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1. Digital-analog quantum convolutional neural networks for image classification

Author

Simen, Anton, Flores-Garrigos, Carlos, Hegade, Narendra N., Montalban, Iraitz, Vives-Gilabert, Yolanda, Michon, Eric, Zhang, Qi, Solano, Enrique, and Martín-Guerrero, José D.

Subjects
Quantum Physics
Abstract

We propose digital-analog quantum kernels for enhancing the detection of complex features in the classification of images. We consider multipartite-entangled analog blocks, stemming from native Ising interactions in neutral-atom quantum processors, and individual operations as digital steps to implement the protocol. To further improving the detection of complex features, we apply multiple quantum kernels by varying the qubit connectivity according to the hardware constraints. An architecture that combines non-trainable quantum kernels and standard convolutional neural networks is used to classify realistic medical images, from breast cancer and pneumonia diseases, with a significantly reduced number of parameters. Despite this fact, the model exhibits better performance than its classical counterparts and achieves comparable metrics according to public benchmarks. These findings demonstrate the relevance of digital-analog encoding, paving the way for surpassing classical models in image recognition approaching us to quantum-advantage regimes., Comment: 7 pages, 3 figures

Published
2024

2. DenseNet and Support Vector Machine classifications of major depressive disorder using vertex-wise cortical features

Author

Belov, Vladimir, Erwin-Grabner, Tracy, Zeng, Ling-Li, Ching, Christopher R. K., Aleman, Andre, Amod, Alyssa R., Basgoze, Zeynep, Benedetti, Francesco, Besteher, Bianca, Brosch, Katharina, Bülow, Robin, Colle, Romain, Connolly, Colm G., Corruble, Emmanuelle, Couvy-Duchesne, Baptiste, Cullen, Kathryn, Dannlowski, Udo, Davey, Christopher G., Dols, Annemiek, Ernsting, Jan, Evans, Jennifer W., Fisch, Lukas, Fuentes-Claramonte, Paola, Gonul, Ali Saffet, Gotlib, Ian H., Grabe, Hans J., Groenewold, Nynke A., Grotegerd, Dominik, Hahn, Tim, Hamilton, J. Paul, Han, Laura K. M., Harrison, Ben J, Ho, Tiffany C., Jahanshad, Neda, Jamieson, Alec J., Karuk, Andriana, Kircher, Tilo, Klimes-Dougan, Bonnie, Koopowitz, Sheri-Michelle, Lancaster, Thomas, Leenings, Ramona, Li, Meng, Linden, David E. J., MacMaster, Frank P., Mehler, David M. A., Meinert, Susanne, Melloni, Elisa, Mueller, Bryon A., Mwangi, Benson, Nenadić, Igor, Ojha, Amar, Okamoto, Yasumasa, Oudega, Mardien L., Penninx, Brenda W. J. H., Poletti, Sara, Pomarol-Clotet, Edith, Portella, Maria J., Pozzi, Elena, Radua, Joaquim, Rodríguez-Cano, Elena, Sacchet, Matthew D., Salvador, Raymond, Schrantee, Anouk, Sim, Kang, Soares, Jair C., Solanes, Aleix, Stein, Dan J., Stein, Frederike, Stolicyn, Aleks, Thomopoulos, Sophia I., Toenders, Yara J., Uyar-Demir, Aslihan, Vieta, Eduard, Vives-Gilabert, Yolanda, Völzke, Henry, Walter, Martin, Whalley, Heather C., Whittle, Sarah, Winter, Nils, Wittfeld, Katharina, Wright, Margaret J., Wu, Mon-Ju, Yang, Tony T., Zarate, Carlos, Veltman, Dick J., Schmaal, Lianne, Thompson, Paul M., and Goya-Maldonado, Roberto

Subjects
Quantitative Biology - Quantitative Methods, Computer Science - Machine Learning, Quantitative Biology - Neurons and Cognition
Abstract

Major depressive disorder (MDD) is a complex psychiatric disorder that affects the lives of hundreds of millions of individuals around the globe. Even today, researchers debate if morphological alterations in the brain are linked to MDD, likely due to the heterogeneity of this disorder. The application of deep learning tools to neuroimaging data, capable of capturing complex non-linear patterns, has the potential to provide diagnostic and predictive biomarkers for MDD. However, previous attempts to demarcate MDD patients and healthy controls (HC) based on segmented cortical features via linear machine learning approaches have reported low accuracies. In this study, we used globally representative data from the ENIGMA-MDD working group containing an extensive sample of people with MDD (N=2,772) and HC (N=4,240), which allows a comprehensive analysis with generalizable results. Based on the hypothesis that integration of vertex-wise cortical features can improve classification performance, we evaluated the classification of a DenseNet and a Support Vector Machine (SVM), with the expectation that the former would outperform the latter. As we analyzed a multi-site sample, we additionally applied the ComBat harmonization tool to remove potential nuisance effects of site. We found that both classifiers exhibited close to chance performance (balanced accuracy DenseNet: 51%; SVM: 53%), when estimated on unseen sites. Slightly higher classification performance (balanced accuracy DenseNet: 58%; SVM: 55%) was found when the cross-validation folds contained subjects from all sites, indicating site effect. In conclusion, the integration of vertex-wise morphometric features and the use of the non-linear classifier did not lead to the differentiability between MDD and HC. Our results support the notion that MDD classification on this combination of features and classifiers is unfeasible.

Published
2023

3. Machine Learning for maximizing the memristivity of single and coupled quantum memristors

Author

Hernani-Morales, Carlos, Alvarado, Gabriel, Albarrán-Arriagada, Francisco, Vives-Gilabert, Yolanda, Solano, Enrique, and Martín-Guerrero, José D.

Subjects
Quantum Physics, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

We propose machine learning (ML) methods to characterize the memristive properties of single and coupled quantum memristors. We show that maximizing the memristivity leads to large values in the degree of entanglement of two quantum memristors, unveiling the close relationship between quantum correlations and memory. Our results strengthen the possibility of using quantum memristors as key components of neuromorphic quantum computing.

Published
2023

4. Physics-Informed Neural Networks for an optimal counterdiabatic quantum computation

Author

Ferrer-Sánchez, Antonio, Flores-Garrigos, Carlos, Hernani-Morales, Carlos, Orquín-Marqués, José J., Hegade, Narendra N., Cadavid, Alejandro Gomez, Montalban, Iraitz, Solano, Enrique, Vives-Gilabert, Yolanda, and Martín-Guerrero, José D.

Subjects
Quantum Physics, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

We introduce a novel methodology that leverages the strength of Physics-Informed Neural Networks (PINNs) to address the counterdiabatic (CD) protocol in the optimization of quantum circuits comprised of systems with $N_{Q}$ qubits. The primary objective is to utilize physics-inspired deep learning techniques to accurately solve the time evolution of the different physical observables within the quantum system. To accomplish this objective, we embed the necessary physical information into an underlying neural network to effectively tackle the problem. In particular, we impose the hermiticity condition on all physical observables and make use of the principle of least action, guaranteeing the acquisition of the most appropriate counterdiabatic terms based on the underlying physics. The proposed approach offers a dependable alternative to address the CD driving problem, free from the constraints typically encountered in previous methodologies relying on classical numerical approximations. Our method provides a general framework to obtain optimal results from the physical observables relevant to the problem, including the external parameterization in time known as scheduling function, the gauge potential or operator involving the non-adiabatic terms, as well as the temporal evolution of the energy levels of the system, among others. The main applications of this methodology have been the $\mathrm{H_{2}}$ and $\mathrm{LiH}$ molecules, represented by a 2-qubit and 4-qubit systems employing the STO-3G basis. The presented results demonstrate the successful derivation of a desirable decomposition for the non-adiabatic terms, achieved through a linear combination utilizing Pauli operators. This attribute confers significant advantages to its practical implementation within quantum computing algorithms., Comment: 28 pages, 10 figures, 1 algorithm, 1 table

Published
2023

5. Active Learning in Physics: From 101, to Progress, and Perspective

Author

Ding, Yongcheng, Martín-Guerrero, José D., Vives-Gilabert, Yolanda, and Chen, Xi

Subjects
Quantum Physics, Computer Science - Machine Learning
Abstract

Active Learning (AL) is a family of machine learning (ML) algorithms that predates the current era of artificial intelligence. Unlike traditional approaches that require labeled samples for training, AL iteratively selects unlabeled samples to be annotated by an expert. This protocol aims to prioritize the most informative samples, leading to improved model performance compared to training with all labeled samples. In recent years, AL has gained increasing attention, particularly in the field of physics. This paper presents a comprehensive and accessible introduction to the theory of AL reviewing the latest advancements across various domains. Additionally, we explore the potential integration of AL with quantum ML, envisioning a synergistic fusion of these two fields rather than viewing AL as a mere extension of classical ML into the quantum realm., Comment: 15 pages

Published
2023
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6. MaRCoS, an open-source electronic control system for low-field MRI

Author

Negnevitsky, Vlad, Vives-Gilabert, Yolanda, Algarín, José M., Craven-Brightman, Lincoln, Pellicer-Guridi, Rubén, O'Reilly, Thomas, Stockmann, Jason P., Webb, Andrew, Alonso, Joseba, and Menküc, Benjamin

Subjects
Physics - Medical Physics, Physics - Instrumentation and Detectors
Abstract

Every magnetic resonance imaging (MRI) device requires an electronic control system that handles pulse sequences and signal detection and processing. Here we provide details on the architecture and performance of MaRCoS, a MAgnetic Resonance COntrol System developed by an open international community of low-field MRI researchers. MaRCoS is inexpensive and can handle cycle-accurate sequences without hard length limitations, rapid bursts of events, and arbitrary waveforms. It can also be easily adapted to meet further specifications required by the various academic and private institutions participating in its development. We describe the MaRCoS hardware, firmware and software that enable all of the above, including a Python-based graphical user interface for pulse sequence implementation, data processing and image reconstruction., Comment: 10 pages, 4 figures

Published
2022
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8. Analysis of structural brain asymmetries in attention‐deficit/hyperactivity disorder in 39 datasets

