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.

Age-Related Effects on Interoceptive Accuracy, General Interoceptive Sensibility, and Specific Interoceptive Sensibility

2020 ◽  
Vol 27 (4) ◽  
pp. 154-170 ◽  
Author(s):  
L. Nusser ◽  
O. Pollatos ◽  
D. Zimprich
Keyword(s):  
Structural Equation ◽  
Empirical Support ◽  
Self Report ◽  
Three Dimensions ◽  
Equation Modeling ◽  
Adult Lifespan ◽  
Age Related ◽  
Physical Diseases ◽  
Interoceptive Accuracy ◽  
Subjective Belief

Abstract. Background: The current research into interoception distinguishes between interoceptive accuracy (IAcc), the accurate detection of internal sensations (e.g., heartbeats) as measured by performance on objective IAcc tasks, and interoceptive sensibility (IS), the subjective belief concerning one’s own experience of internal sensations as measured either through self-report questionnaires or through one’s confidence in the accuracy during an IAcc task. Aims: As the two measures of IS, however, are usually uncorrelated and show differential relationships to IAcc, we suggest different types of IS, a general IS and a specific IS. Further, based on a growing body of research linking IAcc and IS to physical and mental diseases, the development of interoception across the adult lifespan is of importance. Methods: Using Structural Equation Modeling the present paper investigates the relationships among IAcc assessed by a heartbeat counting task, and the two proposed dimensions of IS in 138 participants ( Mage = 42.67, SDage = 18.77). Furthermore, we examine age-related differences in IAcc, as well as in general and specific IS. Results: In terms of the relationship between the three dimensions, general and specific IS were weakly correlated and exhibited different relationships to IAcc. Further, we found different age effects on the three interoceptive dimensions. Whereas IAcc decreased with age, specific IS tend to increase with age, and general IS remained unaffected by age. Conclusion: The findings provide further empirical support for a dissociation between general and specific IS and raised important questions concerning the relation between interoceptive accuracy and the emergence of physical diseases in older age.

scholarly journals On the Impact of Interhemispheric White Matter: Age, Executive Functioning, and Dedifferentiation in the Frontal Lobes

2017 ◽  
Author(s):  
Abigail B. Waters ◽  
Kayle S. Sawyer ◽  
David A. Gansler
Keyword(s):  
Older Adults ◽  
White Matter ◽  
Executive Functioning ◽  
Significant Relationship ◽  
Grey Matter ◽  
Middle Age ◽  
Neural Substrates ◽  
Community Dwelling ◽  
Equation Modeling ◽  
Age Related

AbstractIntroductionIn middle age, declines in executive functioning (EF) are associated with decrements in the quality and/or quantity of white and grey matter. Recruitment of homologous regions has been identified as a compensatory mechanism for cognitive decline in later middle age, however research into neural substrates of EF has yet to be guided by dedifferentiation models. We hypothesized that frontal-parietal grey matter volume, interhemispheric white matter and intrahemispheric white matter fractional anisotropy (FA) will be predictive of EF. Further, we hypothesized that the comparative association between interhemispheric white matter and EF will increase with age, because of compensatory recruitment.MethodsNeurocognitive test data, DTI, and T1 MPRAGE scans (n = 444) were obtained from the NKI-Rockland Sample. Structural equation modeling was used to examine the relationship between age, EF, interhemispheric white matter (forceps minor; FM), intrahemispheric white matter (superior longitudinal fasciculus; SLF), and a frontal-parietal grey matter network. EF and grey matter were modelled as latent variables, with EF examined as the criterion. Additionally, a subsample of participants aged 55-85 (n = 168) was analyzed to examine the influence of age related compensatory mechanisms.ResultsThere was a significant relationship between FM, grey matter, and EF, which was fully mediated by age. There was a significant relationship between SLF and EF, which was not mediated by age. For older adults, only the age-mediated pathway from FM to EF was significant.DiscussionUsing structural imaging data, support was found for age-related interhemispheric mechanisms of compensation, but not intrahemispheric mechanisms.Key points(1) Neural substrates of executive functioning are not static across the lifespan. (2) In older adults, white matter becomes more salient as a structural correlate of executive functioning, as recruitment needs increase. (3) While the importance of interhemispheric white matter is mediated by age, intrahemispheric recruitment remains consistent across the lifespan, and is not the primary mechanism of age-based compensation in community dwelling older adults.

scholarly journals Contributions of White Matter Connectivity and BOLD Modulation to Cognitive Aging: A Lifespan Structure-Function Association Study

2019 ◽  
Vol 30 (3) ◽  
pp. 1649-1661 ◽  
Author(s):  
Christina E Webb ◽  
Karen M Rodrigue ◽  
David A Hoagey ◽  
Chris M Foster ◽  
Kristen M Kennedy
Keyword(s):  
Executive Function ◽  
White Matter ◽  
Structure Function ◽  
Association Study ◽  
Structural Equation ◽  
Equation Modeling ◽  
Age Related ◽  
White Matter Microstructure ◽  
Task Accuracy ◽  
Back Task

Abstract The ability to flexibly modulate brain activation to increasing cognitive challenge decreases with aging. This age-related decrease in dynamic range of function of regional gray matter may be, in part, due to age-related degradation of regional white matter tracts. Here, a lifespan sample of 171 healthy adults (aged 20–94) underwent magnetic resonance imaging (MRI) scanning including diffusion-weighted imaging (for tractography) and functional imaging (a digit n-back task). We utilized structural equation modeling to test the hypothesis that age-related decrements in white matter microstructure are associated with altered blood-oxygen-level-dependent (BOLD) modulation, and both in turn, are associated with scanner-task accuracy and executive function performance. Specified structural equation model evidenced good fit, demonstrating that increased age negatively affects n-back task accuracy and executive function performance in part due to both degraded white matter tract microstructure and reduced task-difficulty-related BOLD modulation. We further demonstrated that poorer white matter microstructure integrity was associated with weakened BOLD modulation, particularly in regions showing positive modulation effects, as opposed to negative modulation effects. This structure-function association study provides further evidence that structural connectivity influences functional activation, and the two mechanisms in tandem are predictive of cognitive performance, both during the task, and for cognition measured outside the scanner environment.

