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Maintenance, reserve and compensation: the cognitive neuroscience of healthy ageing

Nature Reviews Neurosciencevolume 19pages701710 (2018) | Download Citation


Cognitive ageing research examines the cognitive abilities that are preserved and/or those that decline with advanced age. There is great individual variability in cognitive ageing trajectories. Some older adults show little decline in cognitive ability compared with young adults and are thus termed ‘optimally ageing’. By contrast, others exhibit substantial cognitive decline and may develop dementia. Human neuroimaging research has led to a number of important advances in our understanding of the neural mechanisms underlying these two outcomes. However, interpreting the age-related changes and differences in brain structure, activation and functional connectivity that this research reveals is an ongoing challenge. Ambiguous terminology is a major source of difficulty in this venture. Three terms in particular — compensation, maintenance and reserve — have been used in a number of different ways, and researchers continue to disagree about the kinds of evidence or patterns of results that are required to interpret findings related to these concepts. As such inconsistencies can impede progress in both theoretical and empirical research, here, we aim to clarify and propose consensual definitions of these terms.

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Change history

  • 07 November 2018

    In the originally published version of article, there were two errors in the references. The reference “Nilsson, J. & Lövdén, M. Naming is not explaining: future directions for the “cognitive reserve” and “brain maintenance” theories. Alzheimer’s Res. Ther. 10, 34 (2018)” was missing. This reference has been added as REF. 14 in the HTML and PDF versions of the article and cited at the end of the sentence “However, over the years, these terms have been used inconsistently, creating confusion and slowing progress.” on page 701 and at the end of the sentence “If reserve is defined merely as the factor that individuals with greater reserve have and then this factor is used to explain why some individuals have greater reserve, the argument is clearly circular.” on page 704. The reference list has been renumbered accordingly. In addition, in the original reference list, REF. 91 was incorrect. The reference should have read “Cabeza, R. Hemispheric asymmetry reduction in older adults. The HAROLD model. Psychol. Aging 17, 85–100 (2002)”. This reference, which is REF. 92 in the corrected reference list, has been corrected in the HTML and PDF versions of the article.


  1. 1.

    Beard, J. R. et al. The world report on ageing and health: a policy framework for healthy ageing. Lancet 387, 2145–2154 (2016).

  2. 2.

    Gerstorf, D. et al. Secular changes in late-life cognition and well-being: towards a long bright future with a short brisk ending? Psychol. Aging 30, 301–310 (2015).

  3. 3.

    Cabeza, R., Nyberg, L. & Park, D. C. Cognitive Neuroscience of Aging: Linking Cognitive and Cerebral Aging 2nd edn (Oxford Univ. Press, New York, 2017).

  4. 4.

    Sole-Padulles, C. et al. Brain structure and function related to cognitive reserve variables in normal aging, mild cognitive impairment and Alzheimer’s disease. Neurobiol. Aging 30, 1114–1124 (2009).

  5. 5.

    Arenaza-Urquijo, E. M. et al. Association between educational attainment and amyloid deposition across the spectrum from normal cognition to dementia: neuroimaging evidence for protection and compensation. Neurobiol. Aging 59, 72–79 (2017).

  6. 6.

    Barulli, D. & Stern, Y. Efficiency, capacity, compensation, maintenance, plasticity: emerging concepts in cognitive reserve. Trends Cogn. Sci. 17, 502–509 (2013).

  7. 7.

    Nyberg, L., Lovden, M., Riklund, K., Lindenberger, U. & Backman, L. Memory aging and brain maintenance. Trends Cogn. Sci. 16, 292–305 (2012).

  8. 8.

    Grady, C. L. Age-related changes in cortical blood flow activation during perception and memory. Ann. N. Y. Acad. Sci. 777, 14–21 (1996).

  9. 9.

    Rajah, M. N. & D’Esposito, M. Region-specific changes in prefrontal function with age: a review of PET and fMRI studies on working and episodic memory. Brain 128, 1964–1983 (2005).

  10. 10.

