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Sensory, working, long-term, and short-term memory are basic human cognitive abilities. Yet, their nature is not completely understood beyond the well-recognized fact that human memory consists of various systems depending on several distinct brain regions. Still, the fractionation of these memory systems is grounded in scanty, insufficient research. One of the compelling subject areas that have been gaining traction in the field of psychology and neuroscience is the impact of age on the human memory systems. This report syntheses evidence from three recent scientific papers to demonstrate that lifespan memory decline cannot be ascribed to a unitary cause but rather stems from diverse determinants.
Memory lapses and forgetfulness are some of the most common complaints among senior citizens. Henson et al. (2016) argue against the pre-existing deterministic notion that such decline is linear, pre-programmed, and inevitable regardless of a person’s life choices. The purpose of the research by Henson et al. (2016) was to deepen the understanding of differential aging of the brain on differential patterns of memory loss. According to the scholars, provided the findings are meaningful, they could serve as a valuable contribution to future strategies for age-related memory loss prevention.
For their study, Henson et al. (2016) recruited 430 participants between the ages of 18 and 88 years old. They were offered memory tests while their brains were undergoing MRI imaging for GMV (gray matter volumes) and WMI (white matter index) measurements. Interestingly enough, the scholars rejected standardized memory tests that do not make a distinction between three types of memory – associative, item, and priming. The findings demonstrated that age negatively affected the former two types, with the latter being the most resilient to aging effects. However, the three memory factors appeared to have differential sensitivity to age insofar as different contributions from gray- and white matter in the investigated brain regions.
Despite the obvious contribution of this paper, it is important to keep in mind the limitations of its design. Henson et al. (2016) admit that the data used for the present research is cross-sectional, in other words, collected at one point in time. Indeed, a longitudinal design might have served the research purposes better as it would be able to capture the changing dynamics and distinguish the true effects of age. Many socioeconomic factors such as nutrition, lifestyle, and culture shape brain health outcomes that persist into old age. To the study’s credit, however, Henson et al. (2016) became the pioneers in memory research that included individuals ages spanning between 18 and 88 years old. This choice is refreshing when contrasted with studies that only focus on comparing younger participants’ (20-30 y.o.) performance to their older counterparts (60-70 y.o.).
The logical question that the reader might have after becoming familiar with the study by Henson et al. (2016) is what life factors shape memory outcomes in old age, even if at least some decline is seemingly unavoidable. Voluntary lifestyle choices that affect memory in old age are exactly the topic of a paper by Klaming et al. (2017). For their study, the scholars narrow the scope to the impact of lifestyle on episodic memory, defined as an individual’s ability to encode and fetch information in the context of time and place. Episodic memory is crucial to running errands and performing daily tasks, which allows for enhanced autonomy and self-agency in the elderly. The significance of the research lies in its practical implications for memory improvement in old age.
Klaming et al. (2017) retrieved data from Longitudinal Aging Study Amsterdam (LASA), an ongoing prospective population-based study taking place in three geographic locations in the Netherlands. Cognitive function, as well as lifestyle choices information, was collected every three years between 1995 and 2009, making the present study longitudinal. The sample was almost exclusively limited to senior citizens who, at the moment of the first data collection, averaged 74.6 years old. Lifestyle was operationalized as a combination of factors such as smoking and alcohol consumption, sleeping habits, social engagement, and the level of physical activity. Like Henson et al. (2016), Klaming et al. (2017) did not study human memory as a whole but as a system of elements. In the context of this study, the evaluation memory was broken down into memory learning score, memory delayed recall score, and memory retention score.
As expected, Klaming et al. (2017) discovered a positive association between moderate to high levels of physical exercise and episodic memory function. The participants of the study drank 7.5 alcoholic beverages per week, and yet, alcohol consumption did not affect their memory measurements. In fact, alcohol abstinence was associated with worse results as compared to light drinking. Smoking, on the other hand, was a predictor of worse learning abilities. Normal sleep that is not too short or too long in duration and social engagement were determinants of functioning memory in old age. While these findings can be used for the development of intervention programs, it is important to remember that all data were self-reported, which means a possibility of bias.
The connection between lifestyle choices and memory in old age is justifiably optimistic. One may wonder what else could be in a person’s power to make sure they retain their cognitive abilities as they grow older. Apparently, self-image and positive thinking may as well be at play. Stephan et al. (2016) conducted a compelling study investigating how an individual’s perception of age may affect their memory. From the literature on the subject matter, it is known that older adults feel younger than they actually are. The question arises as to whether it is self-delusion or a powerful defense mechanism against age-related brain deterioration.
Stephan et al. (2016) recruited participants from the HRS, a nationally representative longitudinal study of Americans aged 50 and over. The main variables evaluated by Stephan et al. (2016) were subjective age, physical activity, memory, and depressive symptoms. The study also included covariates such as baseline age at the start of the study, sex, BMI (body-mass index), educational background, and medical history (diabetes, hypertension, and others). Even after controlling for covariates, Stephan et al. (2016) were still able to confirm that the perceived younger age was associated with better memory function and slower cognitive decline. Feeling younger was also related to fewer depressive symptoms. In contrast to the study by Klaming et al. (2017), physical activity had no mediating effect on memory function. The present study makes a contribution to the existing knowledge of memory and its determinants in older adults. However, the positive selection of the longitudinal participants is an inarguable caveat as admitted by the authors themselves.
Forgetfulness, confusion, and scatter-mindedness are socially and culturally associated with old age; it is a popular trope and a subject of many anecdotes ranging from entertaining to disheartening. However, the exact mechanisms of such changes have yet to be elucidated. This critical analysis discussed and synthesized evidence on lifespan memory in older adults, changes, and determinants. The existing body of literature confirms the inevitability of age-related cognitive decline. However, it is less linear as previously imagined since memory is far from uniform and regulated by several distinct brain regions. The other two studies challenge the deterministic view on aging and provide practical implications on what interventions can slow down memory decline. There is some debate about specific lifestyle choices and their impact. Yet, the very idea of being in control of one’s brain health can inspire more rigorous, evidence-based memory preservation strategies.
References
Henson, R. N., Campbell, K. L., Davis, S. W., Taylor, J. R., Emery, T., Erzinclioglu, S., & Kievit, R. A. (2016). Multiple determinants of lifespan memory differences. Scientific reports, 6(1), 1-14.
Klaming, R., Annese, J., Veltman, D. J., & Comijs, H. C. (2017). Episodic memory function is affected by lifestyle factors: A 14-year follow-up study in an elderly population. Aging, Neuropsychology, and Cognition, 24(5), 528-542.
Stephan, Y., Sutin, A. R., Caudroit, J., & Terracciano, A. (2016). Subjective age and changes in memory in older adults. Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 71(4), 675-683.
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