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20,230 results on '"Thompson, Paul"'

351. Overview of Scanner Invariant Representations

Author

Moyer, Daniel, Steeg, Greg Ver, and Thompson, Paul M.

Subjects
Quantitative Biology - Quantitative Methods, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Pooled imaging data from multiple sources is subject to bias from each source. Studies that do not correct for these scanner/site biases at best lose statistical power, and at worst leave spurious correlations in their data. Estimation of the bias effects is non-trivial due to the paucity of data with correspondence across sites, so called "traveling phantom" data, which is expensive to collect. Nevertheless, numerous solutions leveraging direct correspondence have been proposed. In contrast to this, Moyer et al. (2019) proposes an unsupervised solution using invariant representations, one which does not require correspondence and thus does not require paired images. By leveraging the data processing inequality, an invariant representation can then be used to create an image reconstruction that is uninformative of its original source, yet still faithful to the underlying structure. In the present abstract we provide an overview of this method., Comment: Accepted as a short paper in MIDL 2020. In accordance with the MIDL 2020 Call for Papers, this short paper is an overview of an already published work arXiv:1904.05375, and was submitted to MIDL in order to allow presentation and discussion at the meeting

Published
2020

367. Herb haven

Author

Thompson, Paul

Published
2003

370. Inside out

Author

Thompson, Paul

Published
2003

372. Prioritizing Genetic Contributors to Cortical Alterations in 22q11.2 Deletion Syndrome Using Imaging Transcriptomics

Author

Forsyth, Jennifer K, Mennigen, Eva, Lin, Amy, Sun, Daqiang, Vajdi, Ariana, Kushan-Wells, Leila, Ching, Christopher RK, Villalon-Reina, Julio E, Thompson, Paul M, Jonas, Rachel K, Pacheco-Hansen, Laura, Bakker, Geor, van Amelsvoort, Therese, Antshel, Kevin M, Fremont, Wanda, Kates, Wendy R, Campbell, Linda E, McCabe, Kathryn L, Craig, Michael C, Daly, Eileen, Gudbrandsen, Maria, Murphy, Clodagh M, Murphy, Declan G, Murphy, Kieran C, Fiksinski, Ania, Koops, Sanne, Vorstman, Jacob, Crowley, T Blaine, Emanuel, Beverly S, Gur, Raquel E, McDonald-McGinn, Donna M, Roalf, David R, Ruparel, Kosha, Schmitt, J Eric, Zackai, Elaine H, Durdle, Courtney A, Goodrich-Hunsaker, Naomi J, Simon, Tony J, Bassett, Anne S, Butcher, Nancy J, Chow, Eva WC, Vila-Rodriguez, Fidel, Cunningham, Adam, Doherty, Joanne L, Linden, David E, Moss, Hayley, Owen, Michael J, van den Bree, Marianne, Crossley, Nicolas A, Repetto, Gabriela M, and Bearden, Carrie E

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Research, Genetics, Pediatric, Biotechnology, 2.1 Biological and endogenous factors, Aetiology, 22q11 Deletion Syndrome, Brain Cortical Thickness, Case-Control Studies, Cerebral Cortex, DNA Copy Number Variations, Gene Expression Profiling, Gene Expression Regulation, Developmental, Haploinsufficiency, Humans, Magnetic Resonance Imaging, MicroRNAs, Mitochondrial Proteins, RNA-Binding Proteins, Receptors, Purinergic P2, copy number variant, cortical thickness, DGCR8, gene expression, surface area, 22q11.2 ENIGMA Consortium, Psychology, Cognitive Sciences, Experimental Psychology, Biological psychology, Cognitive and computational psychology
Abstract

