Raquel E. Gur
University of Pennsylvania
H-index: 165
North America-United States
Description
Raquel E. Gur, With an exceptional h-index of 165 and a recent h-index of 93 (since 2020), a distinguished researcher at University of Pennsylvania, specializes in the field of Neuropsychiatry, Neuroimaging, Schizophrenia, Psychosis, Neurodevelopment.
His recent articles reflect a diverse array of research interests and contributions to the field:
Remote assessment of the Penn computerised neurocognitive battery in individuals with 22q11. 2 deletion syndrome
Validation of the cognitive section of the Penn computerized adaptive test for neurocognitive and clinical psychopathology assessment (CAT-CCNB)
Is Common Genetic Risk for Psychiatric Disorders Associated With Traumatic Experiences in Youth?
Functional connectivity development along the sensorimotor-association axis enhances the cortical hierarchy
Source‐based morphometry reveals structural brain pattern abnormalities in 22q11. 2 deletion syndrome
The schizophrenia syndrome, circa 2024: What we know and how that informs its nature
338. Mediation of Family History Association With Adolescent Behavioral Health by Reported Trauma Exposures
Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation
Professor Information
University | University of Pennsylvania |
---|---|
Position | Professor of Psychiatry |
Citations(all) | 97051 |
Citations(since 2020) | 38289 |
Cited By | 72642 |
hIndex(all) | 165 |
hIndex(since 2020) | 93 |
i10Index(all) | 672 |
i10Index(since 2020) | 504 |
University Profile Page | University of Pennsylvania |
Research & Interests List
Neuropsychiatry
Neuroimaging
Schizophrenia
Psychosis
Neurodevelopment
Top articles of Raquel E. Gur
Remote assessment of the Penn computerised neurocognitive battery in individuals with 22q11. 2 deletion syndrome
Background Neurocognitive functioning is an integral phenotype of 22q11.2 deletion syndrome relating to severity of psychopathology and outcomes. A neurocognitive battery that could be administered remotely to assess multiple cognitive domains would be especially beneficial to research on rare genetic variants, where in‐person assessment can be unavailable or burdensome. The current study compares in‐person and remote assessments of the Penn computerised neurocognitive battery (CNB). Methods Participants (mean age = 17.82, SD = 6.94 years; 48% female) completed the CNB either in‐person at a laboratory (n = 222) or remotely (n = 162). Results Results show that accuracy of CNB performance was equivalent across the two testing locations, while slight differences in speed were detected in 3 of the 11 tasks. Conclusions These findings suggest that the CNB can be used in remote settings to …
Authors
LK White,N Hillman,K Ruparel,TM Moore,RS Gallagher,EJ McClellan,DR Roalf,JC Scott,ME Calkins,DE McGinn,V Giunta,O Tran,TB Crowley,EH Zackai,BS Emanuel,DM McDonald‐McGinn,RE Gur,RC Gur
Journal
Journal of Intellectual Disability Research
Published Date
2024
Validation of the cognitive section of the Penn computerized adaptive test for neurocognitive and clinical psychopathology assessment (CAT-CCNB)
BackgroundThe Penn Computerized Neurocognitive Battery is an efficient tool for assessing brain-behavior domains, and its efficiency was augmented via computerized adaptive testing (CAT). This battery requires validation in a separate sample to establish psychometric properties.MethodsIn a mixed community/clinical sample of N = 307 18-to-35-year-olds, we tested the relationships of the CAT tests with the full-form tests. We compared discriminability among recruitment groups (psychosis, mood, control) and examined how their scores relate to demographics. CAT-Full relationships were evaluated based on a minimum inter-test correlation of 0.70 or an inter-test correlation within at least 0.10 of the full-form correlation with a previous administration of the full battery. Differences in criterion relationships were tested via mixed models.ResultsMost tests (15/17) met the minimum criteria for replacing the full-form …
Authors
Akira Di Sandro,Tyler M Moore,Eirini Zoupou,Kelly P Kennedy,Katherine C Lopez,Kosha Ruparel,Lucky J Njokweni,Sage Rush,Tarlan Daryoush,Olivia Franco,Alesandra Gorgone,Andrew Savino,Paige Didier,Daniel H Wolf,Monica E Calkins,J Cobb Scott,Raquel E Gur,Ruben C Gur
Journal
Brain and Cognition
Published Date
2024/2/1
Is Common Genetic Risk for Psychiatric Disorders Associated With Traumatic Experiences in Youth?
