scholarly journals Erratum to “Neurocognitive reorganization between crystallized intelligence, fluid intelligence and white matter microstructure in two age-heterogeneous developmental cohorts” [Dev. Cogn. Neurosci. 41 (2020) 100743]

2020 ◽  
Vol 42 ◽  
pp. 100769
Author(s):  
Ivan L. Simpson-Kent ◽  
Delia Fuhrmann ◽  
Joe Bathelt ◽  
Jascha Achterberg ◽  
Gesa Sophia Borgeest ◽  
...  
Keyword(s):  
White Matter ◽  
Fluid Intelligence ◽  
Crystallized Intelligence ◽  
White Matter Microstructure

scholarly journals Neurocognitive reorganization between crystallized intelligence, fluid intelligence and white matter microstructure in two age-heterogeneous developmental cohorts

2020 ◽  
Vol 41 ◽  
pp. 100743 ◽  
Author(s):  
Ivan L. Simpson-Kent ◽  
Delia Fuhrmann ◽  
Joe Bathelt ◽  
Jascha Achterberg ◽  
Gesa Sophia Borgeest ◽  
...  
Keyword(s):  
White Matter ◽  
Fluid Intelligence ◽  
Crystallized Intelligence ◽  
White Matter Microstructure

scholarly journals Coupled Changes in Brain White Matter Microstructure and Fluid Intelligence in Later Life

2015 ◽  
Vol 35 (22) ◽  
pp. 8672-8682 ◽  
Author(s):  
Stuart J. Ritchie ◽  
Mark E. Bastin ◽  
Elliot M. Tucker-Drob ◽  
Susana Muñoz Maniega ◽  
Laura E. Engelhardt ◽  
...  
Keyword(s):  
White Matter ◽  
Fluid Intelligence ◽  
Later Life ◽  
Brain White Matter ◽  
White Matter Microstructure

scholarly journals The neural determinants of age-related changes in fluid intelligence: a pre-registered, longitudinal analysis in UK Biobank

2018 ◽  
Vol 3 ◽  
pp. 38 ◽  
Author(s):  
Rogier A. Kievit ◽  
Delia Fuhrmann ◽  
Gesa Sophia Borgeest ◽  
Ivan L. Simpson-Kent ◽  
Richard N. A. Henson
Keyword(s):  
Individual Differences ◽  
White Matter ◽  
Grey Matter ◽  
Fluid Intelligence ◽  
Grey Matter Volume ◽  
Uk Biobank ◽  
Matter Volume ◽  
White Matter Microstructure ◽  
The Mean ◽  
Intelligence Scores

Background: Fluid intelligence declines with advancing age, starting in early adulthood. Within-subject declines in fluid intelligence are highly correlated with contemporaneous declines in the ability to live and function independently. To support healthy aging, the mechanisms underlying these declines need to be better understood. Methods: In this pre-registered analysis, we applied latent growth curve modelling to investigate the neural determinants of longitudinal changes in fluid intelligence across three time points in 185,317 individuals (N=9,719 two waves, N=870 three waves) from the UK Biobank (age range: 39-73 years). Results: We found a weak but significant effect of cross-sectional age on the mean fluid intelligence score, such that older individuals scored slightly lower. However, the mean longitudinal slope was positive, rather than negative, suggesting improvement across testing occasions. Despite the considerable sample size, the slope variance was non-significant, suggesting no reliable individual differences in change over time. This null-result is likely due to the nature of the cognitive test used. In a subset of individuals, we found that white matter microstructure (N=8839, as indexed by fractional anisotropy) and grey-matter volume (N=9931) in pre-defined regions-of-interest accounted for complementary and unique variance in mean fluid intelligence scores. The strongest effects were such that higher grey matter volume in the frontal pole and greater white matter microstructure in the posterior thalamic radiations were associated with higher fluid intelligence scores. Conclusions: In a large preregistered analysis, we demonstrate a weak but significant negative association between age and fluid intelligence. However, we did not observe plausible longitudinal patterns, instead observing a weak increase across testing occasions, and no significant individual differences in rates of change, likely due to the suboptimal task design. Finally, we find support for our preregistered expectation that white- and grey matter make separate contributions to individual differences in fluid intelligence beyond age.

scholarly journals Neurocognitive reorganization between crystallized intelligence, fluid intelligence and white matter microstructure in two age-heterogeneous developmental cohorts

2019 ◽  
Author(s):  
Ivan L. Simpson-Kent ◽  
Delia Fuhrmann ◽  
Joe Bathelt ◽  
Jascha Achterberg ◽  
Gesa Sophia Borgeest ◽  
...  
Keyword(s):  
White Matter ◽  
Cognitive Ability ◽  
Cognitive Abilities ◽  
Structural Equation ◽  
Fluid Intelligence ◽  
Childhood And Adolescence ◽  
Pivotal Phase ◽  
Cross Sectional ◽  
White Matter Microstructure ◽  
Age Range