22q11.2 deletion syndrome (22q11DS) results from a hemizygous deletion that typically spans 46 protein-coding genes and is associated with widespread alterations in brain morphology. The specific genetic mechanisms underlying these alterations remain unclear. In the 22q11.2 ENIGMA Working Group, we characterized cortical alterations in individuals with 22q11DS (n = 232) versus healthy individuals (n = 290) and conducted spatial convergence analyses using gene expression data from the Allen Human Brain Atlas to prioritize individual genes that may contribute to altered surface area (SA) and cortical thickness (CT) in 22q11DS. Total SA was reduced in 22q11DS (Z-score deviance = -1.04), with prominent reductions in midline posterior and lateral association regions. Mean CT was thicker in 22q11DS (Z-score deviance = +0.64), with focal thinning in a subset of regions. Regional expression of DGCR8 was robustly associated with regional severity of SA deviance in 22q11DS; AIFM3 was also associated with SA deviance. Conversely, P2RX6 was associated with CT deviance. Exploratory analysis of gene targets of microRNAs previously identified as down-regulated due to DGCR8 deficiency suggested that DGCR8 haploinsufficiency may contribute to altered corticogenesis in 22q11DS by disrupting cell cycle modulation. These findings demonstrate the utility of combining neuroanatomic and transcriptomic datasets to derive molecular insights into complex, multigene copy number variants.

Published
2021

373. Structural brain imaging studies offer clues about the effects of the shared genetic etiology among neuropsychiatric disorders

Author

Radonjić, Nevena V, Hess, Jonathan L, Rovira, Paula, Andreassen, Ole, Buitelaar, Jan K, Ching, Christopher RK, Franke, Barbara, Hoogman, Martine, Jahanshad, Neda, McDonald, Carrie, Schmaal, Lianne, Sisodiya, Sanjay M, Stein, Dan J, van den Heuvel, Odile A, van Erp, Theo GM, van Rooij, Daan, Veltman, Dick J, Thompson, Paul, and Faraone, Stephen V

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Neurosciences, Serious Mental Illness, Genetics, Brain Disorders, Clinical Research, Autism, Intellectual and Developmental Disabilities (IDD), Schizophrenia, Mental Health, Prevention, Aetiology, 2.1 Biological and endogenous factors, Mental health, Attention Deficit Disorder with Hyperactivity, Autism Spectrum Disorder, Brain, Depressive Disorder, Major, Humans, Neuroimaging, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Genomewide association studies have found significant genetic correlations among many neuropsychiatric disorders. In contrast, we know much less about the degree to which structural brain alterations are similar among disorders and, if so, the degree to which such similarities have a genetic etiology. From the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium, we acquired standardized mean differences (SMDs) in regional brain volume and cortical thickness between cases and controls. We had data on 41 brain regions for: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), epilepsy, major depressive disorder (MDD), obsessive compulsive disorder (OCD), and schizophrenia (SCZ). These data had been derived from 24,360 patients and 37,425 controls. The SMDs were significantly correlated between SCZ and BD, OCD, MDD, and ASD. MDD was positively correlated with BD and OCD. BD was positively correlated with OCD and negatively correlated with ADHD. These pairwise correlations among disorders were correlated with the corresponding pairwise correlations among disorders derived from genomewide association studies (r = 0.494). Our results show substantial similarities in sMRI phenotypes among neuropsychiatric disorders and suggest that these similarities are accounted for, in part, by corresponding similarities in common genetic variant architectures.

Published
2021

374. Coordinating Global Multi-Site Studies of Military-Relevant Traumatic Brain Injury: Opportunities, Challenges, and Harmonization Guidelines

Author

Tate, David F, Dennis, Emily L, Adams, John T, Adamson, Maheen M, Belanger, Heather G, Bigler, Erin D, Bouchard, Heather C, Clark, Alexandra L, Delano-Wood, Lisa M, Disner, Seth G, Eapen, Blessen C, Franz, Carol E, Geuze, Elbert, Goodrich-Hunsaker, Naomi J, Han, Kihwan, Hayes, Jasmeet P, Hinds, Sidney R, Hodges, Cooper B, Hovenden, Elizabeth S, Irimia, Andrei, Kenney, Kimbra, Koerte, Inga K, Kremen, William S, Levin, Harvey S, Lindsey, Hannah M, Morey, Rajendra A, Newsome, Mary R, Ollinger, John, Pugh, Mary Jo, Scheibel, Randall S, Shenton, Martha E, Sullivan, Danielle R, Taylor, Brian A, Troyanskaya, Maya, Velez, Carmen, Wade, Benjamin SC, Wang, Xin, Ware, Ashley L, Zafonte, Ross, Thompson, Paul M, and Wilde, Elisabeth A

