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2. Study design features increase replicability in brain-wide association studies

Author

Kang, Kaidi, Seidlitz, Jakob, Bethlehem, Richard A. I., Xiong, Jiangmei, Jones, Megan T., Mehta, Kahini, Keller, Arielle S., Tao, Ran, Randolph, Anita, Larsen, Bart, Tervo-Clemmens, Brenden, Feczko, Eric, Dominguez, Oscar Miranda, Nelson, Steven M., Schildcrout, Jonathan, Fair, Damien A., Satterthwaite, Theodore D., Alexander-Bloch, Aaron, and Vandekar, Simon

Published
2024
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8. Analysing spatial point patterns in digital pathology: immune cells in high-grade serous ovarian carcinomas

Author

González, Jonatan A., Wrobel, Julia, Vandekar, Simon, and Moraga, Paula

Subjects
Statistics - Applications
Abstract

Multiplex immunofluorescence (mIF) imaging technology facilitates the study of the tumour microenvironment in cancer patients. Due to the capabilities of this emerging bioimaging technique, it is possible to statistically analyse, for example, the co-varying location and functions of multiple different types of immune cells. Complex spatial relationships between different immune cells have been shown to correlate with patient outcomes and may reveal new pathways for targeted immunotherapy treatments. This tutorial reviews methods and procedures relating to spatial point patterns for complex data analysis. We consider tissue cells as a realisation of a spatial point process for each patient. We focus on proper functional descriptors for each observation and techniques that allow us to obtain information about inter-patient variation. Ovarian cancer is the deadliest gynaecological malignancy and can resist chemotherapy treatment effective in cancers. We use a dataset of high-grade serous ovarian cancer samples from 51 patients. We examine the immune cell composition (T cells, B cells, macrophages) within tumours and additional information such as cell classification (tumour or stroma) and other patient clinical characteristics. Our analyses, supported by reproducible software, apply to other digital pathology datasets.

Published
2023

9. RESI: An R Package for Robust Effect Sizes

Author

Jones, Megan, Kang, Kaidi, and Vandekar, Simon

Subjects
Statistics - Computation, Statistics - Methodology
Abstract

Effect size indices are useful parameters that quantify the strength of association and are unaffected by sample size. There are many available effect size parameters and estimators, but it is difficult to compare effect sizes across studies as most are defined for a specific type of population parameter. We recently introduced a new Robust Effect Size Index (RESI) and confidence interval, which is advantageous because it is not model-specific. Here we present the RESI R package, which makes it easy to report the RESI and its confidence interval for many different model classes, with a consistent interpretation across parameters and model types. The package produces coefficient, ANOVA tables, and overall Wald tests for model inputs, appending the RESI estimate and confidence interval to each. The package also includes functions for visualization and conversions to and from other effect size measures. For illustration, we analyze and interpret three different model types., Comment: 25 pages, 2 figures. Submitted to Journal of Statistical Software

Published
2023

11. Accurate confidence interval estimation for non-centrality parameters and effect size indices

Author

Kang, Kaidi, Armstrong, Kristan, Avery, Suzanne, McHugo, Maureen, Heckers, Stephan, and Vandekar, Simon

Subjects
Statistics - Methodology
Abstract

We recently proposed a robust effect size index (RESI) that is related to the non-centrality parameter of a test statistic. RESI is advantageous over common indices because (1) it is widely applicable to many types of data; (2) it can rely on a robust covariance estimate; (3) it can accommodate the existence of nuisance parameters. We provided a consistent estimator for the RESI, however, there is no established confidence interval (CI) estimation procedure for the RESI. Here, we use statistical theory and simulations to evaluate several CI estimation procedures for three estimators of the RESI. Our findings show (1) in contrast to common effect sizes, the robust estimator is consistent for the true effect size; (2) common CI procedures for effect sizes that are non-centrality parameters fail to cover the true effect size at the nominal level. Using the robust estimator along with the proposed bootstrap CI is generally accurate and applicable to conduct consistent estimation and valid inference for the RESI, especially when model assumptions may be violated. Based on the RESI, we propose a general framework for the analysis of effect size (ANOES), such that effect sizes and confidence intervals can be easily reported in an analysis of variance (ANOVA) table format for a wide range of models

Published
2021

12. Faster estimation for constrained gamma mixture models using closed-form estimators

Author

Xiong, Jiangmei, McKinley, Eliot, Roland, Joseph T., Coffey, Robert, Shrubsole, Martha J., Lau, Ken S., and Vandekar, Simon

Subjects
Statistics - Methodology
Abstract

Mixture models are useful in a wide array of applications to identify subpopulations in noisy overlapping distributions. For example, in multiplexed immunofluorescence (mIF), cell image intensities represent expression levels and the cell populations are a noisy mixture of expressed and unexpressed cells. Among mixture models, the gamma mixture model has the strength of being flexible in fitting skewed strictly positive data that occur in many biological measurements. However, the current estimation method uses numerical optimization within the expectation maximization algorithm and is computationally expensive. This makes it infeasible to be applied across many large data sets, as is necessary in mIF data. Powered by a recently developed closed-form estimator for the gamma distribution, we propose a closed-form gamma mixture model that is not only more computationally efficient, but can also incorporate constraints from known biological information to the fitted distribution. We derive the closed-form estimators for the gamma mixture model and use simulations to demonstrate that our model produces comparable results with the current model with significantly less time, and is excellent in constrained model fitting.

