Memory aging and brain maintenance
Authors: Lars Nyberg, Martin Lövdén, Katrine Riklund, Ulman Lindenberger, Lars Bäckman
Journal: Trends in Cognitive Sciences (2012)

Episodic memory and working memory decline with advancing age. Nevertheless, large-scale population-based studies document well-preserved memory functioning in some older individuals. The influential 'reserve' notion holds that individual differences in brain characteristics or in the manner people process tasks allow some individuals to cope better than others with brain pathology and hence show preserved memory performance. Here, we discuss a complementary concept, that of brain maintenance (or relative lack of brain pathology), and argue that it constitutes the primary determinant of successful memory aging. We discuss evidence for brain maintenance at different levels: cellular, neurochemical, gray- and white-matter integrity, and systems-level activation patterns. Various genetic and lifestyle factors support brain maintenance in aging and interventions may be designed to promote maintenance of brain structure and function in late life. Episodic memory and working memory decline with advancing age. Nevertheless, large-scale population-based studies document well-preserved memory functioning in some older individuals. The influential 'reserve' notion holds that individual differences in brain characteristics or in the manner people process tasks allow some individuals to cope better than others with brain pathology and hence show preserved memory performance. Here, we discuss a complementary concept, that of brain maintenance (or relative lack of brain pathology), and argue that it constitutes the primary determinant of successful memory aging. We discuss evidence for brain maintenance at different levels: cellular, neurochemical, gray- and white-matter integrity, and systems-level activation patterns. Various genetic and lifestyle factors support brain maintenance in aging and interventions may be designed to promote maintenance of brain structure and function in late life. Many older adults feel that their memory does not serve them as well as when they were younger [1Reid L.M. MacLullich A.M.J. Subjective memory complaints and cognitive impairment in older people.Dement. Geriatr. Cogn. Disord. 2006; 22: 471-485Crossref PubMed Scopus (148) Google Scholar, 2Vestergren P. Nilsson L.-G. Perceived causes of everyday memory problems in a population-based sample aged 39-99.Appl. Cogn. Psychol. 2011; 25: 641-646Crossref Scopus (9) Google Scholar]. Yet, objective assessments of memory have yielded a more differentiated picture. For one thing, subjective memory complaints may correlate more strongly with mood states than with objective memory performance [3Mowla A. et al.Do memory complaints represent impaired memory performance in patients with major depressive disorder?.Depress. Anxiety. 2007; 25: 92-96Crossref Scopus (9) Google Scholar]. Moreover, not all forms of human memory are equally affected by advancing age. 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Oxford University Press, 2005Google Scholar] have begun to link declining episodic and working memory to neurochemical, structural and functional brain changes. There has been much progress in this interdisciplinary area, partly due to increased availability of brain-imaging technology, a trend toward refined experimental designs with larger sample sizes and greater attention to longitudinal evidence. We begin this review by considering studies on average cross-sectional age differences and longitudinal changes in episodic and working memory, and by discussing interindividual differences in level and change of cognitive functioning in old age. We then place particular focus on describing the structure and function of the brain, as measured by neuroimaging techniques (see Glossary), in individuals who maintain high episodic memory and working memory performance in old age. We introduce the concept of brain maintenance to characterize high-performing older adults, contrasting it to the concept of cognitive/brain reserve, and discuss conditions supporting brain maintenance in later adulthood. Although episodic and working-memory performance decline in adulthood and old age, evidence on the age of onset of decline is mixed. Most cross-sectional studies suggest linear deterioration in episodic memory performance across the adult life span, beginning as early as in the 20s [11Li S.C. et al.Transformations in the couplings among intellectual abilities and constituent cognitive processes across the life span.Psychol. Sci. 2004; 15: 155-163Crossref PubMed Google Scholar, 12Nilsson L.G. et al.The Betula prospective cohort study: Memory, health and aging.Aging Neuropsychol. Cogn. 1997; 4: 1-32Crossref Google Scholar, 13Park D.C. et al.Mediators of long-term memory performance across the life span.Psychol. Aging. 