Cognitive Reserve in the Healthy Elderly: Cognitive and Psychological Factors

SOR-SOCSCI Cognitive reserve in the healthy elderly: cognitive and psychological factors Josef Zihl1,2*, Florian Pargent1, Antonia Schmid1, Osborne F.X. Almeida2, Nuno Sousa3,4, Katrin Walther1, and Thomas Fink1 1 Department Psychology, Neuropsychology, Ludwig-Maximilians-Universität München, Munich, Germany Max Planck Institute of Psychiatry, Munich, Germany 3 Life and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, Braga, Portugal 4 ICVS/3B’s, PT Government Associate Laboratory, Braga/Guimarães, Portugal *Corresponding author’s e-mail address: 2 Published online: 7 October 2015 (version 2) Cite as: Zihl et al. ScienceOpen Research 2015 (DOI: 10.14293/S2199-1006.1.SOR-SOCSCI.A5KKMA.v2) Reviewing status: Please note that this article is under continuous review. For the current reviewing status and the latest referee’s comments please click here or scan the QR code at the end of this article. Primary discipline: Psychology Keywords: Mental aging, Cognitive reserve, Cognitive architecture ABSTRACT [1,2]. In their model of CR, Satz et al. [3] proposed four factors (general intelligence (“g”), complex mental activity, processing resources, and executive function) as “potential reserve proxies” for CR in normal aging. Each of these factors encompasses one of several specific indicators that contribute to, or interact with CR. Examples of such factors include literacy and education, occupation, regular complex mental activities, and cohesiveness of social networks [4–8]. It is also plausible that other variables, such as mood [9] and quality of sleep [10] may also determine cognitive performance in older age. In addition, it should be noted that many of these putative CR-determining factors may be intercorrelated [11], and that they are influenced by individual life experiences and, thus, by developmental trajectories in early adulthood and middle age [12]. Since CR cannot be measured directly, the assessment of proxies is valuable; however, these proxies are likely to be static rather than dynamic representations of CR. From a conceptual and methodological perspective, it seems desirable to define and assess CR in a more direct fashion, e.g., by “forcing” subjects to activate their individual cognitive resources in a mentally challenging task. Such an approach would also fit into a model of task-related brain activity depending on the level of task demands, which helps to explain interindividual differences in the context of brain reserve and thus of the neural basis of CR [13]. Based on this framework, one would predict that subjects with higher functional brain reserve would also show higher performance in such a task because they can activate more cognitive resources in this condition. The gain in performance may thus represent a more valid proxy of CR because it is based on the dynamic use of implicitly existing CR, which cannot be determined validly in a one-trial assessment. A particularly Cognitive reserve (CR) helps explain the mismatch between expected cognitive decline and observed maintenance of cognitive functioning in older age. Factors such as education, literacy, lifestyle, and social networking are usually considered to be proxies of CR and its variability between individuals. A more direct approach to examine CR is through the assessment of capacity to gain from practice in a standardized challenging cognitive task that demands activation of cognitive resources. In this study, we applied a testing-the-limits paradigm to a group of 136 healthy elderly subjects (60–75 years) and additionally examined the possible contribution of complex mental activities and quality of sleep to cognitive performance gain. We found a significant but variable gain and identified verbal memory, cognitive flexibility, and problem-solving as important factors. This outcome is in line with our earlier study on CR in healthy mental aging. Interestingly and contrary to expectations, our analysis revealed that complex mental activities and sleep quality do not significantly influence CR. Best subset regression showed that better verbal memory and higher cognitive flexibility were related to high CR, which could also be seen when contrasting “high” and “low” cognitive performers; again, complex mental activities and sleep quality did not contribute to this measure of CR. In conclusion, the results of this study support and extend previous findings on CR in older age; further, they underline the need for improvements in existing protocols for assessing CR in a dynamic manner. INTRODUCTION The concept of cognitive reserve (CR) attempts to explain inter-individual variability in susceptibility to changes in brain function in pathological, but also normal aging of the brain 1 SOR-SOCSCI Zihl et al.: Cognitive reserve in the healthy elderly: cognitive and psychological factors the study, subjects were given a detailed telephone interview to screen for exclusion criteria, in particular neurological and mental disorders as well as non-correctable visual or auditory impairments and motor limitations of the dominant (right or left) hand. According to the Edinburgh handedness inventory [19], 97% of subjects were right-handed, three were lefthanded, and three were ambidextrous. Two subjects were excluded due to incomplete data sets; thus, 136 participants (68 female, 68 male; age: M = 68.71 years, SD = 3.60 years) were studied in detail. All subjects had at least 14 years of education; thus, the influence of the level of education on cognitive architecture and CR was minimal. Each participant was tested with the Mini-Mental State Examination (MMSE of the CERAD-Plus; [20]) to exclude subjects with global cognitive impairment (MMSE ≤ 26 points). No subject scored lower than this cut-off due to prior verbal screening. In addition, detailed information on education and occupation, medical history, medication, smoking, and alcohol use was collected. sensitive method to assess CR in this framework is the socalled testing-the-limits paradigm [14]. The use of the Digit Symbol Substitution Test (DSST), a multitasking cognitive measure [15], in a testing-the-limits paradigm with systematic repetition offers a way to assess CR in a dynamic way. In the following, we use the abbreviation CR to denote gains in the testing-the-limits paradigm, which serve as “intimate” proxies of CR. In our recent study that contrasted 140 younger with 140 older healthy subjects, all of whom had a similar level of education [16], we used such a paradigm to assess CR. The main outcome of that study was that systematic practice with DSST leads to significant gains in both age groups. Interestingly, although CR was significantly higher in the younger subjects, about 50% of older subjects showed similar CR values, suggesting that CR may, at least partly, represent an individual, age-independent factor. As predicted from the model of Satz et al. [3], CR was significantly asso (...truncated)