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 Contributions of white matter connectivity and BOLD modulation to cognitive aging: A lifespan structure-function association study

2019 ◽  
Author(s):  
Christina E. Webb ◽  
Karen M. Rodrigue ◽  
David A. Hoagey ◽  
Chris M. Foster ◽  
Kristen M. Kennedy
Keyword(s):  
Executive Function ◽  
White Matter ◽  
Structure Function ◽  
Association Study ◽  
Structural Equation ◽  
Equation Modeling ◽  
Age Related ◽  
White Matter Microstructure ◽  
Task Accuracy ◽  
Back Task

AbstractThe ability to flexibly modulate brain activation to increasing cognitive challenge decreases with aging. This age-related decrease in dynamic range of function of regional gray matter may be, in part, due to age-related degradation of regional white matter tracts. Here, a lifespan sample of 171 healthy adults (aged 20-94) underwent MRI scanning including diffusion-weighted imaging (for tractography) and functional imaging (a digit n-back task). We utilized structural equation modeling to test the hypothesis that age-related decrements in white matter microstructure are associated with altered BOLD modulation, and both in turn, are associated with scanner-task accuracy and executive function performance. Specified structural equation model evidenced good fit, demonstrating that increased age negatively affects n-back task accuracy and executive function performance in part due to both degraded white matter tract microstructure and reduced task-difficulty related BOLD modulation. We further demonstrated that poorer white matter microstructure integrity was associated with weakened BOLD modulation, particularly in regions showing positive modulation effects, as opposed to negative modulation effects. This structure-function association study provides further evidence that structural connectivity influences functional activation, and the two mechanisms in tandem are predictive of cognitive performance, both during the task, and for cognition measured outside the scanner environment.

scholarly journals Hippocampal subfields and limbic white matter jointly predict learning rate in older adults

2019 ◽  
Author(s):  
Andrew R. Bender ◽  
Andreas M. Brandmaier ◽  
Sandra Düzel ◽  
Attila Keresztes ◽  
Ofer Pasternak ◽  
...  
Keyword(s):  
Older Adults ◽  
White Matter ◽  
Structural Equation ◽  
Structural Characteristics ◽  
Verbal Learning ◽  
Learning Rate ◽  
Equation Modeling ◽  
Cerebral White Matter ◽  
Fiber Tractography ◽  
Age Related

AbstractAge-related memory impairments have been linked to differences in structural brain parameters, including cerebral white matter (WM) microstructure and hippocampal (HC) volume, but their combined influences are rarely investigated. In a population-based sample of 337 older participants 61–82 years of age (Mage=69.66, SDage=3.92 years) we modeled the independent and joint effects of limbic WM microstructure and HC subfield volumes on verbal learning. Participants completed a verbal learning task over five learning trials and underwent magnetic resonance imaging (MRI), including structural and diffusion scans. We segmented three HC subregions on high-resolution MRI data and sampled mean fractional anisotropy (FA) from bilateral limbic WM tracts identified via deterministic fiber tractography. Using structural equation modeling, we evaluated the associations between learning rate and latent factors representing FA sampled from limbic WM tracts, and HC subfield volumes, as well as their latent interaction. Results showed limbic WM and the interaction of HC and WM – but not HC volume alone – predicted verbal learning rates. Model decomposition revealed HC volume is only positively associated with learning rate in individuals with higher levels of WM anisotropy. We conclude that structural characteristics of limbic WM regions and HC volume jointly contribute to verbal learning in older adults.

scholarly journals Hippocampal Subfields and Limbic White Matter Jointly Predict Learning Rate in Older Adults

2019 ◽  
Vol 30 (4) ◽  
pp. 2465-2477 ◽  
Author(s):  
Andrew R Bender ◽  
Andreas M Brandmaier ◽  
Sandra Düzel ◽  
Attila Keresztes ◽  
Ofer Pasternak ◽  
...  
Keyword(s):  
Older Adults ◽  
White Matter ◽  
Structural Equation ◽  
Structural Characteristics ◽  
Verbal Learning ◽  
Learning Rate ◽  
Equation Modeling ◽  
Cerebral White Matter ◽  
Fiber Tractography ◽  
Age Related

Abstract Age-related memory impairments have been linked to differences in structural brain parameters, including cerebral white matter (WM) microstructure and hippocampal (HC) volume, but their combined influences are rarely investigated. In a population-based sample of 337 older participants aged 61–82 years (Mage = 69.66, SDage = 3.92 years), we modeled the independent and joint effects of limbic WM microstructure and HC subfield volumes on verbal learning. Participants completed a verbal learning task of recall over five repeated trials and underwent magnetic resonance imaging (MRI), including structural and diffusion scans. We segmented three HC subregions on high-resolution MRI data and sampled mean fractional anisotropy (FA) from bilateral limbic WM tracts identified via deterministic fiber tractography. Using structural equation modeling, we evaluated the associations between learning rate and latent factors representing FA sampled from limbic WM tracts, and HC subfield volumes, and their latent interaction. Results showed limbic WM and the interaction of HC and WM—but not HC volume alone—predicted verbal learning rates. Model decomposition revealed HC volume is only positively associated with learning rate in individuals with higher WM anisotropy. We conclude that the structural characteristics of limbic WM regions and HC volume jointly contribute to verbal learning in older adults.

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.

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