scholarly journals A hierarchical watershed model of fluid intelligence in childhood and adolescence

2018 ◽  
Author(s):  
D. Fuhrmann ◽  
I. L. Simpson-Kent ◽  
J. Bathelt ◽  
R. A. Kievit ◽  
Keyword(s):  
White Matter ◽  
Cognitive Abilities ◽  
Structural Equation ◽  
Fluid Intelligence ◽  
Childhood And Adolescence ◽  
Watershed Model ◽  
Early Puberty ◽  
Specific Knowledge ◽  
Independent Effects ◽  
The Relationship

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.

scholarly journals A Hierarchical Watershed Model of Fluid Intelligence in Childhood and Adolescence

2019 ◽  
Vol 30 (1) ◽  
pp. 339-352 ◽  
Author(s):  
Delia Fuhrmann ◽  
Ivan L Simpson-Kent ◽  
Joe Bathelt ◽  
Rogier A Kievit ◽  
◽  
...  
Keyword(s):  
White Matter ◽  
Cognitive Abilities ◽  
Structural Equation ◽  
Fluid Intelligence ◽  
Equation Modeling ◽  
Childhood And Adolescence ◽  
Watershed Model ◽  
Early Puberty ◽  
Independent Effects ◽  
The Relationship

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.

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.

A New View of the Relationship between Creativity and Intelligence

1981 ◽  
Vol 5 (4) ◽  
pp. 295-307
Author(s):  
Steven Harvey
Keyword(s):  
Cognitive Abilities ◽  
Structural Equation ◽  
Creative Thinking ◽  
Fluid Intelligence ◽  
Juvenile Justice System ◽  
Factor Model ◽  
Equation Model ◽  
General Intelligence ◽  
Age Appropriate ◽  
The Relationship

One hundred and fourteen youths involved in a juvenile justice system, half of whom were included because of potential giftedness, were administered the age appropriate Weschler Intelligence Scales and the Torrance Test of Creative Thinking to assess their cognitive abilities. The resulting multivariate data were analyzed using maximum likehood factor analysis and structural equation model to develop a factor model of intellectual and creative abilities and the relationships among them. Two high order factor and five lower level characteristics were isolated. These were defined as general intelligence and general fluency at the higher level, and crystallized and fluid intelligence, verbal and figural divergent production, along with creative energy, at the lower level. While no relationship was found between general intelligence and general fluency, the creative energy factor was found to be influenced by both of these higher order factors. This result was used in discussion related to the theory of creativity.

scholarly journals Age differentiation within grey matter, white matter and between memory and white matter in an adult lifespan cohort

2017 ◽  
Author(s):  
Susanne M. M. de Mooij ◽  
Richard N. A. Henson ◽  
Lourens J. Waldorp ◽  
Cam-CAN ◽  
Rogier A. Kievit
Keyword(s):  
White Matter ◽  
Cognitive Functions ◽  
Structural Equation ◽  
Grey Matter ◽  
Fluid Intelligence ◽  
Cognitive Factors ◽  
Equation Modeling ◽  
Grey Matter Volume ◽  
Adult Lifespan ◽  
Age Related

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.

scholarly journals A watershed model of individual differences in fluid intelligence

2016 ◽  
Author(s):  
Rogier A. Kievit ◽  
Simon W. Davis ◽  
John Griffiths ◽  
Marta Correia ◽  
Cam-CAN ◽  
...  
Keyword(s):  
White Matter ◽  
Processing Speed ◽  
Fluid Intelligence ◽  
White Matter Integrity ◽  
Life Outcomes ◽  
Watershed Model ◽  
Adult Lifespan ◽  
Large N ◽  
Competing Models ◽  
The One