1996; 11: 621-637Crossref PubMed Scopus (262) Google Scholar]. Longitudinal studies that apply appropriate control for practice effects (i.e., test-retest effects) have yielded a very different pattern, indicating that episodic memory performance remains relatively stable until about 60–65 years of age, after which accelerating decline is typically observed [6Rönnlund M. et al.Stability, growth and decline in adult life span development of declarative memory: cross-sectional and longitudinal data from a population-based study.Psychol. Aging. 2005; 20: 3-18Crossref PubMed Scopus (132) Google Scholar, 7Schaie K.W. Developmental Influences on Adult Intelligence: The Seattle Longitudinal Study. Oxford University Press, 2005Crossref Google Scholar]. One source of this discrepancy is that cross-sectional estimates of age-related change are biased by cohort effects, including generational differences in educational attainment. When age differences in educational level are statistically controlled for in cross-sectional analyses, age differences in episodic memory appear at a much later age [6Rönnlund M. et al.Stability, growth and decline in adult life span development of declarative memory: cross-sectional and longitudinal data from a population-based study.Psychol. Aging. 2005; 20: 3-18Crossref PubMed Scopus (132) Google Scholar]. This pattern is illustrated in Figure 1. This figure also shows how appropriate control of practice effects, through the introduction of new samples at subsequent test waves [6Rönnlund M. et al.Stability, growth and decline in adult life span development of declarative memory: cross-sectional and longitudinal data from a population-based study.Psychol. Aging. 2005; 20: 3-18Crossref PubMed Scopus (132) Google Scholar, 7Schaie K.W. Developmental Influences on Adult Intelligence: The Seattle Longitudinal Study. Oxford University Press, 2005Crossref Google Scholar], influences longitudinal estimates of average age-related change in episodic memory performance. Less is known about the average onset of decline in working memory performance. The reason for this lacuna is the absence of lifespan longitudinal studies on working memory that apply appropriate control for practice effects. However, longitudinal evidence exists for some cognitive abilities, such as reasoning [7Schaie K.W. Developmental Influences on Adult Intelligence: The Seattle Longitudinal Study. Oxford University Press, 2005Crossref Google Scholar, 14Rönnlund M. et al.Adult age differences in Tower of Hanoi performance: Influence from demographic and cognitive variables.Aging Neuropsychol. Cogn. 2006; 8: 269-283Crossref Scopus (17) Google Scholar, 15Rönnlund M. Nilsson L.-G. The magnitude, generality and determinants of Flynn effects on declarative memory and visuospatial ability: time-sequential analyses of data from a Swedish cohort study.Intelligence. 2008; 36: 192-209Crossref Scopus (15) Google Scholar], that are highly related to working memory performance [16Kyllonen C. Christal R.E. Reasoning ability is (little more than) working memory capacity.Intelligence. 1990; 14: 389-433Crossref Google Scholar, 17Schmiedek F. et al.Complex span versus updating tasks of working memory: the gap is not that deep.J. Exp. Psychol. Learn. Mem. Cogn. J. Exp. Psychol. Learn. Mem. Cogn. 2009; 35: 1089-1096Crossref PubMed Scopus (48) Google Scholar]. Similar to episodic memory, this evidence suggests a relatively late onset of average age-related decline [7Schaie K.W. Developmental Influences on Adult Intelligence: The Seattle Longitudinal Study. Oxford University Press, 2005Crossref Google Scholar, 14Rönnlund M. et al.Adult age differences in Tower of Hanoi performance: Influence from demographic and cognitive variables.Aging Neuropsychol. Cogn. 2006; 8: 269-283Crossref Scopus (17) Google Scholar, 15Rönnlund M. Nilsson L.