Author

Postema, Merel C, Hoogman, Martine, Ambrosino, Sara, Asherson, Philip, Banaschewski, Tobias, Bandeira, Cibele E, Baranov, Alexandr, Bau, Claiton HD, Baumeister, Sarah, Baur‐Streubel, Ramona, Bellgrove, Mark A, Biederman, Joseph, Bralten, Janita, Brandeis, Daniel, Brem, Silvia, Buitelaar, Jan K, Busatto, Geraldo F, Castellanos, Francisco X, Cercignani, Mara, Chaim‐Avancini, Tiffany M, Chantiluke, Kaylita C, Christakou, Anastasia, Coghill, David, Conzelmann, Annette, Cubillo, Ana I, Cupertino, Renata B, de Zeeuw, Patrick, Doyle, Alysa E, Durston, Sarah, Earl, Eric A, Epstein, Jeffery N, Ethofer, Thomas, Fair, Damien A, Fallgatter, Andreas J, Faraone, Stephen V, Frodl, Thomas, Gabel, Matt C, Gogberashvili, Tinatin, Grevet, Eugenio H, Haavik, Jan, Harrison, Neil A, Hartman, Catharina A, Heslenfeld, Dirk J, Hoekstra, Pieter J, Hohmann, Sarah, Høvik, Marie F, Jernigan, Terry L, Kardatzki, Bernd, Karkashadze, Georgii, Kelly, Clare, Kohls, Gregor, Konrad, Kerstin, Kuntsi, Jonna, Lazaro, Luisa, Lera‐Miguel, Sara, Lesch, Klaus‐Peter, Louza, Mario R, Lundervold, Astri J, Malpas, Charles B, Mattos, Paulo, McCarthy, Hazel, Namazova‐Baranova, Leyla, Nicolau, Rosa, Nigg, Joel T, Novotny, Stephanie E, Weiss, Eileen Oberwelland, Tuura, Ruth L O'Gorman, Oosterlaan, Jaap, Oranje, Bob, Paloyelis, Yannis, Pauli, Paul, Picon, Felipe A, Plessen, Kerstin J, Ramos‐Quiroga, J Antoni, Reif, Andreas, Reneman, Liesbeth, Rosa, Pedro GP, Rubia, Katya, Schrantee, Anouk, Schweren, Lizanne JS, Seitz, Jochen, Shaw, Philip, Silk, Tim J, Skokauskas, Norbert, Vila, Juan C Soliva, Stevens, Michael C, Sudre, Gustavo, Tamm, Leanne, Tovar‐Moll, Fernanda, van Erp, Theo GM, Vance, Alasdair, Vilarroya, Oscar, Vives‐Gilabert, Yolanda, von Polier, Georg G, Walitza, Susanne, Yoncheva, Yuliya N, Zanetti, Marcus V, Ziegler, Georg C, Glahn, David C, and Jahanshad, Neda

Subjects
Biological Psychology, Psychology, Pediatric, Brain Disorders, Mental Health, Neurosciences, Attention Deficit Hyperactivity Disorder (ADHD), Pediatric Research Initiative, Aetiology, 2.1 Biological and endogenous factors, Mental health, Adolescent, Adult, Attention Deficit Disorder with Hyperactivity, Autism Spectrum Disorder, Brain, Caudate Nucleus, Child, Humans, Magnetic Resonance Imaging, Attention&#8208, deficit, hyperactivity disorder, brain asymmetry, brain laterality, structural MRI, large&#8208, scale data, ENIGMA ADHD Working Group, Attention-deficit, large-scale data, Clinical Sciences, Cognitive Sciences, Developmental & Child Psychology, Clinical sciences, Applied and developmental psychology, Clinical and health psychology
Abstract

ObjectiveSome studies have suggested alterations of structural brain asymmetry in attention-deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here, we performed the largest ever analysis of brain left-right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium.MethodsWe analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,933 people with ADHD and 1,829 unaffected controls. Asymmetry Indexes (AIs) were calculated per participant for each bilaterally paired measure, and linear mixed effects modeling was applied separately in children, adolescents, adults, and the total sample, to test exhaustively for potential associations of ADHD with structural brain asymmetries.ResultsThere was no evidence for altered caudate nucleus asymmetry in ADHD, in contrast to prior literature. In children, there was less rightward asymmetry of the total hemispheric surface area compared to controls (t = 2.1, p = .04). Lower rightward asymmetry of medial orbitofrontal cortex surface area in ADHD (t = 2.7, p = .01) was similar to a recent finding for autism spectrum disorder. There were also some differences in cortical thickness asymmetry across age groups. In adults with ADHD, globus pallidus asymmetry was altered compared to those without ADHD. However, all effects were small (Cohen's d from -0.18 to 0.18) and would not survive study-wide correction for multiple testing.ConclusionPrior studies of altered structural brain asymmetry in ADHD were likely underpowered to detect the small effects reported here. Altered structural asymmetry is unlikely to provide a useful biomarker for ADHD, but may provide neurobiological insights into the trait.

Published
2021

9. Characterizing neuroanatomic heterogeneity in people with and without ADHD based on subcortical brain volumes

Author

Li, Ting, van Rooij, Daan, Mota, Nina Roth, Buitelaar, Jan K, Ambrosino, Sara, Banaschewski, Tobias, Bandeira, Cibele E, Bau, Claiton HD, Baumeister, Sarah, Baur‐Streubel, Ramona, Bellgrove, Mark A, Biederman, Joseph, Bralten, Janita, Bramati, Ivanei E, Brandeis, Daniel, Berm, Silvia, Busatto, Geraldo F, Calvo, Anna, Castellanos, Francisco X, Cercignani, Mara, Chantiluke, Kaylita C, Christakou, Anastasia, Coghill, David, Conzelmann, Annette, Cubillo, Ana I, Cupertino, Renata B, de Zeeuw, Parick, Durston, Sarah, Earl, Eric A, Epstein, Jeffery N, Ethofer, Thomas, Fallgatter, Andreas J, Fair, Damien A, Faraone, Stephen V, Frodl, Thomas, Gabel, Matt C, Gogberashvili, Tinatin, Grevet, Eugenio H, Haavik, Jan, Harrison, Neil A, Hartman, Catharina A, Heslenfeld, Dirk J, Hoekstra, Pieter J, Høvik, Marie F, Jahanshad, Neda, Kardatzki, Bernd, Karkashadze, Georgii, Kelly, Clare, Kohls, Gregor, Konrad, Kerstin, Kuntsi, Jonna, Lazaro, Luisa, Lera‐Miguel, Sara, Lesch, Klaus‐Peter, Louza, Mario R, Lundervold, Astri J, Malpas, Charles B, Mattos, Paulo, McCarthy, Hazel, Nicolau, Rosa, Nigg, Joel T, Tuura, Ruth L O'Gorman, Oosterlaan, Jaap, Oranje, Bob, Paloyelis, Yannis, Pauli, Paul, Picon, Felipe A, Plessen, Kerstin J, Ramos‐Quiroga, J Antoni, Reif, Andreas, Reneman, Liesbeth, Rosa, Pedro GP, Rubia, Katya, Schrantee, Anouk, Schweren, Lizanne JS, Seitz, Jochen, Shaw, Philip, Silk, Tim J, Skokauskas, Norbert, Vila, Juan Carlos Soliva, Soloveva, Anastasiia, Stevens, Michael C, Sudre, Gustavo, Tamm, Leanne, Thompson, Paul M, Tovar‐Moll, Fernanda, van Erp, Theo GM, Vance, Alasdair, Vilarroya, Oscar, Vives‐Gilabert, Yolanda, von Polier, Georg G, Walitza, Susanne, Yoncheva, Yuliya N, Zanetti, Marcus V, Ziegler, Georg C, Anikin, Anatoly, Asherson, Philip, Baranov, Alexandr, Chaim‐Avanicini, Tiffany, and Dale, Anders M

Subjects
Biological Psychology, Psychology, Mental Health, Pediatric, Brain Disorders, Attention Deficit Hyperactivity Disorder (ADHD), Clinical Research, Neurosciences, Adult, Attention Deficit Disorder with Hyperactivity, Brain, Case-Control Studies, Female, Humans, Magnetic Resonance Imaging, Male, Thalamus, ADHD, subcortical volume, neuroanatomic heterogeneity, community detection, effect sizes, ENIGMA ADHD Working Group, Clinical Sciences, Cognitive Sciences, Developmental & Child Psychology, Clinical sciences, Applied and developmental psychology, Clinical and health psychology
Abstract

BackgroundAttention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder. Neuroanatomic heterogeneity limits our understanding of ADHD's etiology. This study aimed to parse heterogeneity of ADHD and to determine whether patient subgroups could be discerned based on subcortical brain volumes.MethodsUsing the large ENIGMA-ADHD Working Group dataset, four subsamples of 993 boys with and without ADHD and to subsamples of 653 adult men, 400 girls, and 447 women were included in analyses. We applied exploratory factor analysis (EFA) to seven subcortical volumes in order to constrain the complexity of the input variables and ensure more stable clustering results. Factor scores derived from the EFA were used to build networks. A community detection (CD) algorithm clustered participants into subgroups based on the networks.ResultsExploratory factor analysis revealed three factors (basal ganglia, limbic system, and thalamus) in boys and men with and without ADHD. Factor structures for girls and women differed from those in males. Given sample size considerations, we concentrated subsequent analyses on males. Male participants could be separated into four communities, of which one was absent in healthy men. Significant case-control differences of subcortical volumes were observed within communities in boys, often with stronger effect sizes compared to the entire sample. As in the entire sample, none were observed in men. Affected men in two of the communities presented comorbidities more frequently than those in other communities. There were no significant differences in ADHD symptom severity, IQ, and medication use between communities in either boys or men.ConclusionsOur results indicate that neuroanatomic heterogeneity in subcortical volumes exists, irrespective of ADHD diagnosis. Effect sizes of case-control differences appear more pronounced at least in some of the subgroups.

