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Zoupou E, Moore TM, Kennedy KP, Calkins ME, Gorgone A, Sandro AD, Rush S, Lopez KC, Ruparel K, Daryoush T, Okoyeh P, Savino A, Troyan S, Wolf DH, Scott JC, Gur RE, Gur RC. Validation of the structured interview section of the penn computerized adaptive test for neurocognitive and clinical psychopathology assessment (CAT GOASSESS). Psychiatry Res 2024; 335:115862. [PMID: 38554493 PMCID: PMC11025108 DOI: 10.1016/j.psychres.2024.115862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 02/21/2024] [Accepted: 03/14/2024] [Indexed: 04/01/2024]
Abstract
Large-scale studies and burdened clinical settings require precise, efficient measures that assess multiple domains of psychopathology. Computerized adaptive tests (CATs) can reduce administration time without compromising data quality. We examined feasibility and validity of an adaptive psychopathology measure, GOASSESS, in a clinical community-based sample (N = 315; ages 18-35) comprising three groups: healthy controls, psychosis, mood/anxiety disorders. Assessment duration was compared between the Full and CAT GOASSESS. External validity was tested by comparing how the CAT and Full versions related to demographic variables, study group, and socioeconomic status. The relationships between scale scores and criteria were statistically compared within a mixed-model framework to account for dependency between relationships. Convergent validity was assessed by comparing scores of the CAT and the Full GOASSESS using Pearson correlations. The CAT GOASSESS reduced interview duration by more than 90 % across study groups and preserved relationships to external criteria and demographic variables as the Full GOASSESS. All CAT GOASSESS scales could replace those of the Full instrument. Overall, the CAT GOASSESS showed acceptable psychometric properties and demonstrated feasibility by markedly reducing assessment time compared to the Full GOASSESS. The adaptive version could be used in large-scale studies or clinical settings for intake screening.
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Affiliation(s)
- Eirini Zoupou
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - Tyler M Moore
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - Kelly P Kennedy
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - Monica E Calkins
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - Alesandra Gorgone
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - Akira Di Sandro
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sage Rush
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - Katherine C Lopez
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kosha Ruparel
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - Tarlan Daryoush
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - Paul Okoyeh
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Andrew Savino
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Scott Troyan
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Daniel H Wolf
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - J Cobb Scott
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; VISN 4 Mental Illness Research, Education, and Clinical Center at the Philadelphia VA Medical Center, PA, USA
| | - Raquel E Gur
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - Ruben C Gur
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA.
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Di Sandro A, Moore TM, Zoupou E, Kennedy KP, Lopez KC, Ruparel K, Njokweni LJ, Rush S, Daryoush T, Franco O, Gorgone A, Savino A, Didier P, Wolf DH, Calkins ME, Cobb Scott J, Gur RE, Gur RC. Validation of the cognitive section of the Penn computerized adaptive test for neurocognitive and clinical psychopathology assessment (CAT-CCNB). Brain Cogn 2024; 174:106117. [PMID: 38128447 PMCID: PMC10799332 DOI: 10.1016/j.bandc.2023.106117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 11/27/2023] [Accepted: 11/30/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND The 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. METHODS In 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. RESULTS Most tests (15/17) met the minimum criteria for replacing the full-form with the updated CAT version (mean r = 0.67; range = 0.53-0.80) when compared to relationships of the full-forms with previous administrations of the full-forms (mean r = 0.68; range = 0.50-0.85). Most (16/17) CAT-based relationships with diagnostics and other validity criteria were indistinguishable (interaction p > 0.05) from their full-form counterparts. CONCLUSIONS The updated CNB shows psychometric properties acceptable for research. The full-forms of some tests should be retained due to insufficient time savings to justify the loss in precision.
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Affiliation(s)
- Akira Di Sandro
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Tyler M Moore
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA.