-G. The magnitude, generality and determinants of Flynn effects on declarative memory and visuospatial ability: time-sequential analyses of data from a Swedish cohort study.Intelligence. 2008; 36: 192-209Crossref Scopus (15) Google Scholar]. For example, longitudinal data on visuo-spatial reasoning indicate that decline starts after age 55 [14Rönnlund M. et al.Adult age differences in Tower of Hanoi performance: Influence from demographic and cognitive variables.Aging Neuropsychol. Cogn. 2006; 8: 269-283Crossref Scopus (17) Google Scholar]. Taken together, the available longitudinal evidence does not support a view of an early onset of decline in episodic and working memory. Rather, significant episodic-memory decline is not evident until after age 60 and the limited evidence lends no support for a much earlier onset of working-memory decline. Findings from several large-scale population-based studies demonstrate substantial inter-individual differences in how episodic and working memory change in old age [12Nilsson L.G. et al.The Betula prospective cohort study: Memory, health and aging.Aging Neuropsychol. Cogn. 1997; 4: 1-32Crossref Google Scholar, 18Wilson R.S. et al.Individual differences in rates of change in cognitive abilities of older persons.Psychol. Aging. 2002; 17: 179-193Crossref PubMed Scopus (325) Google Scholar, 19Christensen H. et al.An analysis of diversity in the cognitive performance of elderly community dwellers: individual differences in change scores as a function of age.Psychol. Aging. 1999; 14: 365-379Crossref PubMed Scopus (91) Google Scholar, 20Lindenberger U. Ghisletta P. Cognitive and sensory declines in old age: gauging the evidence for a common cause.Psychol. Aging. 2009; 24: 1-16Crossref PubMed Scopus (51) Google Scholar]. These interindividual differences in change of memory performance increase as a function of advancing adult age [21deFrias C.M. et al.Revisiting the dedifferentiation hypothesis with longitudinal multicohort data.Intelligence. 2007; 35: 381-392Crossref Scopus (48) Google Scholar]. A more rapid than average decline for a certain age group has attracted much interest, as it might be indicative of forthcoming diseases such as dementia [22Wilson R.S. et al.Neurodegenerative basis of cognitive decline.Neurology. 2010; 75: 1070-1078Crossref PubMed Scopus (48) Google Scholar]. Relatively less attention has been paid to individuals who display little or no memory decline. A main reason for this is methodological difficulties – identifying individuals with preserved memory functioning is a challenge and often involves measuring large samples. In one study [23Habib R. et al.Cognitive and non-cognitive factors contributing to the longitudinal identification of successful older adults in the Betula study.Aging Neuropsychol. Cogn. 2007; 14: 257-273Crossref PubMed Scopus (19) Google Scholar], cognitive and non-cognitive data from approximately 1500 adults in the Betula longitudinal study [12Nilsson L.G. et al.The Betula prospective cohort study: Memory, health and aging.Aging Neuropsychol. Cogn. 1997; 4: 1-32Crossref Google Scholar] were analyzed with a factor analytic technique in order to classify individuals in terms of 'usual' versus 'successful' aging [24Rowe J.W. Kahn R.L. Human aging: usual and successful.Science. 1987; 237: 143-149Crossref PubMed Google Scholar]. Results revealed substantial heterogeneity in levels of cognitive performance (Figure 2). Almost 10% of the participants older than 70 years were categorized as meeting the criterion of successful cognitive aging. Longitudinal studies provide additional evidence for heterogeneity in aging trajectories of cognitive performance, including identifying sub-groups of elderly individuals who maintain superior levels of cognitive performance over time [25Persson J. et al.Structure-function correlates of cognitive decline in aging.Cereb. Cortex. 2006; 16: 907-915Crossref PubMed Scopus (143) Google Scholar, 26Persson J. et al.Longitudinal structure – function correlates in elderly reveal MTL dysfunction with cognitive decline.Cereb. Cortex. 