Published
2021

11. Brain Imaging of the Cortex in ADHD: A Coordinated Analysis of Large-Scale Clinical and Population-Based Samples

Author

Hoogman, Martine, Muetzel, Ryan, Guimaraes, Joao P, Shumskaya, Elena, Mennes, Maarten, Zwiers, Marcel P, Jahanshad, Neda, Sudre, Gustavo, Wolfers, Thomas, Earl, Eric A, Soliva Vila, Juan Carlos, Vives-Gilabert, Yolanda, Khadka, Sabin, Novotny, Stephanie E, Hartman, Catharina A, Heslenfeld, Dirk J, Schweren, Lizanne JS, Ambrosino, Sara, Oranje, Bob, de Zeeuw, Patrick, Chaim-Avancini, Tiffany M, Rosa, Pedro GP, Zanetti, Marcus V, Malpas, Charles B, Kohls, Gregor, von Polier, Georg G, Seitz, Jochen, Biederman, Joseph, Doyle, Alysa E, Dale, Anders M, van Erp, Theo GM, Epstein, Jeffery N, Jernigan, Terry L, Baur-Streubel, Ramona, Ziegler, Georg C, Zierhut, Kathrin C, Schrantee, Anouk, Høvik, Marie F, Lundervold, Astri J, Kelly, Clare, McCarthy, Hazel, Skokauskas, Norbert, O’Gorman Tuura, Ruth L, Calvo, Anna, Lera-Miguel, Sara, Nicolau, Rosa, Chantiluke, Kaylita C, Christakou, Anastasia, Vance, Alasdair, Cercignani, Mara, Gabel, Matt C, Asherson, Philip, Baumeister, Sarah, Brandeis, Daniel, Hohmann, Sarah, Bramati, Ivanei E, Tovar-Moll, Fernanda, Fallgatter, Andreas J, Kardatzki, Bernd, Schwarz, Lena, Anikin, Anatoly, Baranov, Alexandr, Gogberashvili, Tinatin, Kapilushniy, Dmitry, Solovieva, Anastasia, El Marroun, Hanan, White, Tonya, Karkashadze, Georgii, Namazova-Baranova, Leyla, Ethofer, Thomas, Mattos, Paulo, Banaschewski, Tobias, Coghill, David, Plessen, Kerstin J, Kuntsi, Jonna, Mehta, Mitul A, Paloyelis, Yannis, Harrison, Neil A, Bellgrove, Mark A, Silk, Tim J, Cubillo, Ana I, Rubia, Katya, Lazaro, Luisa, Brem, Silvia, Walitza, Susanne, Frodl, Thomas, Zentis, Mariam, Castellanos, Francisco X, Yoncheva, Yuliya N, Haavik, Jan, Reneman, Liesbeth, Conzelmann, Annette, Lesch, Klaus-Peter, Pauli, Paul, Reif, Andreas, Tamm, Leanne, Konrad, Kerstin, Oberwelland Weiss, Eileen, Busatto, Geraldo F, and Louza, Mario R

Subjects
Pediatric, Neurosciences, Mental Health, Attention Deficit Hyperactivity Disorder (ADHD), Behavioral and Social Science, Clinical Research, Brain Disorders, Pediatric Research Initiative, Aetiology, 2.1 Biological and endogenous factors, Mental health, Adolescent, Adult, Age Factors, Attention Deficit Disorder with Hyperactivity, Case-Control Studies, Cerebral Cortex, Child, Child, Preschool, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Neuroimaging, Psychiatric Status Rating Scales, Sex Factors, Young Adult, Attention Deficit Hyperactivity Disorder, Cortical Surface Area, Cortical Thickness, Imaging, Meta-Analysis, Neuroanatomy, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

ObjectiveNeuroimaging studies show structural alterations of various brain regions in children and adults with attention deficit hyperactivity disorder (ADHD), although nonreplications are frequent. The authors sought to identify cortical characteristics related to ADHD using large-scale studies.MethodsCortical thickness and surface area (based on the Desikan-Killiany atlas) were compared between case subjects with ADHD (N=2,246) and control subjects (N=1,934) for children, adolescents, and adults separately in ENIGMA-ADHD, a consortium of 36 centers. To assess familial effects on cortical measures, case subjects, unaffected siblings, and control subjects in the NeuroIMAGE study (N=506) were compared. Associations of the attention scale from the Child Behavior Checklist with cortical measures were determined in a pediatric population sample (Generation-R, N=2,707).ResultsIn the ENIGMA-ADHD sample, lower surface area values were found in children with ADHD, mainly in frontal, cingulate, and temporal regions; the largest significant effect was for total surface area (Cohen's d=-0.21). Fusiform gyrus and temporal pole cortical thickness was also lower in children with ADHD. Neither surface area nor thickness differences were found in the adolescent or adult groups. Familial effects were seen for surface area in several regions. In an overlapping set of regions, surface area, but not thickness, was associated with attention problems in the Generation-R sample.ConclusionsSubtle differences in cortical surface area are widespread in children but not adolescents and adults with ADHD, confirming involvement of the frontal cortex and highlighting regions deserving further attention. Notably, the alterations behave like endophenotypes in families and are linked to ADHD symptoms in the population, extending evidence that ADHD behaves as a continuous trait in the population. Future longitudinal studies should clarify individual lifespan trajectories that lead to nonsignificant findings in adolescent and adult groups despite the presence of an ADHD diagnosis.

Published
2019

12. Portable magnetic resonance imaging of patients indoors, outdoors and at home

Author

Guallart-Naval, Teresa, Algarín, José M., Pellicer-Guridi, Rubén, Galve, Fernando, Vives-Gilabert, Yolanda, Bosch, Rubén, Pallás, Eduardo, González, José M., Rigla, Juan P., Martínez, Pablo, Lloris, Francisco J., Borreguero, Jose, Marcos-Perucho, Álvaro, Negnevitsky, Vlad, Martí-Bonmatí, Luis, Ríos, Alfonso, Benlloch, José M., and Alonso, Joseba

Published
2022
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16. Subcortical brain volume differences in participants with attention deficit hyperactivity disorder in children and adults: a cross-sectional mega-analysis

Author

Hoogman, Martine, Bralten, Janita, Hibar, Derrek P, Mennes, Maarten, Zwiers, Marcel P, Schweren, Lizanne SJ, van Hulzen, Kimm JE, Medland, Sarah E, Shumskaya, Elena, Jahanshad, Neda, de Zeeuw, Patrick, Szekely, Eszter, Sudre, Gustavo, Wolfers, Thomas, Onnink, Alberdingk MH, Dammers, Janneke T, Mostert, Jeanette C, Vives-Gilabert, Yolanda, Kohls, Gregor, Oberwelland, Eileen, Seitz, Jochen, Schulte-Rüther, Martin, Ambrosino, Sara, Doyle, Alysa E, Høvik, Marie F, Dramsdahl, Margaretha, Tamm, Leanne, van Erp, Theo GM, Dale, Anders, Schork, Andrew, Conzelmann, Annette, Zierhut, Kathrin, Baur, Ramona, McCarthy, Hazel, Yoncheva, Yuliya N, Cubillo, Ana, Chantiluke, Kaylita, Mehta, Mitul A, Paloyelis, Yannis, Hohmann, Sarah, Baumeister, Sarah, Bramati, Ivanei, Mattos, Paulo, Tovar-Moll, Fernanda, Douglas, Pamela, Banaschewski, Tobias, Brandeis, Daniel, Kuntsi, Jonna, Asherson, Philip, Rubia, Katya, Kelly, Clare, Di Martino, Adriana, Milham, Michael P, Castellanos, Francisco X, Frodl, Thomas, Zentis, Mariam, Lesch, Klaus-Peter, Reif, Andreas, Pauli, Paul, Jernigan, Terry L, Haavik, Jan, Plessen, Kerstin J, Lundervold, Astri J, Hugdahl, Kenneth, Seidman, Larry J, Biederman, Joseph, Rommelse, Nanda, Heslenfeld, Dirk J, Hartman, Catharina A, Hoekstra, Pieter J, Oosterlaan, Jaap, von Polier, Georg, Konrad, Kerstin, Vilarroya, Oscar, Ramos-Quiroga, Josep Antoni, Soliva, Joan Carles, Durston, Sarah, Buitelaar, Jan K, Faraone, Stephen V, Shaw, Philip, Thompson, Paul M, and Franke, Barbara

Subjects
Brain Disorders, Neurosciences, Attention Deficit Hyperactivity Disorder (ADHD), Clinical Research, Mental Health, Pediatric, Biomedical Imaging, 2.1 Biological and endogenous factors, Aetiology, Mental health, Good Health and Well Being, Adolescent, Adult, Attention Deficit Disorder with Hyperactivity, Brain, Case-Control Studies, Child, Child, Preschool, Cross-Sectional Studies, Female, Humans, Linear Models, Longitudinal Studies, Magnetic Resonance Imaging, Male, Middle Aged, Neuroimaging, Young Adult, Clinical Sciences, Public Health and Health Services, Psychology
Abstract

BackgroundNeuroimaging studies have shown structural alterations in several brain regions in children and adults with attention deficit hyperactivity disorder (ADHD). Through the formation of the international ENIGMA ADHD Working Group, we aimed to address weaknesses of previous imaging studies and meta-analyses, namely inadequate sample size and methodological heterogeneity. We aimed to investigate whether there are structural differences in children and adults with ADHD compared with those without this diagnosis.MethodsIn this cross-sectional mega-analysis, we used the data from the international ENIGMA Working Group collaboration, which in the present analysis was frozen at Feb 8, 2015. Individual sites analysed structural T1-weighted MRI brain scans with harmonised protocols of individuals with ADHD compared with those who do not have this diagnosis. Our primary outcome was to assess case-control differences in subcortical structures and intracranial volume through pooling of all individual data from all cohorts in this collaboration. For this analysis, p values were significant at the false discovery rate corrected threshold of p=0·0156.FindingsOur sample comprised 1713 participants with ADHD and 1529 controls from 23 sites with a median age of 14 years (range 4-63 years). The volumes of the accumbens (Cohen's d=-0·15), amygdala (d=-0·19), caudate (d=-0·11), hippocampus (d=-0·11), putamen (d=-0·14), and intracranial volume (d=-0·10) were smaller in individuals with ADHD compared with controls in the mega-analysis. There was no difference in volume size in the pallidum (p=0·95) and thalamus (p=0·39) between people with ADHD and controls. Exploratory lifespan modelling suggested a delay of maturation and a delay of degeneration, as effect sizes were highest in most subgroups of children (21 years): in the accumbens (Cohen's d=-0·19 vs -0·10), amygdala (d=-0·18 vs -0·14), caudate (d=-0·13 vs -0·07), hippocampus (d=-0·12 vs -0·06), putamen (d=-0·18 vs -0·08), and intracranial volume (d=-0·14 vs 0·01). There was no difference between children and adults for the pallidum (p=0·79) or thalamus (p=0·89). Case-control differences in adults were non-significant (all p>0·03). Psychostimulant medication use (all p>0·15) or symptom scores (all p>0·02) did not influence results, nor did the presence of comorbid psychiatric disorders (all p>0·5).InterpretationWith the largest dataset to date, we add new knowledge about bilateral amygdala, accumbens, and hippocampus reductions in ADHD. We extend the brain maturation delay theory for ADHD to include subcortical structures and refute medication effects on brain volume suggested by earlier meta-analyses. Lifespan analyses suggest that, in the absence of well powered longitudinal studies, the ENIGMA cross-sectional sample across six decades of ages provides a means to generate hypotheses about lifespan trajectories in brain phenotypes.FundingNational Institutes of Health.

