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Your search keyword '"Zunta-Soares, Giovana B."' showing total 7 results
Start Over Author "Zunta-Soares, Giovana B." Publisher wiley
7 results on '"Zunta-Soares, Giovana B."'

1. Mega‐analysis methods in ENIGMA : The experience of the generalized anxiety disorder working group

Author

Zugman, André, primary, Harrewijn, Anita, additional, Cardinale, Elise M., additional, Zwiebel, Hannah, additional, Freitag, Gabrielle F., additional, Werwath, Katy E., additional, Bas‐Hoogendam, Janna M., additional, Groenewold, Nynke A., additional, Aghajani, Moji, additional, Hilbert, Kevin, additional, Cardoner, Narcis, additional, Porta‐Casteràs, Daniel, additional, Gosnell, Savannah, additional, Salas, Ramiro, additional, Blair, Karina S., additional, Blair, James R., additional, Hammoud, Mira Z., additional, Milad, Mohammed, additional, Burkhouse, Katie, additional, Phan, K. Luan, additional, Schroeder, Heidi K., additional, Strawn, Jeffrey R., additional, Beesdo‐Baum, Katja, additional, Thomopoulos, Sophia I., additional, Grabe, Hans J., additional, Van der Auwera, Sandra, additional, Wittfeld, Katharina, additional, Nielsen, Jared A., additional, Buckner, Randy, additional, Smoller, Jordan W., additional, Mwangi, Benson, additional, Soares, Jair C., additional, Wu, Mon‐Ju, additional, Zunta‐Soares, Giovana B., additional, Jackowski, Andrea P., additional, Pan, Pedro M., additional, Salum, Giovanni A., additional, Assaf, Michal, additional, Diefenbach, Gretchen J., additional, Brambilla, Paolo, additional, Maggioni, Eleonora, additional, Hofmann, David, additional, Straube, Thomas, additional, Andreescu, Carmen, additional, Berta, Rachel, additional, Tamburo, Erica, additional, Price, Rebecca, additional, Manfro, Gisele G., additional, Critchley, Hugo D., additional, Makovac, Elena, additional, Mancini, Matteo, additional, Meeten, Frances, additional, Ottaviani, Cristina, additional, Agosta, Federica, additional, Canu, Elisa, additional, Cividini, Camilla, additional, Filippi, Massimo, additional, Kostić, Milutin, additional, Munjiza, Ana, additional, Filippi, Courtney A., additional, Leibenluft, Ellen, additional, Alberton, Bianca A. V., additional, Balderston, Nicholas L., additional, Ernst, Monique, additional, Grillon, Christian, additional, Mujica‐Parodi, Lilianne R., additional, Nieuwenhuizen, Helena, additional, Fonzo, Gregory A., additional, Paulus, Martin P., additional, Stein, Murray B., additional, Gur, Raquel E., additional, Gur, Ruben C., additional, Kaczkurkin, Antonia N., additional, Larsen, Bart, additional, Satterthwaite, Theodore D., additional, Harper, Jennifer, additional, Myers, Michael, additional, Perino, Michael T., additional, Yu, Qiongru, additional, Sylvester, Chad M., additional, Veltman, Dick J., additional, Lueken, Ulrike, additional, Van der Wee, Nic J. A., additional, Stein, Dan J., additional, Jahanshad, Neda, additional, Thompson, Paul M., additional, Pine, Daniel S., additional, and Winkler, Anderson M., additional

