram, Simpson, Blair, Soriano-Mas, Carles, Sousa, Nuno, Spalletta, Gianfranco, Stern, Emily, Evelyn Stewart, S, Szeszko, Philip, Tang, Jinsong, Thomopoulos, Sophia, Thorsen, Anders, Yoshida, Tokiko, Tomiyama, Hirofumi, Vai, Benedetta, Veer, Ilya, Venkatasubramanian, Ganesan, Vetter, Nora, Vriend, Chris, Walitza, Susanne, Waller, Lea, Wang, Zhen, Watanabe, Anri, Wolff, Nicole, Yun, Je-Yeon, Zhao, Qing, van Leeuwen, Wieke, van Marle, Hein, van de Mortel, Laurens, van der Straten, Anouk, van der Werf, Ysbrand, Thompson, Paul, Stein, Dan, van den Heuvel, Odile, van Wingen, Guido, and Piacentini, John

Subjects
Humans, Connectome, Brain Mapping, Magnetic Resonance Imaging, Brain, Obsessive-Compulsive Disorder, Biomarkers, Neural Pathways
Abstract

Current knowledge about functional connectivity in obsessive-compulsive disorder (OCD) is based on small-scale studies, limiting the generalizability of results. Moreover, the majority of studies have focused only on predefined regions or functional networks rather than connectivity throughout the entire brain. Here, we investigated differences in resting-state functional connectivity between OCD patients and healthy controls (HC) using mega-analysis of data from 1024 OCD patients and 1028 HC from 28 independent samples of the ENIGMA-OCD consortium. We assessed group differences in whole-brain functional connectivity at both the regional and network level, and investigated whether functional connectivity could serve as biomarker to identify patient status at the individual level using machine learning analysis. The mega-analyses revealed widespread abnormalities in functional connectivity in OCD, with global hypo-connectivity (Cohens d: -0.27 to -0.13) and few hyper-connections, mainly with the thalamus (Cohens d: 0.19 to 0.22). Most hypo-connections were located within the sensorimotor network and no fronto-striatal abnormalities were found. Overall, classification performances were poor, with area-under-the-receiver-operating-characteristic curve (AUC) scores ranging between 0.567 and 0.673, with better classification for medicated (AUC = 0.702) than unmedicated (AUC = 0.608) patients versus healthy controls. These findings provide partial support for existing pathophysiological models of OCD and highlight the important role of the sensorimotor network in OCD. However, resting-state connectivity does not so far provide an accurate biomarker for identifying patients at the individual level.

Published
2023

5. Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group

Author

Han, Laura KM, Dinga, Richard, Hahn, Tim, Ching, Christopher RK, Eyler, Lisa T, Aftanas, Lyubomir, Aghajani, Moji, Aleman, André, Baune, Bernhard T, Berger, Klaus, Brak, Ivan, Filho, Geraldo Busatto, Carballedo, Angela, Connolly, Colm G, Couvy-Duchesne, Baptiste, Cullen, Kathryn R, Dannlowski, Udo, Davey, Christopher G, Dima, Danai, Duran, Fabio LS, Enneking, Verena, Filimonova, Elena, Frenzel, Stefan, Frodl, Thomas, Fu, Cynthia HY, Godlewska, Beata R, Gotlib, Ian H, Grabe, Hans J, Groenewold, Nynke A, Grotegerd, Dominik, Gruber, Oliver, Hall, Geoffrey B, Harrison, Ben J, Hatton, Sean N, Hermesdorf, Marco, Hickie, Ian B, Ho, Tiffany C, Hosten, Norbert, Jansen, Andreas, Kähler, Claas, Kircher, Tilo, Klimes-Dougan, Bonnie, Krämer, Bernd, Krug, Axel, Lagopoulos, Jim, Leenings, Ramona, MacMaster, Frank P, MacQueen, Glenda, McIntosh, Andrew, McLellan, Quinn, McMahon, Katie L, Medland, Sarah E, Mueller, Bryon A, Mwangi, Benson, Osipov, Evgeny, Portella, Maria J, Pozzi, Elena, Reneman, Liesbeth, Repple, Jonathan, Rosa, Pedro GP, Sacchet, Matthew D, Sämann, Philipp G, Schnell, Knut, Schrantee, Anouk, Simulionyte, Egle, Soares, Jair C, Sommer, Jens, Stein, Dan J, Steinsträter, Olaf, Strike, Lachlan T, Thomopoulos, Sophia I, van Tol, Marie-José, Veer, Ilya M, Vermeiren, Robert RJM, Walter, Henrik, van der Wee, Nic JA, van der Werff, Steven JA, Whalley, Heather, Winter, Nils R, Wittfeld, Katharina, Wright, Margaret J, Wu, Mon-Ju, Völzke, Henry, Yang, Tony T, Zannias, Vasileios, de Zubicaray, Greig I, Zunta-Soares, Giovana B, Abé, Christoph, Alda, Martin, Andreassen, Ole A, Bøen, Erlend, Bonnin, Caterina M, Canales-Rodriguez, Erick J, Cannon, Dara, Caseras, Xavier, Chaim-Avancini, Tiffany M, Elvsåshagen, Torbjørn, Favre, Pauline, Foley, Sonya F, and Fullerton, Janice M

Subjects
Depression, Aging, Brain Disorders, Biomedical Imaging, Serious Mental Illness, Mental Health, Major Depressive Disorder, Behavioral and Social Science, Clinical Research, Neurosciences, 2.3 Psychological, social and economic factors, Aetiology, Mental health, Adolescent, Adult, Aged, Brain, Depressive Disorder, Major, Female, Humans, Longitudinal Studies, Magnetic Resonance Imaging, Male, Middle Aged, Young Adult, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.

Published
2021

7. Interactive impact of childhood maltreatment, depression, and age on cortical brain structure: mega-analytic findings from a large multi-site cohort

Author

Tozzi, Leonardo, Garczarek, Lisa, Janowitz, Deborah, Stein, Dan J, Wittfeld, Katharina, Dobrowolny, Henrik, Lagopoulos, Jim, Hatton, Sean N, Hickie, Ian B, Carballedo, Angela, Brooks, Samantha J, Vuletic, Daniella, Uhlmann, Anne, Veer, Ilya M, Walter, Henrik, Bülow, Robin, Völzke, Henry, Klinger-König, Johanna, Schnell, Knut, Schoepf, Dieter, Grotegerd, Dominik, Opel, Nils, Dannlowski, Udo, Kugel, Harald, Schramm, Elisabeth, Konrad, Carsten, Kircher, Tilo, Jüksel, Dilara, Nenadić, Igor, Krug, Axel, Hahn, Tim, Steinsträter, Olaf, Redlich, Ronny, Zaremba, Dario, Zurowski, Bartosz, Fu, Cynthia HY, Dima, Danai, Cole, James, Grabe, Hans J, Connolly, Colm G, Yang, Tony T, Ho, Tiffany C, LeWinn, Kaja Z, Li, Meng, Groenewold, Nynke A, Salminen, Lauren E, Walter, Martin, Simmons, Alan N, van Erp, Theo GM, Jahanshad, Neda, Baune, Bernhard T, van der Wee, Nic JA, van Tol, Marie-Jose, Penninx, Brenda WJH, Hibar, Derrek P, Thompson, Paul M, Veltman, Dick J, Schmaal, Lianne, and Frodl, Thomas

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Clinical Sciences, Psychology, Pediatric, Neurosciences, Clinical Research, Mental Health, Brain Disorders, Depression, Child Abuse and Neglect Research, Behavioral and Social Science, Violence Research, Aetiology, 2.1 Biological and endogenous factors, Adolescent, Adult, Age Factors, Aged, Aged, 80 and over, Brain Cortical Thickness, Case-Control Studies, Cerebral Cortex, Child, Child Abuse, Cohort Studies, Depressive Disorder, Major, Female, Gyrus Cinguli, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Parietal Lobe, Prefrontal Cortex, Temporal Lobe, Young Adult, Childhood maltreatment, cortical thickness, ENIGMA, major depressive disorder, ‘for the ENIGMA-MDD Consortium’, Public Health and Health Services, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