Published
2017

20. 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
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22. 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
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23. Impairments in sleep and brain molecular clearance in people with cognitive deterioration and biological evidence of AD: A report of four cases

Author

Buongiorno, Mariateresa, primary, Granell, Esther, additional, Caruana, Giovanni, additional, Sansa, Gemma, additional, Vives-Gilabert, Yolanda, additional, Cullell, Natalia, additional, Molina-Seguin, Jessica, additional, Almeria, Marta, additional, Artero, Cristina, additional, Sánchez-Benavides, Gonzalo, additional, Ray, Nicola J, additional, Correa, Sonia A.L., additional, and Krupinski, Jerzy, additional

Published
2023
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28. Benchmarking the performance of a low‐cost magnetic resonance control system at multiple sites in the open MaRCoS community

Author

Guallart‐Naval, Teresa, primary, O'Reilly, Thomas, additional, Algarín, José M., additional, Pellicer‐Guridi, Ruben, additional, Vives‐Gilabert, Yolanda, additional, Craven‐Brightman, Lincoln, additional, Negnevitsky, Vlad, additional, Menküc, Benjamin, additional, Galve, Fernando, additional, Stockmann, Jason P., additional, Webb, Andrew, additional, and Alonso, Joseba, additional

Published
2022
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29. Reproducibility in the absence of selective reporting : An illustration from large-scale brain asymmetry research

Author

Kong, Xiang-Zhen, Francks, Clyde, Allen, Nicholas B., Heslenfeld, Dirk, Hester, Robert, Hibar, Derrek Paul, Ho, Beng-Choon, Ho, Tiffany C., Hoekstra, Pieter J., Holst, Ruth J., Hoogman, Martine, Høvik, Marie F., Howells, Fleur M., Ames, David, Hugdahl, Kenneth, Huyser, Chaim, Ingvar, Martin, Ishikawa, Akari, James, Anthony, Jahanshad, Neda, Jernigan, Terry L., Jönsson, Erik G, Kaleda, Vasily, Kelly, Clare, Andreassen, Ole A., Kerich, Michael, Keshavan, Matcheri S., Khadka, Sabin, Kircher, Tilo, Kohls, Gregor, Konrad, Kerstin, Korucuoglu, Ozlem, Krämer, Bernd, Krug, Axel, Kuntsi, Jonna, Vasquez, Alejandro Arias, Kwon, Jun Soo, Lambregts-Rommelse, Nanda, Landén, Mikael, Lázaro, Luisa, Lebedeva, Irina, Lenroot, Rhoshel, Lesch, Klaus-Peter, Li, Qinqin, Lim, Kelvin O., Liu, Jia, Armstrong, Nicola J., Lochner, Christine, London, Edythe D., Lorenzetti, Valentina, Luciano, Michelle, Luijten, Maartje, Lundervold, Astri J., Mackey, Scott, MacMaster, Frank P., Maingault, Sophie, Malpas, Charles B., Asherson, Phil, Malt, Ulrik F., Mataix-Cols, David, Martin-Santos, Rocio, Mayer, Andrew R., McCarthy, Hazel, Medland, Sarah, Metha, Mitul, Mitchell, Philip B., Mueller, Bryon A., Maniega, Susana Muñoz, Bergo, Felipe, Mazoyer, Bernard, McDonald, Colm, McLellan, Quinn, McMahon, Katie L., McPhilemy, Genevieve, Momenan, Reza, Morales, Angelica M., Narayanaswamy, Janardhanan C., Moreira, José Carlos Vasques, Nerland, Stener, Bastin, Mark E., Nestor, Liam, Newman, Erik, Nigg, Joel T., Nordvik, Jan Egil, Novotny, Stephanie, Weiss, Eileen Oberwelland, O'Gorman, Ruth L., Oosterlaan, Jaap, Oranje, Bob, Orr, Catherine, Batalla, Albert, Overs, Bronwyn, Paloyelis, Yannis, Pauli, Paul, Paulus, Martin, Plessen, Kerstin Jessica, Polier, Georg G., Pomarol-Clotet, Edith, Portella, Maria J., Qiu, Jiang, Radua, Joaquim, Bauer, Jochen, Ramos-Quiroga, Josep Antoni, Reddy, Y. C. Janardhan, Reif, Andreas, Roberts, Gloria, Rosa, Pedro, Rubia, Katya, Sacchet, Matthew D., Sachdev, Perminder S., Salvador, Raymond, Schmaal, Lianne, Baune, Bernhard T, Schulte-Rüther, Martin, Schweren, Lizanne, Seitz, Jochen, Serpa, Mauricio Henriques, Shaw, Philip, Shumskaya, Elena, Silk, Timothy J., Simmons, Alan N., Simulionyte, Egle, Sinha, Rajita, Baur-Streubel, Ramona, Sjoerds, Zsuzsika, Smelror, Runar Elle, Soliva, Joan Carlos, Solowij, Nadia, Souza-Duran, Fabio Luisde, Sponheim, Scott R., Stein, Dan J., Stein, Elliot A., Stevens, Michael, Strike, Lachlan T., Biederman, Joseph, Sudre, Gustavo, Sui, Jing, Tamm, Leanne, Temmingh, Hendrik S., Thoma, Robert J., Tomyshev, Alexander, Tronchin, Giulia, Turner, Jessica, Uhlmann, Anne, Erp, Theo G. M., Blaine, Sara K., Heuvel, Odile A., Meer, Dennis, Eijk, Liza, Vance, Alasdair, Veer, Ilya M., Veltman, Dick J., Venkatasubramanian, Ganesan, Vilarroya, Oscar, Vives-Gilabert, Yolanda, Voineskos, Aristotle N, Boedhoe, Premika, Völzke, Henry, Vuletic, Daniella, Walitza, Susanne, Walter, Henrik, Walton, Esther, Wardlaw, Joanna M., Wen, Wei, Westlye, Lars T., Whelan, Christopher D., White, Tonya, Bøen, Erlend, Wiers, Reinout W., Wright, Margaret J., Wittfeld, Katharina, Yang, Tony T., Yasuda, Clarissa L., Yoncheva, Yuliya, Yücel, Murat, Yun, Je-Yeon, Zanetti, Marcus Vinicius, Zhen, Zonglei, Bose, Anushree, Zhu, Xing-xing, Ziegler, Georg C., Zubicaray, Greig I., Zwiers, Marcel, Project, Karolinska Schizophrenia, Glahn, David C., Crivello, Fabrice, Fisher, Simon E., Thompson, Paul M., Bralten, Janita, Farde, Lars, Flyckt, Lena, Engberg, Göran, Erhardt, Sophie, Fatouros-Bergman, Helena, Cervenka, Simon, Schwieler, Lilly, Piehl, Fredrik, Agartz, Ingrid, Collste, Karin, Brandeis, Daniel, Victorsson, Pauliina, Malmqvist, Anna, Hedberg, Mikael, Orhan, Funda, Sellgren, Carl, Brem, Silvia, Mathias, Samuel R., Brodaty, Henry, Yüksel, Dilara, Brooks, Samantha J., Buitelaar, Jan, Bürger, Christian, Bülow, Robin, Calhoun, Vince, Calvo, Anna, Canales-Rodríguez, Erick Jorge, Cannon, Dara M., Guadalupe, Tulio, Caparelli, Elisabeth C., Castellanos, Francisco X., Cendes, Fernando, Chaim-Avancini, Tiffany Moukbel, Chantiluke, Kaylita, Chen, Qun-lin, Chen, Xiayu, Cheng, Yuqi, Christakou, Anastasia, Clark, Vincent P., Abé, Christoph, Coghill, David, Connolly, Colm G., Conzelmann, Annette, Córdova-Palomera, Aldo, Cousijn, Janna, Crow, Tim, Cubillo, Ana, Dannlowski, Udo, Bruttopilo, Sara Ambrosino, Zeeuw, Patrick, Deary, Ian J., Demeter, Damion V., Di Martino, Adriana, Dickie, Erin W, Dietsche, Bruno, Doan, Nhat Trung, Doherty, Colin P., Doyle, Alysa, Durston, Sarah, Earl, Eric, Akudjedu, Theophilus N., Ehrlich, Stefan, Ekman, Carl Johan, Elvsåshagen, Torbjørn, Epstein, Jeffery N., Fair, Damien A., Faraone, Stephen V., Fernández, Guillén, Flint, Claas, Filho, Geraldo Busatto, Förster, Katharina, Aleman, Andre, Fouche, Jean-Paul, Foxe, John J., Frodl, Thomas, Fuentes-Claramonte, Paola, Fullerton, Janice M., Garavan, Hugh, Santos Garcia, Danielle, Gotlib, Ian H., Goudriaan, Anna E., Grabe, Hans Jörgen, Alhusaini, Saud, Groenewold, Nynke A., Grotegerd, Dominik, Gruber, Oliver, Gurholt, Tiril, Haavik, Jan, Hahn, Tim, Hansell, Narelle K., Harris, Mathew A., Hartman, Catharina A., Carmen Valdés Hernández, Maria, Alhusaini, Saud, Del Carmen Valdés Hernández, Maria, Heslenfeld, Dirk, Hester, Robert, Hibar, Derrek Paul, Ho, Beng-Choon, Ho, Tiffany C., Hoekstra, Pieter J., van Holst, Ruth J., Hoogman, Martine, Høvik, Marie F., Allen, Nicholas B., Howells, Fleur M., Hugdahl, Kenneth, Huyser, Chaim, Ingvar, Martin, Ishikawa, Akari, James, Anthony, Jahanshad, Neda, Jernigan, Terry L., Jönsson, Erik G., Kaleda, Vasily, Ames, David, Kelly, Clare, Kerich, Michael, Keshavan, Matcheri S., Khadka, Sabin, Kircher, Tilo, Kohls, Gregor, Konrad, Kerstin, Korucuoglu, Ozlem, Krämer, Bernd, Krug, Axel, Andreassen, Ole A., Kuntsi, Jonna, Kwon, Jun Soo, Lambregts-Rommelse, Nanda, Landén, Mikael, Lázaro, Luisa, Lebedeva, Irina, Lenroot, Rhoshel, Lesch, Klaus-Peter, Li, Qinqin, Lim, Kelvin O., Vasquez, Alejandro Arias, Liu, Jia, Lochner, Christine, London, Edythe D., Lorenzetti, Valentina, Luciano, Michelle, Luijten, Maartje, Lundervold, Astri J., Mackey, Scott, MacMaster, Frank P., Maingault, Sophie, Armstrong, Nicola J., Malpas, Charles B., Malt, Ulrik F., Mataix-Cols, David, Martin-Santos, Rocio, Mayer, Andrew R., McCarthy, Hazel, Medland, Sarah, Metha, Mitul, Mitchell, Philip B., Mueller, Bryon A., Asherson, Phil, Maniega, Susana Muñoz, Mazoyer, Bernard, McDonald, Colm, McLellan, Quinn, McMahon, Katie L., McPhilemy, Genevieve, Momenan, Reza, Morales, Angelica M., Narayanaswamy, Janardhanan C., Moreira, José Carlos Vasques, Bergo, Felipe, Nerland, Stener, Nestor, Liam, Newman, Erik, Nigg, Joel T., Nordvik, Jan Egil, Novotny, Stephanie, Weiss, Eileen Oberwelland, O'Gorman, Ruth L., Oosterlaan, Jaap, Oranje, Bob, Bastin, Mark E., Orr, Catherine, Overs, Bronwyn, Paloyelis, Yannis, Pauli, Paul, Paulus, Martin, Plessen, Kerstin Jessica, von Polier, Georg G., Pomarol-Clotet, Edith, Portella, Maria J., Qiu, Jiang, Batalla, Albert, Radua, Joaquim, Ramos-Quiroga, Josep Antoni, Reddy, Y. C. Janardhan, Reif, Andreas, Roberts, Gloria, Rosa, Pedro, Rubia, Katya, Sacchet, Matthew D., Sachdev, Perminder S., Salvador, Raymond, Bauer, Jochen, Schmaal, Lianne, Schulte-Rüther, Martin, Schweren, Lizanne, Seitz, Jochen, Serpa, Mauricio Henriques, Shaw, Philip, Shumskaya, Elena, Silk, Timothy J., Simmons, Alan N., Simulionyte, Egle, Baune, Bernhard T., Sinha, Rajita, Sjoerds, Zsuzsika, Smelror, Runar Elle, Soliva, Joan Carlos, Solowij, Nadia, Souza-Duran, Fabio Luisde, Sponheim, Scott R., Stein, Dan J., Stein, Elliot A., Stevens, Michael, Baur-Streubel, Ramona, Strike, Lachlan T., Sudre, Gustavo, Sui, Jing, Tamm, Leanne, Temmingh, Hendrik S., Thoma, Robert J., Tomyshev, Alexander, Tronchin, Giulia, Turner, Jessica, Uhlmann, Anne, Biederman, Joseph, van Erp, Theo G. M., van den Heuvel, Odile A., van der Meer, Dennis, van Eijk, Liza, Vance, Alasdair, Veer, Ilya M., Veltman, Dick J., Venkatasubramanian, Ganesan, Vilarroya, Oscar, Vives-Gilabert, Yolanda, Blaine, Sara K., Voineskos, Aristotle N., Völzke, Henry, Vuletic, Daniella, Walitza, Susanne, Walter, Henrik, Walton, Esther, Wardlaw, Joanna M., Wen, Wei, Westlye, Lars T., Whelan, Christopher D., Boedhoe, Premika, White, Tonya, Wiers, Reinout W., Wright, Margaret J., Wittfeld, Katharina, Yang, Tony T., Yasuda, Clarissa L., Yoncheva, Yuliya, Yücel, Murat, Yun, Je-Yeon, Zanetti, Marcus Vinicius, Bøen, Erlend, Zhen, Zonglei, Zhu, Xing-Xing, Ziegler, Georg C., de Zubicaray, Greig I., Zwiers, Marcel, Project, Karolinska Schizophrenia, Glahn, David C., Crivello, Fabrice, Fisher, Simon E., Thompson, Paul M., Bose, Anushree, Francks, Clyde, Farde, Lars, Flyckt, Lena, Engberg, Göran, Erhardt, Sophie, Fatouros-Bergman, Helena, Cervenka, Simon, Schwieler, Lilly, Piehl, Fredrik, Agartz, Ingrid, Bralten, Janita, Collste, Karin, Victorsson, Pauliina, Malmqvist, Anna, Hedberg, Mikael, Orhan, Funda, Sellgren, Carl, Brandeis, Daniel, Kong, Xiang-Zhen, Brem, Silvia, Brodaty, Henry, Yüksel, Dilara, Brooks, Samantha J., Buitelaar, Jan, Bürger, Christian, Bülow, Robin, Calhoun, Vince, Calvo, Anna, Canales-Rodríguez, Erick Jorge, Mathias, Samuel R., Cannon, Dara M., Caparelli, Elisabeth C., Castellanos, Francisco X., Cendes, Fernando, Chaim-Avancini, Tiffany Moukbel, Chantiluke, Kaylita, Chen, Qun-Lin, Chen, Xiayu, Cheng, Yuqi, Christakou, Anastasia, Guadalupe, Tulio, Clark, Vincent P., Coghill, David, Connolly, Colm G., Conzelmann, Annette, Córdova-Palomera, Aldo, Cousijn, Janna, Crow, Tim, Cubillo, Ana, Dannlowski, Udo, de Bruttopilo, Sara Ambrosino, Abé, Christoph, de Zeeuw, Patrick, Deary, Ian J., Demeter, Damion V., Di Martino, Adriana, Dickie, Erin W., Dietsche, Bruno, Doan, Nhat Trung, Doherty, Colin P., Doyle, Alysa, Durston, Sarah, Earl, Eric, Ehrlich, Stefan, Ekman, Carl Johan, Elvsåshagen, Torbjørn, Epstein, Jeffery N., Fair, Damien A., Faraone, Stephen V., Fernández, Guillén, Flint, Claas, Filho, Geraldo Busatto, Akudjedu, Theophilus N., Förster, Katharina, Fouche, Jean-Paul, Foxe, John J., Frodl, Thomas, Fuentes-Claramonte, Paola, Fullerton, Janice M., Garavan, Hugh, do Santos Garcia, Danielle, Gotlib, Ian H., Goudriaan, Anna E., Aleman, Andre, Grabe, Hans Jörgen, Groenewold, Nynke A., Grotegerd, Dominik, Gruber, Oliver, Gurholt, Tiril, Haavik, Jan, Hahn, Tim, Hansell, Narelle K., Harris, Mathew A., Hartman, Catharina A., Ontwikkelingspsychologie (Psychologie, FMG), Adult Psychiatry, APH - Mental Health, ANS - Compulsivity, Impulsivity & Attention, Child and Adolescent Psychiatry & Psychosocial Care, Child Psychiatry, ANS - Cellular & Molecular Mechanisms, Laboratory Genetic Metabolic Diseases, Paediatrics, General Paediatrics, ARD - Amsterdam Reproduction and Development, Paediatric Pulmonology, Graduate School, and APH - Digital Health