2011; https://doi.org/10.1093/cercor/bhr306Crossref PubMed Scopus (9) Google Scholar]. In sum, extant evidence points to substantial individual differences in both level and change of memory performance in old age and to the existence of high-performing older individuals who display little or no performance decline. The large heterogeneity in memory aging and the existence of older adults who show little evidence of decline have led researchers to propose general mechanisms that may protect against imminent age-related decline in cognitive performance [27Falconer D.S. The inheritance of liability to certain diseases, estimated from the incidence among relatives.Ann. Hum. Gen. 1965; 29: 51-76Crossref Google Scholar, 28Nolan K.A. Blas J.P. Preventing cognitive decline.Clin. Geriatr. Med. 1992; 8: 19-34PubMed Google Scholar]. One of these concepts is 'reserve', which, according to a general definition [29OED online (2012) Oxford University Press, <http://oed.com>Google Scholar], denotes the 'supply of a commodity not needed for immediate use but available if required'. The reserve concept has been used to capture properties of brain ('brain reserve'; [30Satz P. Brain reserve capacity on symptom onset after brain injury: A formulation and review of evidence for threshold theory.Neuropsychology. 1993; 7: 273-295Crossref Google Scholar, 31Katzman R. et al.Clinical, pathological and neurochemical changes in dementia - a subgroup with preserved mental status and numerous neocortical plaques.Ann. Neurol. 1988; 23: 138-144Crossref PubMed Google Scholar]) and cognition ('cognitive reserve'; [32Stern Y. What is cognitive reserve? Theory and research application of the reserve concept.JINS. 2002; 8: 448-460Crossref PubMed Scopus (0) Google Scholar]). In either case, the amount of reserve is assumed to determine the relation between senescent and age-graded pathological alterations of the brain and behavioral manifestations:•Brain reserve: 'Individual differences in the brain itself allow some people to cope better than others with brain pathology' ([33Stern Y. Cognitive reserve.Neuropsychologia. 2009; 47: 2015-2028Crossref PubMed Scopus (427) Google Scholar], p. 2016).•Cognitive reserve: 'Individual differences in how people process tasks allow some to cope better than others with brain pathology' ([33Stern Y. Cognitive reserve.Neuropsychologia. 2009; 47: 2015-2028Crossref PubMed Scopus (427) Google Scholar], p. 2016). The brain reserve concept invokes a passive threshold model [30Satz P. Brain reserve capacity on symptom onset after brain injury: A formulation and review of evidence for threshold theory.Neuropsychology. 1993; 7: 273-295Crossref Google Scholar]. That is, this model presupposes that the amount of intact brain (e.g., size, neuronal counts, synaptic density), rather than the amount of a given brain pathology (e.g., beta amyloid), is the best predictor of between-person differences in cognitive functioning. Only when brain resources fall below a given threshold will the pathology begin to dominate behavior. According to this view, successful memory performance in old age is primarily determined by having reached high levels of performance prior to the onset of senescent decline than about minimizing decline itself. That is, an individual with a larger brain reserve will have better memory performance and therefore reach the threshold for functional impairment (e.g., a dementia diagnosis) at a later age. In contrast, the cognitive reserve concept is more 'active' [32Stern Y. What is cognitive reserve? Theory and research application of the reserve concept.JINS. 2002; 8: 448-460Crossref PubMed Scopus (0) Google Scholar, 33Stern Y. Cognitive reserve.Neuropsychologia. 2009; 47: 2015-2028Crossref PubMed Scopus (427) Google Scholar] in the sense that some individuals will cope better with age-related pathology because they react to and compensate for their evolving brain changes. The reserve concepts are undoubtedly of great heuristic value; they have informed the search for conditions that promote successful cognitive aging and continue to be refined and specified in neural terms. 