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44 results on '"Canales-Rodriguez, Erick J."'

1. A diffusion MRI model for random walks confined on cylindrical surfaces: Towards non-invasive quantification of myelin sheath radius

Author

Canales-Rodríguez, Erick J, Tax, Chantal M. W., Fischi-Gomez, Elda, Jones, Derek K., Thiran, Jean-Philippe, and Rafael-Patiño, Jonathan

Subjects
Physics - Medical Physics
Abstract

Quantifying the myelin sheath radius of myelinated axons in vivo is important for understanding, diagnosing, and monitoring various neurological disorders. Despite advancements in diffusion MRI (dMRI) microstructure techniques, models specifically designed to estimate myelin sheath radii remain unavailable. In this proof-of-concept theoretical study, we present two novel dMRI models that characterize the signal from water diffusion confined to cylindrical surfaces, approximating myelin water diffusion. We derive their spherical mean signals, which conveniently eliminate fiber orientation and dispersion effects. These models are further extended to account for multiple concentric cylinders, mimicking the layered structure of myelin. Additionally, we introduce a method to convert histological distributions of axonal inner radii from the literature into myelin sheath radius distributions and derive analytical expressions to estimate the effective myelin sheath radius expected from these distributions. Monte Carlo (MC) simulations conducted in cylindrical and spiral geometries validate the models, demonstrating agreement with analytical predictions across various diffusion regimes and significant correlations between the effective radii estimated from the histological distributions and the effective radius obtained by fitting the resulting dMRI signal to a single-cylinder model. These models may be integrated into existing multi-compartment dMRI techniques, opening the door to non-invasive, in vivo assessments of myelin sheath radii in MRI scanners equipped with strong diffusion gradients that enable measurements with short echo times. Further work is required to validate the technique with real dMRI data., Comment: 55 pages, 7 figures, 1 table, manuscript under review

Published
2024

2. Pore size estimation in axon-mimicking microfibres with diffusion-relaxation MRI

Author

Canales-Rodríguez, Erick J., Pizzolato, Marco, Zhou, Feng-Lei, Barakovic, Muhamed, Thiran, Jean-Philippe, Jones, Derek K., Parker, Geoffrey J. M., and Dyrby, Tim B.

Subjects
Physics - Medical Physics
Abstract

Purpose: This study aims to evaluate two distinct approaches for fibre radius estimation using diffusion-relaxation MRI data acquired in biomimetic microfibre phantoms that mimic hollow axons. The methods considered are the spherical mean power-law approach and a T2-based pore size estimation technique. Theory and Methods: A general diffusion-relaxation theoretical model for the spherical mean signal from water molecules within a distribution of cylinders with varying radii was introduced, encompassing the evaluated models as particular cases. Additionally, a new numerical approach was presented for estimating effective radii (i.e., MRI-visible mean radii) from the ground truth radii distributions, not reliant on previous theoretical approximations and adaptable to various acquisition sequences. The ground truth radii were obtained from Scanning Electron Microscope images. Results: Both methods show a linear relationship between effective radii estimated from MRI data and ground-truth radii distributions, though some discrepancies were observed. The spherical mean power-law method overestimated fibre radii. Conversely, the T2-based method exhibited higher sensitivity to smaller fibre radii but faced limitations in accurately estimating the radius in one particular phantom, possibly due to material-specific relaxation changes. Conclusion: The study demonstrates the feasibility of both techniques to predict pore sizes of hollow microfibres. The T2-based technique, unlike the spherical mean power-law method, does not demand ultra-high diffusion gradients but requires calibration with known radius distributions. This research contributes to the ongoing development and evaluation of neuroimaging techniques for fibre radius estimation, highlights the advantages and limitations of both methods and provides datasets for reproducible research., Comment: 37 pages, 8 figures. Accepted in Magnetic Resonance in Medicine, Dec, 2023

Published
2023

3. CACTUS: A Computational Framework for Generating Realistic White Matter Microstructure Substrates

Author

Villarreal-Haro, Juan Luis, Gardier, Remy, Canales-Rodriguez, Erick J, Gomez, Elda Fischi, Girard, Gabriel, Thiran, Jean-Philippe, and Rafael-Patino, Jonathan

Subjects
Computer Science - Computational Engineering, Finance, and Science
Abstract

Monte-Carlo diffusion simulations are a powerful tool for validating tissue microstructure models by generating synthetic diffusion-weighted magnetic resonance images (DW-MRI) in controlled environments. This is fundamental for understanding the link between micrometre-scale tissue properties and DW-MRI signals measured at the millimetre-scale, optimising acquisition protocols to target microstructure properties of interest, and exploring the robustness and accuracy of estimation methods. However, accurate simulations require substrates that reflect the main microstructural features of the studied tissue. To address this challenge, we introduce a novel computational workflow, CACTUS (Computational Axonal Configurator for Tailored and Ultradense Substrates), for generating synthetic white matter substrates. Our approach allows constructing substrates with higher packing density than existing methods, up to 95 % intra-axonal volume fraction, and larger voxel sizes of up to (500um) 3 with rich fibre complexity. CACTUS generates bundles with angular dispersion, bundle crossings, and variations along the fibres of their inner and outer radii and g-ratio. We achieve this by introducing a novel global cost function and a fibre radial growth approach that allows substrates to match predefined targeted characteristics and mirror those reported in histological studies. CACTUS improves the development of complex synthetic substrates, paving the way for future applications in microstructure imaging., Comment: 21 pages, 7 figures

Published
2023

4. Estimating axon radius using diffusion-relaxation MRI: calibrating a surface-based relaxation model with histology

Author

Barakovic, Muhamed, Pizzolato, Marco, Tax, Chantal M. W., Rudrapatna, Umesh, Magon, Stefano, Dyrby, Tim B., Granziera, Cristina, Thiran, Jean-Philippe, Jones, Derek K., and Canales-Rodríguez, Erick J.

Subjects
Physics - Medical Physics, Physics - Biological Physics, Quantitative Biology - Cell Behavior
Abstract

Axon radius is a potential biomarker for brain diseases and a crucial tissue microstructure parameter that determines the speed of action potentials. Diffusion MRI (dMRI) allows non-invasive estimation of axon radius, but accurately estimating the radius of axons in the human brain is challenging. Most axons in the brain have a radius below one micrometer, which falls below the sensitivity limit of dMRI signals even when using the most advanced human MRI scanners. Therefore, new MRI methods that are sensitive to small axon radii are needed. In this proof-of-concept investigation, we examine whether a surface-based axonal relaxation process could mediate a relationship between intra-axonal T2 and T1 times and inner axon radius, as measured using postmortem histology. A unique in vivo human diffusion-T1-T2 relaxation dataset was acquired on a 3T MRI scanner with ultra-strong diffusion gradients, using a strong diffusion-weighting (i.e., b = 6,000 s/mm$^2$) and multiple inversion and echo times. A second reduced diffusion-T2 dataset was collected at various echo times to evaluate the model further. The intra-axonal relaxation times were estimated by fitting a diffusion-relaxation model to the orientation-averaged spherical mean signals. Our analysis revealed that the proposed surface-based relaxation model effectively explains the relationship between the estimated relaxation times and the histological axon radius measured in various corpus callosum regions. Using these histological values, we developed a novel calibration approach to predict axon radius in other areas of the corpus callosum. Notably, the predicted radii and those determined from histological measurements were in close agreement., Comment: 47 pages, 10 figures

Published
2023
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5. Cellular EXchange Imaging (CEXI): Evaluation of a diffusion model including water exchange in cells using numerical phantoms of permeable spheres

Author

Gardier, Rémy, Haro, Juan Luis Villarreal, Canales-Rodriguez, Erick J., Jelescu, Ileana O., Girard, Gabriel, Rafael-Patino, Jonathan, and Thiran, Jean-Philippe

Subjects
Electrical Engineering and Systems Science - Signal Processing, Physics - Medical Physics
Abstract

Purpose: Biophysical models of diffusion MRI have been developed to characterize microstructure in various tissues, but existing models are not suitable for tissue composed of permeable spherical cells. In this study we introduce Cellular Exchange Imaging (CEXI), a model tailored for permeable spherical cells, and compares its performance to a related Ball \& Sphere (BS) model that neglects permeability. Methods: We generated DW-MRI signals using Monte-Carlo simulations with a PGSE sequence in numerical substrates made of spherical cells and their extracellular space for a range of membrane permeability. From these signals, the properties of the substrates were inferred using both BS and CEXI models. Results: CEXI outperformed the impermeable model by providing more stable estimates cell size and intracellular volume fraction that were diffusion time-independent. Notably, CEXI accurately estimated the exchange time for low to moderate permeability levels previously reported in other studies ($\kappa<25\mu m/s$). However, in highly permeable substrates ($\kappa=50\mu m/s$), the estimated parameters were less stable, particularly the diffusion coefficients. Conclusion: This study highlights the importance of modeling the exchange time to accurately quantify microstructure properties in permeable cellular substrates. Future studies should evaluate CEXI in clinical applications such as lymph nodes, investigate exchange time as a potential biomarker of tumor severity, and develop more appropriate tissue models that account for anisotropic diffusion and highly permeable membranes., Comment: 7 figures, 2 tables, 21 pages, under review

Published
2023
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6. Microstructure estimation from diffusion-MRI: Compartmentalized models in permeable cellular tissue

Author

Gardier, Rémy, Haro, Juan Luis Villarreal, Canales-Rodrıguez, Erick J, Jelescu, Ileana O., Girard, Gabriel, Rafael-Patino, Jonathan, and Thiran, Jean-Philippe

Subjects
Electrical Engineering and Systems Science - Signal Processing, Physics - Medical Physics
Abstract

Diffusion-weighted magnetic resonance imaging (DW-MRI) is used to characterize brain tissue microstructure employing tissue-specific biophysical models. A current limitation, however, is that most of the proposed models are based on the assumption of negligible water exchange between the intra- and extracellular compartments, which might not be valid in various brain tissues, including unmyelinated axons, gray matter, and tumors. The purpose of this work is to quantify the effect of membrane permeability on the estimates of two popular models neglecting exchange, and compare their performance with a model including exchange. To this aim, DW-MRI experiments were performed in controlled environments with Monte-Carlo simulations. The DW-MRI signals were generated in numerical substrates mimicking biological tissue made of spherical cells with permeable membranes like cancerous tissue or the brain gray matter. From these signals, the substrates properties were estimated using SANDI and VERDICT, the two compartment-based models neglecting exchange, and CEXI, a new model which includes exchange. Our results show that, in cellular permeable tissue, the model with exchange outperformed models without exchange in the estimation of the tissue properties by providing more stable estimates of cell size, intracellular volume fraction and extracellular diffusion coefficient. Moreover, the model with exchange estimated accurately the exchange time in the range of permeability reported for cellular tissue. Finally, the simulations performed in this work showed that the exchange between the intracellular and the extracellular space cannot be neglected in permeable tissue with a conventional PGSE sequence, to obtain accurate estimates. Consequently, existing compartmentalized models of impermeable tissue cannot be used for microstructure estimation of cellular permeable tissue., Comment: 29 pages, 8 figures, 3 tables, submitted

Published
2022

8. Multi-compartment diffusion MRI, T2 relaxometry and myelin water imaging as neuroimaging descriptors for anomalous tissue detection

Author

Fischi-Gomez, Elda, Rafael-Patino, Jonathan, Pizzolato, Marco, Piredda, Gian Franco, Hilbert, Tom, Kober, Tobias, Canales-Rodriguez, Erick J., and Thiran, Jean-Philippe

Subjects
Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Multiple sclerosis (MS) is an inflammatory and neurodegenerative disease characterized by diffuse and focal areas of tissue loss. Conventional MRI techniques such as T1-weighted and T2-weighted scans are generally used in the diagnosis and prognosis of the disease. Yet, these methods are limited by the lack of specificity between lesions, their perilesional area and non-lesional tissue. Alternative MRI techniques exhibit a higher level of sensitivity to focal and diffuse MS pathology than conventional MRI acquisitions. However, they still suffer from limited specificity when considered alone. In this work, we have combined tissue microstructure information derived from multicompartment diffusion MRI and T2 relaxometry models to explore the voxel-based prediction power of a machine learning model in a cohort of MS patients and healthy controls. Our results show that the combination of multi-modal features, together with a boosting enhanced decision-tree based classifier, which combines a set of weak classifiers to form a strong classifier via a voting mechanism, is able to utilise the complementary information for the classification of abnormal tissue., Comment: Accepted at ISBI2021