BackgroundChildhood maltreatment (CM) plays an important role in the development of major depressive disorder (MDD). The aim of this study was to examine whether CM severity and type are associated with MDD-related brain alterations, and how they interact with sex and age.MethodsWithin the ENIGMA-MDD network, severity and subtypes of CM using the Childhood Trauma Questionnaire were assessed and structural magnetic resonance imaging data from patients with MDD and healthy controls were analyzed in a mega-analysis comprising a total of 3872 participants aged between 13 and 89 years. Cortical thickness and surface area were extracted at each site using FreeSurfer.ResultsCM severity was associated with reduced cortical thickness in the banks of the superior temporal sulcus and supramarginal gyrus as well as with reduced surface area of the middle temporal lobe. Participants reporting both childhood neglect and abuse had a lower cortical thickness in the inferior parietal lobe, middle temporal lobe, and precuneus compared to participants not exposed to CM. In males only, regardless of diagnosis, CM severity was associated with higher cortical thickness of the rostral anterior cingulate cortex. Finally, a significant interaction between CM and age in predicting thickness was seen across several prefrontal, temporal, and temporo-parietal regions.ConclusionsSeverity and type of CM may impact cortical thickness and surface area. Importantly, CM may influence age-dependent brain maturation, particularly in regions related to the default mode network, perception, and theory of mind.

Published
2020

8. Deep Learning for Quality Control of Subcortical Brain 3D Shape Models

Author

Petrov, Dmitry, Kuznetsov, Boris A. Gutman Egor, van Erp, Theo G. M., Turner, Jessica A., Schmaal, Lianne, Veltman, Dick, Wang, Lei, Alpert, Kathryn, Isaev, Dmitry, Zavaliangos-Petropulu, Artemis, Ching, Christopher R. K., Calhoun, Vince, Glahn, David, Satterthwaite, Theodore D., Andreassen, Ole Andreas, Borgwardt, Stefan, Howells, Fleur, Groenewold, Nynke, Voineskos, Aristotle, Radua, Joaquim, Potkin, Steven G., Crespo-Facorro, Benedicto, Tordesillas-Gutierrez, Diana, Shen, Li, Lebedeva, Irina, Spalletta, Gianfranco, Donohoe, Gary, Kochunov, Peter, Rosa, Pedro G. P., James, Anthony, Dannlowski, Udo, Baune, Bernhard T., Aleman, Andre, Gotlib, Ian H., Walter, Henrik, Walter, Martin, Soares, Jair C., Ehrlich, Stefan, Gur, Ruben C., Doan, N. Trung, Agartz, Ingrid, Westlye, Lars T., Harrisberger, Fabienne, Riecher-Rossler, Anita, Uhlmann, Anne, Stein, Dan J., Dickie, Erin W., Pomarol-Clotet, Edith, Fuentes-Claramonte, Paola, Canales-Rodriguez, Erick Jorge, Salvador, Raymond, Huang, Alexander J., Roiz-Santianez, Roberto, Cong, Shan, Tomyshev, Alexander, Piras, Fabrizio, Vecchio, Daniela, Banaj, Nerisa, Ciullo, Valentina, Hong, Elliot, Busatto, Geraldo, Zanetti, Marcus V., Serpa, Mauricio H., Cervenka, Simon, Kelly, Sinead, Grotegerd, Dominik, Sacchet, Matthew D., Veer, Ilya M., Li, Meng, Wu, Mon-Ju, Irungu, Benson, Walton, Esther, and Thompson, Paul M.

Subjects
Quantitative Biology - Neurons and Cognition
Abstract

We present several deep learning models for assessing the morphometric fidelity of deep grey matter region models extracted from brain MRI. We test three different convolutional neural net architectures (VGGNet, ResNet and Inception) over 2D maps of geometric features. Further, we present a novel geometry feature augmentation technique based on a parametric spherical mapping. Finally, we present an approach for model decision visualization, allowing human raters to see the areas of subcortical shapes most likely to be deemed of failing quality by the machine. Our training data is comprised of 5200 subjects from the ENIGMA Schizophrenia MRI cohorts, and our test dataset contains 1500 subjects from the ENIGMA Major Depressive Disorder cohorts. Our final models reduce human rater time by 46-70%. ResNet outperforms VGGNet and Inception for all of our predictive tasks., Comment: Accepted to Shape in Medical Imaging (ShapeMI) workshop at MICCAI 2018. arXiv admin note: substantial text overlap with arXiv:1707.06353

Published
2018

11. Machine Learning for Large-Scale Quality Control of 3D Shape Models in Neuroimaging

Author

Petrov, Dmitry, Gutman, Boris A., Shih-Hua, Yu, van Erp, Theo G. M., Turner, Jessica A., Schmaal, Lianne, Veltman, Dick, Wang, Lei, Alpert, Kathryn, Isaev, Dmitry, Zavaliangos-Petropulu, Artemis, Ching, Christopher R. K., Calhoun, Vince, Glahn, David, Satterthwaite, Theodore D., Andreasen, Ole Andreas, Borgwardt, Stefan, Howells, Fleur, Groenewold, Nynke, Voineskos, Aristotle, Radua, Joaquim, Potkin, Steven G., Crespo-Facorro, Benedicto, Tordesillas-Gutierrez, Diana, Shen, Li, Lebedeva, Irina, Spalletta, Gianfranco, Donohoe, Gary, Kochunov, Peter, Rosa, Pedro G. P., James, Anthony, Dannlowski, Udo, Baune, Bernhard T., Aleman, Andre, Gotlib, Ian H., Walter, Henrik, Walter, Martin, Soares, Jair C., Ehrlich, Stefan, Gur, Ruben C., Doan, N. Trung, Agartz, Ingrid, Westlye, Lars T., Harrisberger, Fabienne, Riecher-Rossler, Anita, Uhlmann, Anne, Stein, Dan J., Dickie, Erin W., Pomarol-Clotet, Edith, Fuentes-Claramonte, Paola, Canales-Rodriguez, Erick Jorge, Salvador, Raymond, Huang, Alexander J., Roiz-Santianez, Roberto, Cong, Shan, Tomyshev, Alexander, Piras, Fabrizio, Vecchio, Daniela, Banaj, Nerisa, Ciullo, Valentina, Hong, Elliot, Busatto, Geraldo, Zanetti, Marcus V., Serpa, Mauricio H., Cervenka, Simon, Kelly, Sinead, Grotegerd, Dominik, Sacchet, Matthew D., Veer, Ilya M., Li, Meng, Wu, Mon-Ju, Irungu, Benson, Walton, Esther, and Thompson, Paul M.

Subjects
Quantitative Biology - Quantitative Methods
Abstract

As very large studies of complex neuroimaging phenotypes become more common, human quality assessment of MRI-derived data remains one of the last major bottlenecks. Few attempts have so far been made to address this issue with machine learning. In this work, we optimize predictive models of quality for meshes representing deep brain structure shapes. We use standard vertex-wise and global shape features computed homologously across 19 cohorts and over 7500 human-rated subjects, training kernelized Support Vector Machine and Gradient Boosted Decision Trees classifiers to detect meshes of failing quality. Our models generalize across datasets and diseases, reducing human workload by 30-70\%, or equivalently hundreds of human rater hours for datasets of comparable size, with recall rates approaching inter-rater reliability., Comment: Arxiv version of the MICCAI 2017 Machine Learning in Medical Imaging workshop paper

Published
2017

12. Classification of Major Depressive Disorder via Multi-Site Weighted LASSO Model

Author

Zhu, Dajiang, Riedel, Brandalyn C., Jahanshad, Neda, Groenewold, Nynke A., Stein, Dan J., Gotlib, Ian H., Sacchet, Matthew D., Dima, Danai, Cole, James H., Fu, Cynthia H. Y., Walter, Henrik, Veer, Ilya M., Frodl, Thomas, Schmaal, Lianne, Veltman, Dick J., and Thompson, Paul M.

