Neuroimaging of individual differences: A latent variable modeling perspective

2019/01/03 by Shelly R. Cooper, Joshua J. Jackson, Deanna M. Barch +1 · 1 voice · 61 citations
Neuroscience · Psychology · #Artificial intelligence #Cognition #Cognitive Abilities and Testing #Cognitive neuroscience #Cognitive psychology #Computer science #Connectome #Functional Brain Connectivity Studies #Functional connectivity #Functional neuroimaging #Human Connectome Project #Latent variable #Latent variable model #Machine learning #Mental Health Research Topics #Neuroimaging #Neuroscience #Psychology #Structural equation modeling

paper · doi:10.1016/j.neubiorev.2018.12.022

published in Neuroscience & Biobehavioral Reviews 98, 29-46 (Elsevier BV)

openalex publication_date 2019/01/03 · crossref created 2019/01/03 · crossref issued 2019/03/01 · crossref published 2019/03/01 · crossref published-print 2019/03/01 · crossref deposited 2025/09/27 · openalex created_date 2025/10/10 · crossref indexed 2026/08/04 · openalex updated_date 2026/08/06

Citations

• Estimating the reproducibility of psychological science
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• Power failure: why small sample size undermines the reliability of neuroscience
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• THE SIGNIFICANCE OF LIGHT TRAUMA FOR THE INDUCTION, LOCALIZATION, AND FREQUENCY OF SKIN CANCERS.
• Nonconvergence, Improper Solutions, and Starting Values in Lisrel Maximum Likelihood Estimation
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• The Attack of the Psychometricians
• Factors and Taxa, Traits and Types, Differences of Degree and Differences in Kind
• Puzzlingly High Correlations in fMRI Studies of Emotion, Personality, and Social Cognition
• Small sample sizes reduce the replicability of task-based fMRI studies

Cited by

• The longitudinal stability of fMRI activation during reward processing in adolescents and young adults

Discussions

• In a similar vein, combining observations from multiple regions seems to increase sensitivity to individual differences (though I don't think these papers have tested reliability), including work usin [bsky, 0 points, 1 comments]