Published
2021

9. 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
Biological Psychology, Biomedical and Clinical Sciences, Clinical Sciences, Psychology, Major Depressive Disorder, Clinical Research, Mental Illness, Depression, Biomedical Imaging, Serious Mental Illness, Neurosciences, Behavioral and Social Science, Brain Disorders, Mental Health, Mental health, Adolescent, Adult, Aged, Aging, 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, Clinical sciences, Biological psychology, Clinical and health psychology
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

10. Tractography passes the test: Results from the diffusion-simulated connectivity (disco) challenge

Author

Girard, Gabriel, Rafael-Patiño, Jonathan, Truffet, Raphaël, Aydogan, Dogu Baran, Adluru, Nagesh, Nair, Veena A., Prabhakaran, Vivek, Bendlin, Barbara B., Alexander, Andrew L., Bosticardo, Sara, Gabusi, Ilaria, Ocampo-Pineda, Mario, Battocchio, Matteo, Piskorova, Zuzana, Bontempi, Pietro, Schiavi, Simona, Daducci, Alessandro, Stafiej, Aleksandra, Ciupek, Dominika, Bogusz, Fabian, Pieciak, Tomasz, Frigo, Matteo, Sedlar, Sara, Deslauriers-Gauthier, Samuel, Kojčić, Ivana, Zucchelli, Mauro, Laghrissi, Hiba, Ji, Yang, Deriche, Rachid, Schilling, Kurt G, Landman, Bennett A., Cacciola, Alberto, Basile, Gianpaolo Antonio, Bertino, Salvatore, Newlin, Nancy, Kanakaraj, Praitayini, Rheault, Francois, Filipiak, Patryk, Shepherd, Timothy M., Lin, Ying-Chia, Placantonakis, Dimitris G., Boada, Fernando E., Baete, Steven H., Hernández-Gutiérrez, Erick, Ramírez-Manzanares, Alonso, Coronado-Leija, Ricardo, Stack-Sánchez, Pablo, Concha, Luis, Descoteaux, Maxime, Mansour L．, Sina, Seguin, Caio, Zalesky, Andrew, Marshall, Kenji, Canales-Rodríguez, Erick J., Wu, Ye, Ahmad, Sahar, Yap, Pew-Thian, Théberge, Antoine, Gagnon, Florence, Massi, Frédéric, Fischi-Gomez, Elda, Gardier, Rémy, Haro, Juan Luis Villarreal, Pizzolato, Marco, Caruyer, Emmanuel, and Thiran, Jean-Philippe

Published
2023
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11. Efficient sampling and robust 3D diffusion magnetic resonance imaging signal reconstruction

Author

Bates, Alice P., Khalid, Zubair, McEwen, Jason D., Kennedy, Rodney A., Daducci, Alessandro, and Canales-Rodríguez, Erick J.

Subjects
Electrical Engineering and Systems Science - Signal Processing
Abstract

This paper presents novel single and multi-shell sampling schemes for diffusion MRI. In diffusion MRI, it is paramount that the number of samples is as small as possible in order that scan times are practical in a clinical setting. The proposed schemes use an efficient number of measurements in that the number of samples is equal to the degrees of freedom in the orthonormal bases used for reconstruction. Novel reconstruction algorithms based on smaller subsystems of linear equations, as compared to the standard regularized least-squares method, are developed for both single and multi-shells sampling schemes. The smaller matrices used in these novel reconstruction algorithms are designed to be well-conditioned, leading to improved reconstruction accuracy. Accurate and robust reconstruction is also achieved through incorporation of regularization into the novel reconstruction algorithms and using a Rician or non-central Chi noise model. We quantitatively validate our single and multi-shell schemes against standard least-squares reconstruction methods to show that they enable more accurate reconstruction when the number of samples is equal to the degrees of freedom in the basis. Human brain data is also used to qualitatively evaluate reconstruction, Comment: 19 pages, with 6 pages supplementary material attached at the end, submitted to PLOS ONE

Published
2018

12. Evaluating reproducibility and subject-specificity of microstructure-informed connectivity

Author

Koch, Philipp J., Girard, Gabriel, Brügger, Julia, Cadic-Melchior, Andéol G., Beanato, Elena, Park, Chang-Hyun, Morishita, Takuya, Wessel, Maximilian J., Pizzolato, Marco, Canales-Rodríguez, Erick J., Fischi-Gomez, Elda, Schiavi, Simona, Daducci, Alessandro, Piredda, Gian Franco, Hilbert, Tom, Kober, Tobias, Thiran, Jean-Philippe, and Hummel, Friedhelm C.

Published
2022
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13. Insights from the IronTract challenge: Optimal methods for mapping brain pathways from multi-shell diffusion MRI

Author

Maffei, Chiara, Girard, Gabriel, Schilling, Kurt G., Aydogan, Dogu Baran, Adluru, Nagesh, Zhylka, Andrey, Wu, Ye, Mancini, Matteo, Hamamci, Andac, Sarica, Alessia, Teillac, Achille, Baete, Steven H., Karimi, Davood, Yeh, Fang-Cheng, Yildiz, Mert E., Gholipour, Ali, Bihan-Poudec, Yann, Hiba, Bassem, Quattrone, Andrea, Quattrone, Aldo, Boshkovski, Tommy, Stikov, Nikola, Yap, Pew-Thian, de Luca, Alberto, Pluim, Josien, Leemans, Alexander, Prabhakaran, Vivek, Bendlin, Barbara B., Alexander, Andrew L., Landman, Bennett A., Canales-Rodríguez, Erick J., Barakovic, Muhamed, Rafael-Patino, Jonathan, Yu, Thomas, Rensonnet, Gaëtan, Schiavi, Simona, Daducci, Alessandro, Pizzolato, Marco, Fischi-Gomez, Elda, Thiran, Jean-Philippe, Dai, George, Grisot, Giorgia, Lazovski, Nikola, Puch, Santi, Ramos, Marc, Rodrigues, Paulo, Prčkovska, Vesna, Jones, Robert, Lehman, Julia, Haber, Suzanne N., and Yendiki, Anastasia

Published
2022
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14. Virtual Ontogeny of Cortical Growth Preceding Mental Illness

Author

Patel, Yash, Shin, Jean, Abé, Christoph, Agartz, Ingrid, Alloza, Clara, Alnæs, Dag, Ambrogi, Sonia, Antonucci, Linda A., Arango, Celso, Arolt, Volker, Auzias, Guillaume, Ayesa-Arriola, Rosa, Banaj, Nerisa, Banaschewski, Tobias, Bandeira, Cibele, Başgöze, Zeynep, Cupertino, Renata Basso, Bau, Claiton H.D., Bauer, Jochen, Baumeister, Sarah, Bernardoni, Fabio, Bertolino, Alessandro, Bonnin, Caterina del Mar, Brandeis, Daniel, Brem, Silvia, Bruggemann, Jason, Bülow, Robin, Bustillo, Juan R., Calderoni, Sara, Calvo, Rosa, Canales-Rodríguez, Erick J., Cannon, Dara M., Carmona, Susanna, Carr, Vaughan J., Catts, Stanley V., Chenji, Sneha, Chew, Qian Hui, Coghill, David, Connolly, Colm G., Conzelmann, Annette, Craven, Alexander R., Crespo-Facorro, Benedicto, Cullen, Kathryn, Dahl, Andreas, Dannlowski, Udo, Davey, Christopher G., Deruelle, Christine, Díaz-Caneja, Covadonga M., Dohm, Katharina, Ehrlich, Stefan, Epstein, Jeffery, Erwin-Grabner, Tracy, Eyler, Lisa T., Fedor, Jennifer, Fitzgerald, Jacqueline, Foran, William, Ford, Judith M., Fortea, Lydia, Fuentes-Claramonte, Paola, Fullerton, Janice, Furlong, Lisa, Gallagher, Louise, Gao, Bingchen, Gao, Si, Goikolea, Jose M., Gotlib, Ian, Goya-Maldonado, Roberto, Grabe, Hans J., Green, Melissa, Grevet, Eugenio H., Groenewold, Nynke A., Grotegerd, Dominik, Gruber, Oliver, Haavik, Jan, Hahn, Tim, Harrison, Ben J., Heindel, Walter, Henskens, Frans, Heslenfeld, Dirk J., Hilland, Eva, Hoekstra, Pieter J., Hohmann, Sarah, Holz, Nathalie, Howells, Fleur M., Ipser, Jonathan C., Jahanshad, Neda, Jakobi, Babette, Jansen, Andreas, Janssen, Joost, Jonassen, Rune, Kaiser, Anna, Kaleda, Vasiliy, Karantonis, James, King, Joseph A., Kircher, Tilo, Kochunov, Peter, Koopowitz, Sheri-Michelle, Landén, Mikael, Landrø, Nils Inge, Lawrie, Stephen, Lebedeva, Irina, Luna, Beatriz, Lundervold, Astri J., MacMaster, Frank P., Maglanoc, Luigi A., Mathalon, Daniel H., McDonald, Colm, McIntosh, Andrew, Meinert, Susanne, Michie, Patricia T., Mitchell, Philip, Moreno-Alcázar, Ana, Mowry, Bryan, Muratori, Filippo, Nabulsi, Leila, Nenadić, Igor, O'Gorman Tuura, Ruth, Oosterlaan, Jaap, Overs, Bronwyn, Pantelis, Christos, Parellada, Mara, Pariente, Jose C., Pauli, Paul, Pergola, Giulio, Piarulli, Francesco Maria, Picon, Felipe, Piras, Fabrizio, Pomarol-Clotet, Edith, Pretus, Clara, Quidé, Yann, Radua, Joaquim, Ramos-Quiroga, J. Antoni, Rasser, Paul E., Reif, Andreas, Retico, Alessandra, Roberts, Gloria, Rossell, Susan, Rovaris, Diego Luiz, Rubia, Katya, Sacchet, Matthew D., Salavert, Josep, Salvador, Raymond, Sarró, Salvador, Sawa, Akira, Schall, Ulrich, Scott, Rodney, Selvaggi, Pierluigi, Silk, Tim, Sim, Kang, Skoch, Antonin, Spalletta, Gianfranco, Spaniel, Filip, Stein, Dan J., Steinsträter, Olaf, Stolicyn, Aleks, Takayanagi, Yoichiro, Tamm, Leanne, Tavares, Maria, Teumer, Alexander, Thiel, Katharina, Thomopoulos, Sophia I., Tomecek, David, Tomyshev, Alexander S., Tordesillas-Gutiérrez, Diana, Tosetti, Michela, Uhlmann, Anne, Van Rheenen, Tamsyn, Vazquez-Bourgón, Javier, Vernooij, Meike W., Vieta, Eduard, Vilarroya, Oscar, Weickert, Cynthia, Weickert, Thomas, Westlye, Lars T., Whalley, Heather, Willinger, David, Winter, Alexandra, Wittfeld, Katharina, Yang, Tony T., Yoncheva, Yuliya, Zijlmans, Jendé L., Hoogman, Martine, Franke, Barbara, van Rooij, Daan, Buitelaar, Jan, Ching, Christopher R.K., Andreassen, Ole A., Pozzi, Elena, Veltman, Dick, Schmaal, Lianne, van Erp, Theo G.M., Turner, Jessica, Castellanos, F. Xavier, Pausova, Zdenka, Thompson, Paul, and Paus, Tomas

Published
2022
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15. Longitudinal Structural Brain Changes in Bipolar Disorder: A Multicenter Neuroimaging Study of 1232 Individuals by the ENIGMA Bipolar Disorder Working Group

Author

Abé, Christoph, Ching, Christopher R.K., Liberg, Benny, Lebedev, Alexander V., Agartz, Ingrid, Akudjedu, Theophilus N., Alda, Martin, Alnæs, Dag, Alonso-Lana, Silvia, Benedetti, Francesco, Berk, Michael, Bøen, Erlend, Bonnin, Caterina del Mar, Breuer, Fabian, Brosch, Katharina, Brouwer, Rachel M., Canales-Rodríguez, Erick J., Cannon, Dara M., Chye, Yann, Dahl, Andreas, Dandash, Orwa, Dannlowski, Udo, Dohm, Katharina, Elvsåshagen, Torbjørn, Fisch, Lukas, Fullerton, Janice M., Goikolea, Jose M., Grotegerd, Dominik, Haatveit, Beathe, Hahn, Tim, Hajek, Tomas, Heindel, Walter, Ingvar, Martin, Sim, Kang, Kircher, Tilo T.J., Lenroot, Rhoshel K., Malt, Ulrik F., McDonald, Colm, McWhinney, Sean R., Melle, Ingrid, Meller, Tina, Melloni, Elisa M.T., Mitchell, Philip B., Nabulsi, Leila, Nenadić, Igor, Opel, Nils, Overs, Bronwyn J., Panicalli, Francesco, Pfarr, Julia-Katharina, Poletti, Sara, Pomarol-Clotet, Edith, Radua, Joaquim, Repple, Jonathan, Ringwald, Kai G., Roberts, Gloria, Rodriguez-Cano, Elena, Salvador, Raymond, Sarink, Kelvin, Sarró, Salvador, Schmitt, Simon, Stein, Frederike, Suo, Chao, Thomopoulos, Sophia I., Tronchin, Giulia, Vieta, Eduard, Westlye, Lars T., White, Adam G., Yatham, Lakshmi N., Zak, Nathalia, Thompson, Paul M., Andreassen, Ole A., and Landén, Mikael

Published
2022
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16. Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?