Published
2021

13. Atypical Brain Aging and Its Association With Working Memory Performance in Major Depressive Disorder

Author

Adamson, Chris, Adler, Sophie, Alexander-Bloch, Aaron F., Anagnostou, Evdokia, Anderson, Kevin M., Areces-Gonzalez, Ariosky, Astle, Duncan E., Auyeung, Bonnie, Ayub, Muhammad, Bae, Jong Bin, Ball, Gareth, Baron-Cohen, Simon, Beare, Richard, Bedford, Saashi A., Benegal, Vivek, Bethlehem, Richard A.I., Beyer, Frauke, Blangero, John, Cábez, Manuel Blesa, Boardman, James P., Borzage, Matthew, Bosch-Bayard, Jorge F., Bourke, Niall, Bullmore, Edward T., Calhoun, Vince D., Chakravarty, Mallar M., Chen, Christina, Chertavian, Casey, Chetelat, Gaël, Chong, Yap S., Corvin, Aiden, Costantino, Manuela, Courchesne, Eric, Crivello, Fabrice, Cropley, Vanessa L., Crosbie, Jennifer, Crossley, Nicolas, Delarue, Marion, Delorme, Richard, Desrivieres, Sylvane, Devenyi, Gabriel, Di Biase, Maria A., Dolan, Ray, Donald, Kirsten A., Donohoe, Gary, Dorfschmidt, Lena, Dunlop, Katharine, Edwards, Anthony D., Elison, Jed T., Ellis, Cameron T., Elman, Jeremy A., Eyler, Lisa, Fair, Damien A., Fletcher, Paul C., Fonagy, Peter, Franz, Carol E., Galan-Garcia, Lidice, Gholipour, Ali, Giedd, Jay, Gilmore, John H., Glahn, David C., Goodyer, Ian M., Grant, P.E., Groenewold, Nynke A., Gudapati, Shreya, Gunning, Faith M., Gur, Raquel E., Gur, Ruben C., Hammill, Christopher F., Hansson, Oskar, Hedden, Trey, Heinz, Andreas, Henson, Richard N., Heuer, Katja, Hoare, Jacqueline, Holla, Bharath, Holmes, Avram J., Huang, Hao, Ipser, Jonathan, Jack, Clifford R., Jr., Jackowski, Andrea P., Jia, Tianye, Jones, David T., Jones, Peter B., Kahn, Rene S., Karlsson, Hasse, Karlsson, Linnea, Kawashima, Ryuta, Kelley, Elizabeth A., Kern, Silke, Kim, Ki-Woong, Kitzbichler, Manfred G., Kremen, William S., Lalonde, François, Landeau, Brigitte, Lerch, Jason, Lewis, John D., Li, Jiao, Liao, Wei, Liston, Conor, Lombardo, Michael V., Lv, Jinglei, Mallard, Travis T., Marcelis, Machteld, Mathias, Samuel R., Mazoyer, Bernard, McGuire, Philip, Meaney, Michael J., Mechelli, Andrea, Misic, Bratislav, Morgan, Sarah E., Mothersill, David, Ortinau, Cynthia, Ossenkoppele, Rik, Ouyang, Minhui, Palaniyappan, Lena, Paly, Leo, Pan, Pedro M., Pantelis, Christos, Park, Min Tae M., Paus, Tomas, Pausova, Zdenka, Paz-Linares, Deirel, Binette, Alexa Pichet, Pierce, Karen, Qian, Xing, Qiu, Anqi, Raznahan, Armin, Rittman, Timothy, Rodrigue, Amanda, Rollins, Caitlin K., Romero-Garcia, Rafael, Ronan, Lisa, Rosenberg, Monica D., Rowitch, David H., Salum, Giovanni A., Satterthwaite, Theodore D., Schaare, H. Lina, Schabdach, Jenna, Schachar, Russell J., Schöll, Michael, Schultz, Aaron P., Seidlitz, Jakob, Sharp, David, Shinohara, Russell T., Skoog, Ingmar, Smyser, Christopher D., Sperling, Reisa A., Stein, Dan J., Stolicyn, Aleks, Suckling, John, Sullivan, Gemma, Thyreau, Benjamin, Toro, Roberto, Traut, Nicolas, Tsvetanov, Kamen A., Turk-Browne, Nicholas B., Tuulari, Jetro J., Tzourio, Christophe, Vachon-Presseau, Étienne, Valdes-Sosa, Mitchell J., Valdes-Sosa, Pedro A., Valk, Sofie L., van Amelsvoort, Therese, Vandekar, Simon N., Vasung, Lana, Vértes, Petra E., Victoria, Lindsay W., Villeneuve, Sylvia, Villringer, Arno, Vogel, Jacob W., Wagstyl, Konrad, Wang, Yin-Shan S., Warfield, Simon K., Warrier, Varun, Westman, Eric, Westwater, Margaret L., Whalley, Heather C., White, Simon R., Witte, A. Veronica, Yang, Ning, Yeo, B.T. Thomas, Yun, Hyuk Jin, Zalesky, Andrew, Zar, Heather J., Zettergren, Anna, Zhou, Juan H., Ziauddeen, Hisham, Zimmerman, Dabriel, Zugman, Andre, Zuo, Xi-Nian N., Ho, Natalie C.W., Nogovitsyn, Nikita, Metzak, Paul, Ballester, Pedro L., Hassel, Stefanie, Rotzinger, Susan, Poppenk, Jordan, Lam, Raymond W., Taylor, Valerie H., Milev, Roumen, Frey, Benicio N., Harkness, Kate L., Addington, Jean, and Kennedy, Sidney H.