Subjects
P‐hacking, Datasets as Topic, Publication bias, 0302 clinical medicine, 130 000 Cognitive Neurology & Memory, Statistics, team science, Brain asymmetry, Multicenter Studies as Topic, Cervell, Research Articles, Cerebral Cortex, Radiological and Ultrasound Technology, P-hacking, 05 social sciences, Brain, Cerebral cortex, Middle Aged, Magnetic Resonance Imaging, Discoveries in science, Escorça cerebral, Neurology, Biaix de publicació, Anatomy, Psychology, Research Article, Neuroinformatics, Adult, Adolescent, Neuroimaging, Descobriments científics, 050105 experimental psychology, Statistical power, 03 medical and health sciences, Young Adult, Magnetic resonance imaging, Imatges per ressonància magnètica, multisite collaboration, Humans, 0501 psychology and cognitive sciences, Radiology, Nuclear Medicine and imaging, ddc:610, reproducibility, Aged, publication bias, Reproducibility, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], Perspective (graphical), Reproducibility of Results, Brain Cortical Thickness, Research data, Sample size determination, Dades de recerca, Neurology (clinical), Scale (map), Developmental Psychopathology, 030217 neurology & neurosurgery
Abstract

The problem of poor reproducibility of scientific findings has received much attention over recent years, in a variety of fields including psychology and neuroscience. The problem has been partly attributed to publication bias and unwanted practices such as p‐hacking. Low statistical power in individual studies is also understood to be an important factor. In a recent multisite collaborative study, we mapped brain anatomical left–right asymmetries for regional measures of surface area and cortical thickness, in 99 MRI datasets from around the world, for a total of over 17,000 participants. In the present study, we revisited these hemispheric effects from the perspective of reproducibility. Within each dataset, we considered that an effect had been reproduced when it matched the meta‐analytic effect from the 98 other datasets, in terms of effect direction and significance threshold. In this sense, the results within each dataset were viewed as coming from separate studies in an “ideal publishing environment,” that is, free from selective reporting and p hacking. We found an average reproducibility rate of 63.2% (SD = 22.9%, min = 22.2%, max = 97.0%). As expected, reproducibility was higher for larger effects and in larger datasets. Reproducibility was not obviously related to the age of participants, scanner field strength, FreeSurfer software version, cortical regional measurement reliability, or regional size. These findings constitute an empirical illustration of reproducibility in the absence of publication bias or p hacking, when assessing realistic biological effects in heterogeneous neuroscience data, and given typically‐used sample sizes., Region‐wise effect sizes and reproducibility rates of hemispheric asymmetry effects. In general, effects with higher effect sizes showed higher reproducibility, given the same conditions (e.g., sample size and data heterogeneity).

Published
2022

33. Benchmarking the performance of a low‐cost magnetic resonance control system at multiple sites in the open MaRCoS community.

Author

Guallart‐Naval, Teresa, O'Reilly, Thomas, Algarín, José M., Pellicer‐Guridi, Ruben, Vives‐Gilabert, Yolanda, Craven‐Brightman, Lincoln, Negnevitsky, Vlad, Menküc, Benjamin, Galve, Fernando, Stockmann, Jason P., Webb, Andrew, and Alonso, Joseba

Subjects
MAGNETIC control, COMMUNITIES, INTEGRATED software, CONSORTIA
Abstract

Purpose: To describe the current properties and capabilities of an open‐source hardware and software package that is being developed by many sites internationally with the aim of providing an inexpensive yet flexible platform for low‐cost MRI. Methods: This article describes three different setups from 50 to 360 mT in different settings, all of which used the MaRCoS console for acquiring data, and different types of software interface (custom‐built GUI or Pulseq overlay) to acquire it. Results: Images are presented both from phantoms and in vivo from healthy volunteers to demonstrate the image quality that can be obtained from the MaRCoS hardware/software interfaced to different low‐field magnets. Conclusions: The results presented here show that a number of different sequences commonly used in the clinic can be programmed into an open‐source system relatively quickly and easily, and can produce good quality images even at this early stage of development. Both the hardware and software will continue to develop, and it is an aim of this article to encourage other groups to join this international consortium. [ABSTRACT FROM AUTHOR]

Published
2023
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34. Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders

