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 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 Cognitive Processing Speed in Older Adults: Relationship with White Matter Integrity

PLoS ONE ◽  
2012 ◽  
Vol 7 (11) ◽  
pp. e50425 ◽  
Author(s):  
Geoffrey A. Kerchner ◽  
Caroline A. Racine ◽  
Sandra Hale ◽  
Reva Wilheim ◽  
Victor Laluz ◽  
...  
Keyword(s):  
Older Adults ◽  
White Matter ◽  
Cognitive Processing ◽  
Processing Speed ◽  
White Matter Integrity ◽  
Cognitive Processing Speed

scholarly journals S159. REDUCED PROCESSING SPEED IN SCHIZOPHRENIA IS MEDIATED BY WHITE MATTER INTEGRITY

2018 ◽  
Vol 44 (suppl_1) ◽  
pp. S387-S387
Author(s):  
Saetbyeol Cha ◽  
Woon Yoon ◽  
Seung-Hyun Shon ◽  
Jungsun Lee
Keyword(s):  
White Matter ◽  
Processing Speed ◽  
White Matter Integrity

Age Affects White Matter Integrity and Episodic Memory Across the Older Adult Lifespan

2020 ◽  
Author(s):  
Jenna Merenstein ◽  
María M. Corrada ◽  
Claudia H. Kawas ◽  
Ilana J. Bennett
Keyword(s):  
Cognitive Impairment ◽  
White Matter ◽  
Episodic Memory ◽  
Older Adult ◽  
Diffusion Tensor ◽  
Oldest Old ◽  
White Matter Integrity ◽  
Adult Lifespan ◽  
Increased Risk ◽  
Effect Of Age

Aging is accompanied by declines in white matter integrity (e.g., demyelination, decreased fiber density) that contribute to cognitive deficits. Diffusion tensor imaging (DTI) studies have observed these integrity declines in vivo separately in younger-old (ages 65-89) and oldest-old (ages 90+) adults. But it remains unclear whether the effect of age on integrity is magnified in advanced age groups and whether this may result from normal aging or dementia-related pathology. Here, we tested whether age-related differences in white matter integrity followed linear or nonlinear patterns when considering the entire older adult lifespan (n = 108; 65-98 years) and whether these patterns were influenced by oldest-old adults at increased risk of dementia (cognitive impairment no dementia, CIND). To assess the functional impact of white matter aging, we then examined the extent to which it explained age effects on episodic memory performance (delayed recall, recognition). Results revealed significant nonlinear declines in the integrity of medial temporal, callosal, and association fiber classes, with linear declines observed for the projection/thalamic fiber class. These patterns remained after excluding the oldest-old participants with CIND, indicating that larger differences in white matter integrity with increased age cannot solely be explained by pathology associated with early cognitive impairment. We also found that the effect of age on episodic memory was partially mediated by integrity of medial temporal fibers, suggesting that they are essential for facilitating memory-related neural signals across the older adult lifespan.

White matter integrity predicts individual differences in (fluid) intelligence through working memory

2014 ◽  
Vol 60 ◽  
pp. S77 ◽  
Author(s):  
J. Privado ◽  
C. Sáenz de Urturi ◽  
J. Dávila ◽  
C. López ◽  
M. Burgaleta ◽  
...  
Keyword(s):  
Working Memory ◽  
Individual Differences ◽  
White Matter ◽  
Fluid Intelligence ◽  
White Matter Integrity

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 White matter integrity and processing speed in sickle cell anemia

Neurology ◽  
2018 ◽  
Vol 90 (23) ◽  
pp. e2042-e2050 ◽  
Author(s):  
Hanne Stotesbury ◽  
Fenella J. Kirkham ◽  
Melanie Kölbel ◽  
Philippa Balfour ◽  
Jonathan D. Clayden ◽  
...  
Keyword(s):  
White Matter ◽  
Confidence Interval ◽  
Cerebral Infarction ◽  
Sickle Cell ◽  
Sickle Cell Anemia ◽  
Processing Speed ◽  
Volume Fraction ◽  
White Matter Integrity ◽  
Arterial Oxygen ◽  
Silent Cerebral Infarction

ObjectiveThe purpose of this retrospective cross-sectional study was to investigate whether changes in white matter integrity are related to slower processing speed in sickle cell anemia.MethodsThirty-seven patients with silent cerebral infarction, 46 patients with normal MRI, and 32 sibling controls (age range 8–37 years) underwent cognitive assessment using the Wechsler scales and 3-tesla MRI. Tract-based spatial statistics analyses of diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) parameters were performed.ResultsProcessing speed index (PSI) was lower in patients than controls by 9.34 points (95% confidence interval: 4.635–14.855,p= 0.0003). Full Scale IQ was lower by 4.14 scaled points (95% confidence interval: −1.066 to 9.551,p= 0.1), but this difference was abolished when PSI was included as a covariate (p= 0.18). There were no differences in cognition between patients with and without silent cerebral infarction, and both groups had lower PSI than controls (bothp< 0.001). In patients, arterial oxygen content, socioeconomic status, age, and male sex were identified as predictors of PSI, and correlations were found between PSI and DTI scalars (fractional anisotropyr= 0.614,p< 0.00001;r= −0.457,p< 0.00001; mean diffusivityr= −0.341,p= 0.0016; radial diffusivityr= −0.457,p< 0.00001) and NODDI parameters (intracellular volume fractionr= 0.364,p= 0.0007) in widespread regions.ConclusionOur results extend previous reports of impairment that is independent of presence of infarction and may worsen with age. We identify processing speed as a vulnerable domain, with deficits potentially mediating difficulties across other domains, and provide evidence that reduced processing speed is related to the integrity of normal-appearing white matter using microstructure parameters from DTI and NODDI.

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