Neural correlates of resilience to the effects of hippocampal atrophy on memory

Belleville, Sylvie; Mellah, Samira; Cloutier, Simon; Dang‐Vu, Thien Thanh; Duchesne, Simon; Maltezos, Samantha; Phillips, Natalie A.; Hudon, Carol

doi:10.1016/j.nicl.2020.102526

Cited by 12 publications

(7 citation statements)

References 48 publications

(41 reference statements)

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“…All variables were standardized and Winsorized (based on z-scores > |3|). These three measures were selected based on their availability across both datasets and because they have been used in previous studies, with complete CR models, to represent brain structure: GM volume [ 100 , 101 ], hippocampal volume [ 102 , 103 ], and mean cortical thickness [ 9 , 43 , 104 ].…”

Section: Methodsmentioning

confidence: 99%

Verbal intelligence is a more robust cross-sectional measure of cognitive reserve than level of education in healthy older adults

et al. 2021

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Background Cognitive reserve is most commonly measured using socio-behavioural proxy variables. These variables are easy to collect, have a straightforward interpretation, and are widely associated with reduced risk of dementia and cognitive decline in epidemiological studies. However, the specific proxies vary across studies and have rarely been assessed in complete models of cognitive reserve (i.e. alongside both a measure of cognitive outcome and a measure of brain structure). Complete models can test independent associations between proxies and cognitive function in addition to the moderation effect of proxies on the brain-cognition relationship. Consequently, there is insufficient empirical evidence guiding the choice of proxy measures of cognitive reserve and poor comparability across studies. Method In a cross-sectional study, we assessed the validity of 5 common proxies (education, occupational complexity, verbal intelligence, leisure activities, and exercise) and all possible combinations of these proxies in 2 separate community-dwelling older adult cohorts: The Irish Longitudinal Study on Ageing (TILDA; N = 313, mean age = 68.9 years, range = 54–88) and the Cognitive Reserve/Reference Ability Neural Network Study (CR/RANN; N = 234, mean age = 64.49 years, range = 50–80). Fifteen models were created with 3 brain structure variables (grey matter volume, hippocampal volume, and mean cortical thickness) and 5 cognitive variables (verbal fluency, processing speed, executive function, episodic memory, and global cognition). Results No moderation effects were observed. There were robust positive associations with cognitive function, independent of brain structure, for 2 individual proxies (verbal intelligence and education) and 16 composites (i.e. combinations of proxies). Verbal intelligence was statistically significant in all models. Education was significant only in models with executive function as the cognitive outcome variable. Three robust composites were observed in more than two-thirds of brain-cognition models: the composites of (1) occupational complexity and verbal intelligence, (2) education and verbal intelligence, and (3) education, occupational complexity, and verbal intelligence. However, no composite had larger average effects nor was more robust than verbal intelligence alone. Conclusion These results support the use of verbal intelligence as a proxy measure of CR in cross-sectional studies of cognitively healthy older adults.

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Section: Methodsmentioning

confidence: 99%

Verbal intelligence is a more robust cross-sectional measure of cognitive reserve than level of education in healthy older adults

et al. 2021

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“…All variables were standardized and Winsorized (based on z-scores >|3|). These three measures were selected based on their availability across both datasets and because they have been used in previous studies, with complete CR models, to represent brain structure: GM volume (101,102), hippocampal volume (103,104), and mean cortical thickness (9,43,105).…”

Section: Measures: Cognitive Functionmentioning

confidence: 99%

Verbal intelligence is a more robust cross-sectional measure of cognitive reserve than level of education in healthy older adults