Author

Committee, Writing, Disorder, Autism Spectrum, French, Leon, Grevet, Eugenio H, Groenewold, Nynke A, Grotegerd, Dominik, Gruber, Oliver, Gruner, Patricia, Guerrero-Pedraza, Amalia, Gur, Raquel E, Gur, Ruben C, Haar, Shlomi, Haarman, Bartholomeus C M, Thomopoulos, Sophia I, Haavik, Jan, Hahn, Tim, Hajek, Tomas, Harrison, Benjamin J, Harrison, Neil A, Hartman, Catharina A, Whalley, Heather C, Heslenfeld, Dirk J, Hibar, Derrek P, Hilland, Eva, Pozzi, Elena, Hirano, Yoshiyuki, Ho, Tiffany C, Hoekstra, Pieter J, Hoekstra, Liesbeth, Hohmann, Sarah, Hong, L. E., Höschl, Cyril, Høvik, Marie F, Howells, Fleur M, Nenadic, Igor, Abe, Yoshinari, Jalbrzikowski, Maria, James, Anthony C, Janssen, Joost, Jaspers-Fayer, Fern, Xu, Jian, Jonassen, Rune, Karkashadze, Georgii, King, Joseph A, Kircher, Tilo, Kirschner, Matthias, Abé, Christoph, Koch, Kathrin, Kochunov, Peter, Kohls, Gregor, Konrad, Kerstin, Krämer, Bernd, Krug, Axel, Kuntsi, Jonna, Kwon, Jun Soo, Landén, Mikael, Landrø, Nils I, Anticevic, Alan, Lazaro, Luisa, Lebedeva, Irina S, Leehr, Elisabeth J, Lera-Miguel, Sara, Lesch, Klaus-Peter, Lochner, Christine, Louza, Mario R, Luna, Beatriz, Lundervold, Astri J, MacMaster, Frank P, Alda, Martin, Maglanoc, Luigi A, Malpas, Charles B, Portella, Maria J, Marsh, Rachel, Martyn, Fiona M, Mataix-Cols, David, Mathalon, Daniel H, McCarthy, Hazel, McDonald, Colm, McPhilemy, Genevieve, Aleman, Andre, Meinert, Susanne, Menchón, José M, Minuzzi, Luciano, Mitchell, Philip B, Moreno, Carmen, Morgado, Pedro, Muratori, Filippo, Murphy, Clodagh M, Murphy, Declan, Mwangi, Benson, Alloza, Clara, Nabulsi, Leila, Nakagawa, Akiko, Nakamae, Takashi, Namazova, Leyla, Narayanaswamy, Janardhanan, Jahanshad, Neda, Nguyen, Danai D, Nicolau, Rosa, O'Gorman Tuura, Ruth L, O'Hearn, Kirsten, Alonso-Lana, Silvia, Oosterlaan, Jaap, Opel, Nils, Ophoff, Roel A, Oranje, Bob, García de la Foz, Victor Ortiz, Overs, Bronwyn J, Paloyelis, Yannis, Pantelis, Christos, Parellada, Mara, Pauli, Paul, Disorder, Bipolar, Ameis, Stephanie H, Picó-Pérez, Maria, Picon, Felipe A, Piras, Fabrizio, Piras, Federica, Plessen, Kerstin J, Pomarol-Clotet, Edith, Preda, Adrian, Puig, Olga, Quidé, Yann, Radua, Joaquim, Anagnostou, Evdokia, Ramos-Quiroga, J Antoni, Rasser, Paul E, Rauer, Lisa, Reddy, Janardhan, Redlich, Ronny, Reif, Andreas, Reneman, Liesbeth, Repple, Jonathan, Retico, Alessandra, Richarte, Vanesa, McIntosh, Andrew A, Richter, Anja, Rosa, Pedro G P, Rubia, Katya K, Hashimoto, Ryota, Sacchet, Matthew D, Salvador, Raymond, Santonja, Javier, Sarink, Kelvin, Sarró, Salvador, Satterthwaite, Theodore D, Arango, Celso, Sawa, Akira, Schall, Ulrich, Schofield, Peter R, Schrantee, Anouk, Seitz, Jochen, Serpa, Mauricio H, Setién-Suero, Esther, Shaw, Philip, Shook, Devon, Silk, Tim J, Arnold, Paul D, Sim, Kang, Simon, Schmitt, Simpson, Helen Blair, Singh, Aditya, Skoch, Antonin, Skokauskas, Norbert, Soares, Jair C, Soreni, Noam, Soriano-Mas, Carles, Spalletta, Gianfranco, Asherson, Philip, Spaniel, Filip, Lawrie, Stephen M, Stern, Emily R, Stewart, S Evelyn, Takayanagi, Yoichiro, Temmingh, Henk S, Tolin, David F, Tomecek, David, Tordesillas-Gutiérrez, Diana, Tosetti, Michela, Assogna, Francesca, Uhlmann, Anne, van Amelsvoort, Therese, van der Wee, Nic J A, van der Werff, Steven J A, van Haren, Neeltje E M, van Wingen, Guido A, Vance, Alasdair, Vázquez-Bourgon, Javier, Vecchio, Daniela, Venkatasubramanian, Ganesan, Auzias, Guillaume, Vieta, Eduard, Vilarroya, Oscar, Vives-Gilabert, Yolanda, Voineskos, Aristotle N, Völzke, Henry, von Polier, Georg G, Walton, Esther, Weickert, Thomas W, Weickert, Cynthia Shannon, Weideman, Andrea S, Ayesa-Arriola, Rosa, Wittfeld, Katharina, Wolf, Daniel H, Wu, Mon-Ju, Yang, T. T., Yang, Sikun, Yoncheva, Yuliya, Yun, Je-Yeon, Cheng, Yuqi, Zanetti, Marcus V, Ziegler, Georg C, Bakker, Geor, Franke, Barbara, Hoogman, Martine, Buitelaar, Jan K, van Rooij, Daan, Andreassen, Ole A, Ching, Christopher R K, Veltman, Dick J, Schmaal, Lianne, Stein, Dan J, van den Heuvel, Odile A, Disorder, Major Depressive, Banaj, Nerisa, Turner, Jessica A, van Erp, Theo G M, Pausova, Zdenka, Thompson, Paul M, Paus, Tomáš, Attention-Deficit/Hyperactivity Disorder, Banaschewski, Tobias, Bandeira, Cibele E, Baranov, Alexandr, Bargalló, Núria, Bau, Claiton H D, Baumeister, Sarah, Baune, Bernhard T, Bellgrove, Mark A, Benedetti, Francesco, Disorder, Obsessive-Compulsive, Bertolino, Alessandro, Boedhoe, Premika S W, Boks, Marco, Bollettini, Irene, Del Mar Bonnin, Caterina, Borgers, Tiana, Borgwardt, Stefan, Brandeis, Daniel, Brennan, Brian P, Bruggemann, Jason M, Groups, Schizophrenia ENIGMA Working, Bülow, Robin, Busatto, Geraldo F, Calderoni, Sara, Calhoun, Vince D, Calvo, Rosa, Canales-Rodríguez, Erick J, Cannon, Dara M, Carr, Vaughan J, Cascella, Nicola, Cercignani, Mara, Patel, Yash, Chaim-Avancini, Tiffany M, Christakou, Anastasia, Coghill, David, Conzelmann, Annette, Crespo-Facorro, Benedicto, Cubillo, Ana I, Cullen, Kathryn R, Cupertino, Renata B, Daly, Eileen, Dannlowski, Udo, Parker, Nadine, Davey, Christopher G, Denys, Damiaan, Deruelle, Christine, Di Giorgio, Annabella, Dickie, Erin W, Dima, Danai, Dohm, Katharina, Ehrlich, Stefan, Ely, Benjamin A, Erwin-Grabner, Tracy, Shin, Jean, Ethofer, Thomas, Fair, Damien A, Fallgatter, Andreas, Faraone, Stephen V, Fatjó-Vilas, Mar, Fedor, Jennifer M, Fitzgerald, Kate D, Ford, Judith M, Frodl, Thomas, Fu, Cynthia H Y, Howard, Derek, Fullerton, Janice M, Gabel, Matt C, Glahn, David C, Roberts, Gloria, Gogberashvili, Tinatin, Goikolea, Jose M, Gotlib, Ian H, Goya-Maldonado, Roberto, Grabe, Hans, Green, Melissa J, Patel, Y., Parker, N., Shin, J., Howard, D., French, L., Thomopoulos, S. I., Pozzi, E., Abe, Y., Abe, C., Anticevic, A., Alda, M., Aleman, A., Alloza, C., Alonso-Lana, S., Ameis, S. H., Anagnostou, E., Mcintosh, A. A., Arango, C., Arnold, P. D., Asherson, P., Assogna, F., Auzias, G., Ayesa-Arriola, R., Bakker, G., Banaj, N., Banaschewski, T., Bandeira, C. E., Baranov, A., Bargallo, N., Bau, C. H. D., Baumeister, S., Baune, B. T., Bellgrove, M. A., Benedetti, F., Bertolino, A., Boedhoe, P. S. W., Boks, M., Bollettini, I., Del Mar Bonnin, C., Borgers, T., Borgwardt, S., Brandeis, D., Brennan, B. P., Bruggemann, J. M., Bulow, R., Busatto, G. F., Calderoni, S., Calhoun, V. D., Calvo, R., Canales-Rodriguez, E. J., Cannon, D. M., Carr, V. J., Cascella, N., Cercignani, M., Chaim-Avancini, T. M., Christakou, A., Coghill, D., Conzelmann, A., Crespo-Facorro, B., Cubillo, A. I., Cullen, K. R., Cupertino, R. B., Daly, E., Dannlowski, U., Davey, C. G., Denys, D., Deruelle, C., Di Giorgio, A., Dickie, E. W., Dima, D., Dohm, K., Ehrlich, S., Ely, B. A., Erwin-Grabner, T., Ethofer, T., Fair, D. A., Fallgatter, A. J., Faraone, S. V., Fatjo-Vilas, M., Fedor, J. M., Fitzgerald, K. D., Ford, J. M., Frodl, T., Fu, C. H. Y., Fullerton, J. M., Gabel, M. C., Glahn, D. C., Roberts, G., Gogberashvili, T., Goikolea, J. M., Gotlib, I. H., Goya-Maldonado, R., Grabe, H. J., Green, M. J., Grevet, E. H., Groenewold, N. A., Grotegerd, D., Gruber, O., Gruner, P., Guerrero-Pedraza, A., Gur, R. E., Gur, R. C., Haar, S., Haarman, B. C. M., Haavik, J., Hahn, T., Hajek, T., Harrison, B. J., Harrison, N. A., Hartman, C. A., Whalley, H. C., Heslenfeld, D. J., Hibar, D. P., Hilland, E., Hirano, Y., Ho, T. C., Hoekstra, P. J., Hoekstra, L., Hohmann, S., Hong, L. E., Hoschl, C., Hovik, M. F., Howells, F. M., Nenadic, I., Jalbrzikowski, M., James, A. C., Janssen, J., Jaspers-Fayer, F., Xu, J., Jonassen, R., Karkashadze, G., King, J. A., Kircher, T., Kirschner, M., Koch, K., Kochunov, P., Kohls, G., Konrad, K., Kramer, B., Krug, A., Kuntsi, J., Kwon, J. S., Landen, M., Landro, N. I., Lazaro, L., Lebedeva, I. S., Leehr, E. J., Lera-Miguel, S., Lesch, K. -P., Lochner, C., Louza, M. R., Luna, B., Lundervold, A. J., Macmaster, F. P., Maglanoc, L. A., Malpas, C. B., Portella, M. J., Marsh, R., Martyn, F. M., Mataix-Cols, D., Mathalon, D. H., Mccarthy, H., Mcdonald, C., Mcphilemy, G., Meinert, S., Menchon, J. M., Minuzzi, L., Mitchell, P. B., Moreno, C., Morgado, P., Muratori, F., Murphy, C. M., Murphy, D., Mwangi, B., Nabulsi, L., Nakagawa, A., Nakamae, T., Namazova, L., Narayanaswamy, J., Jahanshad, N., Nguyen, D. D., Nicolau, R., O'Gorman Tuura, R. L., O'Hearn, K., Oosterlaan, J., Opel, N., Ophoff, R. A., Oranje, B., Garcia De La Foz, V. O., Overs, B. J., Paloyelis, Y., Pantelis, C., Parellada, M., Pauli, P., Pico-Perez, M., Picon, F. A., Piras, F., Plessen, K. J., Pomarol-Clotet, E., Preda, A., Puig, O., Quide, Y., Radua, J., Ramos-Quiroga, J. A., Rasser, P. E., Rauer, L., Reddy, J., Redlich, R., Reif, A., Reneman, L., Repple, J., Retico, A., Richarte, V., Richter, A., Rosa, P. G. P., Rubia, K. K., Hashimoto, R., Sacchet, M. D., Salvador, R., Santonja, J., Sarink, K., Sarro, S., Satterthwaite, T. D., Sawa, A., Schall, U., Schofield, P. R., Schrantee, A., Seitz, J., Serpa, M. H., Setien-Suero, E., Shaw, P., Shook, D., Silk, T. J., Sim, K., Simon, S., Simpson, H. B., Singh, A., Skoch, A., Skokauskas, N., Soares, J. C., Soreni, N., Soriano-Mas, C., Spalletta, G., Spaniel, F., Lawrie, S. M., Stern, E. R., Stewart, S. E., Takayanagi, Y., Temmingh, H. S., Tolin, D. F., Tomecek, D., Tordesillas-Gutierrez, D., Tosetti, M., Uhlmann, A., Van Amelsvoort, T., Van Der Wee, N. J. A., Van Der Werff, S. J. A., Van Haren, N. E. M., Van Wingen, G. A., Vance, A., Vazquez-Bourgon, J., Vecchio, D., Venkatasubramanian, G., Vieta, E., Vilarroya, O., Vives-Gilabert, Y., Voineskos, A. N., Volzke, H., Von Polier, G. G., Walton, E., Weickert, T. W., Weickert, C. S., Weideman, A. S., Wittfeld, K., Wolf, D. H., Wu, M. -J., Yang, T. T., Yang, K., Yoncheva, Y., Yun, J. -Y., Cheng, Y., Zanetti, M. V., Ziegler, G. C., Franke, B., Hoogman, M., Buitelaar, J. K., Van Rooij, D., Andreassen, O. A., Ching, C. R. K., Veltman, D. J., Schmaal, L., Stein, D. J., Van Den Heuvel, O. A., Turner, J. A., Van Erp, T. G. M., Pausova, Z., Thompson, P. M., Paus, T., Institut de Neurosciences de la Timone (INT), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Pediatric surgery, Radiology and nuclear medicine, Anatomy and neurosciences, Psychiatry, Amsterdam Neuroscience - Brain Imaging, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Amsterdam Neuroscience - Neurodegeneration, Psychiatrie & Neuropsychologie, RS: MHeNs - R2 - Mental Health, MUMC+: MA Med Staf Spec Psychiatrie (9), Adult Psychiatry, ANS - Compulsivity, Impulsivity & Attention, General Paediatrics, ARD - Amsterdam Reproduction and Development, Radiology and Nuclear Medicine, APH - Personalized Medicine, ANS - Brain Imaging, ANS - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Mental Health, University of Zurich, Clinical Cognitive Neuropsychiatry Research Program (CCNP), Clinical Neuropsychology, Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Child and Adolescent Psychiatry / Psychology, IBBA, and Cognitive Psychology