| | - Eirini Zoupou
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA
| | - Kelly P Kennedy
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA
| | - Katherine C Lopez
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Kosha Ruparel
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA
| | - Lucky J Njokweni
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sage Rush
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA
| | - Tarlan Daryoush
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA
| | - Olivia Franco
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA
| | - Alesandra Gorgone
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA
| | - Andrew Savino
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Paige Didier
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Daniel H Wolf
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA
| | - Monica E Calkins
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA
| | - J Cobb Scott
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; VISN4 Mental Illness Research, Education, and Clinical Center at the Philadelphia VA Medical Center, 19104, USA
| | - Raquel E Gur
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA
| | - Ruben C Gur
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA
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Moore TM, Di Sandro A, Scott JC, Lopez KC, Ruparel K, Njokweni LJ, Santra S, Conway DS, Port AM, D'Errico L, Rush S, Wolf DH, Calkins ME, Gur RE, Gur RC. Construction of a computerized adaptive test (CAT-CCNB) for efficient neurocognitive and clinical psychopathology assessment. J Neurosci Methods 2023; 386:109795. [PMID: 36657647 PMCID: PMC9892357 DOI: 10.1016/j.jneumeth.2023.109795] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 12/14/2022] [Accepted: 01/13/2023] [Indexed: 01/18/2023]
Abstract
BACKGROUND Traditional paper-and-pencil neurocognitive evaluations and semi-structured mental health interviews can take hours to administer and score. Computerized assessment has decreased that burden substantially, and contemporary psychometric tools such as item response theory and computerized adaptive testing (CAT) allow even further abbreviation. NEW METHOD The goal of this paper was to describe the application of CAT and related methods to the Penn Computerized Neurocognitive Battery (CNB) and a well-validated clinical assessment in order to increase efficiency in assessment and relevant domain coverage. To calibrate item banks for CAT, N = 5053 participants (63% female; mean age 45 years, range 18-80) were collected from across the United States via crowdsourcing, providing item parameters that were then linked to larger item banks and used in individual test construction. Tests not amenable to CAT were abbreviated using complementary short-form methods. RESULTS The final "CAT-CCNB" battery comprised 21 cognitive tests (compared to 14 in the original) and five adaptive clinical scales (compared to 16 in the original). COMPARISON WITH EXISTING METHODS This new battery, derived with contemporary psychometric approaches, provides further improvements over existing assessments that use collections of fixed-length tests developed for stand-alone administration. The CAT-CCNB provides an improved version of the CNB that shows promise as a maximally efficient tool for neuropsychiatric assessment. CONCLUSIONS We anticipate CAT-CCNB will help satisfy the clear need for broad yet efficient measurement of cognitive and clinical domains, facilitating implementation of large-scale, "big science" approaches to data collection, and potential widespread clinical implementation.
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Affiliation(s)
- Tyler M Moore
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA.
| | - Akira Di Sandro
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - J Cobb Scott
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; VISN4 Mental Illness Research, Education, and Clinical Center at the Philadelphia VA Medical Center, 19104, USA
| | - Katherine C Lopez
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Kosha Ruparel
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA
| | - Lucky J Njokweni
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Satrajit Santra
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - David S Conway
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Allison M Port
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Lisa D'Errico
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sage Rush
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA
| | - Daniel H Wolf
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Monica E Calkins
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA
| | - Raquel E Gur
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA
| | - Ruben C Gur
- Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA
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Lopez KC, Kandala S, Marek S, Barch DM. Development of Network Topology and Functional Connectivity of the Prefrontal Cortex. Cereb Cortex 2019; 30:2489-2505. [DOI: 10.1093/cercor/bhz255] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Accepted: 09/17/2019] [Indexed: 01/08/2023] Open
Abstract
Abstract
The prefrontal cortex (PFC) comprises distinct regions and networks that vary in their trajectories across development. Further understanding these diverging trajectories may elucidate the neural mechanisms by which distinct PFC regions contribute to cognitive maturity. In particular, it remains unclear whether PFC regions of distinct network affiliations differ in topology and their relationship to cognition. We examined 615 individuals (8–21 years) to characterize age-related effects in participation coefficient of 28 PFC regions of distinct networks, evaluating connectivity profiles of each region to understand patterns influencing topological maturity. Findings revealed that PFC regions of attention, frontoparietal, and default mode networks (DMN) displayed varying rates of decline in participation coefficient with age, characterized by stronger connectivity with each PFC’s respective network; suggesting that PFC regions largely aid network segregation. Conversely, PFC regions of the cinguloopercular/salience network increased in participation coefficient with age, marked by stronger between-network connections, suggesting that some PFC regions feature a distinctive ability to facilitate network integration. PFC topology of the DMN, in particular, predicted improvements in global cognition, including motor speed and higher order abilities. Together, these findings elucidate systematic differences in topology across PFC regions of different network affiliation, representing important neural signatures of typical brain development.