AbstractDespite the reliability of intelligence measures in predicting important life outcomes such as educational achievement and mortality, the exact configuration and neural correlates of cognitive abilities remain poorly understood, especially in childhood and adolescence. Therefore, we sought to elucidate the factorial structure and neural substrates of child and adolescent intelligence using two cross-sectional, developmental samples (CALM: N=551 (N=165 imaging), age range: 5-18 years, NKI-Rockland: N=337 (N=65 imaging), age range: 6-18 years). In a preregistered analysis, we used structural equation modelling (SEM) to examine the neurocognitive architecture of individual differences in childhood and adolescent cognitive ability. In both samples, we found that cognitive ability in lower and typical-ability cohorts is best understood as two separable constructs, crystallized and fluid intelligence, which became more distinct across development, in line with the age differentiation hypothesis. Further analyses revealed that white matter microstructure, most prominently the superior longitudinal fasciculus, was strongly associated with crystallized (gc) and fluid (gf) abilities. Finally, we used SEM trees to demonstrate evidence for developmental reorganization of gc and gf and their white matter substrates such that the relationships among these factors dropped between 7-8 years before increasing around age 10. Together, our results suggest that shortly before puberty marks a pivotal phase of change in the neurocognitive architecture of intelligence.

scholarly journals The neural determinants of age-related changes in fluid intelligence: a pre-registered, longitudinal analysis in UK Biobank

2018 ◽  
Vol 3 ◽  
pp. 38 ◽  
Author(s):  
Rogier A. Kievit ◽  
Delia Fuhrmann ◽  
Gesa Sophia Borgeest ◽  
Ivan L. Simpson-Kent ◽  
Richard N. A. Henson
Keyword(s):  
Individual Differences ◽  
White Matter ◽  
Grey Matter ◽  
Fluid Intelligence ◽  
Grey Matter Volume ◽  
Uk Biobank ◽  
Matter Volume ◽  
White Matter Microstructure ◽  
The Mean ◽  
Intelligence Scores

Background: Fluid intelligence declines with advancing age, starting in early adulthood. Within-subject declines in fluid intelligence are highly correlated with contemporaneous declines in the ability to live and function independently. To support healthy aging, the mechanisms underlying these declines need to be better understood. Methods: In this pre-registered analysis, we applied latent growth curve modelling to investigate the neural determinants of longitudinal changes in fluid intelligence across three time points in 185,317 individuals (N=9,719 two waves, N=870 three waves) from the UK Biobank (age range: 39-73 years). Results: We found a weak but significant effect of cross-sectional age on the mean fluid intelligence score, such that older individuals scored slightly lower. However, the mean longitudinal slope was positive, rather than negative, suggesting improvement across testing occasions. Despite the considerable sample size, the slope variance was non-significant, suggesting no reliable individual differences in change over time. This null-result is likely due to the nature of the cognitive test used. In a subset of individuals, we found that white matter microstructure (N=8839, as indexed by fractional anisotropy) and grey-matter volume (N=9931) in pre-defined regions-of-interest accounted for complementary and unique variance in mean fluid intelligence scores. The strongest effects were such that higher grey matter volume in the frontal pole and greater white matter microstructure in the posterior thalamic radiations were associated with higher fluid intelligence scores. Conclusions: In a large preregistered analysis, we demonstrate a weak but significant negative association between age and fluid intelligence. However, we did not observe plausible longitudinal patterns, instead observing a weak increase across testing occasions, and no significant individual differences in rates of change, likely due to the suboptimal task design. Finally, we find support for our preregistered expectation that white- and grey matter make separate contributions to individual differences in fluid intelligence beyond age.

Investment Traits and Intelligence in Adulthood

2013 ◽  
Vol 34 (2) ◽  
pp. 82-89 ◽  
Author(s):  
Sophie von Stumm
Keyword(s):  
Individual Differences ◽  
Personality Traits ◽  
Fluid Intelligence ◽  
Need For Cognition ◽  
Openness To Experience ◽  
Intelligence Tests ◽  
Crystallized Intelligence ◽  
New Knowledge ◽  
The Relationship ◽  
Over Time

Intelligence-as-knowledge in adulthood is influenced by individual differences in intelligence-as-process (i.e., fluid intelligence) and in personality traits that determine when, where, and how people invest their intelligence over time. Here, the relationship between two investment traits (i.e., Openness to Experience and Need for Cognition), intelligence-as-process and intelligence-as-knowledge, as assessed by a battery of crystallized intelligence tests and a new knowledge measure, was examined. The results showed that (1) both investment traits were positively associated with intelligence-as-knowledge; (2) this effect was stronger for Openness to Experience than for Need for Cognition; and (3) associations between investment and intelligence-as-knowledge reduced when adjusting for intelligence-as-process but remained mostly significant.

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