BackgroundIn this study, we explored the relationship between genetics, trauma exposure, and social environment in a community cohort of youth. Since most methods that test gene-environment interaction (GxE) assume independence of genetic and environmental factors we aimed to investigate whether genetic factors play a role in the association between trauma and psychopathology.MethodsOur sample consisted of 5168 European ancestry (EA) and 3170 African ancestry (AA) 8–21-year-old participants (51.7% female). Trauma exposure was assessed through structured psychopathology evaluations, and social environment was determined using census and crime data. Polygenic Scores (PGS) for height, major depression (MDD), schizophrenia, post-traumatic stress disorder, and suicide attempts were calculated in both ancestry groups, whereas intelligence quotient (IQ), attention deficit hyperactivity …
Authors
Alison Merikangas,Laura Schultz,Zoe Rapisardo-Drigot,Ran Barzilay,Barbara Chaiyachati,Tyler Moore,Raquel Gur,Laura Almasy
Journal
Biological Psychiatry
Published Date
2024/5/15
Functional connectivity development along the sensorimotor-association axis enhances the cortical hierarchy
Human cortical maturation has been posited to be organized along the sensorimotor-association (S-A) axis, a hierarchical axis of brain organization that spans from unimodal sensorimotor cortices to transmodal association cortices. Here, we investigate the hypothesis that the development of functional connectivity during childhood through adolescence conforms to the cortical hierarchy defined by the S-A axis. We tested this pre-registered hypothesis in four large-scale, independent datasets (total n = 3,355; ages 5-23 years): the Philadelphia Neurodevelopmental Cohort (n = 1,207), Nathan Kline Institute-Rockland Sample (n = 397), Human Connectome Project: Development (n = 625), and Healthy Brain Network (n = 1,126). In each dataset, the development of functional connectivity systematically varied along the S-A axis. Connectivity in sensorimotor regions increased, whereas connectivity in association cortices declined, refining and reinforcing the cortical hierarchy. These robust and generalizable results establish that the sensorimotor-association axis of cortical organization encodes the dominant pattern of functional connectivity development.
Authors
Audrey Luo,Valerie J Sydnor,Adam Pines,Bart Larsen,Aaron F Alexander-Bloch,Matthew Cieslak,Sydney Covitz,Andrew Chen,Nathalia Bianchini Esper,Eric Feczko,Alexandre R Franco,Raquel E Gur,Ruben C Gur,Audrey Houghton,Fengling Hu,Arielle S Keller,Gregory Kiar,Kahini Mehta,Giovanni A Salum,Tinashe Tapera,Ting Xu,Chenying Zhao,Damien A Fair,Taylor Salo,Russell T Shinohara,Michael P Milham,Theodore D Satterthwaite
Journal
BioRxiv
Published Date
2023
Source‐based morphometry reveals structural brain pattern abnormalities in 22q11. 2 deletion syndrome
22q11.2 deletion syndrome (22q11DS) is the most frequently occurring microdeletion in humans. It is associated with a significant impact on brain structure, including prominent reductions in gray matter volume (GMV), and neuropsychiatric manifestations, including cognitive impairment and psychosis. It is unclear whether GMV alterations in 22q11DS occur according to distinct structural patterns. Then, 783 participants (470 with 22q11DS: 51% females, mean age [SD] 18.2 [9.2]; and 313 typically developing [TD] controls: 46% females, mean age 18.0 [8.6]) from 13 datasets were included in the present study. We segmented structural T1‐weighted brain MRI scans and extracted GMV images, which were then utilized in a novel source‐based morphometry (SBM) pipeline (SS‐Detect) to generate structural brain patterns (SBPs) that capture co‐varying GMV. We investigated the impact of the 22q11.2 deletion …