Published
2024
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17. Diagnostic and Physical Effects in Parasympathetic Response to Social Evaluation in Youth with and without Autism Spectrum Disorder

Author

Muscatello, Rachael A., Kim, Ahra, Vandekar, Simon, and Corbett, Blythe A.

Abstract

Individuals with autism spectrum disorder (ASD) may demonstrate atypical autonomic (ANS) responses; however, research remains inconsistent. This study examined parasympathetic response during social evaluation in 241 youth (10-13 years) with ASD (n = 138) or typical development (TD; n = 103). Diagnosis, age, pubertal development, and body mass index (BMI) were hypothesized to be associated with ANS function. Linear mixed effects models demonstrated lower RSA in ASD relative to TD in a base model with no covariates. However, when accounting for differences in BMI, there was no evidence of atypical parasympathetic regulation in youth with ASD. As lower parasympathetic regulation may increase susceptibility for a number of conditions, it will be important to elucidate the link between BMI and the ANS, especially in ASD.

Published
2022
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18. Molecular cartography uncovers evolutionary and microenvironmental dynamics in sporadic colorectal tumors

Author

Heiser, Cody N., Simmons, Alan J., Revetta, Frank, McKinley, Eliot T., Ramirez-Solano, Marisol A., Wang, Jiawei, Kaur, Harsimran, Shao, Justin, Ayers, Gregory D., Wang, Yu, Glass, Sarah E., Tasneem, Naila, Chen, Zhengyi, Qin, Yan, Kim, William, Rolong, Andrea, Chen, Bob, Vega, Paige N., Drewes, Julia L., Markham, Nicholas O., Saleh, Nabil, Nikolos, Fotis, Vandekar, Simon, Jones, Angela L., Washington, M. Kay, Roland, Joseph T., Chan, Keith S., Schürpf, Thomas, Sears, Cynthia L., Liu, Qi, Shrubsole, Martha J., Coffey, Robert J., and Lau, Ken S.

Published
2023
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21. A Robust Effect Size Index

Author

Vandekar, Simon, Tao, Ran, and Blume, Jeffrey

Subjects
Statistics - Methodology
Abstract

Effect size indices are useful tools in study design and reporting because they are unitless measures of association strength that do not depend on sample size. Existing effect size indices are developed for particular parametric models or population parameters. Here, we propose a robust effect size index based on M-estimators. This approach yields an index that is very generalizable because it is unitless across a wide range of models. We demonstrate that the new index is a function of Cohen's $d$, $R^2$, and standardized log odds ratio when each of the parametric models is correctly specified. We show that existing effect size estimators are biased when the parametric models are incorrect (e.g. under unknown heteroskedasticity). We provide simple formulas to compute power and sample size and use simulations to assess the bias and variance of the effect size estimator in finite samples. Because the new index is invariant across models, it has the potential to make communication and comprehension of effect size uniform across the behavioral sciences.

Published
2019
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22. Robust Spatial Extent Inference with a Semiparametric Bootstrap Joint Testing Procedure

Author

Vandekar, Simon N., Satterthwaite, Theodore D., Xia, Cedric H., Ruparel, Kosha, Gur, Ruben C., Gur, Raquel E., and Shinohara, Russell T.

Subjects
Statistics - Methodology
Abstract

Spatial extent inference (SEI) is widely used across neuroimaging modalities to study brain-phenotype associations that inform our understanding of disease. Recent studies have shown that Gaussian random field (GRF) based tools can have inflated family-wise error rates (FWERs). This has led to fervent discussion as to which preprocessing steps are necessary to control the FWER using GRF-based SEI. The failure of GRF-based methods is due to unrealistic assumptions about the covariance function of the imaging data. The permutation procedure is the most robust SEI tool because it estimates the covariance function from the imaging data. However, the permutation procedure can fail because its assumption of exchangeability is violated in many imaging modalities. Here, we propose the (semi-) parametric bootstrap joint (PBJ; sPBJ) testing procedures that are designed for SEI of multilevel imaging data. The sPBJ procedure uses a robust estimate of the covariance function, which yields consistent estimates of standard errors, even if the covariance model is misspecified. We use our methods to study the association between performance and executive functioning in a working fMRI study. The sPBJ procedure is robust to variance misspecification and maintains nominal FWER in small samples, in contrast to the GRF methods. The sPBJ also has equal or superior power to the PBJ and permutation procedures. We provide an R package https://github.com/simonvandekar/pbj to perform inference using the PBJ and sPBJ procedures

Published
2018

27. Interpretable High-Dimensional Inference Via Score Projection with an Application in Neuroimaging

Author

Vandekar, Simon N., Reiss, Philip T., and Shinohara, Russell T.