Subjects
Allied Health and Rehabilitation Science, Health Sciences, Physical Injury - Accidents and Adverse Effects, Neurosciences, Biomedical Imaging, Traumatic Brain Injury (TBI), Brain Disorders, Traumatic Head and Spine Injury, Detection, screening and diagnosis, 4.2 Evaluation of markers and technologies, Mental health, Neurological, Brain Injuries, Traumatic, Humans, Magnetic Resonance Imaging, Military Personnel, Stress Disorders, Post-Traumatic, Veterans, Biological Psychology, Clinical and Health Psychology, Psychology, Applied and Developmental Psychology, Behavioral and Social Science, Clinical Research, Mental Health, Activities of Daily Living, Aged, Aged, 80 and over, Executive Function, Female, Independent Living, Male, Middle Aged, Neuropsychological Tests, ROC Curve, Regression Analysis, Reproducibility of Results, TBI, traumatic brain injury, military, veteran, blast injury, ENIGMA, Medical and Health Sciences, Psychology and Cognitive Sciences, Experimental Psychology, Biomedical and clinical sciences, Health sciences
Abstract

Traumatic brain injury (TBI) is common among military personnel and the civilian population and is often followed by a heterogeneous array of clinical, cognitive, behavioral, mood, and neuroimaging changes. Unlike many neurological disorders that have a characteristic abnormal central neurologic area(s) of abnormality pathognomonic to the disorder, a sufficient head impact may cause focal, multifocal, diffuse or combination of injury to the brain. This inconsistent presentation makes it difficult to establish or validate biological and imaging markers that could help improve diagnostic and prognostic accuracy in this patient population. The purpose of this manuscript is to describe both the challenges and opportunities when conducting military-relevant TBI research and introduce the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Military Brain Injury working group. ENIGMA is a worldwide consortium focused on improving replicability and analytical power through data sharing and collaboration. In this paper, we discuss challenges affecting efforts to aggregate data in this patient group. In addition, we highlight how "big data" approaches might be used to understand better the role that each of these variables might play in the imaging and functional phenotypes of TBI in Service member and Veteran populations, and how data may be used to examine important military specific issues such as return to duty, the late effects of combat-related injury, and alteration of the natural aging processes.

Published
2021

375. The clinical utility of proton magnetic resonance spectroscopy in traumatic brain injury: recommendations from the ENIGMA MRS working group

Author

Bartnik-Olson, Brenda L, Alger, Jeffry R, Babikian, Talin, Harris, Ashley D, Holshouser, Barbara, Kirov, Ivan I, Maudsley, Andrew A, Thompson, Paul M, Dennis, Emily L, Tate, David F, Wilde, Elisabeth A, and Lin, Alexander

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Brain Disorders, Physical Injury - Accidents and Adverse Effects, Clinical Research, Biomedical Imaging, Traumatic Brain Injury (TBI), Neurosciences, Traumatic Head and Spine Injury, Detection, screening and diagnosis, 4.1 Discovery and preclinical testing of markers and technologies, Neurological, Injuries and accidents, Adult, Brain, Brain Injuries, Traumatic, Child, Humans, Magnetic Resonance Imaging, Magnetic Resonance Spectroscopy, Proton Magnetic Resonance Spectroscopy, Magnetic resonance spectroscopy, Trauma, Brain injury, Concussion, Medical and Health Sciences, Psychology and Cognitive Sciences, Experimental Psychology, Biomedical and clinical sciences, Health sciences, Psychology
Abstract

Proton (1H) magnetic resonance spectroscopy provides a non-invasive and quantitative measure of brain metabolites. Traumatic brain injury impacts cerebral metabolism and a number of research groups have successfully used this technique as a biomarker of injury and/or outcome in both pediatric and adult TBI populations. However, this technique is underutilized, with studies being performed primarily at centers with access to MR research support. In this paper we present a technical introduction to the acquisition and analysis of in vivo 1H magnetic resonance spectroscopy and review 1H magnetic resonance spectroscopy findings in different injury populations. In addition, we propose a basic 1H magnetic resonance spectroscopy data acquisition scheme (Supplemental Information) that can be added to any imaging protocol, regardless of clinical magnetic resonance platform. We outline a number of considerations for study design as a way of encouraging the use of 1H magnetic resonance spectroscopy in the study of traumatic brain injury, as well as recommendations to improve data harmonization across groups already using this technique.