Subjects
Computer Science - Learning, Computer Science - Computational Engineering, Finance, and Science, Statistics - Applications
Abstract

Large-scale collaborative analysis of brain imaging data, in psychiatry and neu-rology, offers a new source of statistical power to discover features that boost ac-curacy in disease classification, differential diagnosis, and outcome prediction. However, due to data privacy regulations or limited accessibility to large datasets across the world, it is challenging to efficiently integrate distributed information. Here we propose a novel classification framework through multi-site weighted LASSO: each site performs an iterative weighted LASSO for feature selection separately. Within each iteration, the classification result and the selected features are collected to update the weighting parameters for each feature. This new weight is used to guide the LASSO process at the next iteration. Only the fea-tures that help to improve the classification accuracy are preserved. In tests on da-ta from five sites (299 patients with major depressive disorder (MDD) and 258 normal controls), our method boosted classification accuracy for MDD by 4.9% on average. This result shows the potential of the proposed new strategy as an ef-fective and practical collaborative platform for machine learning on large scale distributed imaging and biobank data., Comment: Accepted by MICCAI 2017

Published
2017

13. Comparative investigation of appraisal style measures in their predictive potential for stress resilience and implications for predictive modeling of resilience

Author

Petri-Romão, Papoula, primary, Puhlmann, Lara, additional, Zerban, Matthias, additional, Ahrens, Kira Florence, additional, AriasVasquez, Alejandro, additional, Basten, Ulrike, additional, Binder, Harald, additional, Bögemann, Sophie, additional, Chmitorz, Andrea, additional, Farhadyar, Kiana, additional, Fernandez, Guillén, additional, Goris, Annelies, additional, Hendler, Talma, additional, Hermans, Erno, additional, Jacobs, An, additional, Kleim, Birgit, additional, Kobylinska, Dorota, additional, Köber, Göran, additional, Kollmann, Bianca, additional, Krause, Florian, additional, Lerner, Avigail, additional, Lieb, Klaus, additional, Marciniak, Marta Anna, additional, Mituniewicz, Julian, additional, Mor, Netali, additional, Myin-Germeys, Inez, additional, Neumann, Rebecca J, additional, Plichta, Michael, additional, Pooseh, Shakoor, additional, Reif, Andreas, additional, Reppmann, Zala, additional, Riepenhausen, Antje, additional, Robak, Natalia, additional, Roelofs, Karin, additional, Schenk, Charlotte, additional, Schick, Anita, additional, Sebastian, Alexandra, additional, Timmer, Jens, additional, Tüscher, Oliver, additional, van Kraaij, Alex, additional, Veer, Ilya, additional, Wackerhagen, Carolin, additional, Walter, Henrik, additional, Weermeijer, Jeroen Dennis, Merlijn, additional, Wessa, Michele, additional, Yuen, Kenneth S.L., additional, and Kalisch, Raffael, additional

Published
2024
Full Text
View/download PDF

14. Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders: Evidence through univariate and multivariate mega-analysis including 6420 participants from the ENIGMA MDD working group

Author

Opel, Nils, Thalamuthu, Anbupalam, Milaneschi, Yuri, Grotegerd, Dominik, Flint, Claas, Leenings, Ramona, Goltermann, Janik, Richter, Maike, Hahn, Tim, Woditsch, Georg, Berger, Klaus, Hermesdorf, Marco, McIntosh, Andrew, Whalley, Heather C., Harris, Mathew A., MacMaster, Frank P., Walter, Henrik, Veer, Ilya M., Frodl, Thomas, Carballedo, Angela, Krug, Axel, Nenadic, Igor, Kircher, Tilo, Aleman, Andre, Groenewold, Nynke A., Stein, Dan J., Soares, Jair C., Zunta-Soares, Giovana B., Mwangi, Benson, Wu, Mon-Ju, Walter, Martin, Li, Meng, Harrison, Ben J., Davey, Christopher G., Cullen, Kathryn R., Klimes-Dougan, Bonnie, Mueller, Bryon A., Sämann, Philipp G., Penninx, Brenda, Nawijn, Laura, Veltman, Dick J., Aftanas, Lyubomir, Brak, Ivan V., Filimonova, Elena A., Osipov, Evgeniy A., Reneman, Liesbeth, Schrantee, Anouk, Grabe, Hans J., Van der Auwera, Sandra, Wittfeld, Katharina, Hosten, Norbert, Völzke, Henry, Sim, Kang, Gotlib, Ian H., Sacchet, Matthew D., Lagopoulos, Jim, Hatton, Sean N., Hickie, Ian, Pozzi, Elena, Thompson, Paul M., Jahanshad, Neda, Schmaal, Lianne, Baune, Bernhard T., and Dannlowski, Udo

Published
2021
Full Text
View/download PDF

15. Childhood adversity impacts on brain subcortical structures relevant to depression

Author

Frodl, Thomas, Janowitz, Deborah, Schmaal, Lianne, Tozzi, Leonardo, Dobrowolny, Henrik, Stein, Dan J, Veltman, Dick J, Wittfeld, Katharina, van Erp, Theo GM, Jahanshad, Neda, Block, Andrea, Hegenscheid, Katrin, Völzke, Henry, Lagopoulos, Jim, Hatton, Sean N, Hickie, Ian B, Frey, Eva Maria, Carballedo, Angela, Brooks, Samantha J, Vuletic, Daniella, Uhlmann, Anne, Veer, Ilya M, Walter, Henrik, Schnell, Knut, Grotegerd, Dominik, Arolt, Volker, Kugel, Harald, Schramm, Elisabeth, Konrad, Carsten, Zurowski, Bartosz, Baune, Bernhard T, van der Wee, Nic JA, van Tol, Marie-Jose, Penninx, Brenda WJH, Thompson, Paul M, Hibar, Derrek P, Dannlowski, Udo, and Grabe, Hans J

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Clinical Sciences, Psychology, Mental Health, Violence Research, Serious Mental Illness, Behavioral and Social Science, Depression, Major Depressive Disorder, Brain Disorders, Pediatric, Neurosciences, Aetiology, 2.3 Psychological, social and economic factors, Mental health, Adult, Adult Survivors of Child Adverse Events, Antidepressive Agents, Brain, Depressive Disorder, Major, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Organ Size, Psychiatric Status Rating Scales, Sex Characteristics, Software, Surveys and Questionnaires, Childhood adversity, MRI, Caudate, Hippocampus, ENIGMA, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Clinical and health psychology
Abstract

Childhood adversity plays an important role for development of major depressive disorder (MDD). There are differences in subcortical brain structures between patients with MDD and healthy controls, but the specific impact of childhood adversity on such structures in MDD remains unclear. Thus, aim of the present study was to investigate whether childhood adversity is associated with subcortical volumes and how it interacts with a diagnosis of MDD and sex. Within the ENIGMA-MDD network, nine university partner sites, which assessed childhood adversity and magnetic resonance imaging in patients with MDD and controls, took part in the current joint mega-analysis. In this largest effort world-wide to identify subcortical brain structure differences related to childhood adversity, 3036 participants were analyzed for subcortical brain volumes using FreeSurfer. A significant interaction was evident between childhood adversity, MDD diagnosis, sex, and region. Increased exposure to childhood adversity was associated with smaller caudate volumes in females independent of MDD. All subcategories of childhood adversity were negatively associated with caudate volumes in females - in particular emotional neglect and physical neglect (independently from age, ICV, imaging site and MDD diagnosis). There was no interaction effect between childhood adversity and MDD diagnosis on subcortical brain volumes. Childhood adversity is one of the contributors to brain structural abnormalities. It is associated with subcortical brain abnormalities that are relevant to psychiatric disorders such as depression.