Subjects
Mathematics - Statistics Theory
Abstract

In the fields of neuroimaging and genetics, a key goal is testing the association of a single outcome with a very high-dimensional imaging or genetic variable. Often, summary measures of the high-dimensional variable are created to sequentially test and localize the association with the outcome. In some cases, the results for summary measures are significant, but subsequent tests used to localize differences are underpowered and do not identify regions associated with the outcome. Here, we propose a generalization of Rao's score test based on projecting the score statistic onto a linear subspace of a high-dimensional parameter space. In addition, we provide methods to localize signal in the high-dimensional space by projecting the scores to the subspace where the score test was performed. This allows for inference in the high-dimensional space to be performed on the same degrees of freedom as the score test, effectively reducing the number of comparisons. Simulation results demonstrate the test has competitive power relative to others commonly used. We illustrate the method by analyzing a subset of the Alzheimer's Disease Neuroimaging Initiative dataset. Results suggest cortical thinning of the frontal and temporal lobes may be a useful biological marker of Alzheimer's risk.

Published
2017
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28. Faster Family-wise Error Control for Neuroimaging with a Parametric Bootstrap

Author

Vandekar, Simon N., Satterthwaite, Theodore D., Rosen, Adon, Ciric, Rastko, Roalf, David R., Ruparel, Kosha, Gur, Ruben C., Gur, Raquel E., and Shinohara, Russell T.

Subjects
Statistics - Methodology
Abstract

In neuroimaging, hundreds to hundreds of thousands of tests are performed across a set of brain regions or all locations in an image. Recent studies have shown that the most common family-wise error (FWE) controlling procedures in imaging, which rely on classical mathematical inequalities or Gaussian random field theory, yield FWE rates that are far from the nominal level. Depending on the approach used, the FWER can be exceedingly small or grossly inflated. Given the widespread use of neuroimaging as a tool for understanding neurological and psychiatric disorders, it is imperative that reliable multiple testing procedures are available. To our knowledge, only permutation joint testing procedures have been shown to reliably control the FWER at the nominal level. However, these procedures are computationally intensive due to the increasingly available large sample sizes and dimensionality of the images, and analyses can take days to complete. Here, we develop a parametric bootstrap joint testing procedure. The parametric bootstrap procedure works directly with the test statistics, which leads to much faster estimation of adjusted \emph{p}-values than resampling-based procedures while reliably controlling the FWER in sample sizes available in many neuroimaging studies. We demonstrate that the procedure controls the FWER in finite samples using simulations, and present region- and voxel-wise analyses to test for sex differences in developmental trajectories of cerebral blood flow.

Published
2017
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29. Developmental coupling of cerebral blood flow and fMRI fluctuations in youth

Author

Baller, Erica B., Valcarcel, Alessandra M., Adebimpe, Azeez, Alexander-Bloch, Aaron, Cui, Zaixu, Gur, Ruben C., Gur, Raquel E., Larsen, Bart L., Linn, Kristin A., O’Donnell, Carly M., Pines, Adam R., Raznahan, Armin, Roalf, David.R., Sydnor, Valerie J., Tapera, Tinashe M., Tisdall, M. Dylan, Vandekar, Simon, Xia, Cedric H., Detre, John A., Shinohara, Russell T., and Satterthwaite, Theodore D.

Published
2022
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31. Normative brain size variation and brain shape diversity in humans

Author

Reardon, PK, Seidlitz, Jakob, Vandekar, Simon, Liu, Siyuan, Patel, Raihaan, Park, Min Tae M, Alexander-Bloch, Aaron, Clasen, Liv S, Blumenthal, Jonathan D, Lalonde, Francois M, Giedd, Jay N, Gur, Ruben C, Gur, Raquel E, Lerch, Jason P, Chakravarty, M Mallar, Satterthwaite, Theodore D, Shinohara, Russell T, and Raznahan, Armin

Subjects
Biological Psychology, History, Heritage and Archaeology, Human Society, Archaeology, Anthropology, Psychology, Pediatric, Neurosciences, 1.1 Normal biological development and functioning, Underpinning research, Neurological, Biological Evolution, Brain, Humans, Neuroimaging, Organ Size, General Science & Technology
Abstract

Brain size variation over primate evolution and human development is associated with shifts in the proportions of different brain regions. Individual brain size can vary almost twofold among typically developing humans, but the consequences of this for brain organization remain poorly understood. Using in vivo neuroimaging data from more than 3000 individuals, we find that larger human brains show greater areal expansion in distributed frontoparietal cortical networks and related subcortical regions than in limbic, sensory, and motor systems. This areal redistribution recapitulates cortical remodeling across evolution, manifests by early childhood in humans, and is linked to multiple markers of heightened metabolic cost and neuronal connectivity. Thus, human brain shape is systematically coupled to naturally occurring variations in brain size through a scaling map that integrates spatiotemporally diverse aspects of neurobiology.

