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Developing a prototype concurrent design tool for composite topside structures

NAVAL ENGINEERS JOURNAL 1997年第3期109卷 279-290页

作者： Dirlik, S Hambric, S Azarm, S Marquardt, M Hellman, A Bartlett, S Castelli, V Steve Dirlik:began his career at the Naval Surface Warfare Center Carderock Division in 1981 as an aerospace engineer co-op student. He completed his bachelor of science degree in aeropace and ocean engineering from Virginia Polytechnic Institute and State University in 1985 and his master of science degree in aerospace engineering from the University of Maryland in 1990. Mr. Dirlik recently completed a master of science program in applied physics at The Johns Hopins University and currently works in the Radar Cross Section and Target Physics Branch of the Signatures Directorate at the Naval Surface Warfare Center Corderoke Division. He has worked on Navy low observable programs since 1990. Stephen Hambric:is a research associate at the Applied Research Laboratory at The Pennsylvania State University. He received his B. S. and M.S. degree in mechanical engineering from Virginia Polytechnic Institute and State University and his D. Sc. in mechnical engineering from the George Washington University. He has worked on several computer aided multidiscikplinary design and optimization projects over the years including an automated propeller design system and a structural acoustic optimization capability. Dr. Shpour Azarm:is currently working as an associate professor with the Design and Manufacturing Group of the Department of Mechanical Engineering at the University of maryland at College Park. Dr Azarm's expertise is in the areas of optimization-based designed and concurrent design and optimization of multidisciplinary systems. He was a consultant at Black & Decker Corporation (summer 1996) and worked as a Navy senior summer faculty fellow (summer 1995) and a NASA summer faculty fellow (summer 1994). He was a visiting scientist at NASA Langley Research Center for Multidisciplinary Analysis and Applied Structural Optimzatiom at the University of Siegen in Germany (spring 1992) and the Design Institute of the Technical University of Denmark (summer 1990). Dr Azarm was an associate technical editor of the ASME Jour

A prototype concurrent engineering tool has been developed for the preliminary design of composite topside structures for modern navy warships. This tool, named GELS for the Concurrent Engineering of Layered Structures, provides designers with an immediate assessment of the impacts of their decisions on several disciplines which are important to the performance of a modern naval topside structure, including electromagnetic interference effects (EMI), radar cross section (RCS), structural integrity, cost, and weight. Preliminary analysis modules in each of these disciplines are integrated to operate from a common set of design variables and a common materials database. Performance in each discipline and an overall fitness function for the concept are then evaluated. A graphical user interface (GUI) is used to define requirements and to display the results from the technical analysis modules. Optimization techniques, including feasible sequential quadratic programming (FSQP) and exhaustive search are used to modify the design variables to satisfy all requirements simultaneously. The development of this tool, the technical modules, and their integration are discussed noting the decisions and compromises required to develop and integrate the modules into a prototype conceptual design tool.

关键词： Warships

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Comparative cellular analysis of motor cortex in human, marmoset and mouse (vol 598, pg 111, 2021)

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NATURE 2022年第7904期604卷 E8-E8页