Published
2021

376. Toward a global and reproducible science for brain imaging in neurotrauma: the ENIGMA adult moderate/severe traumatic brain injury working group

Author

Olsen, Alexander, Babikian, Talin, Bigler, Erin D, Caeyenberghs, Karen, Conde, Virginia, Dams-O’Connor, Kristen, Dobryakova, Ekaterina, Genova, Helen, Grafman, Jordan, Håberg, Asta K, Heggland, Ingrid, Hellstrøm, Torgeir, Hodges, Cooper B, Irimia, Andrei, Jha, Ruchira M, Johnson, Paula K, Koliatsos, Vassilis E, Levin, Harvey, Li, Lucia M, Lindsey, Hannah M, Livny, Abigail, Løvstad, Marianne, Medaglia, John, Menon, David K, Mondello, Stefania, Monti, Martin M, Newcombe, Virginia FJ, Petroni, Agustin, Ponsford, Jennie, Sharp, David, Spitz, Gershon, Westlye, Lars T, Thompson, Paul M, Dennis, Emily L, Tate, David F, Wilde, Elisabeth A, and Hillary, Frank G

Subjects
Biological Psychology, Psychology, Traumatic Brain Injury (TBI), Neurosciences, Traumatic Head and Spine Injury, Biomedical Imaging, Clinical Research, Brain Disorders, Emerging Infectious Diseases, Physical Injury - Accidents and Adverse Effects, Injuries and accidents, Neurological, Good Health and Well Being, Adult, Brain, Brain Injuries, Traumatic, Humans, Magnetic Resonance Imaging, Neuroimaging, Reproducibility of Results, Brain injury, Radiology, Open Science, Neurodegeneration, Rehabilitation, ENIGMA, Medical and Health Sciences, Psychology and Cognitive Sciences, Experimental Psychology, Biomedical and clinical sciences, Health sciences
Abstract

The global burden of mortality and morbidity caused by traumatic brain injury (TBI) is significant, and the heterogeneity of TBI patients and the relatively small sample sizes of most current neuroimaging studies is a major challenge for scientific advances and clinical translation. The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Adult moderate/severe TBI (AMS-TBI) working group aims to be a driving force for new discoveries in AMS-TBI by providing researchers world-wide with an effective framework and platform for large-scale cross-border collaboration and data sharing. Based on the principles of transparency, rigor, reproducibility and collaboration, we will facilitate the development and dissemination of multiscale and big data analysis pipelines for harmonized analyses in AMS-TBI using structural and functional neuroimaging in combination with non-imaging biomarkers, genetics, as well as clinical and behavioral measures. Ultimately, we will offer investigators an unprecedented opportunity to test important hypotheses about recovery and morbidity in AMS-TBI by taking advantage of our robust methods for large-scale neuroimaging data analysis. In this consensus statement we outline the working group's short-term, intermediate, and long-term goals.

Published
2021

377. Challenges and opportunities for neuroimaging in young patients with traumatic brain injury: a coordinated effort towards advancing discovery from the ENIGMA pediatric moderate/severe TBI group

Author

Dennis, Emily L, Caeyenberghs, Karen, Asarnow, Robert F, Babikian, Talin, Bartnik-Olson, Brenda, Bigler, Erin D, Figaji, Anthony, Giza, Christopher C, Goodrich-Hunsaker, Naomi J, Hodges, Cooper B, Hoskinson, Kristen R, Königs, Marsh, Levin, Harvey S, Lindsey, Hannah M, Livny, Abigail, Max, Jeffrey E, Merkley, Tricia L, Newsome, Mary R, Olsen, Alexander, Ryan, Nicholas P, Spruiell, Matthew S, Suskauer, Stacy J, Thomopoulos, Sophia I, Ware, Ashley L, Watson, Christopher G, Wheeler, Anne L, Yeates, Keith Owen, Zielinski, Brandon A, Thompson, Paul M, Tate, David F, and Wilde, Elisabeth A