'Brain maintenance' is introduced here as a complementary concept (see also [34Lindenberger, U. et al. Heterogeneity in frontal-lobe aging. In Principles of frontal lobe functions (2nd ed.) (Stuss, D.T. and Knight, R.T., eds), Oxford University Press (in press)Google Scholar]). Maintenance denotes 'the process of preserving a condition' [29OED online (2012) Oxford University Press, <http://oed.com>Google Scholar]. That is, whereas the reserve concept seeks to explain why some individuals have intact functioning in the presence of brain pathology, the concept of maintenance focuses on the conditions that promote the preservation of neurochemical, structural and functional brain integrity in old age. Thus, the focus is on the relative lack or postponement of senescent brain changes including pathology, rather than on ways of coping with its presence. We define brain maintenance as follows:•Brain maintenance: 'Individual differences in the manifestation of age-related brain changes and pathology allow some people to show little or no age-related cognitive decline'. Maintenance underscores the evident, but currently undervalued, notion that the primary characteristic of the brains behind successful memory aging is preserved chemistry, structure and function. According to the maintenance hypothesis, minimization of senescent brain changes and absence of pathology are the best predictors of successful memory development in old age. Two patterns of evidence would support the utility of this hypothesis for explaining individual differences in memory aging. First, aging individuals are expected to differ widely in the amount of neurochemical, structural and functional brain changes that they display. Second, the concept assumes a positive association between age-graded losses in brain and cognition: individuals displaying fewer losses in task-related brain properties will display lesser decline in memory performance. As with cognitive functioning, there are marked inter-individual differences in the extent to which the brains of older adults deviate from those of younger adults. Findings from MRI studies show that some older adults have larger hippocampal volumes ([35Lupien S.J. et al.Hippocampal volume is as variable in young as in older adults: implications for the notion of hippocampal atrophy in humans.Neuroimage. 2007; 34: 479-485Crossref PubMed Scopus (67) Google Scholar]; Figure 3a) and show less annual hippocampal volume change than younger adults ([36Fjell A.M. et al.One-year brain atrophy evident in healthy aging.J. Neurosci. 2009; 29: 15223-15231Crossref PubMed Scopus (101) Google Scholar]; Figure 3b). Similar cross-sectional and longitudinal patterns have been reported for other cortical and subcortical structures, including the caudate nucleus ([37Nyberg L. et al.Longitudinal evidence for diminished frontal-cortex function in aging.Proc. Natl. Acad. Sci. U.S.A. 2010; 107: 22682-22686Crossref PubMed Scopus (43) Google Scholar, 38Raz N. et al.Regional brain changes in aging healthy adults: general trends, individual differences and modifiers.Cereb. 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On average, then, aging is associated with changes in brain integrity, often non-linearly, such that volume shrinkage and white-matter pathologies accelerate as a function of age [35Lupien S.J. et al.Hippocampal volume is as variable in young as in older adults: implications for the notion of hippocampal atrophy in humans.Neuroimage. 2007; 34: 479-485Crossref PubMed Scopus (67) Google Scholar, 38Raz N. et al.Regional brain changes in aging healthy adults: general trends, individual differences and modifiers.Cereb. Cortex. 2005; 15: 1676-1689Crossref PubMed Scopus (651) Google Scholar, 39Raz N. et al.Trajectories of brain aging in middle-aged and older adults: regional and individual differences.Neuroimage. 2010; 51: 501-511Crossref PubMed Scopus (81) Google Scholar, 40Raz N. et al.White matter deterioration in 15 months: latent growth curve models in healthy adults.Neurobiol. Aging. 2012; 33: 429Abstract Full Text Full Text PDF PubMed Scopus (6) Google Scholar]. At the same time, aging individuals differ reliably in rate of structural brain changes and brain integrity is relatively well preserved in some older adults. Executive functions comprise several cognitive abilities including working memory [16Kyllonen C. Christal R.E. Reasoning ability is (little more than) working memory capacity.Intelligence. 1990; 14: 389-433Crossref Google Scholar, 17Schmiedek F. et al.Complex span versus updating tasks of working memory: the gap is not that deep.J. Exp. Psychol. Learn. Mem. Cogn. J. Exp. Psychol. Learn. Mem. Cogn. 2009; 35: 1089-1096Crossref PubMed Scopus (48) Google Scholar, 41Miyake A. et al.The unity and diversity of executive functions and their contributions to complex 'Frontal Lobe' tasks: a latent variable analysis.Cogn. Psychol. 2000; 41: 49-100Crossref PubMed Scopus (2211) Google Scholar, 42Smith E.E. Jonides J. Storage and executive processes in the frontal lobes.Science. 