    Persson, J. & Nyberg, L. Altered brain activity in healthy seniors: what does it mean? Prog. Brain Res. 157, 45–56 (2006).

  11. 11.

    Park, D. C. & Reuter-Lorenz, P. The adaptive brain: aging and neurocognitive scaffolding. Annu. Rev. Psychol. 60, 173–196 (2009).

  12. 12.

    Cabeza, R., Anderson, N. D., Locantore, J. K. & McIntosh, A. R. Aging gracefully: compensatory brain activity in high-performing older adults. Neuroimage 17, 1394–1402 (2002).

  13. 13.

    Reuter-Lorenz, P. A. & Cappell, K. A. Neurocognitive aging and the compensation hypothesis. Curr. Direct. Psychol. Sci. 17, 177–182 (2008).

  14. 14.

    Nilsson, J. & Lövdén, M. Naming is not explaining: future directions for the “cognitive reserve” and “brain maintenance” theories. Alzheimer’s Res. Ther. 10, 34 (2018).

  15. 15.

    Cabeza, R., Anderson, N. D., Houle, S., Mangels, J. A. & Nyberg, L. Age-related differences in neural activity during item and temporal-order memory retrieval: a positron emission tomography study. J. Cognitive Neurosci. 12, 1–10 (2000).

  16. 16.

    Cabeza, R. et al. Age-related differences in neural activity during memory encoding and retrieval: a positron emission tomography study. J. Neurosci. 17, 391–400 (1997).

  17. 17.

    Daselaar, S. M. et al. Less wiring, more firing: low-performing older adults compensate for impaired white matter with greater neural activity. Cereb. Cortex 25, 983–990 (2015).

  18. 18.

    Arenaza-Urquijo, E. M. & Vemuri, P. Resistance versus resilience to Alzheimer disease: clarifying terminology for preclinical studies. Neurology 90, 695–703 (2018).

  19. 19.

    Raz, N. & Daugherty, A. M. Pathways to brain aging and their modifiers: free-radical-induced energetic and neural decline in senescence (FRIENDS) model-a mini-review. Gerontology 64, 49–57 (2018).

  20. 20.

    Miller, R. A. Age-related changes in T cell surface markers: a longitudinal analysis in genetically heterogeneous mice. Mech. Ageing Dev. 96, 181–196 (1997).

  21. 21.

    Roy, A. K. et al. Impacts of transcriptional regulation on aging and senescence. Ageing Res. Rev. 1, 367–380 (2002).

  22. 22.

    Foster, T. C. Role of estrogen receptor alpha and beta expression and signaling on cognitive function during aging. Hippocampus 22, 656–669 (2012).

  23. 23.

    Papenberg, G., Salami, A., Persson, J., Lindenberger, U. & Backman, L. Genetics and functional imaging: effects of APOE, BDNF, COMT, and KIBRA in aging. Neuropsychol Rev. 25, 47–62 (2015).

  24. 24.

    Campisi, J. Cellular senescence and apoptosis: how cellular responses might influence aging phenotypes. Exp. Gerontol. 38, 5–11 (2003).

  25. 25.

    Musiek, E. S. & Holtzman, D. M. Mechanisms linking circadian clocks, sleep, and neurodegeneration. Science 354, 1004–1008 (2016).

  26. 26.

    Hullinger, R. & Puglielli, L. Molecular and cellular aspects of age-related cognitive decline and Alzheimer’s disease. Behav. Brain Res. 322, 191–205 (2017).

  27. 27.

    Mattson, M. P. & Arumugam, T. V. Hallmarks of brain aging: adaptive and pathological modification by metabolic states. Cell Metab. 27, 1176–1199 (2018).

  28. 28.

    Santoro, A. et al. Innate immunity and cellular senescence: the good and the bad in the developmental and aged brain. J. Leukoc. Biol. 103, 509–524 (2018).

  29. 29.

    Backman, L., Lindenberger, U., Li, S. C. & Nyberg, L. Linking cognitive aging to alterations in dopamine neurotransmitter functioning: recent data and future avenues. Neurosci. Biobehav. Rev. 34, 670–677 (2010).