Published
2018

33. Biological variation in cervical spinal cord MRI morphometry in healthy individuals and people with multiple sclerosis

Author

Cook, Sarah R., primary, Vasamreddy, Kritin, additional, Combes, Anna, additional, Vandekar, Simon, additional, Visagie, Mereze, additional, Houston, Delaney, additional, Wald, Lily, additional, Kumar, Ashwin, additional, McGrath, Megan, additional, McKnight, Colin D., additional, Bagnato, Francesca, additional, Smith, Seth A., additional, and O'Grady, Kristin P., additional

Published
2024
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37. Differential pre-malignant programs and microenvironment chart distinct paths to malignancy in human colorectal polyps

Author

Chen, Bob, Scurrah, Cherie’ R., McKinley, Eliot T., Simmons, Alan J., Ramirez-Solano, Marisol A., Zhu, Xiangzhu, Markham, Nicholas O., Heiser, Cody N., Vega, Paige N., Rolong, Andrea, Kim, Hyeyon, Sheng, Quanhu, Drewes, Julia L., Zhou, Yuan, Southard-Smith, Austin N., Xu, Yanwen, Ro, James, Jones, Angela L., Revetta, Frank, Berry, Lynne D., Niitsu, Hiroaki, Islam, Mirazul, Pelka, Karin, Hofree, Matan, Chen, Jonathan H., Sarkizova, Siranush, Ng, Kimmie, Giannakis, Marios, Boland, Genevieve M., Aguirre, Andrew J., Anderson, Ana C., Rozenblatt-Rosen, Orit, Regev, Aviv, Hacohen, Nir, Kawasaki, Kenta, Sato, Toshiro, Goettel, Jeremy A., Grady, William M., Zheng, Wei, Washington, M. Kay, Cai, Qiuyin, Sears, Cynthia L., Goldenring, James R., Franklin, Jeffrey L., Su, Timothy, Huh, Won Jae, Vandekar, Simon, Roland, Joseph T., Liu, Qi, Coffey, Robert J., Shrubsole, Martha J., and Lau, Ken S.

Published
2021
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38. Imaging local genetic influences on cortical folding

Author

Alexander-Bloch, Aaron F., Raznahan, Armin, Vandekar, Simon N., Seidlitz, Jakob, Lu, Zhixin, Mathias, Samuel R., Knowles, Emma, Mollon, Josephine, Rodrigue, Amanda, Curran, Joanne E., Görring, Harald H. H., Satterthwaite, Theodore D., Gur, Raquel E., Bassett, Danielle S., Hoftman, Gil D., Pearlson, Godfrey, Shinohara, Russell T., Liu, Siyuan, Fox, Peter T., Almasy, Laura, Blangero, John, and Glahn, David C.