Published
2017

16. Burst versus continuous delivery design in digital mental health interventions: Evidence from a randomized clinical trial

Author

Marciniak, Marta Anna; https://orcid.org/0000-0003-4301-3269, Shanahan, Lilly; https://orcid.org/0000-0002-4534-6924, Yuen, Kenneth S L; https://orcid.org/0000-0002-9465-9070, Veer, Ilya Milos, Walter, Henrik; https://orcid.org/0000-0002-9403-6121, Tuescher, Oliver; https://orcid.org/0000-0002-4023-5301, Kobylińska, Dorota; https://orcid.org/0000-0003-0184-2595, Kalisch, Raffael; https://orcid.org/0000-0002-9503-7601, Hermans, Erno; https://orcid.org/0000-0003-1339-8639, Binder, Harald; https://orcid.org/0000-0002-5666-8662, Kleim, Birgit; https://orcid.org/0000-0001-9114-2917, Marciniak, Marta Anna; https://orcid.org/0000-0003-4301-3269, Shanahan, Lilly; https://orcid.org/0000-0002-4534-6924, Yuen, Kenneth S L; https://orcid.org/0000-0002-9465-9070, Veer, Ilya Milos, Walter, Henrik; https://orcid.org/0000-0002-9403-6121, Tuescher, Oliver; https://orcid.org/0000-0002-4023-5301, Kobylińska, Dorota; https://orcid.org/0000-0003-0184-2595, Kalisch, Raffael; https://orcid.org/0000-0002-9503-7601, Hermans, Erno; https://orcid.org/0000-0003-1339-8639, Binder, Harald; https://orcid.org/0000-0002-5666-8662, and Kleim, Birgit; https://orcid.org/0000-0001-9114-2917

Abstract

Objective Digital mental health interventions delivered via smartphone-based apps effectively treat various conditions; however, optimizing their efficacy while minimizing participant burden remains a key challenge. In this study, we investigated the potential benefits of a burst delivery design (i.e. interventions delivered only in pre-defined time intervals) in comparison to the continuous delivery of interventions. Methods We randomly assigned 93 participants to the continuous delivery (CD) or burst delivery (BD) group. The CD group engaged in ReApp, a mobile app that increases positive cognitive reappraisal with a consistent delivery schedule that provides five prompts per day throughout the 3-week-long study, while the BD group received five daily prompts only in the first and third weeks of the study. Results No significant differences were found between the groups in terms of adherence, mental health outcomes (specifically depressive and anxiety symptoms), level of perceived stress, and perceived helpfulness of intervention. The BD group showed a significantly decreased perceived difficulty of intervention over time. Conclusions The results suggest that the burst delivery may be as suitable for digital mental health interventions as the continuous delivery. The perceived difficulty of the intervention declined more steeply for the BD group, indicating that it improved the feasibility of the positive cognitive reappraisal intervention without hurting its efficacy. This outcome may inform the design of less burdensome interventions with improved outcomes in future research.

Published
2024

17. Burst versus continuous delivery design in digital mental health interventions: Evidence from a randomized clinical trial

Author

Marciniak, Marta Anna, Shanahan, Lilly, Yuen, Kenneth S L, Veer, Ilya Milos, Walter, Henrik, Tuescher, Oliver, Kobylińska, Dorota, Kalisch, Raffael, Hermans, Erno, Binder, Harald, Kleim, Birgit, Marciniak, Marta Anna, Shanahan, Lilly, Yuen, Kenneth S L, Veer, Ilya Milos, Walter, Henrik, Tuescher, Oliver, Kobylińska, Dorota, Kalisch, Raffael, Hermans, Erno, Binder, Harald, and Kleim, Birgit

Abstract

Objective: Digital mental health interventions delivered via smartphone-based apps effectively treat various conditions; however, optimizing their efficacy while minimizing participant burden remains a key challenge. In this study, we investigated the potential benefits of a burst delivery design (i.e. interventions delivered only in pre-defined time intervals) in comparison to the continuous delivery of interventions. Methods: We randomly assigned 93 participants to the continuous delivery (CD) or burst delivery (BD) group. The CD group engaged in ReApp, a mobile app that increases positive cognitive reappraisal with a consistent delivery schedule that provides five prompts per day throughout the 3-week-long study, while the BD group received five daily prompts only in the first and third weeks of the study. Results: No significant differences were found between the groups in terms of adherence, mental health outcomes (specifically depressive and anxiety symptoms), level of perceived stress, and perceived helpfulness of intervention. The BD group showed a significantly decreased perceived difficulty of intervention over time. Conclusions: The results suggest that the burst delivery may be as suitable for digital mental health interventions as the continuous delivery. The perceived difficulty of the intervention declined more steeply for the BD group, indicating that it improved the feasibility of the positive cognitive reappraisal intervention without hurting its efficacy. This outcome may inform the design of less burdensome interventions with improved outcomes in future research.

Published
2024

18. Attentional Biases and Their Association with Substance-Use-Related Problems and Addictive Behaviors:The Utility of a Gamified Value-Modulated Attentional Capture Task

Author

Freichel, René, Christensen, Erynn, Mrkonja, Lana, de Jong, Peter J, Cousijn, Janna, Franken, Ingmar, Yücel, Murat, Lee, Rico, Veer, Ilya M, Albertella, Lucy, Wiers, Reinout W, Freichel, René, Christensen, Erynn, Mrkonja, Lana, de Jong, Peter J, Cousijn, Janna, Franken, Ingmar, Yücel, Murat, Lee, Rico, Veer, Ilya M, Albertella, Lucy, and Wiers, Reinout W

Abstract

BACKGROUND: Attentional biases towards reward stimuli have been implicated in substance use-related problems. The value-modulated attentional capture (VMAC) task assesses such reward-related biases. The VMAC task widely used in lab studies tends to be monotonous and susceptible to low effort. We therefore tested a gamified online version of the VMAC that aimed to increase participant engagement. Our goal was to examine how VMAC is associated with substance use-related problems and addictive behaviors, and whether this association is moderated by cognitive control.METHODS: We recruited 285 participants from an online community, including heavy alcohol users. All participants completed a novel gamified version of the VMAC task, measures of substance use and addictive behaviors (addictive-like eating behavior, problematic smartphone use), the WebExec measure of problems with executive functions, and the Stroop Adaptive Deadline Task (SDL) as a measure of cognitive control.RESULTS: The gamified VMAC task successfully identified value-modulated attentional capture effects towards high-reward stimuli. We found no significant associations between VMAC scores, problematic alcohol or cannabis use, addictive behaviors, or any moderation by a behavioral measure of cognitive control. Exploratory analyses revealed that self-reported cognitive problems were associated with more alcohol-, and cannabis-related problems, and addictive behaviors. Greater attentional capture (VMAC) was associated with more cannabis use-related problems among individuals with higher levels of self-reported cognitive problems.CONCLUSIONS: Our study is one of the first to demonstrate the utility of the gamified version of the VMAC task in capturing attentional reward biases. Self-reported problems with cognitive functions represent a key dimension associated with substance use-related problems and addictive behaviors.