Author

Schilling, Kurt G., Rheault, François, Petit, Laurent, Hansen, Colin B., Nath, Vishwesh, Yeh, Fang-Cheng, Girard, Gabriel, Barakovic, Muhamed, Rafael-Patino, Jonathan, Yu, Thomas, Fischi-Gomez, Elda, Pizzolato, Marco, Ocampo-Pineda, Mario, Schiavi, Simona, Canales-Rodríguez, Erick J., Daducci, Alessandro, Granziera, Cristina, Innocenti, Giorgio, Thiran, Jean-Philippe, Mancini, Laura, Wastling, Stephen, Cocozza, Sirio, Petracca, Maria, Pontillo, Giuseppe, Mancini, Matteo, Vos, Sjoerd B., Vakharia, Vejay N., Duncan, John S., Melero, Helena, Manzanedo, Lidia, Sanz-Morales, Emilio, Peña-Melián, Ángel, Calamante, Fernando, Attyé, Arnaud, Cabeen, Ryan P., Korobova, Laura, Toga, Arthur W., Vijayakumari, Anupa Ambili, Parker, Drew, Verma, Ragini, Radwan, Ahmed, Sunaert, Stefan, Emsell, Louise, De Luca, Alberto, Leemans, Alexander, Bajada, Claude J., Haroon, Hamied, Azadbakht, Hojjatollah, Chamberland, Maxime, Genc, Sila, Tax, Chantal M.W., Yeh, Ping-Hong, Srikanchana, Rujirutana, Mcknight, Colin D., Yang, Joseph Yuan-Mou, Chen, Jian, Kelly, Claire E., Yeh, Chun-Hung, Cochereau, Jerome, Maller, Jerome J., Welton, Thomas, Almairac, Fabien, Seunarine, Kiran K, Clark, Chris A., Zhang, Fan, Makris, Nikos, Golby, Alexandra, Rathi, Yogesh, O'Donnell, Lauren J., Xia, Yihao, Aydogan, Dogu Baran, Shi, Yonggang, Fernandes, Francisco Guerreiro, Raemaekers, Mathijs, Warrington, Shaun, Michielse, Stijn, Ramírez-Manzanares, Alonso, Concha, Luis, Aranda, Ramón, Meraz, Mariano Rivera, Lerma-Usabiaga, Garikoitz, Roitman, Lucas, Fekonja, Lucius S., Calarco, Navona, Joseph, Michael, Nakua, Hajer, Voineskos, Aristotle N., Karan, Philippe, Grenier, Gabrielle, Legarreta, Jon Haitz, Adluru, Nagesh, Nair, Veena A., Prabhakaran, Vivek, Alexander, Andrew L., Kamagata, Koji, Saito, Yuya, Uchida, Wataru, Andica, Christina, Abe, Masahiro, Bayrak, Roza G., Wheeler-Kingshott, Claudia A.M. Gandini, D'Angelo, Egidio, Palesi, Fulvia, Savini, Giovanni, Rolandi, Nicolò, Guevara, Pamela, Houenou, Josselin, López-López, Narciso, Mangin, Jean-François, Poupon, Cyril, Román, Claudio, Vázquez, Andrea, Maffei, Chiara, Arantes, Mavilde, Andrade, José Paulo, Silva, Susana Maria, Calhoun, Vince D., Caverzasi, Eduardo, Sacco, Simone, Lauricella, Michael, Pestilli, Franco, Bullock, Daniel, Zhan, Yang, Brignoni-Perez, Edith, Lebel, Catherine, Reynolds, Jess E, Nestrasil, Igor, Labounek, René, Lenglet, Christophe, Paulson, Amy, Aulicka, Stefania, Heilbronner, Sarah R., Heuer, Katja, Chandio, Bramsh Qamar, Guaje, Javier, Tang, Wei, Garyfallidis, Eleftherios, Raja, Rajikha, Anderson, Adam W., Landman, Bennett A., and Descoteaux, Maxime

Published
2021
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18. DWI Simulation-Assisted Machine Learning Models for Microstructure Estimation

Author

Rafael-Patino, Jonathan, Yu, Thomas, Delvigne, Victor, Barakovic, Muhamed, Pizzolato, Marco, Girard, Gabriel, Jones, Derek K., Canales-Rodríguez, Erick J., Thiran, Jean-Philippe, Hege, Hans-Christian, Series Editor, Hoffman, David, Series Editor, Johnson, Christopher R., Series Editor, Polthier, Konrad, Series Editor, Bonet-Carne, Elisenda, editor, Hutter, Jana, editor, Palombo, Marco, editor, Pizzolato, Marco, editor, Sepehrband, Farshid, editor, and Zhang, Fan, editor

Published
2020
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19. Spherical deconvolution of multichannel diffusion MRI data with non-Gaussian noise models and spatial regularization

Author

Canales-Rodríguez, Erick J., Daducci, Alessandro, Sotiropoulos, Stamatios N., Caruyer, Emmanuel, Aja-Fernández, Santiago, Radua, Joaquim, Mendizabal, Jesús María Yurramendi, Iturria-Medina, Yasser, Melie-García, Lester, Alemán-Gómez, Yasser, Thiran, Jean-Philippe, Sarró, Salvador, Pomarol-Clotet, Edith, and Salvador, Raymond

Subjects
Physics - Medical Physics
Abstract

Spherical deconvolution (SD) methods are widely used to estimate the intra-voxel white-matter fiber orientations from diffusion MRI data. However, while some of these methods assume a zero-mean Gaussian distribution for the underlying noise, its real distribution is known to be non-Gaussian and to depend on the methodology used to combine multichannel signals. Indeed, the two prevailing methods for multichannel signal combination lead to Rician and noncentral Chi noise distributions. Here we develop a Robust and Unbiased Model-BAsed Spherical Deconvolution (RUMBA-SD) technique, intended to deal with realistic MRI noise, based on a Richardson-Lucy (RL) algorithm adapted to Rician and noncentral Chi likelihood models. To quantify the benefits of using proper noise models, RUMBA-SD was compared with dRL-SD, a well-established method based on the RL algorithm for Gaussian noise. Another aim of the study was to quantify the impact of including a total variation (TV) spatial regularization term in the estimation framework. To do this, we developed TV spatially-regularized versions of both RUMBA-SD and dRL-SD algorithms. The evaluation was performed by comparing various quality metrics on 132 three-dimensional synthetic phantoms involving different inter-fiber angles and volume fractions, which were contaminated with noise mimicking patterns generated by data processing in multichannel scanners. The results demonstrate that the inclusion of proper likelihood models leads to an increased ability to resolve fiber crossings with smaller inter-fiber angles and to better detect non-dominant fibers. The inclusion of TV regularization dramatically improved the resolution power of both techniques. The above findings were also verified in brain data.

Published
2014
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20. Structural abnormality in schizophrenia versus bipolar disorder: A whole brain cortical thickness, surface area, volume and gyrification analyses

Author

Madre, Mercè, Canales-Rodríguez, Erick J., Fuentes-Claramonte, Paola, Alonso-Lana, Silvia, Salgado-Pineda, Pilar, Guerrero-Pedraza, Amalia, Moro, Noemí, Bosque, Clara, Gomar, Jesús J., Ortíz-Gil, Jordi, Goikolea, José M., Bonnin, Caterina M, Vieta, Eduard, Sarró, Salvador, Maristany, Teresa, McKenna, Peter J., Salvador, Raymond, and Pomarol-Clotet, Edith

Published
2020
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21. Face-brain correlates as potential sex-specific biomarkers for schizophrenia and bipolar disorder.

Author

Hostalet, Noemí, primary, Fatjó-Vilas, Mar, additional, González, Alejandro, additional, Gonzàlez-Colom, Rubèn, additional, Salgado-Pineda, Pilar, additional, Canales-Rodriguez, Erick J, additional, Aguirre, Candibel, additional, Guerrero, Amalia, additional, Llanos-Torres, Maria, additional, Salvador, Raymond, additional, Pomarol-Clotet, Edith, additional, Sevillano, Xavier, additional, and Martinez-Abadias, Neus, additional

Published
2024
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22. Limits to anatomical accuracy of diffusion tractography using modern approaches

Author

Schilling, Kurt G., Nath, Vishwesh, Hansen, Colin, Parvathaneni, Prasanna, Blaber, Justin, Gao, Yurui, Neher, Peter, Aydogan, Dogu Baran, Shi, Yonggang, Ocampo-Pineda, Mario, Schiavi, Simona, Daducci, Alessandro, Girard, Gabriel, Barakovic, Muhamed, Rafael-Patino, Jonathan, Romascano, David, Rensonnet, Gaëtan, Pizzolato, Marco, Bates, Alice, Fischi, Elda, Thiran, Jean-Philippe, Canales-Rodríguez, Erick J., Huang, Chao, Zhu, Hongtu, Zhong, Liming, Cabeen, Ryan, Toga, Arthur W., Rheault, Francois, Theaud, Guillaume, Houde, Jean-Christophe, Sidhu, Jasmeen, Chamberland, Maxime, Westin, Carl-Fredrik, Dyrby, Tim B., Verma, Ragini, Rathi, Yogesh, Irfanoglu, M. Okan, Thomas, Cibu, Pierpaoli, Carlo, Descoteaux, Maxime, Anderson, Adam W., and Landman, Bennett A.