AbstractFluid intelligence is a crucial cognitive ability that predicts key life outcomes across the lifespan. Strong empirical links exist between fluid intelligence and processing speed on the one hand, and white matter integrity and processing speed on the other. We propose a watershed model that integrates these three explanatory levels in a principled manner in a single statistical model, with processing speed and white matter figuring as intermediate endophenotypes. We fit this model in a large (N=555) adult lifespan cohort from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) using multiple measures of processing speed, white matter health and fluid intelligence. The model fit the data well, outperforming competing models and providing evidence for a many-to-one mapping between white matter integrity, processing speed and fluid intelligence. The model can be naturally extended to integrate other cognitive domains, endophenotypes and genotypes.

scholarly journals PRE/PERINATAL ADVERSITIES AND BEHAVIOURAL OUTCOMES IN EARLY CHILDHOOD: PRELIMINARY FINDINGS FROM THE VANCOUVER LONGITUDINAL STUDY

2011 ◽  
Vol 2 (1/2) ◽  
pp. 36 ◽  
Author(s):  
Patrick Lussier ◽  
Stacy Tzoumakis ◽  
Jay Healey ◽  
Ray Corrado ◽  
Pratibha Reebye
Keyword(s):  
Substance Use ◽  
Longitudinal Study ◽  
Physical Aggression ◽  
Structural Equation ◽  
Childhood And Adolescence ◽  
Structured Interviews ◽  
Birth Complications ◽  
Sexual Behaviours ◽  
Maternal Substance Use ◽  
The Relationship

Several pre/perinatal factors (e.g., birth complications, maternal substance use, low birth weight) have been associated with early neuropsychological deficits and negative behavioural outcomes in infancy, childhood, and adolescence. The current study examines the relationship between maternal substance use during pregnancy and its impact on physical aggression and sexual behaviours in a sample of preschoolers. This study is based on a sample of children (<em>n</em> = 129), boys and girls, recruited as part of the KD-BEAR project, an ongoing longitudinal study conducted in Vancouver, British Columbia, Canada. The sample consisted of clinical referrals for an externalizing disorder and children recruited in daycares located in at-risk neighbourhoods. Semi-structured interviews were completed with the primary caregiver. A series of structural equation modelling showed that children showing higher levels of physical aggression and sexual behaviours were more likely to have been exposed to maternal substance use and pregnancy-related complications. Implications of the study are discussed in light of the scientific literature on the early prevention of aggression and violence.

scholarly journals Cerebral White Matter Myelination and Relations to Age, Gender, and Cognition: A Selective Review

2021 ◽  
Vol 15 ◽  
Author(s):  
Irina S. Buyanova ◽  
Marie Arsalidou
Keyword(s):  
White Matter ◽  
Cognitive Abilities ◽  
Brain Maturation ◽  
Cerebral White Matter ◽  
Childhood And Adolescence ◽  
Spatial And Temporal Patterns ◽  
Fiber Tracts ◽  
Selective Review ◽  
And Gender ◽  
Neuroimaging Techniques

White matter makes up about fifty percent of the human brain. Maturation of white matter accompanies biological development and undergoes the most dramatic changes during childhood and adolescence. Despite the advances in neuroimaging techniques, controversy concerning spatial, and temporal patterns of myelination, as well as the degree to which the microstructural characteristics of white matter can vary in a healthy brain as a function of age, gender and cognitive abilities still exists. In a selective review we describe methods of assessing myelination and evaluate effects of age and gender in nine major fiber tracts, highlighting their role in higher-order cognitive functions. Our findings suggests that myelination indices vary by age, fiber tract, and hemisphere. Effects of gender were also identified, although some attribute differences to methodological factors or social and learning opportunities. Findings point to further directions of research that will improve our understanding of the complex myelination-behavior relation across development that may have implications for educational and clinical practice.