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Affiliation(s)
- Katherine C Lopez
- Department of Psychological & Brain Sciences, Washington University, St Louis, 63130 MO, USA
| | - Sridhar Kandala
- Department of Psychiatry, Washington University, St Louis, 63110 MO, USA
| | - Scott Marek
- Department of Psychiatry, Washington University, St Louis, 63110 MO, USA
| | - Deanna M Barch
- Department of Psychological & Brain Sciences, Washington University, St Louis, 63130 MO, USA
- Department of Psychiatry, Washington University, St Louis, 63110 MO, USA
- Department of Radiology, Washington University, St Louis, 63110 MO, USA
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Marek S, Siegel JS, Gordon EM, Raut RV, Gratton C, Newbold DJ, Ortega M, Laumann TO, Adeyemo B, Miller DB, Zheng A, Lopez KC, Berg JJ, Coalson RS, Nguyen AL, Dierker D, Van AN, Hoyt CR, McDermott KB, Norris SA, Shimony JS, Snyder AZ, Nelson SM, Barch DM, Schlaggar BL, Raichle ME, Petersen SE, Greene DJ, Dosenbach NUF. Spatial and Temporal Organization of the Individual Human Cerebellum. Neuron 2018; 100:977-993.e7. [PMID: 30473014 DOI: 10.1016/j.neuron.2018.10.010] [Citation(s) in RCA: 153] [Impact Index Per Article: 25.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Revised: 08/13/2018] [Accepted: 10/05/2018] [Indexed: 12/18/2022]
Abstract
The cerebellum contains the majority of neurons in the human brain and is unique for its uniform cytoarchitecture, absence of aerobic glycolysis, and role in adaptive plasticity. Despite anatomical and physiological differences between the cerebellum and cerebral cortex, group-average functional connectivity studies have identified networks related to specific functions in both structures. Recently, precision functional mapping of individuals revealed that functional networks in the cerebral cortex exhibit measurable individual specificity. Using the highly sampled Midnight Scan Club (MSC) dataset, we found the cerebellum contains reliable, individual-specific network organization that is significantly more variable than the cerebral cortex. The frontoparietal network, thought to support adaptive control, was the only network overrepresented in the cerebellum compared to the cerebral cortex (2.3-fold). Temporally, all cerebellar resting state signals lagged behind the cerebral cortex (125-380 ms), supporting the hypothesis that the cerebellum engages in a domain-general function in the adaptive control of all cortical processes.
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Affiliation(s)
- Scott Marek
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA.
| | - Joshua S Siegel
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Evan M Gordon
- VISN17 Center of Excellence for Research on Returning War Veterans, Waco, TX 76711, USA; Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX 75235, USA; Department of Psychology and Neuroscience, Baylor University, Waco, TX 76706, USA
| | - Ryan V Raut
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Caterina Gratton
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Dillan J Newbold
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Mario Ortega
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Timothy O Laumann
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Babatunde Adeyemo
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Derek B Miller
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Annie Zheng
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Katherine C Lopez
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Jeffrey J Berg
- Department of Psychology, New York University, New York, NY 10003 USA
| | - Rebecca S Coalson
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Annie L Nguyen
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Donna Dierker
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Andrew N Van
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Catherine R Hoyt
- Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Kathleen B McDermott
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63110, USA; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Scott A Norris
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Abraham Z Snyder
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Steven M Nelson
- VISN17 Center of Excellence for Research on Returning War Veterans, Waco, TX 76711, USA; Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX 75235, USA; Department of Psychology and Neuroscience, Baylor University, Waco, TX 76706, USA
| | - Deanna M Barch
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63110, USA; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Bradley L Schlaggar
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Marcus E Raichle
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Steven E Petersen
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63110, USA; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63110, USA; Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Deanna J Greene
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Nico U F Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110, USA; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63110, USA
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Lopez KC, Leary JB, Pham DL, Chou YY, Dsurney J, Chan L. Brain Volume, Connectivity, and Neuropsychological Performance in Mild Traumatic Brain Injury: The Impact of Post-Traumatic Stress Disorder Symptoms. J Neurotrauma 2016; 34:16-22. [PMID: 26942337 DOI: 10.1089/neu.2015.4323] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Post-traumatic stress disorder (PTSD) is commonly associated with mild traumatic brain injury (mTBI). To better understand their relationship, we examined neuroanatomical structures and neuropsychological performance in a sample of individuals with mTBI, with and without PTSD symptoms. Thirty-nine subjects with mTBI were dichotomized into those with (n = 12) and without (n = 27) significant PTSD symptoms based on scores on the PTSD Checklist. Using a region-of-interest approach, fronto-temporal volumes, fiber bundles obtained by diffusion tensor imaging, and neuropsychological scores were compared between the two groups. After controlling for total intracranial volume and age, subjects with mTBI and PTSD symptoms exhibited volumetric differences in the entorhinal cortex, an area associated with memory networks, relative to mTBI-only patients (F = 4.28; p = 0.046). Additionally, subjects with PTSD symptoms showed reduced white matter integrity in the right cingulum bundle (axial diffusivity, F = 6.04; p = 0.020). Accompanying these structural alterations, mTBI and PTSD subjects also showed impaired performance in encoding (F = 5.98; p = 0.019) and retrieval (F = 7.32; p = 0.010) phases of list learning and in tests of processing speed (Wechsler Adult Intelligence Scale Processing Speed Index, F = 12.23; p = 0.001; Trail Making Test A, F = 5.56; p = 0.024). Increased volume and white matter disruptions in these areas, commonly associated with memory functions, may be related to functional disturbances during cognitively demanding tasks. Differences in brain volume and white matter integrity between mTBI subjects and those with mTBI and co-morbid PTSD symptoms point to neuroanatomical differences that may underlie poorer recovery of mTBI subjects who experience PTSD symptoms. These findings support theoretical models of PTSD and its relationship to learning deficits.