作者： Bakken, Trygve E. Jorstad, Nikolas L. Hu, Qiwen Lake, Blue B. Tian, Wei Kalmbach, Brian E. Crow, Megan Hodge, Rebecca D. Krienen, Fenna M. Sorensen, Staci A. Eggermont, Jeroen Yao, Zizhen Aevermann, Brian D. Aldridge, Andrew I. Bartlett, Anna Bertagnolli, Darren Casper, Tamara Castanon, Rosa G. Crichton, Kirsten Daigle, Tanya L. Dalley, Rachel Dee, Nick Dembrow, Nikolai Diep, Dinh Ding, Song-Lin Dong, Weixiu Fang, Rongxin Fischer, Stephan Goldman, Melissa Goldy, Jeff Graybuck, Lucas T. Herb, Brian R. Hou, Xiaomeng Kancherla, Jayaram Kroll, Matthew Lathia, Kanan van Lew, Baldur Li, Yang Eric Liu, Christine S. Liu, Hanqing Lucero, Jacinta D. Mahurkar, Anup McMillen, Delissa Miller, Jeremy A. Moussa, Marmar Nery, Joseph R. Nicovich, Philip R. Niu, Sheng-Yong Orvis, Joshua Osteen, Julia K. Owen, Scott Palmer, Carter R. Pham, Thanh Plongthongkum, Nongluk Poirion, Olivier Reed, Nora M. Rimorin, Christine Rivkin, Angeline Romanow, William J. Sedeno-Cortes, Adriana E. Siletti, Kimberly Somasundaram, Saroja Sulc, Josef Tieu, Michael Torkelson, Amy Tung, Herman Wang, Xinxin Xie, Fangming Yanny, Anna Marie Zhang, Renee Ament, Seth A. Behrens, M. Margarita Bravo, Hector Corrada Chun, Jerold Dobin, Alexander Gillis, Jesse Hertzano, Ronna Hof, Patrick R. Hollt, Thomas Horwitz, Gregory D. Keene, C. Dirk Kharchenko, Peter V. Ko, Andrew L. Lelieveldt, Boudewijn P. Luo, Chongyuan Mukamel, Eran A. Pinto-Duarte, Antonio Preiss, Sebastian Regev, Aviv Ren, Bing Scheuermann, Richard H. Smith, Kimberly Spain, William J. White, Owen R. Koch, Christof Hawrylycz, Michael Tasic, Bosiljka Macosko, Evan Z. McCarroll, Steven A. Ting, Jonathan T. Zeng, Hongkui Zhang, Kun Feng, Guoping Ecker, Joseph R. Linnarsson, Sten Lein, Ed S. Allen Institute for Brain Science Seattle WA USA Department of Physiology and Biophysics University of Washington Seattle WA USA Department of Biomedical Informatics Harvard Medical School Boston MA USA Department of Bioengineering University of California San Diego La Jolla CA USA The Salk Institute for Biological Studies La Jolla CA USA Epilepsy Center of Excellence Department of Veterans Affairs Medical Center Seattle WA USA Stanley Institute for Cognitive Genomics Cold Spring Harbor Laboratory Cold Spring Harbor NY USA Department of Genetics Harvard Medical School Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA LKEB Department of Radiology Leiden University Medical Center Leiden The Netherlands Pattern Recognition and Bioinformatics group Delft University of Technology Delft The Netherlands J. Craig Venter Institute La Jolla CA USA Department of Pathology University of California San Diego CA USA Division of Vaccine Discovery La Jolla Institute for Immunology La Jolla CA USA Genomic Analysis Laboratory The Salk Institute for Biological Studies La Jolla CA USA Computer Science and Engineering Program University of California San Diego La Jolla CA USA Howard Hughes Medical Institute The Salk Institute for Biological Studies La Jolla CA USA Bioinformatics and Systems Biology Graduate Program University of California San Diego La Jolla CA USA Institute for Genomes Sciences University of Maryland School of Medicine Baltimore MD USA Center for Epigenomics Department of Cellular and Molecular Medicine University of California San Diego La Jolla CA USA Ludwig Institute for Cancer Research La Jolla CA USA Department of Computer Science University of Maryland College Park College Park MD USA Sanford Burnham Prebys Medical Discovery Institute La Jolla CA USA Biomedical Sciences Program School of Medicine University of California San Diego La Jolla CA USA University of Connecticut Storrs CT USA Department

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A large-scale ENIGMA multisite replication study of brain age in depression

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Neuroimage: Reports 2022年第4期2卷 100149-100149页