Published
2024

26. White matter disturbances in major depressive disorder: a coordinated analysis across 20 international cohorts in the ENIGMA MDD working group

Author

van Velzen, Laura S., Kelly, Sinead, Isaev, Dmitry, Aleman, Andre, Aftanas, Lyubomir I., Bauer, Jochen, Baune, Bernhard T., Brak, Ivan V., Carballedo, Angela, Connolly, Colm G., Couvy-Duchesne, Baptiste, Cullen, Kathryn R., Danilenko, Konstantin V., Dannlowski, Udo, Enneking, Verena, Filimonova, Elena, Förster, Katharina, Frodl, Thomas, Gotlib, Ian H., Groenewold, Nynke A., Grotegerd, Dominik, Harris, Mathew A., Hatton, Sean N., Hawkins, Emma L., Hickie, Ian B., Ho, Tiffany C., Jansen, Andreas, Kircher, Tilo, Klimes-Dougan, Bonnie, Kochunov, Peter, Krug, Axel, Lagopoulos, Jim, Lee, Renick, Lett, Tristram A., Li, Meng, MacMaster, Frank P., Martin, Nicholas G., McIntosh, Andrew M., McLellan, Quinn, Meinert, Susanne, Nenadić, Igor, Osipov, Evgeny, Penninx, Brenda W. J. H., Portella, Maria J., Repple, Jonathan, Roos, Annerine, Sacchet, Matthew D., Sämann, Philipp G., Schnell, Knut, Shen, Xueyi, Sim, Kang, Stein, Dan J., van Tol, Marie-Jose, Tomyshev, Alexander S., Tozzi, Leonardo, Veer, Ilya M., Vermeiren, Robert, Vives-Gilabert, Yolanda, Walter, Henrik, Walter, Martin, van der Wee, Nic J. A., van der Werff, Steven J. A., Schreiner, Melinda Westlund, Whalley, Heather C., Wright, Margaret J., Yang, Tony T., Zhu, Alyssa, Veltman, Dick J., Thompson, Paul M., Jahanshad, Neda, and Schmaal, Lianne

Published
2020
Full Text
View/download PDF

27. Identification of neurobehavioural symptom groups based on shared brain mechanisms

Author

Ing, Alex, Sämann, Philipp G., Chu, Congying, Tay, Nicole, Biondo, Francesca, Robert, Gabriel, Jia, Tianye, Wolfers, Thomas, Desrivières, Sylvane, Banaschewski, Tobias, Bokde, Arun L. W., Bromberg, Uli, Büchel, Christian, Conrod, Patricia, Fadai, Tahmine, Flor, Herta, Frouin, Vincent, Garavan, Hugh, Spechler, Philip A., Gowland, Penny, Grimmer, Yvonne, Heinz, Andreas, Ittermann, Bernd, Kappel, Viola, Martinot, Jean-Luc, Meyer-Lindenberg, Andreas, Millenet, Sabina, Nees, Frauke, van Noort, Betteke, Orfanos, Dimitri Papadopoulos, Martinot, Marie-Laure Paillère, Penttilä, Jani, Poustka, Luise, Quinlan, Erin Burke, Smolka, Michael N., Stringaris, Argyris, Struve, Maren, Veer, Ilya M., Walter, Henrik, Whelan, Robert, Andreassen, Ole A., Agartz, Ingrid, Lemaitre, Hervé, Barker, Edward D., Ashburner, John, Binder, Elisabeth, Buitelaar, Jan, Marquand, Andre, Robbins, Trevor W., and Schumann, Gunter

Published
2019
Full Text
View/download PDF

28. Psycho-social factors associated with mental resilience in the Corona lockdown

Author

Veer, Ilya M., Riepenhausen, Antje, Zerban, Matthias, Wackerhagen, Carolin, Puhlmann, Lara M. C., Engen, Haakon, Köber, Göran, Bögemann, Sophie A., Weermeijer, Jeroen, Uściłko, Aleksandra, Mor, Netali, Marciniak, Marta A., Askelund, Adrian Dahl, Al-Kamel, Abbas, Ayash, Sarah, Barsuola, Giulia, Bartkute-Norkuniene, Vaida, Battaglia, Simone, Bobko, Yaryna, Bölte, Sven, Cardone, Paolo, Chvojková, Edita, Damnjanović, Kaja, De Calheiros Velozo, Joana, de Thurah, Lena, Deza-Araujo, Yacila I., Dimitrov, Annika, Farkas, Kinga, Feller, Clémence, Gazea, Mary, Gilan, Donya, Gnjidić, Vedrana, Hajduk, Michal, Hiekkaranta, Anu P., Hofgaard, Live S., Ilen, Laura, Kasanova, Zuzana, Khanpour, Mohsen, Lau, Bobo Hi Po, Lenferink, Dionne B., Lindhardt, Thomas B., Magas, Dávid Á., Mituniewicz, Julian, Moreno-López, Laura, Muzychka, Sofiia, Ntafouli, Maria, O’Leary, Aet, Paparella, Ilenia, Põldver, Nele, Rintala, Aki, Robak, Natalia, Rosická, Anna M., Røysamb, Espen, Sadeghi, Siavash, Schneider, Maude, Siugzdaite, Roma, Stantić, Mirta, Teixeira, Ana, Todorovic, Ana, Wan, Wendy W. N., van Dick, Rolf, Lieb, Klaus, Kleim, Birgit, Hermans, Erno J., Kobylińska, Dorota, Hendler, Talma, Binder, Harald, Myin-Germeys, Inez, van Leeuwen, Judith M. C., Tüscher, Oliver, Yuen, Kenneth S. L., Walter, Henrik, and Kalisch, Raffael

Published
2021
Full Text
View/download PDF

29. Imager—A mobile health mental imagery‐based ecological momentary intervention targeting reward sensitivity: A randomized controlled trial.

Author

Marciniak, Marta Anna, Shanahan, Lilly, Myin‐Germeys, Inez, Veer, Ilya Milos, Yuen, Kenneth S. L., Binder, Harald, Walter, Henrik, Hermans, Erno J., Kalisch, Raffael, and Kleim, Birgit

Subjects
REWARD (Psychology), ECOLOGICAL momentary assessments (Clinical psychology), MOBILE health, RANDOMIZED controlled trials, MENTAL health, MENTAL illness
Abstract

Robust reward sensitivity may help preserve mental well‐being in the face of adversity and has been proposed as a key stress resilience factor. Here, we present a mobile health application, "Imager," which targets reward sensitivity by training individuals to create mental images of future rewarding experiences. We conducted a two‐arm randomized controlled trial with 95 participants screened for reward sensitivity. Participants in the intervention group received an ecological momentary intervention—Imager, which encouraged participants to create mental images of rewarding events for 1 week. The control group participants received only ecological momentary assessment, without the instruction to generate mental images. Adherence to Imager was high; participants in the intervention group engaged in 88% of the planned activities. In the follow‐up assessment, the intervention group reported less mental health symptoms, mainly in depression (β = −0.34, df = 93, p =.004) and less perceived stress (β = −0.18, df = 93, p =.035), than control group participants and compared with the baseline assessment. Our results show the positive effects of Imager on mental health symptoms. The encouraging effects of the app on mental health outcomes may lead to greater use of ecological momentary interventions in the clinical preventive practice of affective disorders. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

30. Imager—A mobile health mental imagery‐based ecological momentary intervention targeting reward sensitivity: A randomized controlled trial

Author

Marciniak, Marta Anna, primary, Shanahan, Lilly, additional, Myin‐Germeys, Inez, additional, Veer, Ilya Milos, additional, Yuen, Kenneth S. L., additional, Binder, Harald, additional, Walter, Henrik, additional, Hermans, Erno J., additional, Kalisch, Raffael, additional, and Kleim, Birgit, additional

Published
2023
Full Text
View/download PDF

31. Psychological Resilience Factors and Their Association With Weekly Stressor Reactivity During the COVID-19 Outbreak in Europe: Prospective Longitudinal Study

