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 ◽  
...  

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.

2018 ◽  
Author(s):  
D. Fuhrmann ◽  
I. L. Simpson-Kent ◽  
J. Bathelt ◽  
R. A. Kievit ◽  

AbstractFluid intelligence is the capacity to solve novel problems in the absence of task-specific knowledge, and is highly predictive of outcomes like educational attainment and psychopathology. Here, we modelled the neurocognitive architecture of fluid intelligence in two cohorts: CALM (N = 551, aged 5 - 17 years) and NKI-RS (N = 335, aged 6 - 17 years). We used multivariate Structural Equation Modelling to test a preregistered watershed model of fluid intelligence. This model predicts that white matter contributes to intermediate cognitive phenotypes, like working memory and processing speed, which, in turn, contribute to fluid intelligence. We found that this model performed well for both samples and explained large amounts of variance in fluid intelligence (R2CALM = 51.2%, R2NKI-RS = 78.3%). The relationship between cognitive abilities and white matter differed with age, showing a dip in strength around ages 7 - 12 years. This age-effect may reflect a reorganization of the neurocognitive architecture around pre- and early puberty. Overall, these findings highlight that intelligence is part of a complex hierarchical system of partially independent effects.


2019 ◽  
Vol 30 (1) ◽  
pp. 339-352 ◽  
Author(s):  
Delia Fuhrmann ◽  
Ivan L Simpson-Kent ◽  
Joe Bathelt ◽  
Rogier A Kievit ◽  
◽  
...  

AbstractFluid intelligence is the capacity to solve novel problems in the absence of task-specific knowledge and is highly predictive of outcomes like educational attainment and psychopathology. Here, we modeled the neurocognitive architecture of fluid intelligence in two cohorts: the Centre for Attention, Leaning and Memory sample (CALM) (N = 551, aged 5–17 years) and the Enhanced Nathan Kline Institute—Rockland Sample (NKI-RS) (N = 335, aged 6–17 years). We used multivariate structural equation modeling to test a preregistered watershed model of fluid intelligence. This model predicts that white matter contributes to intermediate cognitive phenotypes, like working memory and processing speed, which, in turn, contribute to fluid intelligence. We found that this model performed well for both samples and explained large amounts of variance in fluid intelligence (R2CALM = 51.2%, R2NKI-RS = 78.3%). The relationship between cognitive abilities and white matter differed with age, showing a dip in strength around ages 7–12 years. This age effect may reflect a reorganization of the neurocognitive architecture around pre- and early puberty. Overall, these findings highlight that intelligence is part of a complex hierarchical system of partially independent effects.


2020 ◽  
Author(s):  
Anne-Lise Goddings ◽  
David Roalf ◽  
Catherine Lebel ◽  
Christian K. Tamnes

Diffusion magnetic resonance imaging (dMRI) provides indirect measures of white matter microstructure that can be used to make inferences about structural connectivity within the brain. Over the last decade, a growing literature of cross-sectional and longitudinal studies have documented relationships between dMRI indices and cognitive development. In this review, we provide a brief overview of dMRI methods and how they can be used to study white matter and connectivity, briefly discuss challenges with using dMRI in child and adolescent populations, and review the extant literature examining the links between dMRI indices and executive functions during development. We explore the links between white matter microstructure and specific executive functions: inhibition, working memory and cognitive shifting, as well as performance on complex executive function tasks. Where there is concordance in findings across studies, this is highlighted, and potential explanations for discrepancies between results are discussed. Finally, we explore future directions that are necessary to better understand the links between child and adolescent development of executive functions and structural connectivity of the brain.


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 ◽  
...  