  30. 30.

    Sampedro-Piquero, P., Alvarez-Suarez, P. & Begega, A. Coping with stress during aging: the importance of a resilient brain. Curr. Neuropharmacol. 16, 284–296 (2018).

  31. 31.

    Rosario, E. R., Chang, L., Head, E. H., Stanczyk, F. Z. & Pike, C. J. Brain levels of sex steroid hormones in men and women during normal aging and in Alzheimer’s disease. Neurobiol. Aging 32, 604–613 (2011).

  32. 32.

    Morgan, D. G. The dopamine and serotonin systems during aging in human and rodent brain. A brief review. Prog. Neuropsychopharmacol. Biol. Psychiatry 11, 153–157 (1987).

  33. 33.

    Freeman, G. B. & Gibson, G. E. Dopamine, acetylcholine, and glutamate interactions in aging. Behavioral and neurochemical correlates. Ann. N. Y. Acad. Sci. 515, 191–202 (1988).

  34. 34.

    Valenzuela, M. J., Breakspear, M. & Sachdev, P. Complex mental activity and the aging brain: molecular, cellular and cortical network mechanisms. Brain Res. Rev. 56, 198–213 (2007).

  35. 35.

    Hibar, D. P. et al. Common genetic variants influence human subcortical brain structures. Nature 520, 224–229 (2015).

  36. 36.

    Sperling, R. Potential of functional MRI as a biomarker in early Alzheimer’s disease. Neurobiol. Aging 32 (Suppl. 1), S37–S43 (2011).

  37. 37.

    Grady, C. L. The cognitive neuroscience of ageing. Nat. Rev. Neurosci. 13, 491–505 (2012).

  38. 38.

    Tromp, D., Dufour, A., Lithfous, S., Pebayle, T. & Despres, O. Episodic memory in normal aging and Alzheimer disease: insights from imaging and behavioral studies. Ageing Res. Rev. 24, 232–262 (2015).

  39. 39.

    Walhovd, K. B. et al. Consistent neuroanatomical age-related volume differences across multiple samples. Neurobiol. Aging 32, 916–932 (2011).

  40. 40.

    Rajah, M. N., Maillet, D. & Grady, C. L. in The Wiley Handbook of Cognitive Neuroscience of Memory (eds Addis, D., Barense, M. & Duarte, A.) 347–361 (Wiley Publishers, New York, 2015).

  41. 41.

    Nyberg, L. et al. Longitudinal evidence for diminished frontal cortex function in aging. Proc. Natl Acad. Sci. USA 107, 22682–22686 (2010).

  42. 42.

    Salat, D. H. et al. Age-related changes in prefrontal white matter measured by diffusion tensor imaging. Ann. N. Y. Acad. Sci. 1064, 37–49 (2005).

  43. 43.

    Giorgio, A. et al. Age-related changes in grey and white matter structure throughout adulthood. Neuroimage 51, 943–951 (2010).

  44. 44.

    Madden, D. J. et al. Adult age differences in functional connectivity during executive control. Neuroimage 52, 643–657 (2010).

  45. 45.

    Craik, F. I. M. & Salthouse, T. A. The Handbook of Aging and Cognition (Lawrence Erlbaum Associates, Mahwah, NJ, 2000).

  46. 46.

    Lindenberger, U. Human cognitive aging: corriger la fortune? Science 346, 572–578 (2014).

  47. 47.

    World Health Organisation. World Report on Ageing and Health (eds Beard, J., Officer, A. & Cassels, A.) (WHO, Luxembourg, 2015).

  48. 48.

    Habib, R., Nyberg, L. & Nilsson, L. G. Cognitive and non-cognitive factors contributing to the longitudinal identification of successful older adults in the Betula study. Aging Neuropsychol. Cogn. 14, 257–273 (2007).

  49. 49.

    Ronnlund, M. & Nilsson, L. G. Flynn effects on sub-factors of episodic and semantic memory: parallel gains over time and the same set of determining factors. Neuropsychologia 47, 2174–2180 (2009).