Subjects
Brain Disorders, Clinical Research, Neurosciences, Biomedical Imaging, Physical Injury - Accidents and Adverse Effects, Pediatric, Childhood Injury, Pediatric Research Initiative, Unintentional Childhood Injury, Traumatic Brain Injury (TBI), Traumatic Head and Spine Injury, Injuries and accidents, Adolescent, Adult, Biomarkers, Brain Injuries, Traumatic, Child, Humans, Magnetic Resonance Imaging, Neuroimaging, traumatic brain injury, ENIGMA, Moderate-severe TBI, Medical and Health Sciences, Psychology and Cognitive Sciences, Experimental Psychology
Abstract

Traumatic brain injury (TBI) is a major cause of death and disability in children in both developed and developing nations. Children and adolescents suffer from TBI at a higher rate than the general population, and specific developmental issues require a unique context since findings from adult research do not necessarily directly translate to children. Findings in pediatric cohorts tend to lag behind those in adult samples. This may be due, in part, both to the smaller number of investigators engaged in research with this population and may also be related to changes in safety laws and clinical practice that have altered length of hospital stays, treatment, and access to this population. The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Pediatric Moderate/Severe TBI (msTBI) group aims to advance research in this area through global collaborative meta-analysis of neuroimaging data. In this paper, we discuss important challenges in pediatric TBI research and opportunities that we believe the ENIGMA Pediatric msTBI group can provide to address them. With the paucity of research studies examining neuroimaging biomarkers in pediatric patients with TBI and the challenges of recruiting large numbers of participants, collaborating to improve statistical power and to address technical challenges like lesions will significantly advance the field. We conclude with recommendations for future research in this field of study.

Published
2021

380. Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium

Author

Zhu, Xi, Kim, Yoojean, Ravid, Orren, He, Xiaofu, Suarez-Jimenez, Benjamin, Zilcha-Mano, Sigal, Lazarov, Amit, Lee, Seonjoo, Abdallah, Chadi G., Angstadt, Michael, Averill, Christopher L., Baird, C. Lexi, Baugh, Lee A., Blackford, Jennifer U., Bomyea, Jessica, Bruce, Steven E., Bryant, Richard A., Cao, Zhihong, Choi, Kyle, Cisler, Josh, Cotton, Andrew S., Daniels, Judith K., Davenport, Nicholas D., Davidson, Richard J., DeBellis, Michael D., Dennis, Emily L., Densmore, Maria, deRoon-Cassini, Terri, Disner, Seth G., Hage, Wissam El, Etkin, Amit, Fani, Negar, Fercho, Kelene A., Fitzgerald, Jacklynn, Forster, Gina L., Frijling, Jessie L., Geuze, Elbert, Gonenc, Atilla, Gordon, Evan M., Gruber, Staci, Grupe, Daniel W, Guenette, Jeffrey P., Haswell, Courtney C., Herringa, Ryan J., Herzog, Julia, Hofmann, David Bernd, Hosseini, Bobak, Hudson, Anna R., Huggins, Ashley A., Ipser, Jonathan C., Jahanshad, Neda, Jia-Richards, Meilin, Jovanovic, Tanja, Kaufman, Milissa L., Kennis, Mitzy, King, Anthony, Kinzel, Philipp, Koch, Saskia B.J., Koerte, Inga K., Koopowitz, Sheri M., Korgaonkar, Mayuresh S., Krystal, John H., Lanius, Ruth, Larson, Christine L., Lebois, Lauren A.M., Li, Gen, Liberzon, Israel, Lu, Guang Ming, Luo, Yifeng, Magnotta, Vincent A., Manthey, Antje, Maron-Katz, Adi, May, Geoffery, McLaughlin, Katie, Mueller, Sven C., Nawijn, Laura, Nelson, Steven M., Neufeld, Richard W.J., Nitschke, Jack B, O'Leary, Erin M., Olatunji, Bunmi O., Olff, Miranda, Peverill, Matthew, Phan, K. Luan, Qi, Rongfeng, Quidé, Yann, Rektor, Ivan, Ressler, Kerry, Riha, Pavel, Ross, Marisa, Rosso, Isabelle M., Salminen, Lauren E., Sambrook, Kelly, Schmahl, Christian, Shenton, Martha E., Sheridan, Margaret, Shih, Chiahao, Sicorello, Maurizio, Sierk, Anika, Simmons, Alan N., Simons, Raluca M., Simons, Jeffrey S., Sponheim, Scott R., Stein, Murray B., Stein, Dan J., Stevens, Jennifer S., Straube, Thomas, Sun, Delin, Théberge, Jean, Thompson, Paul M., Thomopoulos, Sophia I., van der Wee, Nic J.A., van der Werff, Steven J.A., van Erp, Theo G.M., van Rooij, Sanne J.H., van Zuiden, Mirjam, Varkevisser, Tim, Veltman, Dick J., Vermeiren, Robert R.J.M., Walter, Henrik, Wang, Li, Wang, Xin, Weis, Carissa, Winternitz, Sherry, Xie, Hong, Zhu, Ye, Wall, Melanie, Neria, Yuval, and Morey, Rajendra A.