Published
2019
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25. Brain morphometry of Dravet Syndrome

Author

Pérez, Alejandro, García-Pentón, Lorna, Canales-Rodríguez, Erick J., Lerma-Usabiaga, Garikoitz, Iturria-Medina, Yasser, Román, Francisco J., Davidson, Doug, Alemán-Gómez, Yasser, Acha, Joana, and Carreiras, Manuel

Published
2014
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26. Greater male than female variability in regional brain structure across the lifespan

Author

Wierenga, Lara M., Doucet, Gaelle E., Dima, Danai, Agartz, Ingrid, Aghajani, Moji, Akudjedu, Theophilus N., Albajes-Eizagirre, Anton, Alnaes, Dag, Alpert, Kathryn, I, Andreassen, Ole A., Anticevic, Alan, Asherson, Philip, Banaschewski, Tobias, Bargallo, Nuria, Baumeister, Sarah, Baur-Streubel, Ramona, Bertolino, Alessandro, Bonvino, Aurora, Boomsma, Dorret, I, Borgwardt, Stefan, Bourque, Josiane, den Braber, Anouk, Brandeis, Daniel, Breier, Alan, Brodaty, Henry, Brouwer, Rachel M., Buitelaar, Jan K., Busatto, Geraldo F., Calhoun, Vince D., Canales-Rodriguez, Erick J., Cannon, Dara M., Caseras, Xavier, Castellanos, Francisco X., Chaim-Avancini, Tiffany M., Ching, Christopher R. K., Clark, Vincent P., Conrod, Patricia J., Conzelmann, Annette, Crivello, Fabrice, Davey, Christopher G., Dickie, Erin W., Ehrlich, Stefan, Van't Ent, Dennis, Fisher, Simon E., Fouche, Jean-Paul, Franke, Barbara, Fuentes-Claramonte, Paola, de Geus, Eco J. C., Di Giorgio, Annabella, Glahn, David C., Gotlib, Ian H., Grabe, Hans J., Gruber, Oliver, Gruner, Patricia, Gur, Raquel E., Gur, Ruben C., Gurholt, Tiril P., de Haan, Lieuwe, Haatveit, Beathe, Harrison, Ben J., Hartman, Catharina A., Hatton, Sean N., Heslenfeld, Dirk J., van den Heuvel, Odile A., Hickie, Ian B., Hoekstra, Pieter J., Hohmann, Sarah, Holmes, Avram J., Hoogman, Martine, Hosten, Norbert, Howells, Fleur M., Pol, Hilleke E. Hulshoff, Huyser, Chaim, Jahanshad, Neda, James, Anthony C., Jiang, Jiyang, Jonsson, Erik G., Joska, John A., Kalnin, Andrew J., Klein, Marieke, Koenders, Laura, Kolskar, Knut K., Kramer, Bernd, Kuntsi, Jonna, Lagopoulos, Jim, Lazaro, Luisa, Lebedeva, Irina S., Lee, Phil H., Lochner, Christine, Machielsen, Marise W. J., Maingault, Sophie, Martin, Nicholas G., Martinez-Zalacain, Ignacio, Mataix-Cols, David, Mazoyer, Bernard, McDonald, Brenna C., McDonald, Colm, McIntosh, Andrew M., McMahon, Katie L., McPhilemy, Genevieve, van der Meer, Dennis, Menchon, Jose M., Naaijen, Jilly, Nyberg, Lars, Oosterlaan, Jaap, Paloyelis, Yannis, Pauli, Paul, Pergola, Giulio, Pomarol-Clotet, Edith, Portella, Maria J., Radua, Joaquim, Reif, Andreas, Richard, Genevieve, Roffman, Joshua L., Rosa, Pedro G. P., Sacchet, Matthew D., Sachdev, Perminder S., Salvador, Raymond, Sarro, Salvador, Satterthwaite, Theodore D., Saykin, Andrew J., Serpa, Mauricio H., Sim, Kang, Simmons, Andrew, Smoller, Jordan W., Sommer, Iris E., Soriano-Mas, Carles, Stein, Dan J., Strike, Lachlan T., Szeszko, Philip R., Temmingh, Henk S., Thomopoulos, Sophia, I, Tomyshev, Alexander S., Trollor, Julian N., Uhlmann, Anne, Veer, Ilya M., Veltman, Dick J., Voineskos, Aristotle, Volzke, Henry, Walter, Henrik, Wang, Lei, Wang, Yang, Weber, Bernd, Wen, Wei, West, John D., Westlye, Lars T., Whalley, Heather C., Williams, Steven C. R., Wittfeld, Katharina, Wolf, Daniel H., Wright, Margaret J., Yoncheva, Yuliya N., Zanetti, Marcus, V, Ziegler, Georg C., de Zubicaray, Greig, I, Thompson, Paul M., Crone, Eveline A., Frangou, Sophia, Tamnes, Christian K., Wierenga, Lara M., Doucet, Gaelle E., Dima, Danai, Agartz, Ingrid, Aghajani, Moji, Akudjedu, Theophilus N., Albajes-Eizagirre, Anton, Alnaes, Dag, Alpert, Kathryn, I, Andreassen, Ole A., Anticevic, Alan, Asherson, Philip, Banaschewski, Tobias, Bargallo, Nuria, Baumeister, Sarah, Baur-Streubel, Ramona, Bertolino, Alessandro, Bonvino, Aurora, Boomsma, Dorret, I, Borgwardt, Stefan, Bourque, Josiane, den Braber, Anouk, Brandeis, Daniel, Breier, Alan, Brodaty, Henry, Brouwer, Rachel M., Buitelaar, Jan K., Busatto, Geraldo F., Calhoun, Vince D., Canales-Rodriguez, Erick J., Cannon, Dara M., Caseras, Xavier, Castellanos, Francisco X., Chaim-Avancini, Tiffany M., Ching, Christopher R. K., Clark, Vincent P., Conrod, Patricia J., Conzelmann, Annette, Crivello, Fabrice, Davey, Christopher G., Dickie, Erin W., Ehrlich, Stefan, Van't Ent, Dennis, Fisher, Simon E., Fouche, Jean-Paul, Franke, Barbara, Fuentes-Claramonte, Paola, de Geus, Eco J. C., Di Giorgio, Annabella, Glahn, David C., Gotlib, Ian H., Grabe, Hans J., Gruber, Oliver, Gruner, Patricia, Gur, Raquel E., Gur, Ruben C., Gurholt, Tiril P., de Haan, Lieuwe, Haatveit, Beathe, Harrison, Ben J., Hartman, Catharina A., Hatton, Sean N., Heslenfeld, Dirk J., van den Heuvel, Odile A., Hickie, Ian B., Hoekstra, Pieter J., Hohmann, Sarah, Holmes, Avram J., Hoogman, Martine, Hosten, Norbert, Howells, Fleur M., Pol, Hilleke E. Hulshoff, Huyser, Chaim, Jahanshad, Neda, James, Anthony C., Jiang, Jiyang, Jonsson, Erik G., Joska, John A., Kalnin, Andrew J., Klein, Marieke, Koenders, Laura, Kolskar, Knut K., Kramer, Bernd, Kuntsi, Jonna, Lagopoulos, Jim, Lazaro, Luisa, Lebedeva, Irina S., Lee, Phil H., Lochner, Christine, Machielsen, Marise W. J., Maingault, Sophie, Martin, Nicholas G., Martinez-Zalacain, Ignacio, Mataix-Cols, David, Mazoyer, Bernard, McDonald, Brenna C., McDonald, Colm, McIntosh, Andrew M., McMahon, Katie L., McPhilemy, Genevieve, van der Meer, Dennis, Menchon, Jose M., Naaijen, Jilly, Nyberg, Lars, Oosterlaan, Jaap, Paloyelis, Yannis, Pauli, Paul, Pergola, Giulio, Pomarol-Clotet, Edith, Portella, Maria J., Radua, Joaquim, Reif, Andreas, Richard, Genevieve, Roffman, Joshua L., Rosa, Pedro G. P., Sacchet, Matthew D., Sachdev, Perminder S., Salvador, Raymond, Sarro, Salvador, Satterthwaite, Theodore D., Saykin, Andrew J., Serpa, Mauricio H., Sim, Kang, Simmons, Andrew, Smoller, Jordan W., Sommer, Iris E., Soriano-Mas, Carles, Stein, Dan J., Strike, Lachlan T., Szeszko, Philip R., Temmingh, Henk S., Thomopoulos, Sophia, I, Tomyshev, Alexander S., Trollor, Julian N., Uhlmann, Anne, Veer, Ilya M., Veltman, Dick J., Voineskos, Aristotle, Volzke, Henry, Walter, Henrik, Wang, Lei, Wang, Yang, Weber, Bernd, Wen, Wei, West, John D., Westlye, Lars T., Whalley, Heather C., Williams, Steven C. R., Wittfeld, Katharina, Wolf, Daniel H., Wright, Margaret J., Yoncheva, Yuliya N., Zanetti, Marcus, V, Ziegler, Georg C., de Zubicaray, Greig, I, Thompson, Paul M., Crone, Eveline A., Frangou, Sophia, and Tamnes, Christian K.

Abstract

For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders.

Published
2022
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27. Cortical thickness across the lifespan : Data from 17,075 healthy individuals aged 3-90 years