1999; 283: 1657-1661Crossref PubMed Scopus (1447) Google Scholar]. Up to the present, attempts to link aging-related structural alterations of the brain to executive functioning have yielded mixed results [43Fjell A.M. et al.Selective increase of cortical thickness in high-performing elderly-structural indices of optimal cognitive aging.Neuroimage. 2006; 29: 984-994Crossref PubMed Scopus (53) Google Scholar, 44Kochunov P. et al.Can structural MRI indices of cerebral integrity track cognitive trends in executive control function during normal maturation and adulthood?.Hum. Brain Mapp. 2009; 30: 2581-2594Crossref PubMed Scopus (20) Google Scholar, 45Raz N. et al.Neuroanatomical correlates of fluid intelligence in healthy adults and persons with vascular risk factors.Cereb. 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As shown in Figure 4a , a thicker cortical mantle in the fronto-parietal network, presumed to be engaged during WCST performance, was related to better WCST performance. Cortical thickness was a reliable predictor of WCST performance beyond chronological age (see Figure 4b). Importantly, the authors also observed reliable age-group × cortical-thickness interactions in several task-relevant areas, reflecting stronger positive associations between cortical thickness and WCST performance in older than in younger adults. Although the cross-sectional design of this study does not permit direct conclusions about individual differences in rate of decline, the finding that the associations between cortical thickness and executive performance increased reliably from early to late adulthood renders it likely that individual differences in rates of performance-related cortical thinning do in fact exist. Individual differences in the thinning of the cortical mantle may be due to a combination of several processes, such as rarefaction of dendritic arbors, spines and synapses, cell shrinkage, and cortical myelin loss [48Burke S.N. Barnes C.A. Neural plasticity in the ageing brain.Nat. Rev. Neurosci. 2006; 7: 30-40Crossref PubMed Scopus (357) Google Scholar, 49Morrison J.H. Hof P.R. Life and death of neurons in the aging brain.Science. 1997; 278: 412-419Crossref PubMed Scopus (721) Google Scholar]. The interaction between cortical thickness and age further suggests that between-person variations in thickness are more likely to result in functional impairments if cortical thickness has fallen below a certain level. Conversely, executive functions are more likely to be maintained into old age if cortical thinning progresses at a slow pace. Longitudinal studies on the link between changes in cognition and brain volume are relatively sparse. In a recent review, Salthouse [50Salthouse T.A. Neuroanatomical substrates of age-related cognitive decline.Psychol. Bull. 2011; 137: 753-784Crossref PubMed Scopus (50) Google Scholar] reported eight studies, half of which showed a significant association between fewer senescent changes in grey or white matter volume and higher cognitive performance, whereas the other half showed no significant association. To our knowledge, there is only one longitudinal study investigating the association between changes in white matter integrity, measured with diffusion-tensor imaging, and cognition [51Charlton R.A. et al.Diffusion tensor imaging detects age related white matter change over a 2 year follow-up which is associated with working memory decline.J. Neurol. Neurosurg. Psychiatry. 2010; 81: 13-19Crossref PubMed Scopus (26) Google Scholar]. In this study, fewer alterations in whole-brain white matter microstructure were weakly linked to less negative changes in working-memory performance. In sum, although limited, the available evidence supports the notion that less structural brain change is associated with better memory performance in old age. Additional evidence for brain maintenance in aging is provided by fMRI studies, but the findings form a rather complex pattern. First, functional neuroanatomical correlates of age-related cognitive deficits have been documented in numerous studies in the form of reduced regional BOLD signal change in older compared to younger adults. Such reductions in BOLD signal change have been linked to age-related changes in grey matter [37Nyberg L. et al.Longitudinal evidence for diminished frontal-cortex function in aging.Proc. Natl. Acad. Sci. 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