Author

Bögemann, Sophie A, primary, Puhlmann, Lara M C, additional, Wackerhagen, Carolin, additional, Zerban, Matthias, additional, Riepenhausen, Antje, additional, Köber, Göran, additional, Yuen, Kenneth S L, additional, Pooseh, Shakoor, additional, Marciniak, Marta A, additional, Reppmann, Zala, additional, Uściƚko, Aleksandra, additional, Weermeijer, Jeroen, additional, Lenferink, Dionne B, additional, Mituniewicz, Julian, additional, Robak, Natalia, additional, Donner, Nina C, additional, Mestdagh, Merijn, additional, Verdonck, Stijn, additional, van Dick, Rolf, additional, Kleim, Birgit, additional, Lieb, Klaus, additional, van Leeuwen, Judith M C, additional, Kobylińska, Dorota, additional, Myin-Germeys, Inez, additional, Walter, Henrik, additional, Tüscher, Oliver, additional, Hermans, Erno J, additional, Veer, Ilya M, additional, and Kalisch, Raffael, additional

Published
2023
Full Text
View/download PDF

32. Value-modulated attentional capture in reward and punishment contexts, attentional control, and their relationship with psychopathology

Author

Freichel, René, primary, Mrkonja, Lana, additional, de Jong, Peter J., additional, Cousijn, Janna, additional, Franken, Ingmar, additional, Ruiter, Tom A., additional, Le Pelley, Mike, additional, Albertella, Lucy, additional, Watson, Poppy, additional, Veer, Ilya M., additional, and Wiers, Reinout W., additional

Published
2023
Full Text
View/download PDF

33. Attentional Biases and Their Association with Substance-Use-Related Problems and Addictive Behaviors: The Utility of a Gamified Value-Modulated Attentional Capture Task

Author

Freichel, René, primary, Christensen, Erynn, additional, Mrkonja, Lana, additional, de Jong, Peter J., additional, Cousijn, Janna, additional, Franken, Ingmar H.A., additional, Yucel, Murat, additional, Lee, Rico, additional, Veer, Ilya, additional, Albertella, Lucy, additional, and Wiers, Reinout, additional

Published
2023
Full Text
View/download PDF

35. Structural and functional brain connectivity in presymptomatic familial frontotemporal dementia

Author

Dopper, Elise GP, Rombouts, Serge ARB, Jiskoot, Lize C, Heijer, Tom den, de Graaf, J Roos A, de Koning, Inge, Hammerschlag, Anke R, Seelaar, Harro, Seeley, William W, Veer, Ilya M, van Buchem, Mark A, Rizzu, Patrizia, and van Swieten, John C

Subjects
Alzheimer's Disease, Aging, Dementia, Neurodegenerative, Rare Diseases, Biomedical Imaging, Prevention, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Acquired Cognitive Impairment, Brain Disorders, Neurosciences, Frontotemporal Dementia (FTD), Clinical Research, Neurological, Adult, Aged, Brain Chemistry, Case-Control Studies, Female, Frontal Lobe, Frontotemporal Dementia, Genetic Predisposition to Disease, Humans, Male, Middle Aged, Mutation, Nerve Net, Risk, Structure-Activity Relationship, Clinical Sciences, Cognitive Sciences, Neurology & Neurosurgery
Abstract

ObjectiveWe aimed to investigate whether cognitive deficits and structural and functional connectivity changes can be detected before symptom onset in a large cohort of carriers of microtubule-associated protein tau and progranulin mutations.MethodsIn this case-control study, 75 healthy individuals (aged 20-70 years) with 50% risk for frontotemporal dementia (FTD) underwent DNA screening, neuropsychological assessment, and structural and functional MRI. We used voxel-based morphometry and tract-based spatial statistics for voxelwise analyses of gray matter volume and diffusion tensor imaging measures. Using resting-state fMRI scans, we assessed whole-brain functional connectivity to frontoinsula, anterior midcingulate cortex (aMCC), and posterior cingulate cortex.ResultsAlthough carriers (n = 37) and noncarriers (n = 38) had similar neuropsychological performance, worse performance on Stroop III, Ekman faces, and Happé cartoons correlated with higher age in carriers, but not controls. Reduced fractional anisotropy and increased radial diffusivity throughout frontotemporal white matter tracts were found in carriers and correlated with higher age. Reductions in functional aMCC connectivity were found in carriers compared with controls, and connectivity between frontoinsula and aMCC seeds and several brain regions significantly decreased with higher age in carriers but not controls. We found no significant differences or age correlations in posterior cingulate cortex connectivity. No differences in regional gray matter volume were found.ConclusionsThis study convincingly demonstrates that alterations in structural and functional connectivity develop before the first symptoms of FTD arise. These findings suggest that diffusion tensor imaging and resting-state fMRI may have the potential to become sensitive biomarkers for early FTD in future clinical trials.

Published
2013

37. ENIGMA MDD: seven years of global neuroimaging studies of major depression through worldwide data sharing

Author

Schmaal, Lianne, Pozzi, Elena, C. Ho, Tiffany, van Velzen, Laura S., Veer, Ilya M., Opel, Nils, Van Someren, Eus J. W., Han, Laura K. M., Aftanas, Lybomir, Aleman, André, Baune, Bernhard T., Berger, Klaus, Blanken, Tessa F., Capitão, Liliana, Couvy-Duchesne, Baptiste, R. Cullen, Kathryn, Dannlowski, Udo, Davey, Christopher, Erwin-Grabner, Tracy, Evans, Jennifer, Frodl, Thomas, Fu, Cynthia H. Y., Godlewska, Beata, Gotlib, Ian H., Goya-Maldonado, Roberto, Grabe, Hans J., Groenewold, Nynke A., Grotegerd, Dominik, Gruber, Oliver, Gutman, Boris A., Hall, Geoffrey B., Harrison, Ben J., Hatton, Sean N., Hermesdorf, Marco, Hickie, Ian B., Hilland, Eva, Irungu, Benson, Jonassen, Rune, Kelly, Sinead, Kircher, Tilo, Klimes-Dougan, Bonnie, Krug, Axel, Landrø, Nils Inge, Lagopoulos, Jim, Leerssen, Jeanne, Li, Meng, Linden, David E. J., MacMaster, Frank P., M. McIntosh, Andrew, Mehler, David M. A., Nenadić, Igor, Penninx, Brenda W. J. H., Portella, Maria J., Reneman, Liesbeth, Rentería, Miguel E., Sacchet, Matthew D., G. Sämann, Philipp, Schrantee, Anouk, Sim, Kang, Soares, Jair C., Stein, Dan J., Tozzi, Leonardo, van Der Wee, Nic J. A., van Tol, Marie-José, Vermeiren, Robert, Vives-Gilabert, Yolanda, Walter, Henrik, Walter, Martin, Whalley, Heather C., Wittfeld, Katharina, Whittle, Sarah, Wright, Margaret J., Yang, Tony T., Zarate, Jr, Carlos, Thomopoulos, Sophia I., Jahanshad, Neda, Thompson, Paul M., and Veltman, Dick J.