Author

Frangou, Sophia, Modabbernia, Amirhossein, Williams, Steven C. R., Papachristou, Efstathios, Doucet, Gaelle E., Agartz, Ingrid, Aghajani, Moji, Akudjedu, Theophilus N., Albajes-Eizagirre, Anton, Alnaes, Dag, Alpert, Kathryn, I, Andersson, Micael, Andreasen, Nancy C., Andreassen, Ole A., Asherson, Philip, Banaschewski, Tobias, Bargallo, Nuria, Baumeister, Sarah, Baur-Streubel, Ramona, Bertolino, Alessandro, Bonvino, Aurora, Boomsma, Dorret, I, Borgwardt, Stefan, Bourque, Josiane, Brandeis, Daniel, Breier, Alan, Brodaty, Henry, Brouwer, Rachel M., Buitelaar, Jan K., Busatto, Geraldo F., Buckner, Randy L., Calhoun, Vincent, Canales-Rodriguez, Erick J., Cannon, Dara M., Caseras, Xavier, Castellanos, Francisco X., Cervenka, Simon, Chaim-Avancini, Tiffany M., Ching, Christopher R. K., Chubar, Victoria, Clark, Vincent P., Conrod, Patricia, Conzelmann, Annette, Crespo-Facorro, Benedicto, Crivello, Fabrice, Crone, Eveline A., Dale, Anders M., Davey, Christopher, de Geus, Eco J. C., de Haan, Lieuwe, de Zubicaray, Greig, I, den Braber, Anouk, Dickie, Erin W., Di Giorgio, Annabella, Doan, Nhat Trung, Dorum, Erlend S., Ehrlich, Stefan, Erk, Susanne, Espeseth, Thomas, Fatouros-Bergman, Helena, Fisher, Simon E., Fouche, Jean-Paul, Franke, Barbara, Frodl, Thomas, Fuentes-Claramonte, Paola, Glahn, David C., Gotlib, Ian H., Grabe, Hans-Joergen, Grimm, Oliver, Groenewold, Nynke A., Grotegerd, Dominik, Gruber, Oliver, Gruner, Patricia, Gur, Rachel E., Gur, Ruben C., Harrison, Ben J., Hartman, Catharine A., Hatton, Sean N., Heinz, Andreas, Heslenfeld, Dirk J., Hibar, Derrek P., Hickie, Ian B., Ho, Beng-Choon, Hoekstra, Pieter J., Hohmann, Sarah, Holmes, Avram J., Hoogman, Martine, Hosten, Norbert, Howells, Fleur M., Pol, Hilleke E. Hulshoff, Huyser, Chaim, Jahanshad, Neda, James, Anthony, Jernigan, Terry L., Jiang, Jiyang, Jonsson, Erik G., Joska, John A., Kahn, Rene, Kalnin, Andrew, Kanai, Ryota, Klein, Marieke, Klyushnik, Tatyana P., Koenders, Laura, Koops, Sanne, Kraemer, Bernd, Kuntsi, Jonna, Lagopoulos, Jim, Lazaro, Luisa, Lebedeva, Irina, Lee, Won Hee, Lesch, Klaus-Peter, Lochner, Christine, Machielsen, Marise W. J., Maingault, Sophie, Martin, Nicholas G., Martinez-Zalacain, Ignacio, Mataix-Cols, David, Mazoyer, Bernard, McDonald, Colm, McDonald, Brenna C., McIntosh, Andrew M., McMahon, Katie L., McPhilemy, Genevieve, Menchon, Jose M., Medland, Sarah E., Meyer-Lindenberg, Andreas, Naaijen, Jilly, Najt, Pablo, Nakao, Tomohiro, Nordvik, Jan E., Nyberg, Lars, Oosterlaan, Jaap, de la Foz, Victor Ortiz-Garcia, Paloyelis, Yannis, Pauli, Paul, Pergola, Giulio, Pomarol-Clotet, Edith, Portella, Maria J., Potkin, Steven G., Radua, Joaquim, Reif, Andreas, Rinker, Daniel A., Roffman, Joshua L., Rosa, Pedro G. P., Sacchet, Matthew D., Sachdev, Perminder S., Salvador, Raymond, Sanchez-Juan, Pascual, Sarro, Salvador, Satterthwaite, Theodore D., Saykin, Andrew J., Serpa, Mauricio H., Schmaal, Lianne, Schnell, Knut, Schumann, Gunter, Sim, Kang, Smoller, Jordan W., Sommer, Iris, Soriano-Mas, Carles, Stein, Dan J., Strike, Lachlan T., Swagerman, Suzanne C., Tamnes, Christian K., Temmingh, Henk S., Thomopoulos, Sophia, I, Tomyshev, Alexander S., Tordesillas-Gutierrez, Diana, Trollor, Julian N., Turner, Jessica A., Uhlmann, Anne, van den Heuvel, Odile A., van den Meer, Dennis, van der Wee, Nic J. A., van Haren, Neeltje E. M., van't Ent, Dennis, van Erp, Theo G. M., Veer, Ilya M., Veltman, Dick J., Voineskos, Aristotle, Voelzke, Henry, Walter, Henrik, Walton, Esther, Wang, Lei, Wang, Yang, Wassink, Thomas H., Weber, Bernd, Wen, Wei, West, John D., Westlye, Lars T., Whalley, Heather, Wierenga, Lara M., Wittfeld, Katharina, Wolf, Daniel H., Worker, Amanda, Wright, Margaret J., Yang, Kun, Yoncheva, Yulyia, Zanetti, Marcus, V, Ziegler, Georg C., Thompson, Paul M., Dima, Danai, Frangou, Sophia, Modabbernia, Amirhossein, Williams, Steven C. R., Papachristou, Efstathios, Doucet, Gaelle E., Agartz, Ingrid, Aghajani, Moji, Akudjedu, Theophilus N., Albajes-Eizagirre, Anton, Alnaes, Dag, Alpert, Kathryn, I, Andersson, Micael, Andreasen, Nancy C., Andreassen, Ole A., Asherson, Philip, Banaschewski, Tobias, Bargallo, Nuria, Baumeister, Sarah, Baur-Streubel, Ramona, Bertolino, Alessandro, Bonvino, Aurora, Boomsma, Dorret, I, Borgwardt, Stefan, Bourque, Josiane, Brandeis, Daniel, Breier, Alan, Brodaty, Henry, Brouwer, Rachel M., Buitelaar, Jan K., Busatto, Geraldo F., Buckner, Randy L., Calhoun, Vincent, Canales-Rodriguez, Erick J., Cannon, Dara M., Caseras, Xavier, Castellanos, Francisco X., Cervenka, Simon, Chaim-Avancini, Tiffany M., Ching, Christopher R. K., Chubar, Victoria, Clark, Vincent P., Conrod, Patricia, Conzelmann, Annette, Crespo-Facorro, Benedicto, Crivello, Fabrice, Crone, Eveline A., Dale, Anders M., Davey, Christopher, de Geus, Eco J. C., de Haan, Lieuwe, de Zubicaray, Greig, I, den Braber, Anouk, Dickie, Erin W., Di Giorgio, Annabella, Doan, Nhat Trung, Dorum, Erlend S., Ehrlich, Stefan, Erk, Susanne, Espeseth, Thomas, Fatouros-Bergman, Helena, Fisher, Simon E., Fouche, Jean-Paul, Franke, Barbara, Frodl, Thomas, Fuentes-Claramonte, Paola, Glahn, David C., Gotlib, Ian H., Grabe, Hans-Joergen, Grimm, Oliver, Groenewold, Nynke A., Grotegerd, Dominik, Gruber, Oliver, Gruner, Patricia, Gur, Rachel E., Gur, Ruben C., Harrison, Ben J., Hartman, Catharine A., Hatton, Sean N., Heinz, Andreas, Heslenfeld, Dirk J., Hibar, Derrek P., Hickie, Ian B., Ho, Beng-Choon, Hoekstra, Pieter J., Hohmann, Sarah, Holmes, Avram J., Hoogman, Martine, Hosten, Norbert, Howells, Fleur M., Pol, Hilleke E. Hulshoff, Huyser, Chaim, Jahanshad, Neda, James, Anthony, Jernigan, Terry L., Jiang, Jiyang, Jonsson, Erik G., Joska, John A., Kahn, Rene, Kalnin, Andrew, Kanai, Ryota, Klein, Marieke, Klyushnik, Tatyana P., Koenders, Laura, Koops, Sanne, Kraemer, Bernd, Kuntsi, Jonna, Lagopoulos, Jim, Lazaro, Luisa, Lebedeva, Irina, Lee, Won Hee, Lesch, Klaus-Peter, Lochner, Christine, Machielsen, Marise W. J., Maingault, Sophie, Martin, Nicholas G., Martinez-Zalacain, Ignacio, Mataix-Cols, David, Mazoyer, Bernard, McDonald, Colm, McDonald, Brenna C., McIntosh, Andrew M., McMahon, Katie L., McPhilemy, Genevieve, Menchon, Jose M., Medland, Sarah E., Meyer-Lindenberg, Andreas, Naaijen, Jilly, Najt, Pablo, Nakao, Tomohiro, Nordvik, Jan E., Nyberg, Lars, Oosterlaan, Jaap, de la Foz, Victor Ortiz-Garcia, Paloyelis, Yannis, Pauli, Paul, Pergola, Giulio, Pomarol-Clotet, Edith, Portella, Maria J., Potkin, Steven G., Radua, Joaquim, Reif, Andreas, Rinker, Daniel A., Roffman, Joshua L., Rosa, Pedro G. P., Sacchet, Matthew D., Sachdev, Perminder S., Salvador, Raymond, Sanchez-Juan, Pascual, Sarro, Salvador, Satterthwaite, Theodore D., Saykin, Andrew J., Serpa, Mauricio H., Schmaal, Lianne, Schnell, Knut, Schumann, Gunter, Sim, Kang, Smoller, Jordan W., Sommer, Iris, Soriano-Mas, Carles, Stein, Dan J., Strike, Lachlan T., Swagerman, Suzanne C., Tamnes, Christian K., Temmingh, Henk S., Thomopoulos, Sophia, I, Tomyshev, Alexander S., Tordesillas-Gutierrez, Diana, Trollor, Julian N., Turner, Jessica A., Uhlmann, Anne, van den Heuvel, Odile A., van den Meer, Dennis, van der Wee, Nic J. A., van Haren, Neeltje E. M., van't Ent, Dennis, van Erp, Theo G. M., Veer, Ilya M., Veltman, Dick J., Voineskos, Aristotle, Voelzke, Henry, Walter, Henrik, Walton, Esther, Wang, Lei, Wang, Yang, Wassink, Thomas H., Weber, Bernd, Wen, Wei, West, John D., Westlye, Lars T., Whalley, Heather, Wierenga, Lara M., Wittfeld, Katharina, Wolf, Daniel H., Worker, Amanda, Wright, Margaret J., Yang, Kun, Yoncheva, Yulyia, Zanetti, Marcus, V, Ziegler, Georg C., Thompson, Paul M., and Dima, Danai

Abstract

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.

Published
2022
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28. Dissociable Cellular and Genetic Mechanisms of Cortical Thinning at Different Life Stages

Author

Modabbernia, Amirhossein, primary, Vidal-Pineiro, Didac, additional, Agartz, Ingrid, additional, Andreassen, Ole A, additional, Ayesa-Arriola, Rosa, additional, Bertolino, Alessandro, additional, Boomsma, Dorret I, additional, Bourque, Josiane, additional, Breier, Alan, additional, Brouwer, Rachel M, additional, Buitelaar, Jan K, additional, Canales-Rodriguez, Erick J, additional, Caseras, Xavier, additional, Conrod, Patricia J, additional, Crespo-Facorro, Benedicto, additional, Crivello, Fabrice, additional, Crone, Eveline A, additional, de Zubicaray, Greig I, additional, Dickie, Erin W, additional, Dima, Danai, additional, Frenzel, Stefan, additional, Fisher, Simon E., additional, Franke, Barbara, additional, Glahn, David C, additional, Grabe, Hans-Jorgen, additional, Grotegerd, Dominik, additional, Gruber, Oliver, additional, Guerrero-Pedraza, Amalia, additional, Gur, Raquel E, additional, Gur, Ruben C, additional, Hartman, Catharina A, additional, Hoekstra, Pieter J, additional, Hulshoff Pol, Hilleke E, additional, Jahanshad, Neda, additional, Jernigan, Terry L, additional, Jiang, Jiyang, additional, Kalnin, Andrew J, additional, Kochan, Nicole A, additional, Mazoyer, Bernard, additional, McDonald, Brenna C, additional, McMahon, Katie L, additional, Nyberg, Lars, additional, Oosterlaan, Jaap, additional, Pomarol-Clotet, Edith, additional, Radua, Joaquim, additional, Sachdev, Perminder S, additional, Satterthwaite, Theodore D, additional, Salvador, Raymond, additional, Sarro, Salvador, additional, Saykin, Andrew J, additional, Schumann, Gunter, additional, Smoller, Jordan W, additional, Sommer, Iris E, additional, Espeseth, Thomas, additional, Thomopoulos, Sophia I, additional, Trollor, Julian N, additional, van 't Ent, Dennis, additional, Voineskos, Aristotle, additional, Wang, Yang, additional, Weber, Bernd, additional, Wen, Wei, additional, Westlye, Lars T, additional, Whalley, Heather C, additional, Williams, Steven CR, additional, Wittfeld, Katharina, additional, Wright, Margaret J, additional, Thompson, Paul M, additional, Paus, Thomas, additional, and Frangou, Sophia, additional

Published
2022
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33. Brain aging in major depressive disorder: Results from the ENIGMA major depressive disorder working group

Author

Han, Laura K M, Dinga, Richard, Hahn, Tim, Ching, Christopher R K, 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 L S, Enneking, Verena, Filimonova, Elena, Frenzel, Stefan, Frodl, Thomas, Fu, Cynthia H Y, 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 G P, 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 R J M, Walter, Henrik, van der Wee, Nic J A, van der Werff, Steven J A, 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, Fullerton, Janice M, Goikolea, Jose M, Haarman, Bartholomeus C M, Hajek, Tomas, Henry, Chantal, Houenou, Josselin, Howells, Fleur M, Ingvar, Martin, Kuplicki, Rayus, Lafer, Beny, Landén, Mikael, Machado-Vieira, Rodrigo, Malt, Ulrik F, McDonald, Colm, Mitchell, Philip B, Nabulsi, Leila, Otaduy, Maria Concepcion Garcia, Overs, Bronwyn J, Polosan, Mircea, Pomarol-Clotet, Edith, Radua, Joaquim, Rive, Maria M, Roberts, Gloria, Ruhe, Henricus G, Salvador, Raymond, Sarró, Salvador, Satterthwaite, Theodore D, Savitz, Jonathan, Schene, Aart H, Schofield, Peter R, Serpa, Mauricio H, Sim, Kang, Soeiro-de-Souza, Marcio Gerhardt, Sutherland, Ashley N, Temmingh, Henk S, Timmons, Garrett M, Uhlmann, Anne, Vieta, Eduard, Wolf, Daniel H, Zanetti, Marcus V, Jahanshad, Neda, Thompson, Paul M, Veltman, Dick J, Penninx, Brenda W J H, Marquand, Andre F, Cole, James H, Schmaal, Lianne, Han, Laura K M, Dinga, Richard, Hahn, Tim, Ching, Christopher R K, 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 L S, Enneking, Verena, Filimonova, Elena, Frenzel, Stefan, Frodl, Thomas, Fu, Cynthia H Y, 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 G P, 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 R J M, Walter, Henrik, van der Wee, Nic J A, van der Werff, Steven J A, 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, Fullerton, Janice M, Goikolea, Jose M, Haarman, Bartholomeus C M, Hajek, Tomas, Henry, Chantal, Houenou, Josselin, Howells, Fleur M, Ingvar, Martin, Kuplicki, Rayus, Lafer, Beny, Landén, Mikael, Machado-Vieira, Rodrigo, Malt, Ulrik F, McDonald, Colm, Mitchell, Philip B, Nabulsi, Leila, Otaduy, Maria Concepcion Garcia, Overs, Bronwyn J, Polosan, Mircea, Pomarol-Clotet, Edith, Radua, Joaquim, Rive, Maria M, Roberts, Gloria, Ruhe, Henricus G, Salvador, Raymond, Sarró, Salvador, Satterthwaite, Theodore D, Savitz, Jonathan, Schene, Aart H, Schofield, Peter R, Serpa, Mauricio H, Sim, Kang, Soeiro-de-Souza, Marcio Gerhardt, Sutherland, Ashley N, Temmingh, Henk S, Timmons, Garrett M, Uhlmann, Anne, Vieta, Eduard, Wolf, Daniel H, Zanetti, Marcus V, Jahanshad, Neda, Thompson, Paul M, Veltman, Dick J, Penninx, Brenda W J H, Marquand, Andre F, Cole, James H, and Schmaal, Lianne