Psychological Adjustment During Multiple Transitions Between Childhood and Adolescence

2019 ◽  
Vol 40 (4) ◽  
pp. 566-598 ◽  
Author(s):  
Gabriela Gniewosz ◽  
Burkhard Gniewosz
Keyword(s):  
Psychological Adjustment ◽  
Structural Equation ◽  
Specific Effect ◽  
Educational Background ◽  
Childhood And Adolescence ◽  
Parent Child Relationship ◽  
Early Puberty ◽  
Child Relationship ◽  
Resource Effects ◽  
Parent Child

Based on the temporal framework of transition experiences, this study tested time-graded patterns of family resource effects on children’s and early adolescents’ psychological adjustment during a time of multiple transitions. Using data of a longitudinal study including 2,020 German children covering the age span between 8 and 12 ( nboys = 1,035, ngirls = 985), internalizing and externalizing problems were predicted by parent-child relationship and family’s educational background in a multi-group structural equation model, applying time-lagged autoregressive models. The results showed positive resource effects especially through parent-child relationship. The gender-specific effect patterns over time supported the assumption of stronger resource effects when early puberty onset and secondary school transition co-occurred. Thus, it is important to provide support for this vulnerable group during times of multiple transitions.

scholarly journals On the Positive Relationship between Breastfeeding & Intelligence

2017 ◽  
Author(s):  
Brian Boutwell
Keyword(s):  
Cognitive Abilities ◽  
Observational Studies ◽  
Structural Equation ◽  
Maternal Education ◽  
National Sample ◽  
Multiple Intelligence ◽  
Cognitive Stimulation ◽  
Equation Modeling ◽  
Childhood And Adolescence ◽  
Confounding Variables

A wealth of literature has examined the association between breastfeeding and the development of cognitive abilities in childhood. In particular, at least some evidence exists suggesting that breastfed children perform better on measures of intelligence later in life. While a correlation appears to be present, fewer observational studies have included appropriate adjustment for potentially confounding variables; maternal intelligence, maternal education, and cognitive stimulation provided by mothers being chief among them. As a result, we analyze a national sample of approximately 790 American respondents in order to test the association between breastfeeding and intelligence during childhood and adolescence using multiple intelligence tests and controlling for a range of key covariates. Our results suggest that the correlation between breastfeeding throughout the first six months of life and intelligence is statistically significant and consistent, yet of substantively minor impact.Keywords: Intelligence; breastfeeding; development; structural equation modeling

scholarly journals Predicting Academic Achievement with Cognitive Abilities: Cross-Sectional Study across School Education

2020 ◽  
Vol 10 (10) ◽  
pp. 158
Author(s):  
Tatiana Tikhomirova ◽  
Artem Malykh ◽  
Sergey Malykh
Keyword(s):  
Academic Achievement ◽  
Working Memory ◽  
Information Processing ◽  
Processing Speed ◽  
Cognitive Abilities ◽  
Fluid Intelligence ◽  
Number Sense ◽  
Information Processing Speed ◽  
Cross Sectional ◽  
The Relationship

The relationship between cognitive abilities and academic achievement across schooling from the first to the eleventh grade was analyzed. Information processing speed, visuospatial working memory, number sense, and fluid intelligence were considered predictors of general academic achievement, which was derived from grades in mathematics, language, and biology. This cross-sectional study involved 1560 pupils who were in grades 1–11 at general education schools and were aged from 6.8 to 19.1 years (50.4% were boys). Information processing speed, visuospatial working memory, and number sense were measured using the Choice Reaction Time, Corsi Block-Tapping, and Number Sense computerized tests, respectively. Fluid intelligence was measured using the paper-and-pencil version of the Standard Progressive Matrices test. Correlation analysis and structural equation modeling were carried out. It was shown that it is possible to describe the structure of the relationship between cognitive abilities and academic achievement for all levels of schooling with a single model. In this model, information processing speed is the key predictor of fluid intelligence, working memory, and number sense, which in turn contribute to individual differences in academic success. Additionally, the specificity of the relationship between individual indicators of cognitive abilities and academic achievement at each level of schooling was revealed.

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