  50. 50.

    Trahan, L. H., Stuebing, K. K., Fletcher, J. M. & Hiscock, M. The Flynn effect: a meta-analysis. Psychol. Bull. 140, 1332–1360 (2014).

  51. 51.

    Deary, I. J., Whiteman, M. C., Starr, J. M., Whalley, L. J. & Fox, H. C. The impact of childhood intelligence on later life: following up the Scottish mental surveys of 1932 and 1947. J. Pers Soc. Psychol. 86, 130–147 (2004).

  52. 52.

    Nyberg, L., Pudas, S. & Lundquist, A. in Cogntiive Neuroscience of Aging 2nd edn (eds Cabeza, R., Nyberg, L. & Park, D. C.) (Oxford Univ. Press, 2016).

  53. 53.

    Raz, N. et al. Regional brain changes in aging healthy adults: general trends, individual differences and modifiers. Cereb. Cortex 15, 1676–1689 (2005).

  54. 54.

    Ghisletta, P., Rabbitt, P., Lunn, M. & Lindenberger, U. Two thirds of the age-based changes in fluid and crystallized intelligence, perceptual speed, and memory in adulthood are shared. Intelligence 40, 260–268 (2012).

  55. 55.

    Stern, Y., Gazes, Y., Razlighi, Q., Steffener, J. & Habeck, C. A task-invariant cognitive reserve network. Neuroimage 178, 36–45 (2018).

  56. 56.

    Piras, F., Cherubini, A., Caltagirone, C. & Spalletta, G. Education mediates microstructural changes in bilateral hippocampus. Hum. Brain Mapp. 32, 282–289 (2011).

  57. 57.

    Stern, Y. Cognitive reserve and Alzheimer disease. Alzheimer Dis. Assoc. Disord. 20, 112–117 (2006).

  58. 58.

    Scarmeas, N. et al. Cognitive reserve-mediated modulation of positron emission tomographic activations during memory tasks in Alzheimer disease. Arch. Neurol. 61, 73–78 (2004).

  59. 59.

    Stern, Y. Cognitive reserve. Neuropsychologia 47, 2015–2028 (2009).

  60. 60.

    Soldan, A. et al. Relationship of medial temporal lobe atrophy, APOE genotype, and cognitive reserve in preclinical Alzheimer’s disease. Hum. Brain Mapp. 36, 2826–2841 (2015).

  61. 61.

    Bialystok, E., Craik, F. I. M. & Luk, G. Bilingualism: consequences for mind and brain. Trends Cogn. Sci. 16, 240–250 (2012).

  62. 62.

    Prakash, R. S., Voss, M. W., Erickson, K. I. & Kramer, A. F. Physical activity and cognitive vitality. Annu. Rev. Psychol. 66, 769–797 (2015).

  63. 63.

    Scarmeas, N. & Stern, Y. Cognitive reserve and lifestyle. J. Clin. Exp. Neuropsychol. 25, 625–633 (2003).

  64. 64.

    Bialystok, E., Craik, F. I. M. & Freedman, M. Bilingualism as a protection against the onset of symptoms of dementia. Neuropsychologia 45, 459–464 (2007).

  65. 65.

    Alladi, S. et al. Bilingualism delays age at onset of dementia, independent of education and immigration status. Neurology 81, 1938–1944 (2013).

  66. 66.

    Anthony, M. & Lin, F. A. Systematic review for functional neuroimaging studies of cognitive reserve across the cognitive aging spectrum. Arch. Clin. Neuropsychol. (2017).

  67. 67.

    Reed, B. R. et al. Cognitive activities during adulthood are more important than education in building reserve. J. Int. Neuropsychol. Soc. 17, 615–624 (2011).

  68. 68.

    Zahodne, L. B. et al. Quantifying cognitive reserve in older adults by decomposing episodic memory variance: replication and extension. J. Int. Neuropsychol. Soc. 19, 854–862 (2013).

  69. 69.