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

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

Author

Han, Laura K. M., primary, Dinga, Richard, additional, Hahn, Tim, additional, Ching, Christopher R. K., additional, Eyler, Lisa T., additional, Aftanas, Lyubomir, additional, Aghajani, Moji, additional, Aleman, André, additional, Baune, Bernhard T., additional, Berger, Klaus, additional, Brak, Ivan, additional, Filho, Geraldo Busatto, additional, Carballedo, Angela, additional, Connolly, Colm G., additional, Couvy-Duchesne, Baptiste, additional, Cullen, Kathryn R., additional, Dannlowski, Udo, additional, Davey, Christopher G., additional, Dima, Danai, additional, Duran, Fabio L. S., additional, Enneking, Verena, additional, Filimonova, Elena, additional, Frenzel, Stefan, additional, Frodl, Thomas, additional, Fu, Cynthia H. Y., additional, Godlewska, Beata R., additional, Gotlib, Ian H., additional, Grabe, Hans J., additional, Groenewold, Nynke A., additional, Grotegerd, Dominik, additional, Gruber, Oliver, additional, Hall, Geoffrey B., additional, Harrison, Ben J., additional, Hatton, Sean N., additional, Hermesdorf, Marco, additional, Hickie, Ian B., additional, Ho, Tiffany C., additional, Hosten, Norbert, additional, Jansen, Andreas, additional, Kähler, Claas, additional, Kircher, Tilo, additional, Klimes-Dougan, Bonnie, additional, Krämer, Bernd, additional, Krug, Axel, additional, Lagopoulos, Jim, additional, Leenings, Ramona, additional, MacMaster, Frank P., additional, MacQueen, Glenda, additional, McIntosh, Andrew, additional, McLellan, Quinn, additional, McMahon, Katie L., additional, Medland, Sarah E., additional, Mueller, Bryon A., additional, Mwangi, Benson, additional, Osipov, Evgeny, additional, Portella, Maria J., additional, Pozzi, Elena, additional, Reneman, Liesbeth, additional, Repple, Jonathan, additional, Rosa, Pedro G. P., additional, Sacchet, Matthew D., additional, Sämann, Philipp G., additional, Schnell, Knut, additional, Schrantee, Anouk, additional, Simulionyte, Egle, additional, Soares, Jair C., additional, Sommer, Jens, additional, Stein, Dan J., additional, Steinsträter, Olaf, additional, Strike, Lachlan T., additional, Thomopoulos, Sophia I., additional, van Tol, Marie-José, additional, Veer, Ilya M., additional, Vermeiren, Robert R. J. M., additional, Walter, Henrik, additional, van der Wee, Nic J. A., additional, van der Werff, Steven J. A., additional, Whalley, Heather, additional, Winter, Nils R., additional, Wittfeld, Katharina, additional, Wright, Margaret J., additional, Wu, Mon-Ju, additional, Völzke, Henry, additional, Yang, Tony T., additional, Zannias, Vasileios, additional, de Zubicaray, Greig I., additional, Zunta-Soares, Giovana B., additional, Abé, Christoph, additional, Alda, Martin, additional, Andreassen, Ole A., additional, Bøen, Erlend, additional, Bonnin, Caterina M., additional, Canales-Rodriguez, Erick J., additional, Cannon, Dara, additional, Caseras, Xavier, additional, Chaim-Avancini, Tiffany M., additional, Elvsåshagen, Torbjørn, additional, Favre, Pauline, additional, Foley, Sonya F., additional, Fullerton, Janice M., additional, Goikolea, Jose M., additional, Haarman, Bartholomeus C. M., additional, Hajek, Tomas, additional, Henry, Chantal, additional, Houenou, Josselin, additional, Howells, Fleur M., additional, Ingvar, Martin, additional, Kuplicki, Rayus, additional, Lafer, Beny, additional, Landén, Mikael, additional, Machado-Vieira, Rodrigo, additional, Malt, Ulrik F., additional, McDonald, Colm, additional, Mitchell, Philip B., additional, Nabulsi, Leila, additional, Otaduy, Maria Concepcion Garcia, additional, Overs, Bronwyn J., additional, Polosan, Mircea, additional, Pomarol-Clotet, Edith, additional, Radua, Joaquim, additional, Rive, Maria M., additional, Roberts, Gloria, additional, Ruhe, Henricus G., additional, Salvador, Raymond, additional, Sarró, Salvador, additional, Satterthwaite, Theodore D., additional, Savitz, Jonathan, additional, Schene, Aart H., additional, Schofield, Peter R., additional, Serpa, Mauricio H., additional, Sim, Kang, additional, Soeiro-de-Souza, Marcio Gerhardt, additional, Sutherland, Ashley N., additional, Temmingh, Henk S., additional, Timmons, Garrett M., additional, Uhlmann, Anne, additional, Vieta, Eduard, additional, Wolf, Daniel H., additional, Zanetti, Marcus V., additional, Jahanshad, Neda, additional, Thompson, Paul M., additional, Veltman, Dick J., additional, Penninx, Brenda W. J. H., additional, Marquand, Andre F., additional, Cole, James H., additional, and Schmaal, Lianne, additional

Published
2020
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36. Greater male than female variability in regional brain structure across the lifespan

Author

Wierenga, Lara M., Doucet, Gaelle E., Dima, Danai, Agartz, Ingrid, Aghajani, Moji, Akudjedu, Theophilus N., Albajes-Eizagirre, Anton, Alnaes, Dag, Alpert, Kathryn, I, Andreassen, Ole A., Anticevic, Alan, Asherson, Philip, Banaschewski, Tobias, Bargallo, Nuria, Baumeister, Sarah, Baur-Streubel, Ramona, Bertolino, Alessandro, Bonvino, Aurora, Boomsma, Dorret, I, Borgwardt, Stefan, Bourque, Josiane, den Braber, Anouk, Brandeis, Daniel, Breier, Alan, Brodaty, Henry, Brouwer, Rachel M., Buitelaar, Jan K., Busatto, Geraldo F., Calhoun, Vince D., Canales-Rodriguez, Erick J., Cannon, Dara M., Caseras, Xavier, Castellanos, Francisco X., Chaim-Avancini, Tiffany M., Ching, Christopher R. K., Clark, Vincent P., Conrod, Patricia J., Conzelmann, Annette, Crivello, Fabrice, Davey, Christopher G., Dickie, Erin W., Ehrlich, Stefan, Van't Ent, Dennis, Fisher, Simon E., Fouche, Jean-Paul, Franke, Barbara, Fuentes-Claramonte, Paola, de Geus, Eco J. C., Di Giorgio, Annabella, Glahn, David C., Gotlib, Ian H., Grabe, Hans J., Gruber, Oliver, Gruner, Patricia, Gur, Raquel E., Gur, Ruben C., Gurholt, Tiril P., de Haan, Lieuwe, Haatveit, Beathe, Harrison, Ben J., Hartman, Catharina A., Hatton, Sean N., Heslenfeld, Dirk J., van den Heuvel, Odile A., Hickie, Ian B., Hoekstra, Pieter J., Hohmann, Sarah, Holmes, Avram J., Hoogman, Martine, Hosten, Norbert, Howells, Fleur M., Pol, Hilleke E. Hulshoff, Huyser, Chaim, Jahanshad, Neda, James, Anthony C., Jiang, Jiyang, Jonsson, Erik G., Joska, John A., Kalnin, Andrew J., Klein, Marieke, Koenders, Laura, Kolskar, Knut K., Kramer, Bernd, Kuntsi, Jonna, Lagopoulos, Jim, Lazaro, Luisa, Lebedeva, Irina S., Lee, Phil H., Lochner, Christine, Machielsen, Marise W. J., Maingault, Sophie, Martin, Nicholas G., Martinez-Zalacain, Ignacio, Mataix-Cols, David, Mazoyer, Bernard, McDonald, Brenna C., McDonald, Colm, McIntosh, Andrew M., McMahon, Katie L., McPhilemy, Genevieve, van der Meer, Dennis, Menchon, Jose M., Naaijen, Jilly, Nyberg, Lars, Oosterlaan, Jaap, Paloyelis, Yannis, Pauli, Paul, Pergola, Giulio, Pomarol-Clotet, Edith, Portella, Maria J., Radua, Joaquim, Reif, Andreas, Richard, Genevieve, Roffman, Joshua L., Rosa, Pedro G. P., Sacchet, Matthew D., Sachdev, Perminder S., Salvador, Raymond, Sarro, Salvador, Satterthwaite, Theodore D., Saykin, Andrew J., Serpa, Mauricio H., Sim, Kang, Simmons, Andrew, Smoller, Jordan W., Sommer, Iris E., Soriano-Mas, Carles, Stein, Dan J., Strike, Lachlan T., Szeszko, Philip R., Temmingh, Henk S., Thomopoulos, Sophia, I, Tomyshev, Alexander S., Trollor, Julian N., Uhlmann, Anne, Veer, Ilya M., Veltman, Dick J., Voineskos, Aristotle, Volzke, Henry, Walter, Henrik, Wang, Lei, Wang, Yang, Weber, Bernd, Wen, Wei, West, John D., Westlye, Lars T., Whalley, Heather C., Williams, Steven C. R., Wittfeld, Katharina, Wolf, Daniel H., Wright, Margaret J., Yoncheva, Yuliya N., Zanetti, Marcus, V, Ziegler, Georg C., de Zubicaray, Greig, I, Thompson, Paul M., Crone, Eveline A., Frangou, Sophia, Tamnes, Christian K., Wierenga, Lara M., Doucet, Gaelle E., Dima, Danai, Agartz, Ingrid, Aghajani, Moji, Akudjedu, Theophilus N., Albajes-Eizagirre, Anton, Alnaes, Dag, Alpert, Kathryn, I, Andreassen, Ole A., Anticevic, Alan, Asherson, Philip, Banaschewski, Tobias, Bargallo, Nuria, Baumeister, Sarah, Baur-Streubel, Ramona, Bertolino, Alessandro, Bonvino, Aurora, Boomsma, Dorret, I, Borgwardt, Stefan, Bourque, Josiane, den Braber, Anouk, Brandeis, Daniel, Breier, Alan, Brodaty, Henry, Brouwer, Rachel M., Buitelaar, Jan K., Busatto, Geraldo F., Calhoun, Vince D., Canales-Rodriguez, Erick J., Cannon, Dara M., Caseras, Xavier, Castellanos, Francisco X., Chaim-Avancini, Tiffany M., Ching, Christopher R. K., Clark, Vincent P., Conrod, Patricia J., Conzelmann, Annette, Crivello, Fabrice, Davey, Christopher G., Dickie, Erin W., Ehrlich, Stefan, Van't Ent, Dennis, Fisher, Simon E., Fouche, Jean-Paul, Franke, Barbara, Fuentes-Claramonte, Paola, de Geus, Eco J. C., Di Giorgio, Annabella, Glahn, David C., Gotlib, Ian H., Grabe, Hans J., Gruber, Oliver, Gruner, Patricia, Gur, Raquel E., Gur, Ruben C., Gurholt, Tiril P., de Haan, Lieuwe, Haatveit, Beathe, Harrison, Ben J., Hartman, Catharina A., Hatton, Sean N., Heslenfeld, Dirk J., van den Heuvel, Odile A., Hickie, Ian B., Hoekstra, Pieter J., Hohmann, Sarah, Holmes, Avram J., Hoogman, Martine, Hosten, Norbert, Howells, Fleur M., Pol, Hilleke E. Hulshoff, Huyser, Chaim, Jahanshad, Neda, James, Anthony C., Jiang, Jiyang, Jonsson, Erik G., Joska, John A., Kalnin, Andrew J., Klein, Marieke, Koenders, Laura, Kolskar, Knut K., Kramer, Bernd, Kuntsi, Jonna, Lagopoulos, Jim, Lazaro, Luisa, Lebedeva, Irina S., Lee, Phil H., Lochner, Christine, Machielsen, Marise W. J., Maingault, Sophie, Martin, Nicholas G., Martinez-Zalacain, Ignacio, Mataix-Cols, David, Mazoyer, Bernard, McDonald, Brenna C., McDonald, Colm, McIntosh, Andrew M., McMahon, Katie L., McPhilemy, Genevieve, van der Meer, Dennis, Menchon, Jose M., Naaijen, Jilly, Nyberg, Lars, Oosterlaan, Jaap, Paloyelis, Yannis, Pauli, Paul, Pergola, Giulio, Pomarol-Clotet, Edith, Portella, Maria J., Radua, Joaquim, Reif, Andreas, Richard, Genevieve, Roffman, Joshua L., Rosa, Pedro G. P., Sacchet, Matthew D., Sachdev, Perminder S., Salvador, Raymond, Sarro, Salvador, Satterthwaite, Theodore D., Saykin, Andrew J., Serpa, Mauricio H., Sim, Kang, Simmons, Andrew, Smoller, Jordan W., Sommer, Iris E., Soriano-Mas, Carles, Stein, Dan J., Strike, Lachlan T., Szeszko, Philip R., Temmingh, Henk S., Thomopoulos, Sophia, I, Tomyshev, Alexander S., Trollor, Julian N., Uhlmann, Anne, Veer, Ilya M., Veltman, Dick J., Voineskos, Aristotle, Volzke, Henry, Walter, Henrik, Wang, Lei, Wang, Yang, Weber, Bernd, Wen, Wei, West, John D., Westlye, Lars T., Whalley, Heather C., Williams, Steven C. R., Wittfeld, Katharina, Wolf, Daniel H., Wright, Margaret J., Yoncheva, Yuliya N., Zanetti, Marcus, V, Ziegler, Georg C., de Zubicaray, Greig, I, Thompson, Paul M., Crone, Eveline A., Frangou, Sophia, and Tamnes, Christian K.