Published
2020

45. The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution

Author

Aberle, Denise, Achilefu, Samuel I., Ademuyiwa, Foluso O., Adey, Andrew C., Aft, Rebecca L., Agarwal, Rachana, Aguilar, Ruben A., Alikarami, Fatemeh, Allaj, Viola, Amos, Christopher, Anders, Robert A., Angelo, Michael R., Anton, Kristen, Ashenberg, Orr, Aster, Jon C., Babur, Ozgun, Bahmani, Amir, Balsubramani, Akshay, Barrett, David, Beane, Jennifer, Bender, Diane E., Bernt, Kathrin, Berry, Lynne, Betts, Courtney B., Bletz, Julie, Blise, Katie, Boire, Adrienne, Boland, Genevieve, Borowsky, Alexander, Bosse, Kristopher, Bott, Matthew, Boyden, Ed, Brooks, James, Bueno, Raphael, Burlingame, Erik A., Cai, Qiuyin, Campbell, Joshua, Caravan, Wagma, Cerami, Ethan, Chaib, Hassan, Chan, Joseph M., Chang, Young Hwan, Chatterjee, Deyali, Chaudhary, Ojasvi, Chen, Alyce A., Chen, Bob, Chen, Changya, Chen, Chia-hui, Chen, Feng, Chen, Yu-An, Chheda, Milan G., Chin, Koei, Chiu, Roxanne, Chu, Shih-Kai, Chuaqui, Rodrigo, Chun, Jaeyoung, Cisneros, Luis, Coffey, Robert J., Colditz, Graham A., Cole, Kristina, Collins, Natalie, Contrepois, Kevin, Coussens, Lisa M., Creason, Allison L., Crichton, Daniel, Curtis, Christina, Davidsen, Tanja, Davies, Sherri R., de Bruijn, Ino, Dellostritto, Laura, De Marzo, Angelo, Demir, Emek, DeNardo, David G., Diep, Dinh, Ding, Li, Diskin, Sharon, Doan, Xengie, Drewes, Julia, Dubinett, Stephen, Dyer, Michael, Egger, Jacklynn, Eng, Jennifer, Engelhardt, Barbara, Erwin, Graham, Esplin, Edward D., Esserman, Laura, Felmeister, Alex, Feiler, Heidi S., Fields, Ryan C., Fisher, Stephen, Flaherty, Keith, Flournoy, Jennifer, Ford, James M., Fortunato, Angelo, Frangieh, Allison, Frye, Jennifer L., Fulton, Robert S., Galipeau, Danielle, Gan, Siting, Gao, Jianjiong, Gao, Long, Gao, Peng, Gao, Vianne R., Geiger, Tim, George, Ajit, Getz, Gad, Ghosh, Sharmistha, Giannakis, Marios, Gibbs, David L., Gillanders, William E., Goecks, Jeremy, Goedegebuure, Simon P., Gould, Alanna, Gowers, Kate, Gray, Joe W., Greenleaf, William, Gresham, Jeremy, Guerriero, Jennifer L., Guha, Tuhin K., Guimaraes, Alexander R., Guinney, Justin, Gutman, David, Hacohen, Nir, Hanlon, Sean, Hansen, Casey R., Harismendy, Olivier, Harris, Kathleen A., Hata, Aaron, Hayashi, Akimasa, Heiser, Cody, Helvie, Karla, Herndon, John M., Hirst, Gilliam, Hodi, Frank, Hollmann, Travis, Horning, Aaron, Hsieh, James J., Hughes, Shannon, Huh, Won Jae, Hunger, Stephen, Hwang, Shelley E., Iacobuzio-Donahue, Christine A., Ijaz, Heba, Izar, Benjamin, Jacobson, Connor A., Janes, Samuel, Jané-Valbuena, Judit, Jayasinghe, Reyka G., Jiang, Lihua, Johnson, Brett E., Johnson, Bruce, Ju, Tao, Kadara, Humam, Kaestner, Klaus, Kagan, Jacob, Kalinke, Lukas, Keith, Robert, Khan, Aziz, Kibbe, Warren, Kim, Albert H., Kim, Erika, Kim, Junhyong, Kolodzie, Annette, Kopytra, Mateusz, Kotler, Eran, Krueger, Robert, Krysan, Kostyantyn, Kundaje, Anshul, Ladabaum, Uri, Lake, Blue B., Lam, Huy, Laquindanum, Rozelle, Lau, Ken S., Laughney, Ashley M., Lee, Hayan, Lenburg, Marc, Leonard, Carina, Leshchiner, Ignaty, Levy, Rochelle, Li, Jerry, Lian, Christine