Boyle

Knight

Looze

et al. 2021

Preprint

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BackgroundCognitive reserve is most commonly measured using socio-behavioural proxy variables. These variables are easy to collect, have a straightforward interpretation, and are widely associated with reduced risk of dementia and cognitive decline in epidemiological studies. However, the specific proxies vary across studies and have rarely been assessed in complete models of cognitive reserve (i.e., alongside both a measure of cognitive outcome and a measure of brain structure). Complete models can test independent associations between proxies and cognitive function in addition to the moderation effect of proxies on the brain-cognition relationship. Consequently, there is insufficient empirical evidence guiding the choice of proxy measures of cognitive reserve and poor comparability across studies.MethodIn a cross-sectional study, we assessed the validity of 5 common proxies (education, occupational complexity, verbal intelligence, leisure activities, and exercise) and all possible combinations of these proxies in 2 separate community-dwelling older adult cohorts: The Irish Longitudinal Study on Ageing (TILDA; N = 313, mean age = 68.9 years, range = 54–88) and the Cognitive Reserve/Reference Ability Neural Network Study (CR/RANN; N = 234, mean age = 64.49 years, range = 50–80). 15 models were created with 3 brain structure variables (grey matter volume, hippocampal volume, and mean cortical thickness) and 5 cognitive variables (verbal fluency, processing speed, executive function, episodic memory, and global cognition).ResultsNo moderation effects were observed. There were robust positive associations with cognitive function, independent of brain structure, for 2 individual proxies (verbal intelligence and education), and 16 composites (i.e., combinations of proxies). Verbal intelligence was statistically significant in all models. Education was significant only in models with executive function as the cognitive outcome variable. Three robust composites were observed in more than two thirds of brain-cognition models: the composites of 1) occupational complexity and verbal intelligence, 2) education and verbal intelligence, and 3) education, occupational complexity and verbal intelligence. However, no composite had larger average effects nor was more robust than verbal intelligence alone.ConclusionThese results support the use of verbal intelligence as a proxy measure of CR in cross-sectional studies of cognitively healthy older adults.

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“…This was necessary to avoid a drastic reduction in training set sample size but it reduced the number of edges in each connectivity matrix by 58%, from 35,778 to 20,910. The loss of this information in the training set, from a region that has been previously associated with CR (Belleville et al, 2021; Marques et al, 2016; Stern et al, 2018), may have hindered the ability to develop a generalizable measure of CR.…”

Section: Discussionmentioning

confidence: 99%

“…The theoretical criteria for neuroimaging measures of CR have been satisfied in previous work. Belleville et al (2021) identified a pattern of increased activation in the right inferior temporal gyrus that was positively associated with a composite CR proxy and that moderated the relationship between hippocampal volume and associative memory performance, i.e. compensating for reduced hippocampal volume.…”

Section: Introductionmentioning

confidence: 93%

Connectome-based predictive modeling of cognitive reserve using task-based functional connectivity

Boyle

Connaughton

McGlinchey

et al. 2022

Preprint

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Cognitive reserve supports cognitive function in the presence of pathology or atrophy. Functional neuroimaging may enable direct and accurate measurement of cognitive reserve which could have considerable clinical potential. The present study aimed to develop and validate a measure of cognitive reserve using task-based fMRI data that could then be applied to independent resting-state data. Connectome-based predictive modeling with leave-one-out cross-validation was applied to predict a residual measure of cognitive reserve using task-based functional connectivity from the Cognitive Reserve/Reference Ability Neural Network studies (n = 220, mean age = 51.91 years, SD = 17.04 years). Three network-strength predicted cognitive reserve measures were generated that accurately predicted the residual measures of unseen participants. The theoretical validity of these measures was established via a positive correlation with a socio-behavioural proxy of cognitive reserve (verbal intelligence) and a positive correlation with global cognition, independent of brain structure. This fitted model was then applied to external test data: resting-state functional connectivity data from The Irish Longitudinal Study on Ageing (TILDA, n = 294, mean age = 68.3 years, SD = 7.18 years). The network-strength predicted measures were not positively associated with a residual measure of cognitive reserve nor with measures of verbal intelligence and global cognition. The present study demonstrated that task-based functional connectivity data can be used to generate theoretically valid measures of cognitive reserve. Further work is needed to establish if, and how, measures of cognitive reserve derived from task-based functional connectivity can be applied to independent resting-state data.

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Neural correlates of resilience to the effects of hippocampal atrophy on memory

Cited by 12 publications

References 48 publications

Verbal intelligence is a more robust cross-sectional measure of cognitive reserve than level of education in healthy older adults

Verbal intelligence is a more robust cross-sectional measure of cognitive reserve than level of education in healthy older adults

Verbal intelligence is a more robust cross-sectional measure of cognitive reserve than level of education in healthy older adults

Connectome-based predictive modeling of cognitive reserve using task-based functional connectivity

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