Abstract

For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders.

Published
2020
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37. What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from theENIGMABipolar Disorder Working Group

Author

Ching, Christopher R. K., Hibar, Derrek P., Gurholt, Tiril P., Nunes, Abraham, Thomopoulos, Sophia I., Abe, Christoph, Agartz, Ingrid, Brouwer, Rachel M., Cannon, Dara M., de Zwarte, Sonja M. C., Eyler, Lisa T., Favre, Pauline, Hajek, Tomas, Haukvik, Unn K., Houenou, Josselin, Landen, Mikael, Lett, Tristram A., McDonald, Colm, Nabulsi, Leila, Patel, Yash, Pauling, Melissa E., Paus, Tomas, Radua, Joaquim, Soeiro-de-Souza, Marcio G., Tronchin, Giulia, van Haren, Neeltje E. M., Vieta, Eduard, Walter, Henrik, Zeng, Ling-Li, Alda, Martin, Almeida, Jorge, Alnaes, Dag, Alonso-Lana, Silvia, Altimus, Cara, Bauer, Michael, Baune, Bernhard T., Bearden, Carrie E., Bellani, Marcella, Benedetti, Francesco, Berk, Michael, Bilderbeck, Amy C., Blumberg, Hilary P., Boen, Erlend, Bollettini, Irene, del Mar Bonnin, Caterina, Brambilla, Paolo, Canales-Rodriguez, Erick J., Caseras, Xavier, Dandash, Orwa, Dannlowski, Udo, Delvecchio, Giuseppe, Diaz-Zuluaga, Ana M., Dima, Danai, Duchesnay, Edouard, Elvsashagen, Torbjorn, Fears, Scott C., Frangou, Sophia, Fullerton, Janice M., Glahn, David C., Goikolea, Jose M., Green, Melissa J., Grotegerd, Dominik, Gruber, Oliver, Haarman, Bartholomeus C. M., Henry, Chantal, Howells, Fleur M., Ives-Deliperi, Victoria, Jansen, Andreas, Kircher, Tilo T. J., Knoechel, Christian, Kramer, Bernd, Lafer, Beny, Lopez-Jaramillo, Carlos, Machado-Vieira, Rodrigo, MacIntosh, Bradley J., Melloni, Elisa M. T., Mitchell, Philip B., Nenadic, Igor, Nery, Fabiano, Nugent, Allison C., Oertel, Viola, Ophoff, Roel A., Ota, Miho, Overs, Bronwyn J., Pham, Daniel L., Phillips, Mary L., Pineda-Zapata, Julian A., Poletti, Sara, Polosan, Mircea, Pomarol-Clotet, Edith, Pouchon, Arnaud, Quide, Yann, Rive, Maria M., Roberts, Gloria, Ruhe, Henricus G., Salvador, Raymond, Sarro, Salvador, Satterthwaite, Theodore D., Schene, Aart H., Sim, Kang, Soares, Jair C., Staeblein, Michael, Stein, Dan J., Tamnes, Christian K., Thomaidis, Georgios V., Upegui, Cristian Vargas, Veltman, Dick J., Wessa, Michele, Westlye, Lars T., Whalley, Heather C., Wolf, Daniel H., Wu, Mon-Ju, Yatham, Lakshmi N., Zarate, Carlos A., Thompson, Paul M., Andreassen, Ole A., Ching, Christopher R. K., Hibar, Derrek P., Gurholt, Tiril P., Nunes, Abraham, Thomopoulos, Sophia I., Abe, Christoph, Agartz, Ingrid, Brouwer, Rachel M., Cannon, Dara M., de Zwarte, Sonja M. C., Eyler, Lisa T., Favre, Pauline, Hajek, Tomas, Haukvik, Unn K., Houenou, Josselin, Landen, Mikael, Lett, Tristram A., McDonald, Colm, Nabulsi, Leila, Patel, Yash, Pauling, Melissa E., Paus, Tomas, Radua, Joaquim, Soeiro-de-Souza, Marcio G., Tronchin, Giulia, van Haren, Neeltje E. M., Vieta, Eduard, Walter, Henrik, Zeng, Ling-Li, Alda, Martin, Almeida, Jorge, Alnaes, Dag, Alonso-Lana, Silvia, Altimus, Cara, Bauer, Michael, Baune, Bernhard T., Bearden, Carrie E., Bellani, Marcella, Benedetti, Francesco, Berk, Michael, Bilderbeck, Amy C., Blumberg, Hilary P., Boen, Erlend, Bollettini, Irene, del Mar Bonnin, Caterina, Brambilla, Paolo, Canales-Rodriguez, Erick J., Caseras, Xavier, Dandash, Orwa, Dannlowski, Udo, Delvecchio, Giuseppe, Diaz-Zuluaga, Ana M., Dima, Danai, Duchesnay, Edouard, Elvsashagen, Torbjorn, Fears, Scott C., Frangou, Sophia, Fullerton, Janice M., Glahn, David C., Goikolea, Jose M., Green, Melissa J., Grotegerd, Dominik, Gruber, Oliver, Haarman, Bartholomeus C. M., Henry, Chantal, Howells, Fleur M., Ives-Deliperi, Victoria, Jansen, Andreas, Kircher, Tilo T. J., Knoechel, Christian, Kramer, Bernd, Lafer, Beny, Lopez-Jaramillo, Carlos, Machado-Vieira, Rodrigo, MacIntosh, Bradley J., Melloni, Elisa M. T., Mitchell, Philip B., Nenadic, Igor, Nery, Fabiano, Nugent, Allison C., Oertel, Viola, Ophoff, Roel A., Ota, Miho, Overs, Bronwyn J., Pham, Daniel L., Phillips, Mary L., Pineda-Zapata, Julian A., Poletti, Sara, Polosan, Mircea, Pomarol-Clotet, Edith, Pouchon, Arnaud, Quide, Yann, Rive, Maria M., Roberts, Gloria, Ruhe, Henricus G., Salvador, Raymond, Sarro, Salvador, Satterthwaite, Theodore D., Schene, Aart H., Sim, Kang, Soares, Jair C., Staeblein, Michael, Stein, Dan J., Tamnes, Christian K., Thomaidis, Georgios V., Upegui, Cristian Vargas, Veltman, Dick J., Wessa, Michele, Westlye, Lars T., Whalley, Heather C., Wolf, Daniel H., Wu, Mon-Ju, Yatham, Lakshmi N., Zarate, Carlos A., Thompson, Paul M., and Andreassen, Ole A.

Abstract

MRI-derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis-driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large-scale meta- and mega-analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large-scale, collaborative studies of mental illness.

Published
2020
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38. An overlapping pattern of cerebral cortical thinning is associated with both positive symptoms and aggression in schizophrenia via the ENIGMA consortium

Author

Wong, Ting Yat, primary, Radua, Joaquim, additional, Pomarol-Clotet, Edith, additional, Salvador, Raymond, additional, Albajes-Eizagirre, Anton, additional, Solanes, Aleix, additional, Canales-Rodriguez, Erick J., additional, Guerrero-Pedraza, Amalia, additional, Sarro, Salvador, additional, Kircher, Tilo, additional, Nenadic, Igor, additional, Krug, Axel, additional, Grotegerd, Dominik, additional, Dannlowski, Udo, additional, Borgwardt, Stefan, additional, Riecher-Rössler, Anita, additional, Schmidt, Andre, additional, Andreou, Christina, additional, Huber, Christian G., additional, Turner, Jessica, additional, Calhoun, Vince, additional, Jiang, Wenhao, additional, Clark, Sarah, additional, Walton, Esther, additional, Spalletta, Gianfranco, additional, Banaj, Nerisa, additional, Piras, Fabrizio, additional, Ciullo, Valentina, additional, Vecchio, Daniela, additional, Lebedeva, Irina, additional, Tomyshev, Alexander S., additional, Kaleda, Vasily, additional, Klushnik, Tatyana, additional, Filho, Geraldo Busatto, additional, Zanetti, Marcus Vinicius, additional, Serpa, Mauricio Henriques, additional, Penteado Rosa, Pedro Gomes, additional, Hashimoto, Ryota, additional, Fukunaga, Masaki, additional, Richter, Anja, additional, Krämer, Bernd, additional, Gruber, Oliver, additional, Voineskos, Aristotle N., additional, Dickie, Erin W., additional, Tomecek, David, additional, Skoch, Antonin, additional, Spaniel, Filip, additional, Hoschl, Cyril, additional, Bertolino, Alessandro, additional, Bonvino, Aurora, additional, Di Giorgio, Annabella, additional, Holleran, Laurena, additional, Ciufolini, Simone, additional, Marques, Tiago Reis, additional, Dazzan, Paola, additional, Murray, Robin, additional, Lamsma, Jelle, additional, Cahn, Wiepke, additional, van Haren, Neeltje, additional, Díaz-Zuluaga, Ana M., additional, Pineda-Zapata, Julián A., additional, Vargas, Cristian, additional, López-Jaramillo, Carlos, additional, van Erp, Theo G. M., additional, Gur, Ruben C., additional, and Nickl-Jockschat, Thomas, additional

Published
2019
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39. Brain Aging in Major Depressive Disorder: Results from the ENIGMA Major Depressive Disorder working group