    Reed, B. R. et al. Measuring cognitive reserve based on the decomposition of episodic memory variance. Brain 133, 2196–2209 (2010).

  70. 70.

    Bernardi, G. et al. How skill expertise shapes the brain functional architecture: an fMRI study of visuo-spatial and motor processing in professional racing-car and naive drivers. PLOS ONE 8, e77764 (2013).

  71. 71.

    Adamson, M. M. et al. Higher landing accuracy in expert pilots is associated with lower activity in the caudate nucleus. PLOS ONE 9, e112607 (2014).

  72. 72.

    Kim, W. et al. An fMRI study of differences in brain activity among elite, expert, and novice archers at the moment of optimal aiming. Cogn. Behav. Neurol. 27, 173–182 (2014).

  73. 73.

    Kozasa, E. H. et al. Effects of a 7-day meditation retreat on the brain function of meditators and non-meditators during an attention task. Front. Hum. Neurosci. 12, 222 (2018).

  74. 74.

    Li, Y. et al. Sound credit scores and financial decisions despite cognitive aging. Proc. Natl Acad. Sci. USA 112, 65–69 (2015).

  75. 75.

    Lindenberger, U., Kliegl, R. & Baltes, P. B. Professional expertise does not eliminate age-differences in imagery-based memory performance during adulthood. Psychol. Aging 7, 585–593 (1992).

  76. 76.

    Morrow, D., Leirer, V., Altieri, P. & Fitzsimmons, C. When expertise reduces age-differences in performance. Psychol. Aging 9, 134–148 (1994).

  77. 77.

    Vaci, N., Gula, B. & Bilalic, M. Is age really cruel to experts? Compensatory effects of activity. Psychol. Aging 30, 740–754 (2015).

  78. 78.

    Stern, Y., Albert, S., Tang, M. & Tsai, W. Rate of memory decline in AD is related to education and occupation. Neurology 1, 1942–1947 (1999).

  79. 79.

    Ten Brinke, L. F. et al. Aerobic exercise increases cortical white matter volume in older adults with vascular cognitive impairment: a 6-month randomized controlled trial. Alzheimers Dement. 11, 606 (2015).

  80. 80.

    Gorbach, T. et al. Longitudinal association between hippocampus atrophy and episodic-memory decline. Neurobiol. Aging 51, 167–176 (2017).

  81. 81.

    Persson, J. et al. Longitudinal structure–function correlates in elderly reveal MTL dysfunction with cognitive decline. Cereb. Cortex 22, 2297–2304 (2012).

  82. 82.

    Pudas, S. et al. Brain characteristics of individuals resisting age-related cognitive decline over two decades. J. Neurosci. 33, 8668–8677 (2013).

  83. 83.

    Miller, E. K. & Cohen, J. D. An integrative theory of prefrontal cortex function. Annu. Rev. Neurosci. 24, 167–202 (2001).

  84. 84.

    Raz, N. & Lindenberger, U. Only time will tell: cross-sectional studies offer no solution to the age-brain-cognition triangle: comment on Salthouse (2011). Psychol. Bull. 137, 790–795 (2011).

  85. 85.

    Kovari, E., Herrmann, F. R., Bouras, C. & Gold, G. Amyloid deposition is decreasing in aging brains: an autopsy study of 1,599 older people. Neurology 82, 326–331 (2014).

  86. 86.

    Lovden, M., Backman, L., Lindenberger, U., Schaefer, S. & Schmiedek, F. A. Theoretical framework for the study of adult cognitive plasticity. Psychol. Bull. 136, 659–676 (2010).

  87. 87.

    Beam, C. R. & Turkheimer, E. Phenotype-environment correlations in longitudinal twin models. Dev. Psychopathol. 25, 7–16 (2013).

  88. 88.

    Lovden, M., Ghisletta, P. & Lindenberger, U. Social participation attenuates decline in perceptual speed in old and very old age. Psychol. Aging 20, 423–434 (2005).

  89. 89.