G., Lim, Kian-Huat, Lin, Jia-Ren, Lin, Yiyun, Liu, Qi, Liu, Ruiyang, Lively, Tracy, Longabaugh, William J.R., Longacre, Teri, Ma, Cynthia X., Macedonia, Mary Catherine, Madison, Tyler, Maher, Christopher A., Maitra, Anirban, Makinen, Netta, Makowski, Danika, Maley, Carlo, Maliga, Zoltan, Mallo, Diego, Maris, John, Markham, Nick, Marks, Jeffrey, Martinez, Daniel, Mashl, Robert J., Masilionais, Ignas, Mason, Jennifer, Massagué, Joan, Massion, Pierre, Mattar, Marissa, Mazurchuk, Richard, Mazutis, Linas, Mazzilli, Sarah A., McKinley, Eliot T., McMichael, Joshua F., Merrick, Daniel, Meyerson, Matthew, Miessner, Julia R., Mills, Gordon B., Mills, Meredith, Mondal, Suman B., Mori, Motomi, Mori, Yuriko, Moses, Elizabeth, Mosse, Yael, Muhlich, Jeremy L., Murphy, George F., Navin, Nicholas E., Nawy, Tal, Nederlof, Michel, Ness, Reid, Nevins, Stephanie, Nikolov, Milen, Nirmal, Ajit Johnson, Nolan, Garry, Novikov, Edward, Oberdoerffer, Philipp, O’Connell, Brendan, Offin, Michael, Oh, Stephen T., Olson, Anastasiya, Ooms, Alex, Ossandon, Miguel, Owzar, Kouros, Parmar, Swapnil, Patel, Tasleema, Patti, Gary J., Pe’er, Dana, Pe'er, Itsik, Peng, Tao, Persson, Daniel, Petty, Marvin, Pfister, Hanspeter, Polyak, Kornelia, Pourfarhangi, Kamyar, Puram, Sidharth V., Qiu, Qi, Quintanal-Villalonga, Álvaro, Raj, Arjun, Ramirez-Solano, Marisol, Rashid, Rumana, Reeb, Ashley N., Regev, Aviv, Reid, Mary, Resnick, Adam, Reynolds, Sheila M., Riesterer, Jessica L., Rodig, Scott, Roland, Joseph T., Rosenfield, Sonia, Rotem, Asaf, Roy, Sudipta, Rozenblatt-Rosen, Orit, Rudin, Charles M., Ryser, Marc D., Santagata, Sandro, Santi-Vicini, Maria, Sato, Kazuhito, Schapiro, Denis, Schrag, Deborah, Schultz, Nikolaus, Sears, Cynthia L., Sears, Rosalie C., Sen, Subrata, Sen, Triparna, Shalek, Alex, Sheng, Jeff, Sheng, Quanhu, Shoghi, Kooresh I., Shrubsole, Martha J., Shyr, Yu, Sibley, Alexander B., Siex, Kiara, Simmons, Alan J., Singer, Dinah S., Sivagnanam, Shamilene, Slyper, Michal, Snyder, Michael P., Sokolov, Artem, Song, Sheng-Kwei, Sorger, Peter K., Southard-Smith, Austin, Spira, Avrum, Srivastava, Sudhir, Stein, Janet, Storm, Phillip, Stover, Elizabeth, Strand, Siri H., Su, Timothy, Sudar, Damir, Sullivan, Ryan, Surrey, Lea, Suvà, Mario, Tan, Kai, Terekhanova, Nadezhda V., Ternes, Luke, Thammavong, Lisa, Thibault, Guillaume, Thomas, George V., Thorsson, Vésteinn, Todres, Ellen, Tran, Linh, Tyler, Madison, Uzun, Yasin, Vachani, Anil, Van Allen, Eliezer, Vandekar, Simon, Veis, Deborah J., Vigneau, Sébastien, Vossough, Arastoo, Waanders, Angela, Wagle, Nikhil, Wang, Liang-Bo, Wendl, Michael C., West, Robert, Williams, Elizabeth H., Wu, Chi-yun, Wu, Hao, Wu, Hung-Yi, Wyczalkowski, Matthew A., Xie, Yubin, Yang, Xiaolu, Yapp, Clarence, Yu, Wenbao, Yuan, Yinyin, Zhang, Dadong, Zhang, Kun, Zhang, Mianlei, Zhang, Nancy, Zhang, Yantian, Zhao, Yanyan, Zhou, Daniel Cui, Zhou, Zilu, Zhu, Houxiang, Zhu, Qin, Zhu, Xiangzhu, Zhu, Yuankun, Zhuang, Xiaowei, Hupalowska, Anna, Rood, Jennifer E., Hanlon, Sean E., Hughes, Shannon K., Hwang, E. Shelley, Johnson, Bruce E., Shalek, Alex K., Spira, Avrum E., and West, Robert B.