Author

Han, Laura K M, primary, Dinga, Richard, additional, Hahn, Tim, additional, Ching, Christopher R K, additional, Eyler, Lisa T, additional, Aftanas, Lyubomir, additional, Aghajani, Moji, additional, Aleman, André, additional, Baune, Bernhard T, additional, Berger, Klaus, additional, Brak, Ivan, additional, Filho, Geraldo Busatto, additional, Carballedo, Angela, additional, Connolly, Colm G, additional, Couvy-Duchesne, Baptiste, additional, Cullen, Kathryn, additional, Dannlowski, Udo, additional, Davey, Christopher G, additional, Dima, Danai, additional, Duran, Fabio L S, additional, Enneking, Verena, additional, Filimonova, Elena, additional, Frenzel, Stefan, additional, Frodl, Thomas, additional, Fu, Cynthia H Y, additional, Godlewska, Beata R, additional, Gotlib, Ian H, additional, Grabe, Hans J, additional, Groenewold, Nynke A, additional, Grotegerd, Dominik, additional, Gruber, Oliver, additional, Hall, Geoffrey B, additional, Harrison, Ben J, additional, Hatton, Sean N, additional, Hermesdorf, Marco, additional, Hickie, Ian B, additional, Ho, Tiffany C, additional, Hosten, Norbert, additional, Jansen, Andreas, additional, Kähler, Claas, additional, Kircher, Tilo, additional, Klimes-Dougan, Bonnie, additional, Krämer, Bernd, additional, Krug, Axel, additional, Lagopoulos, Jim, additional, Leenings, Ramona, additional, MacMaster, Frank P, additional, MacQueen, Glenda, additional, McIntosh, Andrew, additional, McLellan, Quinn, additional, McMahon, Katie L, additional, Medland, Sarah E, additional, Mueller, Bryon A, additional, Mwangi, Benson, additional, Osipov, Evgeny, additional, Portella, Maria J, additional, Pozzi, Elena, additional, Reneman, Liesbeth, additional, Repple, Jonathan, additional, Rosa, Pedro G P, additional, Sacchet, Matthew D, additional, Sämann, Philipp G, additional, Schnell, Knut, additional, Schrantee, Anouk, additional, Simulionyte, Egle, additional, Soares, Jair C, additional, Sommer, Jens, additional, Stein, Dan J, additional, Steinsträter, Olaf, additional, Strike, Lachlan T, additional, Thomopoulos, Sophia I, additional, van Tol, Marie-José, additional, Veer, Ilya M, additional, Vermeiren, Robert R J M, additional, Walter, Henrik, additional, van der Wee, Nic J A, additional, van der Werff, Steven J A, additional, Whalley, Heather, additional, Winter, Nils R, additional, Wittfeld, Katharina, additional, Wright, Margaret J, additional, Wu, Mon-Ju, additional, Völzke, Henry, additional, Yang, Tony T, additional, Zannias, Vasileios, additional, Zubicaray, Greig I de, additional, Zunta-Soares, Giovana B, additional, Abé, Christoph, additional, Alda, Martin, additional, Andreassen, Ole A, additional, Bøen, Erlend, additional, Bonnin, Caterina M, additional, Canales-Rodriguez, Erick J, additional, Cannon, Dara, additional, Caseras, Xavier, additional, Chaim-Avancini, Tiffany M, additional, Elvsåshagen, Torbjørn, additional, Favre, Pauline, additional, Foley, Sonya F, additional, Fullerton, Janice M, additional, Goikolea, Jose M, additional, Haarman, Bartholomeus C M, additional, Hajek, Tomas, additional, Henry, Chantal, additional, Houenou, Josselin, additional, Howells, Fleur M, additional, Ingvar, Martin, additional, Kuplicki, Rayus, additional, Lafer, Beny, additional, Landén, Mikael, additional, Machado-Vieira, Rodrigo, additional, Malt, Ulrik F, additional, McDonald, Colm, additional, Mitchell, Philip B, additional, Nabulsi, Leila, additional, Otaduy, Maria Concepcion Garcia, additional, Overs, Bronwyn J, additional, Polosan, Mircea, additional, Pomarol-Clotet, Edith, additional, Radua, Joaquim, additional, Rive, Maria M, additional, Roberts, Gloria, additional, Ruhe, Henricus G, additional, Salvador, Raymond, additional, Sarró, Salvador, additional, Satterthwaite, Theodore D, additional, Savitz, Jonathan, additional, Schene, Aart H, additional, Schofield, Peter R, additional, Serpa, Mauricio H, additional, Sim, Kang, additional, Soeiro-de-Souza, Marcio Gerhardt, additional, Sutherland, Ashley N, additional, Temmingh, Henk S, additional, Timmons, Garrett M, additional, Uhlmann, Anne, additional, Vieta, Eduard, additional, Wolf, Daniel H, additional, Zanetti, Marcus V, additional, Jahanshad, Neda, additional, Thompson, Paul M, additional, Veltman, Dick J, additional, Penninx, Brenda W J H, additional, Marquand, Andre F, additional, Cole, James H, additional, and Schmaal, Lianne, additional

Published
2019
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41. An overlapping pattern of cerebral cortical thinning is associated with both positive symptoms and aggression in schizophrenia via the ENIGMA consortium.

Author

Wong, Ting Yat, Radua, Joaquim, Pomarol-Clotet, Edith, Salvador, Raymond, Albajes-Eizagirre, Anton, Solanes, Aleix, Canales-Rodriguez, Erick J., Guerrero-Pedraza, Amalia, Sarro, Salvador, Kircher, Tilo, Nenadic, Igor, Krug, Axel, Grotegerd, Dominik, Dannlowski, Udo, Borgwardt, Stefan, Riecher-Rössler, Anita, Schmidt, Andre, Andreou, Christina, Huber, Christian G., and Turner, Jessica

Subjects
CEREBRAL cortical thinning, RISK factors of aggression, BRAIN, CEREBRAL cortex, COGNITION disorders, MAGNETIC resonance imaging, REGRESSION analysis, SCHIZOPHRENIA, WORD deafness, GRAY matter (Nerve tissue)
Abstract

Background: Positive symptoms are a useful predictor of aggression in schizophrenia. Although a similar pattern of abnormal brain structures related to both positive symptoms and aggression has been reported, this observation has not yet been confirmed in a single sample. Method: To study the association between positive symptoms and aggression in schizophrenia on a neurobiological level, a prospective meta-analytic approach was employed to analyze harmonized structural neuroimaging data from 10 research centers worldwide. We analyzed brain MRI scans from 902 individuals with a primary diagnosis of schizophrenia and 952 healthy controls. Results: The result identified a widespread cortical thickness reduction in schizophrenia compared to their controls. Two separate meta-regression analyses revealed that a common pattern of reduced cortical gray matter thickness within the left lateral temporal lobe and right midcingulate cortex was significantly associated with both positive symptoms and aggression. Conclusion: These findings suggested that positive symptoms such as formal thought disorder and auditory misperception, combined with cognitive impairments reflecting difficulties in deploying an adaptive control toward perceived threats, could escalate the likelihood of aggression in schizophrenia. [ABSTRACT FROM AUTHOR]

Published
2020
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42. Reducing acquisition time for microstructure imaging with spatially-regularized global optimization

Author

Auría Rasclosa, Anna, Romascano, David Paul Roger, Canales-Rodriguez, Erick J., Dyrby, Tim B., Alexander, Daniel C., Thiran, Jean-Philippe, Wiaux, Yves, and Daducci, Alessandro

Subjects
White Matter modeling, LTS5, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Microstructure imaging, Diffusion MRI, Convex optimization
Abstract

Microstructure imaging with diffusion MRI (dMRI) is usually based on fitting models to the data using voxelwise nonlinear procedures that (i) are time consuming and (ii) need long acquisitions. Recently, we introduced the AMICO framework to accelerate the fit; here, we propose an extension to enable faster acquisitions, too. Our formulation allows exploiting information from neighboring voxels that is not accessible with existing approaches.

Published
2016

43. Reducing acquisition time for axon diameter mapping using global optimization in the spatial-angular-microstructure space

Author

Auría Rasclosa, Anna, Romascano, David Paul Roger, Canales-Rodriguez, Erick J., Dyrby, Tim B., Alexander, Daniel C., Thiran, Jean-Philippe, Wiaux, Yves, and Daducci, Alessandro

Subjects
White Matter modeling, LTS5, Physics::Medical Physics, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Microstructure imaging, Diffusion MRI, Convex optimization, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

State-of-the-art microstructure imaging methods usually fit biophysical models to the diffusion MRI data on a voxel-by-voxel basis using non-linear procedures that require both long acquisitions and processing time. We recently introduced AMICO, a framework to reformulate these techniques as efficient linear problems and enable faster reconstructions. Here, we propose an extension that enables robust reconstructions from a reduced number of diffusion measurements, thus leading to faster acquisitions, too. Our novel formulation estimates simultaneously the microstructure configuration in all voxels as a global optimization problem, exploiting information from neighboring voxels that cannot be taken into account with existing techniques.

Published
2016

44. Increased power by harmonizing structural MRI site differences with the ComBat batch method in ENIGMA

Author

Radua, Joaquim, Vieta, Eduard, Shinohara, Russell, Kochunov, Peter, Quide, Yann, Green, Melissa J., Weickert, Cynthia S., Weickert, Thomas, Bruggemann, Jason, Kircher, Tilo, Nenadic, Igor, Cairns, Murray J., Seal, Marc, Schall, Ulrich, Henskens, Frans, Fullerton, Janice M., Mowry, Bryan, Pantelis, Christos, Lenroot, Rhoshel, Cropley, Vanessa, Loughland, Carmel, Scott, Rodney, Wolf, Daniel, Satterthwaite, Theodore D., Tan, Yunlong, Sim, Kang, Piras, Fabrizio, Spalletta, Gianfranco, Banaj, Nerisa, Pomarol-Clotet, Edith, Solanes, Aleix, Albajes-Eizagirre, Anton, Canales-Rodriguez, Erick J., Sarro, Salvador, Di Giorgio, Annabella, Bertolino, Alessandro, Staeblein, Michael, Oertel, Viola, Knoechel, Christian, Borgwardt, Stefan, du Plessis, Stefan, Yun, Je-Yeon, Kwon, Jun Soo, Dannlowski, Udo, Hahn, Tim, Grotegerd, Dominik, Alloza, Clara, Arango, Celso, Janssen, Joost, Diaz-Caneja, Covadonga, Jiang, Wenhao, Calhoun, Vince, Ehrlich, Stefan, Yang, Kun, Cascella, Nicola G., Takayanagi, Yoichiro, Sawa, Akira, Tomyshev, Alexander, Lebedeva, Irina, Kaleda, Vasily, Kirschner, Matthias, Hoschl, Cyril, Tomecek, David, Skoch, Antonin, van Amelsvoort, Therese, Bakker, Geor, James, Anthony, Preda, Adrian, Weideman, Andrea, Stein, Dan J., Howells, Fleur, Uhlmann, Anne, Temmingh, Henk, Lopez-Jaramillo, Carlos, Diaz-Zuluaga, Ana, Fortea, Lydia, Martinez-Heras, Eloy, Solana, Elisabeth, Llufriu, Sara, Jahanshad, Neda, Thompson, Paul, Turner, Jessica, and van Erp, Theo

Subjects
mega-analysis, schizophrenia, volume, neuroimaging, brain, gray matter, cortical thickness, surface-based analysis
Abstract

A common limitation of neuroimaging studies is their small sample sizes. To overcome this hurdle, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium combines neuroimaging data from many institutions worldwide. However, this introduces heterogeneity due to different scanning devices and sequences. ENIGMA projects commonly address this heterogeneity with random-effects meta-analysis or mixed-effects mega -analysis. Here we tested whether the batch adjustment method, ComBat, can further reduce site-related het-erogeneity and thus increase statistical power. We conducted random-effects meta-analyses, mixed-effects mega -analyses and ComBat mega-analyses to compare cortical thickness, surface area and subcortical volumes between 2897 individuals with a diagnosis of schizophrenia and 3141 healthy controls from 33 sites. Specifically, we compared the imaging data between individuals with schizophrenia and healthy controls, covarying for age and sex. The use of ComBat substantially increased the statistical significance of the findings as compared to random - effects meta-analyses. The findings were more similar when comparing ComBat with mixed-effects mega-analysis, although ComBat still slightly increased the statistical significance. ComBat also showed increased statistical power when we repeated the analyses with fewer sites. Results were nearly identical when we applied the ComBat harmonization separately for cortical thickness, cortical surface area and subcortical volumes. Therefore, we recommend applying the ComBat function to attenuate potential effects of site in ENIGMA projects and other multi-site structural imaging work. We provide easy-to-use functions in R that work even if imaging data are partially missing in some brain regions, and they can be trained with one data set and then applied to another (a requirement for some analyses such as machine learning).

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