    Cabeza, R. & Dennis, N. A. in Principles of Frontal Lobe Function (eds Stuss, D. T. & Knight, R. T.) (Oxford Univ. Press, New York, 2013).

  90. 90.

    Bakker, A. et al. Reduction of hippocampal hyperactivity improves cognition in amnestic mild cognitive impairment. Neuron 74, 467–474 (2012).

  91. 91.

    Spreng, R. N., Wojtowicz, M. & Grady, C. L. Reliable differences in brain activity between young and old adults: a quantitative meta-analysis across multiple cognitive domains. Neurosci. Biobehav. Rev. 34, 1178–1194 (2010).

  92. 92.

    Cabeza, R. Hemispheric asymmetry reduction in older adults. The HAROLD model. Psychol. Aging 17, 85–100 (2002).

  93. 93.

    Falk, E. B. et al. What is a representative brain? Neuroscience meets population science. Proc. Natl Acad. Sci. USA 110, 17615–17622 (2013).

  94. 94.

    Albert, M. S. et al. The diagnosis of mild cognitive impairment due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 7, 270–279 (2011).

  95. 95.

    Driscoll, I. & Troncoso, J. Asymptomatic Alzheimer’s disease: a prodrome or a state of resilience? Curr. Alzheimer Res. 8, 330–335 (2011).

  96. 96.

    Brickman, A. M. et al. White matter hyperintensities and cognition: testing the reserve hypothesis. Neurobiol. Aging 32, 1588–1598 (2011).

  97. 97.

    Landau, S. M. et al. Association of lifetime cognitive engagement and low β-amyloid deposition. Arch. Neurol. 69, 623–629 (2012).

  98. 98.

    Soldan, A. et al. Relationship of cognitive reserve and cerebrospinal fluid biomarkers to the emergence of clinical symptoms in preclinical Alzheimer’s disease. Neurobiol. Aging 34, 2827–2834 (2013).

  99. 99.

    Dickerson, B. C. et al. Medial temporal lobe function and structure in mild cognitive impairment. Ann. Neurol. 56, 27–35 (2004).

  100. 100.

    Huijbers, W. et al. Amyloid-β deposition in mild cognitive impairment is associated with increased hippocampal activity, atrophy and clinical progression. Brain 138, 1023–1035 (2015).

  101. 101.

    Clement, F. & Belleville, S. Compensation and disease severity on the memory-related activations in mild cognitive impairment. Biol. Psychiatry 68, 894–902 (2010).

  102. 102.

    Bookheimer, S. Y. et al. Patterns of brain activation in people at risk for Alzheimer’s disease. N. Engl. J. Med. 343, (450–456 (2000).

  103. 103.

    Rajah, M. N. et al. Family history and APOE4 risk for Alzheimer’s disease impact the neural correlates of episodic memory by early midlife. Neuroimage Clin. 14, 760–774 (2017).

  104. 104.

    Celone, K. A. et al. Alterations in memory networks in mild cognitive impairment and Alzheimer’s disease: an independent component analysis. J. Neurosci. 26, 10222–10231 (2006).

  105. 105.

    Elman, J. A. et al. Neural compensation in older people with brain amyloid-beta deposition. Nat. Neurosci. 17, 1316–1318 (2014).

  106. 106.

    Esposito, Z. et al. Amyloid β, glutamate, excitotoxicity in Alzheimer’s disease: are we on the right track? Cns Neurosci. Ther. 19, 549–555 (2013).

  107. 107.

    Rudy, C. C., Hunsberger, H. C., Weitzner, D. S. & Reed, M. N. The role of the tripartite glutamatergic synapse in the pathophysiology of Alzheimer’s disease. Aging Dis. 6, 131–148 (2015).

  108. 108.

    Belleville, S. et al. Training-related brain plasticity in subjects at risk of developing Alzheimer’s disease. Brain 134, 1623–1634 (2011).

  109. 109.

    Kievit, R. A., Frankenhuis, W. E., Waldorp, L. J. & Borsboom, D. Simpson’s paradox in psychological science: a practical guide. Frontiers Psychol. 4, 14 (2013).