Published
2020
Full Text
View/download PDF

38. Correction: Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders

Author

Opel, Nils, Thalamuthu, Anbupalam, Milaneschi, Yuri, Grotegerd, Dominik, Flint, Claas, Leenings, Ramona, Goltermann, Janik, Richter, Maike, Hahn, Tim, Woditsch, Georg, Berger, Klaus, Hermesdorf, Marco, McIntosh, Andrew, Whalley, Heather C., Harris, Mathew A., MacMaster, Frank P., Walter, Henrik, Veer, Ilya M., Frodl, Thomas, Carballedo, Angela, Krug, Axel, Nenadic, Igor, Kircher, Tilo, Aleman, Andre, Groenewold, Nynke A., Stein, Dan J., Soares, Jair C., Zunta-Soares, Giovana B., Mwangi, Benson, Wu, Mon-Ju, Walter, Martin, Li, Meng, Harrison, Ben J., Davey, Christopher G., Cullen, Kathryn R., Klimes-Dougan, Bonnie, Mueller, Bryon A., Sämann, Philipp G., Penninx, Brenda, Nawijn, Laura, Veltman, Dick J., Aftanas, Lyubomir, Brak, Ivan V., Filimonova, Elena A., Osipov, Evgeniy A., Reneman, Liesbeth, Schrantee, Anouk, Grabe, Hans J., Van der Auwera, Sandra, Wittfeld, Katharina, Hosten, Norbert, Völzke, Henry, Sim, Kang, Gotlib, Ian H., Sacchet, Matthew D., Lagopoulos, Jim, Hatton, Sean N., Hickie, Ian, Pozzi, Elena, Thompson, Paul M., Jahanshad, Neda, Schmaal, Lianne, Baune, Bernhard T., and Dannlowski, Udo

Published
2021
Full Text
View/download PDF

39. Dynamic Modelling of Mental Resilience in Young Adults: Protocol for a Longitudinal Observational Study (DynaM-OBS)

Author

Wackerhagen, Carolin, primary, Veer, Ilya M, additional, van Leeuwen, Judith M C, additional, Reppmann, Zala, additional, Riepenhausen, Antje, additional, Bögemann, Sophie A, additional, Mor, Netali, additional, Puhlmann, Lara M C, additional, Uściƚko, Aleksandra, additional, Zerban, Matthias, additional, Mituniewicz, Julian, additional, Lerner, Avigail, additional, Yuen, Kenneth S L, additional, Köber, Göran, additional, Marciniak, Marta A, additional, Pooseh, Shakoor, additional, Weermeijer, Jeroen, additional, Arias-Vásquez, Alejandro, additional, Binder, Harald, additional, de Raedt, Walter, additional, Kleim, Birgit, additional, Myin-Germeys, Inez, additional, Roelofs, Karin, additional, Timmer, Jens, additional, Tüscher, Oliver, additional, Hendler, Talma, additional, Kobylińska, Dorota, additional, Hermans, Erno J, additional, Kalisch, Raffael, additional, and Walter, Henrik, additional

Published
2023
Full Text
View/download PDF

45. ReApp – an mHealth app increasing reappraisal: results from two randomized controlled trials

Author

Marciniak, Marta Anna, primary, Shanahan, Lilly, additional, Myin-Germeys, Inez, additional, Veer, Ilya, additional, Yuen, Kenneth S.L., additional, Binder, Harald, additional, Walter, Henrik, additional, Hermans, Erno, additional, Kobylinska, Dorota, additional, Tüscher, Oliver, additional, Kalisch, Raffael, additional, and Kleim, Birgit, additional

Published
2023
Full Text
View/download PDF

47. Value-modulated attentional capture in reward and punishment contexts, attentional control, and their relationship with psychopathology

Author

Freichel, René, Mrkonja, Lana, de Jong, Peter J., Cousijn, Janna, Franken, Ingmar, Ruiter, Tom A., Le Pelley, Mike, Albertella, Lucy, Watson, Poppy, Veer, Ilya M., Wiers, Reinout W., Freichel, René, Mrkonja, Lana, de Jong, Peter J., Cousijn, Janna, Franken, Ingmar, Ruiter, Tom A., Le Pelley, Mike, Albertella, Lucy, Watson, Poppy, Veer, Ilya M., and Wiers, Reinout W.

Abstract

Attentional bias towards rewards has been extensively studied in both healthy and clinical populations. Several studies have shown an association between reward value-modulated attentional capture (VMAC) and greater substance use. However, less is known about the association between these VMAC effects and internalizing symptoms. Moreover, while VMAC effects have also been found in punishment contexts, the association between punishment VMAC and psychopathology has not been studied so far. In the present two-part preregistered study, we adapted a novel VMAC task to also include a punishment context and examined associations with internalizing symptoms and substance use. Our results showed consistent VMAC effects in reward contexts across two separate studies. Attentional capture was stronger for distractors associated with high rewards than for low rewards. We replicated and extended previous findings by showing such VMAC effects in a substantially shorter task that also included alternating punishment blocks. Contrary to our expectations, we found no VMAC effects in punishment contexts and no direct associations between VMAC and symptom measures. Our results speak to the feasibility of assessing VMAC effects using a scalable and short behavioral online task, but the relationship with the development of internalizing and externalizing psychopathology remains uncertain.

Published
2023

48. 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

49. Coping with COVID: risk and resilience factors for mental health in a German representative panel study

Author

Riepenhausen, A, Veer, I, Wackerhagen, C, Reppmann, Z, Köber, G, Ayuso-Mateos, J, Bögemann, S, Corrao, G, Felez-Nobrega, M, Abad, J, Hermans, E, van Leeuwen, J, Lieb, K, Lorant, V, Mary-Krause, M, Mediavilla, R, Melchior, M, Mittendorfer-Rutz, E, Monzio Compagnoni, M, Pan, K, Puhlmann, L, Roelofs, K, Sijbrandij, M, Smith, P, Tüscher, O, Witteveen, A, Zerban, M, Kalisch, R, Kröger, H, Walter, H, Riepenhausen, Antje, Veer, Ilya M., Wackerhagen, Carolin, Reppmann, Zala C., Köber, Göran, Ayuso-Mateos, José Luis, Bögemann, Sophie A., Corrao, Giovanni, Felez-Nobrega, Mireia, Abad, Josep Maria Haro, Hermans, Erno, van Leeuwen, Judith, Lieb, Klaus, Lorant, Vincent, Mary-Krause, Murielle, Mediavilla, Roberto, Melchior, Maria, Mittendorfer-Rutz, Ellenor, Monzio Compagnoni, Matteo, Pan, Kuan-Yu, Puhlmann, Lara, Roelofs, Karin, Sijbrandij, Marit, Smith, Pierre, Tüscher, Oliver, Witteveen, Anke, Zerban, Matthias, Kalisch, Raffael, Kröger, Hannes, Walter, Henrik, Riepenhausen, A, Veer, I, Wackerhagen, C, Reppmann, Z, Köber, G, Ayuso-Mateos, J, Bögemann, S, Corrao, G, Felez-Nobrega, M, Abad, J, Hermans, E, van Leeuwen, J, Lieb, K, Lorant, V, Mary-Krause, M, Mediavilla, R, Melchior, M, Mittendorfer-Rutz, E, Monzio Compagnoni, M, Pan, K, Puhlmann, L, Roelofs, K, Sijbrandij, M, Smith, P, Tüscher, O, Witteveen, A, Zerban, M, Kalisch, R, Kröger, H, Walter, H, Riepenhausen, Antje, Veer, Ilya M., Wackerhagen, Carolin, Reppmann, Zala C., Köber, Göran, Ayuso-Mateos, José Luis, Bögemann, Sophie A., Corrao, Giovanni, Felez-Nobrega, Mireia, Abad, Josep Maria Haro, Hermans, Erno, van Leeuwen, Judith, Lieb, Klaus, Lorant, Vincent, Mary-Krause, Murielle, Mediavilla, Roberto, Melchior, Maria, Mittendorfer-Rutz, Ellenor, Monzio Compagnoni, Matteo, Pan, Kuan-Yu, Puhlmann, Lara, Roelofs, Karin, Sijbrandij, Marit, Smith, Pierre, Tüscher, Oliver, Witteveen, Anke, Zerban, Matthias, Kalisch, Raffael, Kröger, Hannes, and Walter, Henrik