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Affiliation(s)
- Katherine C Lopez
- 1 Center for Neuroscience and Regenerative Medicine, National Institutes of Health , Bethesda, Maryland
| | - Jacob B Leary
- 2 Rehabilitation Medicine Department, Clinical Center, National Institutes of Health , Bethesda, Maryland
| | - Dzung L Pham
- 1 Center for Neuroscience and Regenerative Medicine, National Institutes of Health , Bethesda, Maryland
| | - Yi-Yu Chou
- 1 Center for Neuroscience and Regenerative Medicine, National Institutes of Health , Bethesda, Maryland
| | - John Dsurney
- 1 Center for Neuroscience and Regenerative Medicine, National Institutes of Health , Bethesda, Maryland
| | - Leighton Chan
- 1 Center for Neuroscience and Regenerative Medicine, National Institutes of Health , Bethesda, Maryland.,2 Rehabilitation Medicine Department, Clinical Center, National Institutes of Health , Bethesda, Maryland
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Lopez KC, Lalonde F, Mattai A, Wade B, Clasen L, Rapoport J, Giedd JN. Quantitative morphology of the corpus callosum in obsessive-compulsive disorder. Psychiatry Res 2013; 212:1-6. [PMID: 23453697 PMCID: PMC4043277 DOI: 10.1016/j.pscychresns.2012.10.012] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2012] [Revised: 10/28/2012] [Accepted: 10/29/2012] [Indexed: 11/25/2022]
Abstract
Neuroimaging studies have implicated the corpus callosum (CC) in the pathophysiology of obsessive-compulsive disorder (OCD). Putative dysfunctions in prefrontal cortical regions suggest anomalies in anterior segments of the CC. However, recent studies have also implicated the middle and posterior CC. The present study soughts to examine the CC using parcellation scheme informed by diffusion tensor imaging. Anatomic brain magnetic resonance scans were obtained from 21 OCD subjects (mean age=26.9 ± 9.93) and 42 healthy age- and sex-matched controls (mean age=26.6 ± 9.46) between the ages of 14 and 49. Area and volume measures of five subregions of the CC were obtained via manual tracings. A multivariate analysis of variance (after correcting for multiple comparisons) identified smaller area and volume in the mid-anterior region of the CC in OCD patients relative to controls. These findings implicate medio-frontal regions of the cortex in the pathophysiology of OCD.
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Affiliation(s)
| | | | | | | | | | | | - Jay N. Giedd
- Corresponding author. Tel.: +301 435 4517; fax: +301 480 8898. (J.N. Giedd).
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Lee NR, Wallace GL, Adeyemi EI, Lopez KC, Blumenthal JD, Clasen LS, Giedd JN. Dosage effects of X and Y chromosomes on language and social functioning in children with supernumerary sex chromosome aneuploidies: implications for idiopathic language impairment and autism spectrum disorders. J Child Psychol Psychiatry 2012; 53:1072-81. [PMID: 22827287 PMCID: PMC3480208 DOI: 10.1111/j.1469-7610.2012.02573.x] [Citation(s) in RCA: 55] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
BACKGROUND Supernumerary sex chromosome aneuploidies (X/Y-aneuploidies), the presence of extra X and/or Y chromosomes, are associated with heightened rates of language impairments and social difficulties. However, no single study has examined different language domains and social functioning in the same sample of children with tri-, tetra-, and pentasomy X/Y-aneuploidy. The current research sought to fill this gap in the literature and to examine dosage effects of X and Y chromosomes on language and social functioning. METHODS Participants included 110 youth with X/Y-aneuploidies (32 female) and 52 with typical development (25 female) matched on age (mean ∼12 years; range 4-22) and maternal education. Participants completed the Wechsler intelligence scales, and parents completed the children's communication checklist-2 and the social responsiveness scale to assess language skills and autistic traits, respectively. RESULTS Both supernumerary X and Y chromosomes were related to depressed structural and pragmatic language skills and increased autistic traits. The addition of a Y chromosome had a disproportionately greater impact on pragmatic language; the addition of one or more X chromosomes had a disproportionately greater impact on structural language. CONCLUSIONS Given that we link extra X chromosomes with structural language impairments and an extra Y chromosome with pragmatic language impairments, X/Y-aneuploidies may provide clues to genetic mechanisms contributing to idiopathic language impairment and autism spectrum disorders.
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Affiliation(s)
- Nancy Raitano Lee
- Child Psychiatry Branch, National Institute of Mental Health, NIH, Bethesda, MD 20892, USA.
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