作者： Han, Laura K.M. Dinga, Richard Leenings, Ramona Hahn, Tim Cole, James H. Aftanas, Lyubomir I. Amod, Alyssa R. Besteher, Bianca Colle, Romain Corruble, Emmanuelle Couvy-Duchesne, Baptiste Danilenko, Konstantin V. Fuentes-Claramonte, Paola Gonul, Ali Saffet Gotlib, Ian H. Goya-Maldonado, Roberto Groenewold, Nynke A. Hamilton, Paul Ichikawa, Naho Ipser, Jonathan C. Itai, Eri Koopowitz, Sheri-Michelle Li, Meng Okada, Go Okamoto, Yasumasa Churikova, Olga S. Osipov, Evgeny A. Penninx, Brenda W.J.H. Pomarol-Clotet, Edith Rodríguez-Cano, Elena Sacchet, Matthew D. Shinzato, Hotaka Sim, Kang Stein, Dan J. Uyar-Demir, Aslihan Veltman, Dick J. Schmaal, Lianne Centre for Youth Mental Health The University of Melbourne Parkville VIC Australia Orygen Parkville VIC Australia Department of Cognitive Science & Artificial Intelligence Tilburg University Tilburg Netherlands Institute for Translational Psychiatry University of Münster Münster Germany Faculty of Mathematics and Computer Science University of Münster Münster Germany Centre for Medical Image Computing Department of Computer Science University College London United Kingdom Dementia Research Centre Queen Square Institute of Neurology University College London United Kingdom Scientific Research Institute of Neuroscience and Medicine Novosibirsk Russian Federation Novosibirsk State University Novosibirsk Russian Federation Department of Psychiatry & Mental Health Neuroscience Institute University of Cape Town South Africa Department of Psychiatry and Psychotherapy Jena University Hospital Jena Germany Service Hospitalo-Universitaire de Psychiatrie de Bicêtre Mood Center Paris Saclay Assistance Publique-Hôpitaux de Paris Hôpitaux Universitaires Paris-Saclay Hôpital de Bicêtre Le Kremlin Bicêtre F-94275 France MOODS Team INSERM 1018 CESP (Centre de Recherche en Epidémiologie et Santé des Populations) Université Paris-Saclay Faculté de Médecine Paris-Saclay Le Kremlin Bicêtre F-94275 France Sorbonne Université Institut du Cerveau - Paris Brain Institute - ICM CNRS Inria Inserm AP-HP Hôpital de La Pitié Salpêtrière Paris F-75013 France Institute for Molecular Bioscience The University of Queensland St Lucia 4072 QLD Australia FIDMAG Hermanas Hospitalarias Research Foundation Barcelona Spain CIBERSAM Barcelona Spain SoCAT Lab Department of Psychiatry School of Medicine Ege University Izmir Turkey Department of Psychology Stanford University Stanford CA United States Laboratory of Systems Neuroscience and Imaging in Psychiatry (SNIP-Lab) University Medical Center Göttingen Göttingen Germany Center for Social and Affective Neuroscience Department o

Background: Several studies have evaluated whether depressed persons have older appearing brains than their nondepressed peers. However, the estimated neuroimaging-derived “brain age gap” has varied from study to study, likely driven by differences in training and testing sample (size), age range, and used modality/features. To validate our previously developed ENIGMA brain age model and the identified brain age gap, we aim to replicate the presence and effect size estimate previously found in the largest study in depression to date (N = 2126 controls & N = 2675 cases;+1.08 years [SE 0.22], Cohen's d = 0.14, 95% CI: 0.08–0.20), in independent cohorts that were not part of the original study. Methods: A previously trained brain age model (***/enigma_brainage) based on 77 FreeSurfer brain regions of interest was used to obtain unbiased brain age predictions in 751 controls and 766 persons with depression (18–75 years) from 13 new cohorts collected from 20 different scanners. Meta-regressions were used to examine potential moderating effects of basic cohort characteristics (e.g., clinical and scan technical) on the brain age gap. Results: Our ENIGMA MDD brain age model generalized reasonably well to controls from the new cohorts (predicted age vs. age: r = 0.73, R² = 0.47, MAE = 7.50 years), although the performance varied from cohort to cohort. In these new cohorts, on average, depressed persons showed a significantly higher brain age gap of +1 year (SE 0.35) (Cohen's d = 0.15, 95% CI: 0.05–0.25) compared with controls, highly similar to our previous finding. Significant moderating effects of FreeSurfer version 6.0 (d = 0.41, p = 0.007) and Philips scanner vendor (d = 0.50, p < 0.0001) were found, leading to more positive effect size estimates. Conclusions: This study further validates our previously developed ENIGMA brain age algorithm. Importantly, we replicated the brain age gap in depression with a comparable effect size. Thus, two large-s