Subjects
Male, Obsessive-Compulsive Disorder, Bipolar Disorder, Autism Spectrum Disorder, Autism, [SDV]Life Sciences [q-bio], Gene Expression, cytology [Cerebral Cortex], Cohort Studies, Fetal Development, physiology [Gene Expression], 2738 Psychiatry and Mental Health, 0302 clinical medicine, diagnostic imaging [Cerebral Cortex], SCHIZOPHRENIA, BRAIN, Child, Obsessive-compulsive disorder (OCD), Original Investigation, Aged, 80 and over, Cerebral Cortex, 0303 health sciences, pathology [Depressive Disorder, Major], Principal Component Analysis, Adolescent psychiatry, 10058 Department of Child and Adolescent Psychiatry, Middle Aged, diagnostic imaging [Obsessive-Compulsive Disorder], REGIONS, Magnetic Resonance Imaging, 3. Good health, FALSE DISCOVERY RATE, Psychiatry and Mental health, Autism spectrum disorder, Schizophrenia, growth & development [Cerebral Cortex], Child, Preschool, Major depressive disorder, diagnostic imaging [Schizophrenia], Esquizofrènia, Female, Psiquiatria infantil, Psiquiatria de l'adolescència, diagnostic imaging [Autism Spectrum Disorder], Adult, medicine.medical_specialty, Adolescent, Human Development, 610 Medicine & health, diagnostic imaging [Bipolar Disorder], pathology [Autism Spectrum Disorder], diagnostic imaging [Depressive Disorder, Major], 03 medical and health sciences, Young Adult, All institutes and research themes of the Radboud University Medical Center, Neuroimaging, SDG 3 - Good Health and Well-being, CEREBRAL-CORTEX, Child psychiatry, medicine, Attention deficit hyperactivity disorder, Humans, Bipolar disorder, ddc:610, Psychiatry, pathology [Schizophrenia], 030304 developmental biology, Aged, Depressive Disorder, Major, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], business.industry, DENDRITE, Computational Biology, Correction, pathology [Attention Deficit Disorder with Hyperactivity], physiology [Fetal Development], medicine.disease, PATHOLOGY, pathology [Bipolar Disorder], pathology [Obsessive-Compulsive Disorder], 10036 Medical Clinic, Attention Deficit Disorder with Hyperactivity, 10054 Clinic for Psychiatry, Psychotherapy, and Psychosomatics, Case-Control Studies, DENSITY, ORIGINS, HIPPOCAMPUS, diagnostic imaging [Attention Deficit Disorder with Hyperactivity], pathology [Cerebral Cortex], Autisme, business, Neuroscience, 030217 neurology & neurosurgery, physiology [Human Development]
Abstract

[Importance] Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood., [Objective] To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia., [Design, Setting, and Participants] Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244., [Main Outcomes and Measures] Interregional profiles of group difference in cortical thickness between cases and controls., [Results] A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders., [Conclusions and Relevance] In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.

Published
2021

35. Modeling magnetic emissions combining image processing and an optimization algorithm

Author

Vives-Gilabert, Yolanda, Arcambal, Christian, Louis, Anne, Eudeline, Philippe, and Mazari, Belahcene

Subjects
Electromagnetic measurements -- Methods, Image processing -- Methods, Algorithms -- Research, Electronic equipment and supplies -- Models, Magnetic fields -- Models, Mathematical optimization, Algorithm, Business, Computers, Electronics, Electronics and electrical industries
Published
2009

36. Generador de Señales y Osciloscopio Virtual

Author

Castells Ramón, Francisco Sales and Vives Gilabert, Yolanda

Subjects
TECNOLOGIA ELECTRONICA, 3307 - Tecnología electrónica, Generador de señales, Osciloscopio
Abstract

En este laboratorio virtual el alumno podrá configurar los parámetros de una señal según se haría en un generador de funciones y configurar los parámetros para su visualización según se haría en un osciloscopio. El resultado de esta visualización es la que se muestra en pantalla., Para el correcto uso de este laboratorio virtual, debe configurarse la señal según los siguientes parámetros: - Tipo: senoidal, triangular o cuadrada - Frecuencia: entre 1Hz y 1MHz - Amplitud: entre 10mV y 15V - Offset: entre -10V y 10V A continuación deberá seleccionar la configuración de visualización, incluyendo escalas de amplitud, de tiempos, canales a visualizar y acoplamiento AC/DC, tanto del canal 1 (CH1) como del canal 2 (CH2).

Published
2020

37. Rectificador de onda completa con filtro C y carga resistiva

Author

Castells Ramón, Francisco Sales and Vives Gilabert, Yolanda

Subjects
TECNOLOGIA ELECTRONICA, Diodo, Condensador, 3307 - Tecnología electrónica, Rectificador
Abstract

En este laboratorio virtual se muestra la forma de onda en cada etapa de un rectificador de onda completa con filtro C y carga resistiva: - Señal de entrada - Señal rectificada - Salida filtrada, Como parámetros de entrada se requiere introducir la amplitud de la señal senoidal (la frecuencia es fija, de 50Hz), la capacidad del condensador y la resistencia de carga.

Published
2020

38. Rectificador de media onda con filtro C y carga resistiva

Author

Castells Ramón, Francisco Sales and Vives Gilabert, Yolanda

Subjects
TECNOLOGIA ELECTRONICA, 3307 - Tecnología electrónica, Rectificador
Abstract

En este laboratorio virtual se muestra la forma de onda en cada etapa de un rectificador de media onda con filtro C y carga resistiva: - Señal de entrada - Señal rectificada - Salida filtrada, Como parámetros de entrada se requiere introducir la amplitud de la señal senoidal (la frecuencia es fija, de 50Hz), la capacidad del condensador y la resistencia de carga.

