Why the study?
Most neuroimaging and electroencephalography studies of cognitive reserve focus solely on formal education, leaving the role of other contributors such as working and leisure activities understudied.
Does the P300 EEG component correlate with cognitive reserve index subcomponents in older adults?
Does the P300 EEG component correlate with cognitive reserve index subcomponents in older adults?
P300 EEG characteristics show complex relationships with different subcomponents of cognitive reserve, suggesting EEG can serve as an objective proxy for cognitive reserve.
Answers are grounded in this paper and cite their sources.
May support P300 as cognitive reserve proxy in older adults; hypothesis-generating, requires prospective validation.
Cognitive reserve (CR) postulates that individual differences in task performance can be attributed to differences in the brain's ability to recruit additional networks or adopt alternative cognitive strategies. Variables that are descriptive of lifetime experience such as socioeconomic status, educational attainment, and leisure activity are common proxies of CR. CR is mostly studied using neuroimaging techniques such as functional MRI (fMRI) in which case individuals with a higher CR were observed to activate a smaller brain network compared to individuals with a lower CR, when performing a task equally effectively (higher efficiency), and electroencephalography (EEG) where a particular EEG component (P300) that reflects the attention and working memory load, has been targeted. Despite the contribution of multiple factors such as age, education (formal and informal), working, leisure, and household activities in CR formation, most neuroimaging studies, and those using EEG in particular, focus on formal education level only. The aim of the current EEG study is to investigate how the P300 component, evoked in response to an oddball paradigm, is associated with other components of CR besides education, such as working and leisure activity in older adults. We have used hereto a recently introduced CR index questionnaire (CRIq) that quantifies both professional and leisure activities in terms of their cognitive demand and number of years practiced, as well as a data-driven approach for EEG analysis. We observed complex relationships between CRIq subcomponents and P300 characteristics. These results are especially important given that, unlike previous studies, our measurements (P300 and CRIq) do not require active use of the same executive function and, thus, render our results free of a collinearity bias.
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Khachatryan et al. (2021) studied this question.
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