Authors
Ruiyang Ge,Christopher RK Ching,Anne S Bassett,Leila Kushan,Kevin M Antshel,Therese van Amelsvoort,Geor Bakker,Nancy J Butcher,Linda E Campbell,Eva WC Chow,Michael Craig,Nicolas A Crossley,Adam Cunningham,Eileen Daly,Joanne L Doherty,Courtney A Durdle,Beverly S Emanuel,Ania Fiksinski,Jennifer K Forsyth,Wanda Fremont,Naomi J Goodrich‐Hunsaker,Maria Gudbrandsen,Raquel E Gur,Maria Jalbrzikowski,Wendy R Kates,Amy Lin,David EJ Linden,Kathryn L McCabe,Donna McDonald‐McGinn,Hayley Moss,Declan G Murphy,Kieran C Murphy,Michael J Owen,Julio E Villalon‐Reina,Gabriela M Repetto,David R Roalf,Kosha Ruparel,J Eric Schmitt,Sanne Schuite‐Koops,Kathleen Angkustsiri,Daqiang Sun,Ariana Vajdi,Marianne van den Bree,Jacob Vorstman,Paul M Thompson,Fidel Vila‐Rodriguez,Carrie E Bearden
Journal
Human brain mapping
Published Date
2024/1
The schizophrenia syndrome, circa 2024: What we know and how that informs its nature
With new data about different aspects of schizophrenia being continually generated, it becomes necessary to periodically revisit exactly what we know. Along with a need to review what we currently know about schizophrenia, there is an equal imperative to evaluate the construct itself. With these objectives, we undertook an iterative, multi-phase process involving fifty international experts in the field, with each step building on learnings from the prior one. This review assembles currently established findings about schizophrenia (construct, etiology, pathophysiology, clinical expression, treatment) and posits what they reveal about its nature. Schizophrenia is a heritable, complex, multi-dimensional syndrome with varying degrees of psychotic, negative, cognitive, mood, and motor manifestations. The illness exhibits a remitting and relapsing course, with varying degrees of recovery among affected individuals with most …
Authors
Rajiv Tandon,Henry Nasrallah,Schahram Akbarian,William T Carpenter Jr,Lynn E DeLisi,Wolfgang Gaebel,Michael F Green,Raquel E Gur,Stephan Heckers,John M Kane,Dolores Malaspina,Andreas Meyer-Lindenberg,Robin Murray,Michael Owen,Jordan W Smoller,Walid Yassine,Matcheri Keshavan
Published Date
2024/2/1
338. Mediation of Family History Association With Adolescent Behavioral Health by Reported Trauma Exposures
BackgroundFamily history of psychopathology (FH) can influence adolescent mental health through both environment and genetics. Simultaneously, traumatic events are widely recognized as conveying significant risk for psychopathology. Interrogation of the potential indirect pathway of FH via trauma on psychopathology is warranted, particularly when viewed as a potentially actionable point of intervention.MethodsThe Philadelphia Neurodevelopmental Cohort is a deeply-phenotyped collection of 9,498 youth who were recruited through nonpsychiatric pediatric clinics. We tested associations of FH (count [0 to 4] of categories: psychosis, mood, suicide attempt, and substance use), youth trauma exposure, geocoded structural neighborhood environment, and genomic factor of polygenic scores for psychopathologies (depression, PTSD, schizophrenia, bipolar, cross-disorder) with overall adolescent …
Authors
Barbara Chaiyachati,Jamie L Catalano,Laura M Schultz,Laura Almasy,Elina Visoki,Jakob Seidlitz,Tyler M Moore,Jerome Taylor,Monica E Calkins,Raquel E Gur,Ran Barzilay
Journal
Biological Psychiatry
Published Date
2024/5/15
Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation
The value of normative models in research and clinical practice relies on their robustness and a systematic comparison of different modelling algorithms and parameters; however, this has not been done to date. We aimed to identify the optimal approach for normative modelling of brain morphometric data through systematic empirical benchmarking, by quantifying the accuracy of different algorithms and identifying parameters that optimised model performance. We developed this framework with regional morphometric data from 37 407 healthy individuals (53% female and 47% male; aged 3–90 years) from 87 datasets from Europe, Australia, the USA, South Africa, and east Asia following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The …
Authors
Ruiyang Ge,Yuetong Yu,Yi Xuan Qi,Yu-nan Fan,Shiyu Chen,Chuntong Gao,Shalaila S Haas,Faye New,Dorret I Boomsma,Henry Brodaty,Rachel M Brouwer,Randy Buckner,Xavier Caseras,Fabrice Crivello,Eveline A Crone,Susanne Erk,Simon E Fisher,Barbara Franke,David C Glahn,Udo Dannlowski,Dominik Grotegerd,Oliver Gruber,Hilleke E Hulshoff Pol,Gunter Schumann,Christian K Tamnes,Henrik Walter,Lara M Wierenga,Neda Jahanshad,Paul M Thompson,Sophia Frangou,Ingrid Agartz,Philip Asherson,Rosa Ayesa-Arriola,Nerisa Banaj,Tobias Banaschewski,Sarah Baumeister,Alessandro Bertolino,Stefan Borgwardt,Josiane Bourque,Daniel Brandeis,Alan Breier,Jan K Buitelaar,Dara M Cannon,Simon Cervenka,Patricia J Conrod,Benedicto Crespo-Facorro,Christopher G Davey,Lieuwe de Haan,Greig I de Zubicaray,Annabella Di Giorgio,Thomas Frodl,Patricia Gruner,Raquel E Gur,Ruben C Gur,Ben J Harrison,Sean N Hatton,Ian Hickie,Fleur M Howells,Chaim Huyser,Terry L Jernigan,Jiyang Jiang,John A Joska,René S Kahn,Andrew J Kalnin,Nicole A Kochan,Sanne Koops,Jonna Kuntsi,Jim Lagopoulos,Luisa Lazaro,Irina S Lebedeva,Christine Lochner,Nicholas G Martin,Bernard Mazoyer,Brenna C McDonald,Colm McDonald,Katie L McMahon,Sarah Medland,Amirhossein Modabbernia,Benson Mwangi,Tomohiro Nakao,Lars Nyberg,Fabrizio Piras,Maria J Portella,Jiang Qiu,Joshua L Roffman,Perminder S Sachdev,Nicole Sanford,Theodore D Satterthwaite,Andrew J Saykin,Carl M Sellgren,Kang Sim,Jordan W Smoller,Jair C Soares,Iris E Sommer,Gianfranco Spalletta,Dan J Stein,Sophia I Thomopoulos,Alexander S Tomyshev,Diana Tordesillas-Gutiérrez,Julian N Trollor,Dennis van't Ent,Odile A van den Heuvel,Theo GM van Erp,Neeltje EM van Haren,Daniela Vecchio,Dick J Veltman,Yang Wang,Bernd Weber,Dongtao Wei,Wei Wen,Lars T Westlye,Steven CR Williams,Margaret J Wright,Mon-Ju Wu,Kevin Yu
Published Date
2024/3/1
Professor FAQs
What is Raquel E. Gur's h-index at University of Pennsylvania?
The h-index of Raquel E. Gur has been 93 since 2020 and 165 in total.
What are Raquel E. Gur's top articles?
The articles with the titles of
Remote assessment of the Penn computerised neurocognitive battery in individuals with 22q11. 2 deletion syndrome
Validation of the cognitive section of the Penn computerized adaptive test for neurocognitive and clinical psychopathology assessment (CAT-CCNB)
Is Common Genetic Risk for Psychiatric Disorders Associated With Traumatic Experiences in Youth?
Functional connectivity development along the sensorimotor-association axis enhances the cortical hierarchy
Source‐based morphometry reveals structural brain pattern abnormalities in 22q11. 2 deletion syndrome
The schizophrenia syndrome, circa 2024: What we know and how that informs its nature
338. Mediation of Family History Association With Adolescent Behavioral Health by Reported Trauma Exposures
Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation
...
are the top articles of Raquel E. Gur at University of Pennsylvania.
What are Raquel E. Gur's research interests?
The research interests of Raquel E. Gur are: Neuropsychiatry, Neuroimaging, Schizophrenia, Psychosis, Neurodevelopment
What is Raquel E. Gur's total number of citations?
Raquel E. Gur has 97,051 citations in total.
What are the co-authors of Raquel E. Gur?
The co-authors of Raquel E. Gur are Jeffrey Lieberman, Ruben Gur, Ming T. Tsuang, Larry J. Seidman, Abass Alavi, Tyrone Cannon.