Published
2020

39. Curva de Lissajous

Author

Castells Ramón, Francisco Sales and Vives Gilabert, Yolanda

Subjects
TECNOLOGIA ELECTRONICA, 3307 - Tecnología electrónica, Lissajous
Abstract

Este laboratorio virtual representa la curva de Lissajous correspondiente a dos señales senoidales con un desfase entre ellas., Como parámetros de entrada deben introducirse las amplitudes de ambas señales y el desfase entre ellas. Como resultado se muestra la curva, con los siguientes valores que serán necesarios para que el usuario pueda calcular la fase según el método de la curva de Lissajous: - En el eje x: Amplitud máxima (se muestra en el semieje negativo) y corte sobre el eje horizontal (se muestra en el semieje positivo) - En el eje y: Amplitud máxima (se muestra en el semieje negativo) y corte sobre el eje vertical (se muestra en el semieje positivo)

Published
2020

40. Rectificador de media onda con filtro C y estabilizador Zener

Author

Castells Ramón, Francisco Sales and Vives Gilabert, Yolanda

Subjects
TECNOLOGIA ELECTRONICA, Zener, Estabilizador, 3307 - Tecnología electrónica, Rectificador
Abstract

En este laboratorio virtual se muestra la forma de onda en cada etapa de un rectificador de media onda con filtro C y estabilizador Zener: - Señal de entrada - Señal rectificada - Señal en el condensador - Señal estabilizada a la salida, Como parámetros de entrada se requiere introducir la amplitud de la señal senoidal (la frecuencia es fija, de 50Hz) y los valores del condensador, la resistencia R1, la tensión de Zener y la resistencia de carga.

Published
2020

41. Rectificador de onda completa con filtro C y estabilizador Zener

Author

Castells Ramón, Francisco Sales and Vives Gilabert, Yolanda

Subjects
TECNOLOGIA ELECTRONICA, Estabilizador, 3307 - Tecnología electrónica, Rectificador, Fuente de alimentación
Abstract

En este laboratorio virtual se muestra la forma de onda en cada etapa de un rectificador de onda completa con filtro C y estabilizador Zener: - Señal de entrada - Señal rectificada - Señal en el condensador - Señal estabilizada a la salida, Como parámetros de entrada se requiere introducir la amplitud de la señal senoidal (la frecuencia es fija, de 50Hz) y los valores del condensador, la resistencia R1, la tensión de Zener y la resistencia de carga.

Published
2020

42. Circuito RC: Carga y descarga de un condensador

Author

Castells Ramón, Francisco Sales and Vives Gilabert, Yolanda

Subjects
TECNOLOGIA ELECTRONICA, Condensador, 3307 - Tecnología electrónica, Circuito RC
Abstract

En este laboratorio virtual el usuario podrá visualizar el proceso de carga y descarga de un condensador a través de un circuito RC. A partir de la observación del resultado se podrá determinar si el condensador se llega a cargar completamente al final del semiciclo correspondiente, de forma que se puede ajustar el valor de la capacidad del condensador (o el valor de la resistencia) para conseguir el objetivo de carga deseado., Como parámetros de entrada debe introducirse la amplitud y frecuencia de la señal cuadrada, además de los valores de resistencia (en ohmios) y capacidad del condensador (en faradios).

Published
2020

43. Modeling magnetic radiations of electronic circuits using near-field scanning method

Author

Vives-Gilabert, Yolanda, Arcambal, Christian, Louis, Anne, de Daran, Francois, Eudeline, Philippe, and Mazari, Belahcene

Subjects
Magnetic dipoles -- Analysis, Electronic circuits -- Usage, Business, Computers, Electronics, Electronics and electrical industries
Abstract

In this paper, a simple method to obtain the equivalent radiation emitting sources of an electronic circuit using the near-field scanning method is presented. The model is based on a set of elemental dipoles that substitutes the electronic circuit and radiates the same magnetic field. Two different approaches are presented: a set of electric dipoles and a set of magnetic dipoles. In order to build the model, both the magnitude and phase of the magnetic field are required. These measurements are carried out using the 'near-field scanning method,' and two procedures are presented: using the vector network analyzer and the spectrum analyzer. Finally, the model is applied to two different cases: to obtain the radiated near-field of a component (microcontroller) and to obtain the field of a complete electronic board. Index Terms--Electromagnetic inverse problem, equivalent electromagnetic model, modeling radiated emissions, near-field scanning method.

Published
2007

44. Classification model based on strain measurements to identify patients with arrhythmogenic cardiomyopathy with left ventricular involvement

Author

Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica, Instituto de Salud Carlos III, Ministerio de Economía y Empresa, European Regional Development Fund, Vives-Gilabert, Yolanda, Zorio, Esther, Sanz-Sánchez, Jorge, Calvillo-Batllés, Pilar, Millet Roig, José, Castells, Francisco, Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica, Instituto de Salud Carlos III, Ministerio de Economía y Empresa, European Regional Development Fund, Vives-Gilabert, Yolanda, Zorio, Esther, Sanz-Sánchez, Jorge, Calvillo-Batllés, Pilar, Millet Roig, José, and Castells, Francisco

Abstract

[EN] Background and objective: A heterogenous expression characterizes arrhythmogenic cardiomyopathy (AC). The evaluation of regional wall movement included in the current Task Force Criteria is only qualitative and restricted to the right ventricle. However, a strain-based approach could precisely quantify myocardial deformation in both ventricles. We aim to define and modelize the strain behavior of the left ventricle in AC patients with left ventricular (LV) involvement by applying algorithms such as Principal Component Analysis (PCA), clustering and naive Bayes (NB) classifiers. Methods: Thirty-six AC patients with LV involvement and twenty-three non-affected family members (controls) were enrolled. Feature-tracking analysis was applied to cine cardiac magnetic resonance imaging to assess strain time series from a 3D approach, to which PCA was applied. A Two-Step clustering algorithm separated the patients' group into clusters according to their level of LV strain impairment. A statistical characterization between controls and the new AC subgroups was done. Finally, a NB classifier was built and new data from a small evolutive dataset was predicted. Results: 60% of AC-LV patients showed mildly affected strain and 40% severely affected strain. Both groups and controls exhibited statistically significant differences, especially when comparing controls and severely affected AC-LV patients. The classification accuracy of the strain NB classifier reached 82.76%. The model performance was as good as to classify the individuals with a 100% sensitivity and specificity for severely impaired strain patients, 85.7% and 81.1% for mildly impaired strain patients, and 69.9% and 91.4% for normal strain, respectively. Even when the severely affected LV-AC group was excluded, LV strain showed a good accuracy to differentiate patients and controls. The prediction of the evolutive dataset revealed a progressive alteration of strain in time. Conclusions: Our LV strain classificatio

Published
2020

45. Generador de Señales y Osciloscopio Virtual

Author

Universitat Politècnica de València. Escuela Politécnica Superior de Gandia - Escola Politècnica Superior de Gandia, Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica, Castells Ramón, Francisco Sales, Vives Gilabert, Yolanda, Universitat Politècnica de València. Escuela Politécnica Superior de Gandia - Escola Politècnica Superior de Gandia, Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica, Castells Ramón, Francisco Sales, and Vives Gilabert, Yolanda

Abstract

En este laboratorio virtual el alumno podrá configurar los parámetros de una señal según se haría en un generador de funciones y configurar los parámetros para su visualización según se haría en un osciloscopio. El resultado de esta visualización es la que se muestra en pantalla.

Published
2020

46. Curva de Lissajous

Author

Universitat Politècnica de València. Escuela Politécnica Superior de Gandia - Escola Politècnica Superior de Gandia, Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica, Castells Ramón, Francisco Sales, Vives Gilabert, Yolanda, Universitat Politècnica de València. Escuela Politécnica Superior de Gandia - Escola Politècnica Superior de Gandia, Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica, Castells Ramón, Francisco Sales, and Vives Gilabert, Yolanda

Abstract

Este laboratorio virtual representa la curva de Lissajous correspondiente a dos señales senoidales con un desfase entre ellas.

Published
2020

47. Rectificador de onda completa con filtro C y estabilizador Zener

Author

Universitat Politècnica de València. Escuela Politécnica Superior de Gandia - Escola Politècnica Superior de Gandia, Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica, Castells Ramón, Francisco Sales, Vives Gilabert, Yolanda, Universitat Politècnica de València. Escuela Politécnica Superior de Gandia - Escola Politècnica Superior de Gandia, Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica, Castells Ramón, Francisco Sales, and Vives Gilabert, Yolanda

Abstract

En este laboratorio virtual se muestra la forma de onda en cada etapa de un rectificador de onda completa con filtro C y estabilizador Zener: - Señal de entrada - Señal rectificada - Señal en el condensador - Señal estabilizada a la salida

Published
2020

48. Circuito RC: Carga y descarga de un condensador

Author

Universitat Politècnica de València. Escuela Politécnica Superior de Gandia - Escola Politècnica Superior de Gandia, Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica, Castells Ramón, Francisco Sales, Vives Gilabert, Yolanda, Universitat Politècnica de València. Escuela Politécnica Superior de Gandia - Escola Politècnica Superior de Gandia, Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica, Castells Ramón, Francisco Sales, and Vives Gilabert, Yolanda

Abstract

En este laboratorio virtual el usuario podrá visualizar el proceso de carga y descarga de un condensador a través de un circuito RC. A partir de la observación del resultado se podrá determinar si el condensador se llega a cargar completamente al final del semiciclo correspondiente, de forma que se puede ajustar el valor de la capacidad del condensador (o el valor de la resistencia) para conseguir el objetivo de carga deseado.

Published
2020

49. Rectificador de media onda con filtro C y estabilizador Zener

Author

Universitat Politècnica de València. Escuela Politécnica Superior de Gandia - Escola Politècnica Superior de Gandia, Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica, Castells Ramón, Francisco Sales, Vives Gilabert, Yolanda, Universitat Politècnica de València. Escuela Politécnica Superior de Gandia - Escola Politècnica Superior de Gandia, Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica, Castells Ramón, Francisco Sales, and Vives Gilabert, Yolanda

Abstract

En este laboratorio virtual se muestra la forma de onda en cada etapa de un rectificador de media onda con filtro C y estabilizador Zener: - Señal de entrada - Señal rectificada - Señal en el condensador - Señal estabilizada a la salida

Published
2020

50. Rectificador de media onda con filtro C y carga resistiva

Author

Universitat Politècnica de València. Escuela Politécnica Superior de Gandia - Escola Politècnica Superior de Gandia, Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica, Castells Ramón, Francisco Sales, Vives Gilabert, Yolanda, Universitat Politècnica de València. Escuela Politécnica Superior de Gandia - Escola Politècnica Superior de Gandia, Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica, Castells Ramón, Francisco Sales, and Vives Gilabert, Yolanda

Abstract

En este laboratorio virtual se muestra la forma de onda en cada etapa de un rectificador de media onda con filtro C y carga resistiva: - Señal de entrada - Señal rectificada - Salida filtrada

Published
2020

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