  110. 110.

    Rossi, S. et al. Age-related functional changes of prefrontal cortex in long-term memory: a repetitive transcranial magnetic stimulation study. J. Neurosci. 24, 7939–7944 (2004).

  111. 111.

    Cappell, K. A., Gmeindl, L. & Reuter-Lorenz, P. A. Age differences in prefontal recruitment during verbal working memory maintenance depend on memory load. Cortex 46, 462–473 (2010).

  112. 112.

    Daselaar, S. M., Fleck, M., Dobbins, I. G., Madden, D. J. & Cabeza, R. Effects of healthy aging on hippocampal and rhinal memory functions: an event-related fMRI study. Cereb. Cortex 16, 1771–1782 (2006).

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This manuscript presents a summary of discussions from a 2-day symposium held at McGill University, Montreal, Canada, from 31 May–2 June 2017, which was funded by a Canadian Institutes of Health Research (CIHR) Planning and Dissemination Grant 373172 awarded to M.N.R. and R.C. and by institutional funds from Duke University (North Carolina, USA) and the Douglas Hospital Research Centre (Montreal, Canada). R.C. is supported by a grant from the US National Institutes of Health (NIH; RO1-AG19731). M.A. is supported by a grant from the NIH National Institute on Aging (NIA; P50-AG005146). S.B. is supported by a grant from the National Sciences and Engineering Research Council of Canada (NSERC; RGPIN-2016-06132). F.I.M.C. is supported by a grant from the Natural Sciences and Engineering Research Council (NSERC; A8261). A.D. is supported by a grant from NIH (R56-AG049793). C.L.G. is supported by a grant from CIHR (MOP-143311). U.L. is supported by the Max Planck Society. L.N. is support by a scholar grant from the Knut and Alice Wallenberg Foundation. D.C.P. is supported by a grant from the NIH (R01-AG006265). P.A.R.-L. is supported by a grant from the NIH (R21-AG045460). M.D.R. is supported by a grant from the NIH (RF1-AG039103). M.N.R. is supported by grants from CIHR (MOP 126105) and NSERC (RGPIN-2018-05761).

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Nature Reviews Neuroscience thanks C. Brayne, R. Dixon, W. Jagust and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Author information


  1. Center for Cognitive Neuroscience, Department of Psychology and Neuroscience, Duke University, Durham, NC, USA

    • Roberto Cabeza
  2. Departments of Psychiatry and Neurology, John Hopkins University, Baltimore, MD, USA

    • Marilyn Albert
  3. Research Center of the Institut Universitaire de Gériatrie de Montréal, Montreal, Quebec, Canada

    • Sylvie Belleville
  4. Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada

    • Fergus I. M. Craik
    •  & Cheryl L. Grady
  5. School of Psychology, Georgia Tech, Atlanta, GA, USA

    • Audrey Duarte
  6. Max Planck Institute for Human Development and Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany

    • Ulman Lindenberger
  7. Departments of Radiation Sciences and Integrated Medical Biology, UFBI, Umeå University, Umeå, Sweden

    • Lars Nyberg
  8. Center for Vital Longevity, University of Texas, Dallas, TX, USA

    • Denise C. Park
    •  & Michael D. Rugg
  9. Department of Psychology, University of Michigan, Ann Arbor, MI, USA

    • Patricia A. Reuter-Lorenz
  10. Interdisciplinary School of Health Sciences, University of Ottawa, Ottowa, Ontario, Canada

    • Jason Steffener
  11. Departments of Psychiatry & Psychology, McGill University and Douglas Hospital Research Centre, Montreal, Quebec, Canada

    • M. Natasha Rajah


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R.C., M.A., S.B., F.I.M.C., A.D., C.L.G., U.L., L.N., D.C.P., P.A.R.-L., M.D.R., J.S. and M.N.R. researched data for the article, made a substantial contribution to the discussion of content, wrote the article and reviewed and/or edited the manuscript before submission.

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The authors declare no competing interests.

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Correspondence to Roberto Cabeza.

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