关键词： Biological aging Brain age Depression ENIGMA consortium Replication study

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Analysis of the BraTS 2023 Intracranial Meningioma Segmentation Challenge

arXiv

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arXiv 2024年

作者： LaBella, Dominic Baid, Ujjwal Khanna, Omaditya McBurney-Lin, Shan McLean, Ryan Nedelec, Pierre Rashid, Arif Tahon, Nourel Hoda Altes, Talissa Bhalerao, Radhika Dhemesh, Yaseen Godfrey, Devon Hilal, Fathi Floyd, Scott Janas, Anastasia Kazerooni, Anahita Fathi Kirkpatrick, John Kent, Collin Kofler, Florian Leu, Kevin Maleki, Nazanin Menze, Bjoern Pajot, Maxence Reitman, Zachary J. Rudie, Jeffrey D. Saluja, Rachit Velichko, Yury Wang, Chunhao Warman, Pranav Adewole, Maruf Albrecht, Jake Anazodo, Udunna Anwar, Syed Muhammad Bergquist, Timothy Chen, Sully Francis Chung, Verena Conte, Gian-Marco Dako, Farouk Eddy, James Ezhov, Ivan Khalili, Nastaran Iglesias, Juan Eugenio Jiang, Zhifan Johanson, Elaine Van Leemput, Koen Li, Hongwei Bran Linguraru, Marius George Liu, Xinyang Mahtabfar, Aria Meier, Zeke Moawad, Ahmed W. Mongan, John Piraud, Marie Shinohara, Russell Takeshi Wiggins, Walter F. Abayazeed, Aly H. Akinola, Rachel Jakab, András Bilello, Michel de Verdier, Maria Correia Crivellaro, Priscila Davatzikos, Christos Farahani, Keyvan Freymann, John Hess, Christopher Huang, Raymond Lohmann, Philipp Moassefi, Mana Pease, Matthew W. Vollmuth, Phillipp Sollmann, Nico Diffley, David Nandolia, Khanak K. Warren, Daniel I. Hussain, Ali Fehringer, Pascal Bronstein, Yulia Deptula, Lisa Stein, Evan G. Taherzadeh, Mahsa de Oliveira, Eduardo Portela Haughey, Aoife Kontzialis, Marinos Saba, Luca Turner, Benjamin Brüßeler, Melanie M.T. Ansari, Shehbaz Gkampenis, Athanasios Weiss, David Maximilian Mansour, Aya Shawali, Islam H. Yordanov, Nikolay Stein, Joel M. Hourani, Roula Moshebah, Mohammed Yahya Abouelatta, Ahmed Magdy Rizvi, Tanvir Willms, Klara Martin, Dann C. Okar, Abdullah D'Anna, Gennaro Taha, Ahmed Sharifi, Yasaman Faghani, Shahriar Kite, Dominic Pinho, Marco Haider, Muhammad Ammar Aristizabal, Alejandro Karargyris, Alexandros Kassem, Hasan Pati, Sarthak Sheller, Micah Alonso-Basanta, Michelle Villanueva-Meyer, Javier Rauschecker, Andreas M. Nada, Ayman Aboian, Mariam Flanders, Adam E. Wiestler, Benedikt Bakas, Spyridon Ca Duke University Medical Center Department of Radiation Oncology DurhamNC United States Division of Computational Pathology Department of Pathology Laboratory Medicine Indiana University School of Medicine IndianapolisIN United States Center for Federated Learning in Medicine Indiana University IndianapolisIN United States Department of Neurosurgery Thomas Jefferson University PhiladelphiaPA United States University of California San FranciscoCA United States Yale University New HavenCT United States Department of Radiation Oncology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States University of Missouri ColumbiaMO United States Department of Biostatistics and Health Data Science Indiana University School of Medicine IndianapolisIN United States Children's Hospital of Philadelphia University of Pennsylvania PhiladelphiaPA United States University of Pennsylvania PhiladelphiaPA United States Helmholtz AI Helmholtz Munich Germany Department of Informatics Technical University Munich Germany TranslaTUM - Central Institute for Translational Cancer Research Technical University of Munich Germany Department of Diagnostic and Interventional Neuroradiology School of Medicine Klinikum rechts der Isar Technical University of Munich Germany San FranciscoCA United States Biomedical Image Analysis and Machine Learning Department of Quantitative Biomedicine University of Zurich Switzerland Department of Neuroradiology Technical University of Munich Munich Germany University of San Diego CA United States Cornell University IthacaNY United States Department of Radiology Northwestern University EvanstonIL United States Duke University Medical Center School of Medicine DurhamNC United States Lab Crestview Radiology Lagos Nigeria Sage Bionetworks United States McGill University MontrealQC Canada Children's National Hospital WashingtonDC United States George Washington University WashingtonDC United State