2017 ◽  
Author(s):  
Susanne M. M. de Mooij ◽  
Richard N. A. Henson ◽  
Lourens J. Waldorp ◽  
Cam-CAN ◽  
Rogier A. Kievit

AbstractIt is well-established that brain structures and cognitive functions change across the lifespan. A longstanding hypothesis called age differentiation additionally posits that the relations between cognitive functions also change with age. To date however, evidence for age-related differentiation is mixed, and no study has examined differentiation of the relationship between brain and cognition. Here we use multi-group Structural Equation Modeling and SEM Trees to study differences within and between brain and cognition across the adult lifespan (18-88 years) in a large (N>646, closely matched across sexes), population-derived sample of healthy human adults from the Cambridge Centre for Ageing and Neuroscience (www.cam-can.org). After factor analyses of grey-matter volume (from T1- and T2-weighted MRI) and white-matter organisation (fractional anisotropy from Diffusion-weighted MRI), we found evidence for differentiation of grey and white matter, such that the covariance between brain factors decreased with age. However, we found no evidence for age differentiation between fluid intelligence, language and memory, suggesting a relatively stable covariance pattern between cognitive factors. Finally, we observed a specific pattern of age differentiation between brain and cognitive factors, such that a white matter factor, which loaded most strongly on the hippocampal cingulum, became less correlated with memory performance in later life. These patterns are compatible with reorganization of cognitive functions in the face of neural decline, and/or with the emergence of specific subpopulations in old age.Significance statementThe theory of age differentiation posits age-related changes in the relationships between cognitive domains, either weakening (differentiation) or strengthening (de-differentiation), but evidence for this hypothesis is mixed. Using age-varying covariance models in a large cross-sectional adult lifespan sample, we found age-related reductions in the covariance among both brain measures (neural differentiation), but no covariance change between cognitive factors of fluid intelligence, language and memory. We also observed evidence of uncoupling (differentiation) between a white matter factor and cognitive factors in older age, most strongly for memory. Together, our findings support age-related differentiation as a complex, multifaceted pattern that differs for brain and cognition, and discuss several mechanisms that might explain the changing relationship between brain and cognition.


2020 ◽  
Vol 41 ◽  
pp. 100743 ◽  
Author(s):  
Ivan L. Simpson-Kent ◽  
Delia Fuhrmann ◽  
Joe Bathelt ◽  
Jascha Achterberg ◽  
Gesa Sophia Borgeest ◽  
...  

2020 ◽  
Vol 26 (7) ◽  
pp. 679-689
Author(s):  
Chang Hyun Lee ◽  
Do Hoon Kim

AbstractObjective:The aim of this study was to model the relationships among white matter hyperintensities (WMHs), depressive symptoms, and cognitive function and to examine the mediating effect of depressive symptoms on the relationship between WMHs and cognitive impairment.Methods:We performed structural equation modeling using cross-sectional data from 1158 patients from the Clinical Research for Dementia of South Korea (CREDOS) registry who were diagnosed with mild-to-moderate dementia. Periventricular white matter hyperintensities (PWMHs) and deep white matter hyperintensities (DWMHs) were obtained separately on the protocol of magnetic resonance imaging (MRI). Depression and cognitive function were assessed using the Korean Form of the Geriatric Depression Scale (KGDS) and the Seoul Neuropsychological Screening Battery (SNSB), respectively.Results:The model that best reflected the relationships among the variables was the model in which DWMHs affected cognitive function directly and indirectly through the depressive symptoms; on the other hand, PWMHs only directly affected cognitive function.Conclusions:This study presents the mediation model including the developmental pathway from DWMHs to cognitive impairment through depressive symptoms and suggests that the two types of WMHs may affect cognitive impairment through different pathways.


1997 ◽  
Vol 8 (6) ◽  
pp. 442-447 ◽  
Author(s):  
Robert Plomin ◽  
David W. Fulker ◽  
Robin Corley ◽  
John C DeFries

Children increasingly resemble their parents in cognitive abilities from infancy through adolescence Results obtained from a 20-year longitudinal adoption study of 245 adopted children and their biological and adoptive parents, as well as 245 matched nonadoptive (control) parents and offspring, show that this increasing resemblance is due to genetic factors Adopted children resemble their adoptive parents slightly in early childhood but not at all in middle childhood or adolescence In contrast, during childhood and adolescence, adopted children become more like their biological parents, and to the same degree as children and parents in control families Although these results were strongest for general cognitive ability and verbal ability similar results were found for other specific cognitive abilities—spatial ability, speed of processing, and recognition memory These findings indicate that within this population, genes that stably affect cognitive abilities in adulthood do not all come into play until adolescence and that environmental factors that contribute to cognitive development are not correlated with parents' cognitive ability


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