Published
2023
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382. Circular-SWAT for deep learning based diagnostic classification of Alzheimer's disease: application to metabolome data

Author

Kaddurah-Daouk, Rima, Kueider-Paisley, Alexandra, Doraiswamy, P. Murali, Blach, Colette, Moseley, Arthur, Thompson, Will, St John-Williams, Lisa, Mahmoudiandehkhordi, Siamak, Tenenbaum, Jessica, Welsh-Balmer, Kathleen, Plassman, Brenda, Saykin, Andrew J., Nho, Kwangsik, Risacher, Shannon L., Kastenmüller, Gabi, Arnold, Matthias, Han, Xianlin, Baillie, Rebecca, Knight, Rob, Dorrestein, Pieter, Brewer, James, Mayer, Emeran, Labus, Jennifer, Baldi, Pierre, Gupta, Arpana, Fiehn, Oliver, Barupal, Dinesh, Meikle, Peter, Mazmanian, Sarkis, Rader, Dan, Kling, Mitchel, Shaw, Leslie, Trojanowski, John, van Duijin, Cornelia, Nevado-Holgado, Alejo, Bennett, David, Krishnan, Ranga, Keshavarzian, Ali, Vogt, Robin, Ikram, Arfan, Hankemeier, Thomas, Thiele, Ines, Price, Nathan, Funk, Cory, Baloni, Priyanka, Jia, Wei, Wishart, David, Brinton, Roberta, Chang, Rui, Farrer, Lindsay, Au, Rhoda, Qiu, Wendy, Würtz, Peter, Koal, Therese, Mangravite, Lara, Krumsiek, Jan, Suhre, Karsten, Newman, John, Moreno, Herman, Foroud, Tatania, Sacks, Frank, Jansson, Janet, Weiner, Michael W., Aisen, Paul, Petersen, Ronald, Jack, Clifford R., Jr., Jagust, William, Trojanowki, John Q., Toga, Arthur W., Beckett, Laurel, Green, Robert C., Morris, John C., Perrin, Richard J., Shaw, Leslie M., Khachaturian, Zaven, Carrillo, Maria, Potter, William, Barnes, Lisa, Bernard, Marie, Gonzalez, Hector, Ho, Carole, Hsiao, John K., Jackson, Jonathan, Masliah, Eliezer, Masterman, Donna, Okonkwo, Ozioma, Perrin, Richard, Ryan, Laurie, Silverberg, Nina, Fleisher, Adam, Sacrey, Diana Truran, Fockler, Juliet, Conti, Cat, Veitch, Dallas, Neuhaus, John, Jin, Chengshi, Nosheny, Rachel, Ashford, Miriam, Flenniken, Derek, Kormos, Adrienne, Montine, Tom, Rafii, Michael, Raman, Rema, Jimenez, Gustavo, Donohue, Michael, Gessert, Devon, Salazar, Jennifer, Zimmerman, Caileigh, Cabrera, Yuliana, Walter, Sarah, Miller, Garrett, Coker, Godfrey, Clanton, Taylor, Hergesheimer, Lindsey, Smith, Stephanie, Adegoke, Olusegun, Mahboubi, Payam, Moore, Shelley, Pizzola, Jeremy, Shaffer, Elizabeth, Sloan, Brittany, Harvey, Danielle, Forghanian-Arani, Arvin, Borowski, Bret, Ward, Chad, Schwarz, Christopher, Jones, David, Gunter, Jeff, Kantarci, Kejal, Senjem, Matthew, Vemuri, Prashanthi, Reid, Robert, Fox, Nick