Published
2020
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46. Atypical brain aging and its association with working memory performance in major depressive disorder

Author

Ho, Natalie C.W., primary, Bethlehem, Richard AI., additional, Seidlitz, Jakob, additional, Nogovitsyn, Nikita, additional, Metzak, Paul, additional, Ballester, Pedro L., additional, Hassel, Stefanie, additional, Rotzinger, Susan, additional, Poppenk, Jordan, additional, Lam, Raymond W., additional, Taylor, Valerie H., additional, Milev, Roumen, additional, Adamson, Chris, additional, Adler, Sophie, additional, Alexander-Bloch, Aaron F., additional, Anagnostou, Evdokia, additional, Anderson, Kevin M., additional, Areces-Gonzalez, Ariosky, additional, Astle, Duncan E., additional, Auyeung, Bonnie, additional, Ayub, Muhammad, additional, Bae, Jong Bin, additional, Ball, Gareth, additional, Baron-Cohen, Simon, additional, Beare, Richard, additional, Bedford, Saashi A., additional, Benegal, Vivek, additional, Bethlehem, Richard A.I., additional, Beyer, Frauke, additional, Blangero, John, additional, Blesa Cábez, Manuel, additional, Boardman, James P., additional, Borzage, Matthew, additional, Bosch-Bayard, Jorge F., additional, Bourke, Niall, additional, Bullmore, Edward T., additional, Calhoun, Vince D., additional, Chakravarty, Mallar M., additional, Chen, Christina, additional, Chertavian, Casey, additional, Chetelat, Gaël, additional, Chong, Yap S., additional, Corvin, Aiden, additional, Costantino, Manuela, additional, Courchesne, Eric, additional, Crivello, Fabrice, additional, Cropley, Vanessa L., additional, Crosbie, Jennifer, additional, Crossley, Nicolas, additional, Delarue, Marion, additional, Delorme, Richard, additional, Desrivieres, Sylvane, additional, Devenyi, Gabriel, additional, Di Biase, Maria A., additional, Dolan, Ray, additional, Donald, Kirsten A., additional, Donohoe, Gary, additional, Dorfschmidt, Lena, additional, Dunlop, Katharine, additional, Edwards, Anthony D., additional, Elison, Jed T., additional, Ellis, Cameron T., additional, Elman, Jeremy A., additional, Eyler, Lisa, additional, Fair, Damien A., additional, Fletcher, Paul C., additional, Fonagy, Peter, additional, Franz, Carol E., additional, Galan-Garcia, Lidice, additional, Gholipour, Ali, additional, Giedd, Jay, additional, Gilmore, John H., additional, Glahn, David C., additional, Goodyer, Ian M., additional, Grant, P.E., additional, Groenewold, Nynke A., additional, Gudapati, Shreya, additional, Gunning, Faith M., additional, Gur, Raquel E., additional, Gur, Ruben C., additional, Hammill, Christopher F., additional, Hansson, Oskar, additional, Hedden, Trey, additional, Heinz, Andreas, additional, Henson, Richard N., additional, Heuer, Katja, additional, Hoare, Jacqueline, additional, Holla, Bharath, additional, Holmes, Avram J., additional, Huang, Hao, additional, Ipser, Jonathan, additional, Jack, Clifford R., additional, Jackowski, Andrea P., additional, Jia, Tianye, additional, Jones, David T., additional, Jones, Peter B., additional, Kahn, Rene S., additional, Karlsson, Hasse, additional, Karlsson, Linnea, additional, Kawashima, Ryuta, additional, Kelley, Elizabeth A., additional, Kern, Silke, additional, Kim, Ki-Woong, additional, Kitzbichler, Manfred G., additional, Kremen, William S., additional, Lalonde, François, additional, Landeau, Brigitte, additional, Lerch, Jason, additional, Lewis, John D., additional, Li, Jiao, additional, Liao, Wei, additional, Liston, Conor, additional, Lombardo, Michael V., additional, Lv, Jinglei, additional, Mallard, Travis T., additional, Marcelis, Machteld, additional, Mathias, Samuel R., additional, Mazoyer, Bernard, additional, McGuire, Philip, additional, Meaney, Michael J., additional, Mechelli, Andrea, additional, Misic, Bratislav, additional, Morgan, Sarah E., additional, Mothersill, David, additional, Ortinau, Cynthia, additional, Ossenkoppele, Rik, additional, Ouyang, Minhui, additional, Palaniyappan, Lena, additional, Paly, Leo, additional, Pan, Pedro M., additional, Pantelis, Christos, additional, Park, Min Tae M., additional, Paus, Tomas, additional, Pausova, Zdenka, additional, Paz-Linares, Deirel, additional, Pichet Binette, Alexa, additional, Pierce, Karen, additional, Qian, Xing, additional, Qiu, Anqi, additional, Raznahan, Armin, additional, Rittman, Timothy, additional, Rodrigue, Amanda, additional, Rollins, Caitlin K., additional, Romero-Garcia, Rafael, additional, Ronan, Lisa, additional, Rosenberg, Monica D., additional, Rowitch, David H., additional, Salum, Giovanni A., additional, Satterthwaite, Theodore D., additional, Schaare, H. Lina, additional, Schabdach, Jenna, additional, Schachar, Russell J., additional, Schöll, Michael, additional, Schultz, Aaron P., additional, Sharp, David, additional, Shinohara, Russell T., additional, Skoog, Ingmar, additional, Smyser, Christopher D., additional, Sperling, Reisa A., additional, Stein, Dan J., additional, Stolicyn, Aleks, additional, Suckling, John, additional, Sullivan, Gemma, additional, Thyreau, Benjamin, additional, Toro, Roberto, additional, Traut, Nicolas, additional, Tsvetanov, Kamen A., additional, Turk-Browne, Nicholas B., additional, Tuulari, Jetro J., additional, Tzourio, Christophe, additional, Vachon-Presseau, Étienne, additional, Valdes-Sosa, Mitchell J., additional, Valdes-Sosa, Pedro A., additional, Valk, Sofie L., additional, van Amelsvoort, Therese, additional, Vandekar, Simon N., additional, Vasung, Lana, additional, Vértes, Petra E., additional, Victoria, Lindsay W., additional, Villeneuve, Sylvia, additional, Villringer, Arno, additional, Vogel, Jacob W., additional, Wagstyl, Konrad, additional, Wang, Yin-Shan S., additional, Warfield, Simon K., additional, Warrier, Varun, additional, Westman, Eric, additional, Westwater, Margaret L., additional, Whalley, Heather C., additional, White, Simon R., additional, Witte, A. Veronica, additional, Yang, Ning, additional, Yeo, B.T. Thomas, additional, Yun, Hyuk Jin, additional, Zalesky, Andrew, additional, Zar, Heather J., additional, Zettergren, Anna, additional, Zhou, Juan H., additional, Ziauddeen, Hisham, additional, Zimmerman, Dabriel, additional, Zugman, Andre, additional, Zuo, Xi-Nian N., additional, Frey, Benicio N., additional, Harkness, Kate L., additional, Addington, Jean, additional, and Kennedy, Sidney H., additional

Published
2024
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49. MIMoSA: An Approach to Automatically Segment T2 Hyperintense and T1 Hypointense Lesions in Multiple Sclerosis

Author

Valcarcel, Alessandra M., Linn, Kristin A., Khalid, Fariha, Vandekar, Simon N., Tauhid, Shahamat, Satterthwaite, Theodore D., Muschelli, John, Bakshi, Rohit, Shinohara, Russell T., Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Crimi, Alessandro, editor, Bakas, Spyridon, editor, Kuijf, Hugo, editor, Keyvan, Farahani, editor, Reyes, Mauricio, editor, and van Walsum, Theo, editor

Published
2019
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