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Hinton KE, Lahey BB, Villalta-Gil V, Boyd BD, Yvernault BC, Werts KB, Plassard AJ, Applegate B, Woodward ND, Landman BA, Zald DH. Right Fronto-Subcortical White Matter Microstructure Predicts Cognitive Control Ability on the Go/No-go Task in a Community Sample. Front Hum Neurosci 2018; 12:127. [PMID: 29706875 PMCID: PMC5908979 DOI: 10.3389/fnhum.2018.00127] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2017] [Accepted: 03/19/2018] [Indexed: 01/27/2023] Open
Abstract
Go/no-go tasks are widely used to index cognitive control. This construct has been linked to white matter microstructure in a circuit connecting the right inferior frontal gyrus (IFG), subthalamic nucleus (STN), and pre-supplementary motor area. However, the specificity of this association has not been tested. A general factor of white matter has been identified that is related to processing speed. Given the strong processing speed component in successful performance on the go/no-go task, this general factor could contribute to task performance, but the general factor has often not been accounted for in past studies of cognitive control. Further, studies on cognitive control have generally employed small unrepresentative case-control designs. The present study examined the relationship between go/no-go performance and white matter microstructure in a large community sample of 378 subjects that included participants with a range of both clinical and subclinical nonpsychotic psychopathology. We found that white matter microstructure properties in the right IFG-STN tract significantly predicted task performance, and remained significant after controlling for dimensional psychopathology. The general factor of white matter only reached statistical significance when controlling for dimensional psychopathology. Although the IFG-STN and general factor tracts were highly correlated, when both were included in the model, only the IFG-STN remained a significant predictor of performance. Overall, these findings suggest that while a general factor of white matter can be identified in a young community sample, white matter microstructure properties in the right IFG-STN tract show a specific relationship to cognitive control. The findings highlight the importance of examining both specific and general correlates of cognition, especially in tasks with a speeded component.
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Affiliation(s)
- Kendra E Hinton
- Department of Psychological Sciences, Vanderbilt University, Nashville, TN, United States
| | - Benjamin B Lahey
- Department of Public Health Sciences, University of Chicago, Chicago, IL, United States
| | - Victoria Villalta-Gil
- Department of Psychological Sciences, Vanderbilt University, Nashville, TN, United States
| | - Brian D Boyd
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | | | - Katherine B Werts
- Department of Psychological Sciences, Vanderbilt University, Nashville, TN, United States
| | - Andrew J Plassard
- School of Engineering, Vanderbilt University, Nashville, TN, United States
| | - Brooks Applegate
- Department of Educational Leadership, Research and Technology, Western Michigan University, Kalamazoo, MI, United States
| | - Neil D Woodward
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Bennett A Landman
- School of Engineering, Vanderbilt University, Nashville, TN, United States
| | - David H Zald
- Department of Psychological Sciences, Vanderbilt University, Nashville, TN, United States
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Lahey BB, Zald DH, Perkins SF, Villalta‐Gil V, Werts KB, Van Hulle CA, Rathouz PJ, Applegate B, Class QA, Poore HE, Watts AL, Waldman ID. Measuring the hierarchical general factor model of psychopathology in young adults. Int J Methods Psychiatr Res 2018; 27:e1593. [PMID: 28990308 PMCID: PMC5834349 DOI: 10.1002/mpr.1593] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [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: 06/16/2017] [Revised: 08/02/2017] [Accepted: 09/04/2017] [Indexed: 01/20/2023] Open
Abstract
There is evidence that models of psychopathology specifying a general factor and specific second-order factors fit better than competing structural models. Nonetheless, additional tests are needed to examine the generality and boundaries of the general factor model. In a selected second wave of a cohort study, first-order dimensions of psychopathology symptoms in 499 23- to 31-year-old twins were analyzed. Using confirmatory factor analysis, a bifactor model specifying a general factor and specific internalizing and externalizing factors fit better than competing models. Factor loadings in this model were sex invariant despite greater variances in the specific internalizing factor among females and greater variances in the general and specific externalizing factors among males. The bifactor structure was robust to the exclusion of any single first-order dimension of psychopathology. Furthermore, the results were essentially unchanged when all overlapping symptoms that define multiple disorders were excluded from symptom dimensions. Furthermore, the best-fitting bifactor model also emerged in exploratory structural equation modeling with freely estimated cross-loadings. The general factor of psychopathology was robust across variations in measurement and analysis.
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Affiliation(s)
- Benjamin B. Lahey
- Department of Public Health SciencesUniversity of ChicagoChicagoIllinoisUSA
| | - David H. Zald
- Departments of Psychology and PsychiatryVanderbilt UniversityNashvilleTennesseeUSA
| | - Scott F. Perkins
- Departments of Psychology and PsychiatryVanderbilt UniversityNashvilleTennesseeUSA
| | | | - Katherine B. Werts
- Departments of Psychology and PsychiatryVanderbilt UniversityNashvilleTennesseeUSA
| | - Carol A. Van Hulle
- Department of Biostatistics and Medical InformaticsUniversity of WisconsinMadisonWisconsinUSA
| | - Paul J. Rathouz
- Department of Biostatistics and Medical InformaticsUniversity of WisconsinMadisonWisconsinUSA
| | - Brooks Applegate
- Department of Educational Leadership, Research and TechnologyWestern Michigan UniversityKalamazooMichiganUSA
| | - Quetzal A. Class
- Department of Obstetrics and GynecologyUniversity of Illinois at ChicagoChicagoIllinoisUSA
| | - Holly E. Poore
- Department of PsychologyEmory UniversityAtlantaGeorgiaUSA
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