Abstract

Background: The COVID-19 pandemic might affect mental health. Data from population-representative panel surveys with multiple waves including pre-COVID data investigating risk and protective factors are still rare. Methods: In a stratified random sample of the German household population (n=6,684), we conducted survey-weighted multiple linear regressions to determine the association of various psychological risk and protective factors assessed between 2015 and 2020 with changes in psychological distress (PD; measured via PHQ-4) from pre-pandemic (average of 2016 and 2019) to peri-pandemic (both 2020 and 2021) time points. Control analyses on PD change between two pre-pandemic time points (2016 and 2019) were conducted. Regularized regressions were computed to inform on which factors were statistically most influential in the multicollinear setting. Results: PHQ-4 scores in 2020 (M=2.45) and 2021 (M=2.21) were elevated compared to 2019 (M=1.79). Several risk factors (catastrophizing, neuroticism, asking for instrumental support) and protective factors (perceived stress recovery, positive reappraisal, optimism) were identified for the peri-pandemic outcomes. Control analyses revealed that in pre-pandemic times, neuroticism and optimism were predominantly related to PD changes. Regularized regression mostly confirmed the results and highlighted perceived stress recovery as most consistent influential protective factor across peri-pandemic outcomes. Conclusions: We identified several psychological risk and protective factors related to PD outcomes during the COVID-19 pandemic. Comparison to pre-pandemic data stress the relevance of longitudinal assessments to potentially reconcile contradictory findings. Implications and suggestions for targeted prevention and intervention programs during highly stressful times such as pandemics are discussed.

Published
2023

50. Psychological Resilience Factors and Their Association With Weekly Stressor Reactivity During the COVID-19 Outbreak in Europe: Prospective Longitudinal Study

Author

Bögemann, Sophie A; https://orcid.org/0000-0001-9382-0769, Puhlmann, Lara M C; https://orcid.org/0000-0002-0870-8770, Wackerhagen, Carolin; https://orcid.org/0000-0002-5689-3472, Zerban, Matthias; https://orcid.org/0000-0002-2684-3271, Riepenhausen, Antje; https://orcid.org/0000-0001-8749-5349, Köber, Göran; https://orcid.org/0000-0001-7038-0860, Yuen, Kenneth S L; https://orcid.org/0000-0002-9465-9070, Pooseh, Shakoor; https://orcid.org/0000-0002-5441-9507, Marciniak, Marta Anna; https://orcid.org/0000-0003-4301-3269, Reppmann, Zala; https://orcid.org/0000-0001-8633-9651, Uściƚko, Aleksandra; https://orcid.org/0000-0002-0001-7190, Weermeijer, Jeroen; https://orcid.org/0000-0002-6288-795X, Lenferink, Dionne B; https://orcid.org/0009-0009-1699-8315, Mituniewicz, Julian; https://orcid.org/0000-0002-9717-5784, Robak, Natalia; https://orcid.org/0000-0002-5482-3745, Donner, Nina C; https://orcid.org/0000-0003-0548-1408, Mestdagh, Merijn; https://orcid.org/0000-0001-5077-861X, Verdonck, Stijn; https://orcid.org/0000-0002-2199-1072, van Dick, Rolf; https://orcid.org/0000-0002-6308-9466, Kleim, Birgit; https://orcid.org/0000-0001-9114-2917, Lieb, Klaus; https://orcid.org/0000-0002-9609-4261, van Leeuwen, Judith M C; https://orcid.org/0000-0001-7105-0038, Kobylińska, Dorota; https://orcid.org/0000-0003-0184-2595, Myin-Germeys, Inez; https://orcid.org/0000-0002-3731-4930, Walter, Henrik; https://orcid.org/0000-0002-9403-6121, Tüscher, Oliver; https://orcid.org/0000-0002-4023-5301, Hermans, Erno J; https://orcid.org/0000-0003-1339-8639, Veer, Ilya M; https://orcid.org/0000-0002-6733-3593, Kalisch, Raffael; https://orcid.org/0000-0002-9503-7601, Bögemann, Sophie A; https://orcid.org/0000-0001-9382-0769, Puhlmann, Lara M C; https://orcid.org/0000-0002-0870-8770, Wackerhagen, Carolin; https://orcid.org/0000-0002-5689-3472, Zerban, Matthias; https://orcid.org/0000-0002-2684-3271, Riepenhausen, Antje; https://orcid.org/0000-0001-8749-5349, Köber, Göran; https://orcid.org/0000-0001-7038-0860, Yuen, Kenneth S L; https://orcid.org/0000-0002-9465-9070, Pooseh, Shakoor; https://orcid.org/0000-0002-5441-9507, Marciniak, Marta Anna; https://orcid.org/0000-0003-4301-3269, Reppmann, Zala; https://orcid.org/0000-0001-8633-9651, Uściƚko, Aleksandra; https://orcid.org/0000-0002-0001-7190, Weermeijer, Jeroen; https://orcid.org/0000-0002-6288-795X, Lenferink, Dionne B; https://orcid.org/0009-0009-1699-8315, Mituniewicz, Julian; https://orcid.org/0000-0002-9717-5784, Robak, Natalia; https://orcid.org/0000-0002-5482-3745, Donner, Nina C; https://orcid.org/0000-0003-0548-1408, Mestdagh, Merijn; https://orcid.org/0000-0001-5077-861X, Verdonck, Stijn; https://orcid.org/0000-0002-2199-1072, van Dick, Rolf; https://orcid.org/0000-0002-6308-9466, Kleim, Birgit; https://orcid.org/0000-0001-9114-2917, Lieb, Klaus; https://orcid.org/0000-0002-9609-4261, van Leeuwen, Judith M C; https://orcid.org/0000-0001-7105-0038, Kobylińska, Dorota; https://orcid.org/0000-0003-0184-2595, Myin-Germeys, Inez; https://orcid.org/0000-0002-3731-4930, Walter, Henrik; https://orcid.org/0000-0002-9403-6121, Tüscher, Oliver; https://orcid.org/0000-0002-4023-5301, Hermans, Erno J; https://orcid.org/0000-0003-1339-8639, Veer, Ilya M; https://orcid.org/0000-0002-6733-3593, and Kalisch, Raffael; https://orcid.org/0000-0002-9503-7601

Abstract

Background Cross-sectional relationships between psychosocial resilience factors (RFs) and resilience, operationalized as the outcome of low mental health reactivity to stressor exposure (low “stressor reactivity” [SR]), were reported during the first wave of the COVID-19 pandemic in 2020. Objective Extending these findings, we here examined prospective relationships and weekly dynamics between the same RFs and SR in a longitudinal sample during the aftermath of the first wave in several European countries. Methods Over 5 weeks of app-based assessments, participants reported weekly stressor exposure, mental health problems, RFs, and demographic data in 1 of 6 different languages. As (partly) preregistered, hypotheses were tested cross-sectionally at baseline (N=558), and longitudinally (n=200), using mixed effects models and mediation analyses. Results RFs at baseline, including positive appraisal style (PAS), optimism (OPT), general self-efficacy (GSE), perceived good stress recovery (REC), and perceived social support (PSS), were negatively associated with SR scores, not only cross-sectionally (baseline SR scores; all P<.001) but also prospectively (average SR scores across subsequent weeks; positive appraisal (PA), P=.008; OPT, P<.001; GSE, P=.01; REC, P<.001; and PSS, P=.002). In both associations, PAS mediated the effects of PSS on SR (cross-sectionally: 95% CI –0.064 to –0.013; prospectively: 95% CI –0.074 to –0.0008). In the analyses of weekly RF-SR dynamics, the RFs PA of stressors generally and specifically related to the COVID-19 pandemic, and GSE were negatively associated with SR in a contemporaneous fashion (PA, P<.001; PAC,P=.03; and GSE, P<.001), but not in a lagged fashion (PA, P=.36; PAC, P=.52; and GSE, P=.06). Conclusions We identified psychological RFs that prospectively predict resilience and cofluctuate with weekly SR within individuals. These prospective results endorse that the previously reported RF-SR associations do not exclusively reflect

Published
2023

Catalog

Books, media, physical & digital resources
See catalog results