We describe the design and results from the BraTS 2023 Intracranial Meningioma Segmentation Challenge. The BraTS Meningioma Challenge differed from prior BraTS Glioma challenges in that it focused on meningiomas, which are typically benign extra-axial tumors with diverse radiologic and anatomical presentation and a propensity for multiplicity. Nine participating teams each developed deep-learning automated segmentation models using image data from the largest multi-institutional systematically expert annotated multilabel multi-sequence meningioma MRI dataset to date, which included 1000 training set cases, 141 validation set cases, and 283 hidden test set cases. Each case included T2, T2/FLAIR, T1, and T1Gd brain MRI sequences with associated tumor compartment labels delineating enhancing tumor, non-enhancing tumor, and surrounding non-enhancing T2/FLAIR hyperintensity. Participant automated segmentation models were evaluated and ranked based on a scoring system evaluating lesion-wise metrics including dice similarity coefficient (DSC) and 95% Hausdorff Distance. The top ranked team had a lesion-wise median dice similarity coefficient (DSC) of 0.976, 0.976, and 0.964 for enhancing tumor, tumor core, and whole tumor, respectively and a corresponding average DSC of 0.899, 0.904, and 0.871, respectively. These results serve as state-of-the-art benchmarks for future pre-operative meningioma automated segmentation algorithms. Additionally, we found that 1286 of 1424 cases (90.3%) had at least 1 compartment voxel abutting the edge of the skull-stripped image edge, which requires further investigation into optimal pre-processing face anonymization steps. © 2024, CC BY.

关键词： Tumors

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Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures

arXiv

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arXiv 2022年

作者： Belov, Vladimir Erwin-Grabner, Tracy Gonul, Ali Saffet Amod, Alyssa R. Ojha, Amar Aleman, Andre Dols, Annemiek Schrantee, Anouk Uyar-Demir, Aslihan Harrison, Ben J. Mwangi, Benson Besteher, Bianca Klimes-Dougan, Bonnie Penninx, Brenda W.J.H. Mueller, Bryon A. Zarate, Carlos Davey, Christopher G. Ching, Christopher R.K. Connolly, Colm G. Fu, Cynthia H.Y. Stein, Dan J. Dima, Danai Linden, David E.J. Mehler, David M.A. Pomarol-Clotet, Edith Pozzi, Elena Melloni, Elisa Benedetti, Francesco MacMaster, Frank P. Grabe, Hans J. Völzke, Henry Gotlib, Ian H. Soares, Jair C. Evans, Jennifer W. Sim, Kang Wittfeld, Katharina Cullen, Kathryn Reneman, Liesbeth Oudega, Mardien L. Wright, Margaret J. Portella, Maria J. Sacchet, Matthew D. Li, Meng Aghajani, Moji Wu, Mon-Ju Jaworska, Natalia Jahanshad, Neda van der Wee, Nic J.A. Groenewold, Nynke Hamilton, Paul J. Sämann, Philipp G. Bülow, Robin Poletti, Sara Whittle, Sarah Thomopoulos, Sophia I. van der Werff, Steven J.A. Koopowitz, Sheri-Michelle Lancaster, Thomas Ho, Tiffany C. Yang, Tony T. Basgoze, Zeynep Veltman, Dick J. Schmaal, Lianne Thompson, Paul M. Goya-Maldonado, Roberto Georg-August University Von-Siebold-Str. 5 Goettingen37075 Germany SoCAT Lab Department of Psychiatry School of Medicine Ege University Izmir Turkey Department of Psychiatry & Mental Health University of Cape Town Cape Town South Africa Center for Neuroscience University of Pittsburgh PittsburghPA United States Center for Neural Basis of Cognition University of Pittsburgh PittsburghPA United States Department of Biomedical Sciences of Cells and Systems University Medical Center Groningen University of Groningen Groningen Netherlands Department of Psychiatry Amsterdam UMC Vrije Universiteit Amsterdam Amsterdam Neuroscience Amsterdam Public Health Research Institute Amsterdam Netherlands Amsterdam University Medical Centers Location AMC Department of Radiology and Nuclear Medicine Amsterdam Netherlands Melbourne Neuropsychiatry Centre Department of Psychiatry The University of Melbourne ParkvilleVIC Australia Louis A. Faillace MD Department of Psychiatry and Behavioral Sciences The University of Texas Health Science Center at Houston HoustonTX United States Center of Excellence On Mood Disorders Louis A. Faillace MD Department of Psychiatry and Behavioral Sciences McGovern Medical School The University of Texas Health Science Center HoustonTX United States Department of Psychiatry and Psychotherapy Jena University Hospital Jena Germany Department of Psychology University of Minnesota MinneapolisMN United States Department of Psychiatry and Behavioral Science University of Minnesota Medical School MinneapolisMN United States Section on the Neurobiology and Treatment of Mood Disorders National Institute of Mental Health BethesdaMD United States Imaging Genetics Center Mark & Mary Stevens Neuroimaging and Informatics Institute Keck School of Medicine University of Southern California Marina del ReyCA90274 United States Department of Biomedical Sciences Florida Stateu University TallahasseeFL United States School of Psychology University

Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (n=5,356) to provide a generalizable ML classification benchmark of major depressive disorder (MDD). Using brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD vs healthy controls (HC) with around 62% balanced accuracy, but when harmonizing the data using ComBat balanced accuracy dropped to approximately 52%. Similar results were observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may achieve more encouraging prospects. © 2022, CC BY-NC-ND.

关键词： Brain mapping

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Publisher Correction: Neuroanatomical dimensions in medication-free individuals with major depressive disorder and treatment response to SSRI antidepressant medications or placebo

Nature Mental Health

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Nature Mental Health 2024年 1120页

作者： Cynthia H. Y. Fu Danilo Arnone Roland Zahn Allan H. Young Mathilde Antoniades Guray Erus Jose A. Garcia Yong Fan Haochang Shou Ashish Singh Christos Davatzikos Stephen R. Arnott Stephen C. Strother Taolin Chen Kun Qin Qiyong Gong Ki Sueng Choi Helen S. Mayberg Cherise Chin Fatt Madhukar H. Trivedi Benicio N. Frey Vibe G. Frokjaer Melanie Ganz Gitte M. Knudsen Beata R. Godlewska Catherine J. Harmer Stefanie Hassel Keith Ho Susan Rotzinger Sidney H. Kennedy Andrew M. McIntosh Aleks Stolicyn Heather C. Whalley Matthew D. Sacchet Jonathan Savitz Teresa A. Victor Martin P. Paulus Irina Strigo Duygu Tosun Dongtao Wei Jiang Qiu Toby Wise Ian M. Anderson J. F. William Deakin Rebecca Elliott W. Edward Craighead Boadie W. Dunlop Ian H. Gotlib Chao-Gan Yan School of Psychology University of East London London UK Centre for Affective Disorders Department of Psychological Medicine Institute of Psychiatry Psychology and Neuroscience King’s College London London UK South London and Maudsley NHS Foundation Trust Bethlem Royal Hospital London UK Center for Biomedical Image Computing and Analytics Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Penn Statistics in Imaging and Visualization Endeavor (PennSIVE) Center Department of Biostatistics Epidemiology and Informatics University of Pennsylvania Philadelphia PA USA Rotman Research Institute Baycrest Centre Toronto Ontario Canada Department of Medical Biophysics University of Toronto Toronto Ontario Canada Huaxi MR Research Center Department of Radiology West China Hospital Sichuan University Chengdu China Research Unit of Psychoradiology Chinese Academy of Medical Sciences Chengdu China Department of Radiology Taihe Hospital Hubei University of Medicine Shiyan China Nash Family Center for Advanced Circuit Therapeutics Icahn School of Medicine at Mount Sinai New York NY USA Department of Psychiatry Center for Depression Research and Clinical Care University of Texas Southwestern Medical Center Dallas TX USA Department of Psychiatry and Behavioural Neurosciences McMaster University Hamilton Ontario Canada Mood Disorders Treatment and Research Centre and Women’s Health Concerns Clinic St Joseph’s Healthcare Hamilton Hamilton Ontario Canada Neurobiology Research Unit University Hospital Rigshospitalet Copenhagen Denmark Department of Clinical Medicine Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark Department of Psychiatry Psychiatric Centre Copenhagen Copenhagen Denmark Department of Computer Science University of Copenhagen Copenhagen Denmark Department of Psychiatry University of Oxford Oxford UK Oxford Health NHS Foundation Trust Warneford Hospital Oxford UK Mathison Centre for Me

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