C., Malone, Ian, Thompson, Paul, Thomopoulos, Sophia I., Nir, Talia M., Jahanshad, Neda, DeCarli, Charles, Knaack, Alexander, Fletcher, Evan, Tosun-Turgut, Duygu, Chen, Stephanie Rossi, Choe, Mark, Crawford, Karen, Yushkevich, Paul A., Das, Sandhitsu, Koeppe, Robert A., Reiman, Eric M., Chen, Kewei, Mathis, Chet, Landau, Susan, Cairns, Nigel J., Householder, Erin, Franklin, Erin, Bernhardt, Haley, Taylor-Reinwald, Lisa, Korecka, Magdalena, Figurski, Michal, Neu, Scott, Apostolova, Liana G., Shen, Li, Foroud, Tatiana M., Nudelman, Kelly, Faber, Kelley, Wilmes, Kristi, Thal, Leon, Silbert, Lisa C., Lind, Betty, Crissey, Rachel, Kaye, Jeffrey A., Carter, Raina, Dolen, Sara, Quinn, Joseph, Schneider, Lon S., Pawluczyk, Sonia, Becerra, Mauricio, Teodoro, Liberty, Dagerman, Karen, Spann, Bryan M., Vanderswag, Helen, Ziolkowski, Jaimie, Heidebrink, Judith L., Zbizek-Nulph, Lisa, Lord, Joanne L., Mason, Sara S., Albers, Colleen S., Knopman, David, Johnson, Kris, Villanueva-Meyer, Javier, Pavlik, Valory, Pacini, Nathaniel, Lamb, Ashley, Kass, Joseph S., Doody, Rachelle S., Shibley, Victoria, Chowdhury, Munir, Rountree, Susan, Dang, Mimi, Stern, Yaakov, Honig, Lawrence S., Mintz, Akiva, Ances, Beau, Winkfield, David, Carroll, Maria, Stobbs-Cucchi, Georgia, Oliver, Angela, Creech, Mary L., Mintun, Mark A., Schneider, Stacy, Geldmacher, David, Love, Marissa Natelson, Griffith, Randall, Clark, David, Brockington, John, Marson, Daniel, Grossman, Hillel, Goldstein, Martin A., Greenberg, Jonathan, Mitsis, Effie, Shah, Raj C., Lamar, Melissa, Samuels, Patricia, Duara, Ranjan, Greig-Custo, Maria T., Rodriguez, Rosemarie, Albert, Marilyn, Onyike, Chiadi, Farrington, Leonie, Rudow, Scott, Brichko, Rottislav, Kielb, Stephanie, Smith, Amanda, Raj, Balebail Ashok, Fargher, Kristin, Sadowski, Martin, Wisniewski, Thomas, Shulman, Melanie, Faustin, Arline, Rao, Julia, Castro, Karen M., Ulysse, Anaztasia, Chen, Shannon, Sheikh, Mohammed O., Singleton-Garvin, Jamika, Petrella, JeffreyR., James, Olga, Wong, Terence Z., Borges-Neto, Salvador, Karlawish, Jason H., Wolk, David A., Vaishnavi, Sanjeev, Clark, Christopher M., Arnold, Steven E., Smith, Charles D., Jicha, Gregory A., Raslau, Flavius D., Lopez, Oscar L., Oakley, MaryAnn, Simpson, Donna M., Porsteinsson, Anton P., Martin, Kim, Kowalski, Nancy, Keltz, Melanie, Goldstein, Bonnie S., Makino, Kelly M., Ismail, M. 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2023
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