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

Author

Yu Y, Cui HQ, Haas SS, New F, Sanford N, Yu K, Zhan D, Yang G, Gao JH, Wei D, Qiu J, Banaj N, Boomsma DI, Breier A, Brodaty H, Buckner RL, Buitelaar JK, Cannon DM, Caseras X, Clark VP, Conrod PJ, Crivello F, Crone EA, Dannlowski U, Davey CG, de Haan L, de Zubicaray GI, Di Giorgio A, Fisch L, Fisher SE, Franke B, Glahn DC, Grotegerd D, Gruber O, Gur RE, Gur RC, Hahn T, Harrison BJ, Hatton S, Hickie IB, Hulshoff Pol HE, Jamieson AJ, Jernigan TL, Jiang J, Kalnin AJ, Kang S, Kochan NA, Kraus A, Lagopoulos J, Lazaro L, McDonald BC, McDonald C, McMahon KL, Mwangi B, Piras F, Rodriguez-Cruces R, Royer J, Sachdev PS, Satterthwaite TD, Saykin AJ, Schumann G, Sevaggi P, Smoller JW, Soares JC, Spalletta G, Tamnes CK, Trollor JN, Van't Ent D, Vecchio D, Walter H, Wang Y, Weber B, Wen W, Wierenga LM, Williams SCR, Wu MJ, Zunta-Soares GB, Bernhardt B, Thompson P, Frangou S, and Ge R

Subjects
Humans, Adolescent, Female, Aged, Adult, Child, Young Adult, Male, Aged, 80 and over, Child, Preschool, Middle Aged, Neuroimaging methods, Neuroimaging standards, Sample Size, Brain diagnostic imaging, Brain anatomy & histology, Brain growth & development, Aging physiology, Magnetic Resonance Imaging methods
Abstract

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

Published
2024
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7. Mega-analysis methods in ENIGMA: The experience of the generalized anxiety disorder working group.

Author

Zugman A, Harrewijn A, Cardinale EM, Zwiebel H, Freitag GF, Werwath KE, Bas-Hoogendam JM, Groenewold NA, Aghajani M, Hilbert K, Cardoner N, Porta-Casteràs D, Gosnell S, Salas R, Blair KS, Blair JR, Hammoud MZ, Milad M, Burkhouse K, Phan KL, Schroeder HK, Strawn JR, Beesdo-Baum K, Thomopoulos SI, Grabe HJ, Van der Auwera S, Wittfeld K, Nielsen JA, Buckner R, Smoller JW, Mwangi B, Soares JC, Wu MJ, Zunta-Soares GB, Jackowski AP, Pan PM, Salum GA, Assaf M, Diefenbach GJ, Brambilla P, Maggioni E, Hofmann D, Straube T, Andreescu C, Berta R, Tamburo E, Price R, Manfro GG, Critchley HD, Makovac E, Mancini M, Meeten F, Ottaviani C, Agosta F, Canu E, Cividini C, Filippi M, Kostić M, Munjiza A, Filippi CA, Leibenluft E, Alberton BAV, Balderston NL, Ernst M, Grillon C, Mujica-Parodi LR, van Nieuwenhuizen H, Fonzo GA, Paulus MP, Stein MB, Gur RE, Gur RC, Kaczkurkin AN, Larsen B, Satterthwaite TD, Harper J, Myers M, Perino MT, Yu Q, Sylvester CM, Veltman DJ, Lueken U, Van der Wee NJA, Stein DJ, Jahanshad N, Thompson PM, Pine DS, and Winkler AM

Subjects
Humans, Anxiety Disorders diagnostic imaging, Cerebral Cortex diagnostic imaging, Data Interpretation, Statistical, Meta-Analysis as Topic, Multicenter Studies as Topic methods, Multicenter Studies as Topic standards, Neuroimaging methods, Neuroimaging standards
Abstract

The ENIGMA group on Generalized Anxiety Disorder (ENIGMA-Anxiety/GAD) is part of a broader effort to investigate anxiety disorders using imaging and genetic data across multiple sites worldwide. The group is actively conducting a mega-analysis of a large number of brain structural scans. In this process, the group was confronted with many methodological challenges related to study planning and implementation, between-country transfer of subject-level data, quality control of a considerable amount of imaging data, and choices related to statistical methods and efficient use of resources. This report summarizes the background information and rationale for the various methodological decisions, as well as the approach taken to implement them. The goal is to document the approach and help guide other research groups working with large brain imaging data sets as they develop their own analytic pipelines for mega-analyses., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Published
2022
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