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 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 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.

Sleep Mediates Age-Related Executive Function for Older Adults with Limited Cognitive Reserve

2020 ◽  
pp. 1-11
Author(s):  
Denise Parker ◽  
Romola S. Bucks ◽  
Stephanie R. Rainey-Smith ◽  
Erica Hodgson ◽  
Lara Fine ◽  
...  
Keyword(s):  
Older Adults ◽  
Executive Function ◽  
Structural Equation ◽  
Cognitive Reserve ◽  
Experimental Studies ◽  
Community Dwelling ◽  
Equation Modeling ◽  
Sleep Quantity ◽  
Age Related ◽  
The Impact

Abstract Objective: Sleep quantity and quality are associated with executive function (EF) in experimental studies, and in individuals with sleep disorders. With advancing age, sleep quantity and quality decline, as does the ability to perform EF tasks, suggesting that sleep disruption may contribute to age-related EF declines. This cross-sectional cohort study tested the hypothesis that poorer sleep quality (i.e., the frequency and duration of awakenings) and/or quantity may partly account for age-related EF deficits. Method: Community-dwelling older adults (N = 184) completed actigraphic sleep monitoring then a range of EF tasks. Two EF factors were extracted using exploratory structural equation modeling. Sleep variables did not mediate the relationship between age and EF factors. Post hoc moderated mediation analyses were conducted to test whether cognitive reserve compensates for sleep-related EF deficits, using years of education as a proxy measure of cognitive reserve. Results: We found a significant interaction between cognitive reserve and the number and frequency of awakenings, explaining a small (approximately 3%), but significant amount of variance in EF. Specifically, in individuals with fewer than 11 years of education, greater sleep disturbance was associated with poorer EF, but sleep did not impact EF in those with more education. There was no association between age and sleep quantity. Conclusions: This study highlights the role of cognitive reserve in the sleep–EF relationship, suggesting individuals with greater cognitive reserve may be able to counter the impact of disturbed sleep on EF. Therefore, improving sleep may confer some protection against EF deficits in vulnerable older adults.

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 Cooperative contributions of structural and functional connectivity to successful memory in aging

2019 ◽  
Vol 3 (1) ◽  
pp. 173-194 ◽  
Author(s):  
Simon W. Davis ◽  
Amanda Szymanski ◽  
Homa Boms ◽  
Thomas Fink ◽  
Roberto Cabeza
Keyword(s):  
Older Adults ◽  
Functional Connectivity ◽  
Structural Equation ◽  
Healthy Aging ◽  
Memory Performance ◽  
Structural Connectivity ◽  
Equation Modeling ◽  
Cognitive Changes ◽  
Age Related ◽  
The Relationship

Understanding the precise relation between functional connectivity and structural (white matter) connectivity and how these relationships account for cognitive changes in older adults are major challenges for neuroscience. We investigate these issues using an approach in which structural equation modeling (SEM) is employed to integrate functional and structural connectivity data from younger and older adults ( n = 62), analyzed with a common framework based on regions connected by canonical tract groups (CTGs). CTGs (e.g., uncinate fasciculus) serve as a common currency between functional and structural connectivity matrices, and ensure equivalent sparsity in connectome information. We used this approach to investigate the neural mechanisms supporting memory for items and memory for associations, and how they are affected by healthy aging. We found that different structural and functional CTGs made independent contributions to source and item memory performance, suggesting that both forms of connectivity underlie age-related differences in specific forms of memory. Furthermore, the relationship between functional and structural connectivity was best explained by a general relationship between latent constructs—a relationship absent in any specific CTG group. These results provide insights into the relationship between structural and functional connectivity patterns, and elucidate their relative contribution to age-related differences in source memory performance.

Effect of the Interaction Between Hypertension and Cerebral White Matter Changes on the Progression of Alzheimer Disease

2018 ◽  
Vol 15 (14) ◽  
pp. 1354-1360 ◽  
Author(s):  
Ping-Song Chou ◽  
Yi-Hui Kao ◽  
Meng-Ni Wu ◽  
Mei-Chuan Chou ◽  
Chun-Hung Chen ◽  
...  
Keyword(s):  
White Matter ◽  
Alzheimer Disease ◽  
Rating Scale ◽  
Vital Role ◽  
Independent Effect ◽  
Cerebral White Matter ◽  
Clinical Dementia Rating ◽  
White Matter Changes ◽  
Age Related ◽  
The Mean

Background: Cerebrovascular pathologies and hypertension could play a vital role in Alzheimer disease (AD) progression. However, whether cerebrovascular pathologies and hypertension accelerate the AD progression through an independent or interaction effect is unknown. Objective: To investigate the effect of the interactions of cerebrovascular pathologies and hypertension on AD progression. Method: A retrospective longitudinal study was conducted to compare AD courses in patients with different severities of cerebral White Matter Changes (WMCs) in relation to hypertension. Annual comprehensive psychometrics were performed. WMCs were rated using a rating scale for Age-related WMCs (ARWMC). Results: In total, 278 patients with sporadic AD were enrolled in this study. The mean age of the patients was 76.6 ± 7.4 years, and 166 patients had hypertension. Among AD patients with hypertension, those with deterioration in clinical dementia rating-sum of box (CDR-SB) and CDR had significantly severe baseline ARWMC scales in total (CDR-SB: 5.8 vs. 3.6, adjusted P = 0.04; CDR: 6.4 vs. 4.4, adjusted P = 0.04) and frontal area (CDR-SB: 2.4 vs. 1.2, adjusted P = 0.01; CDR: 2.4 vs. 1.7, adjusted P < 0.01) compared with those with no deterioration in psychometrics after adjustment for confounders. By contrast, among AD patients without hypertension, no significant differences in ARWMC scales were observed between patients with and without deterioration. Conclusion: The effect of cerebrovascular pathologies on AD progression between those with and without hypertension might differ. An interaction but not independent effect of hypertension and WMCs on the progression of AD is possible.

Sign in / Sign up

Export Citation Format

Share Document