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OPINION

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

An Author Correction to this article was published on 07 November 2018

A Publisher Correction to this article was published on 07 November 2018

This article has been updated

Abstract

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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Fig. 1: Similarities and differences between reserve, maintenance and compensation.
Fig. 2: Stable cognitive performance is associated with brain maintenance.
Fig. 3: Compensation mechanisms: upregulation, selection and reorganization.

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.

References

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

    PubMed  Google Scholar 

  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).

    PubMed  Google Scholar 

  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).

    Google Scholar 

  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).

    CAS  PubMed  Google Scholar 

  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).

    CAS  PubMed  Google Scholar 

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

    Google Scholar 

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

    PubMed  Google Scholar 

  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).

    CAS  Google Scholar 

  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).

    PubMed  Google Scholar 

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

    PubMed  Google Scholar 

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

    PubMed  PubMed Central  Google Scholar 

  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).

    PubMed  Google Scholar 

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

    Google Scholar 

  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).

    Google Scholar 

  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).

    CAS  Google Scholar 

  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).

    CAS  PubMed  PubMed Central  Google Scholar 

  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).

    PubMed  Google Scholar 

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

    PubMed  PubMed Central  Google Scholar 

  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).

    CAS  PubMed  Google Scholar 

  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).

    CAS  Google Scholar 

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

    CAS  PubMed  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  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).

    PubMed  Google Scholar 

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

    CAS  PubMed  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  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).

    CAS  PubMed  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  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).

    CAS  PubMed  Google Scholar 

  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).

    PubMed  Google Scholar 

  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).

    CAS  PubMed  PubMed Central  Google Scholar 

  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).

    CAS  PubMed  Google Scholar 

  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).

    CAS  PubMed  Google Scholar 

  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).

    CAS  PubMed  Google Scholar 

  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).

    CAS  PubMed  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

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

    PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  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).

    CAS  PubMed  Google Scholar 

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

    PubMed  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  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).

    CAS  PubMed  Google Scholar 

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

    PubMed  Google Scholar 

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

    PubMed  Google Scholar 

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

    Google Scholar 

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

    CAS  PubMed  Google Scholar 

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

  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).

    Google Scholar 

  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).

    PubMed  Google Scholar 

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

    PubMed  PubMed Central  Google Scholar 

  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).

    PubMed  Google Scholar 

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

    PubMed  Google Scholar 

  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).

    Google Scholar 

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

    PubMed  Google Scholar 

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

    PubMed  Google Scholar 

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

    PubMed  Google Scholar 

  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).

    PubMed  PubMed Central  Google Scholar 

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

    PubMed  PubMed Central  Google Scholar 

  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).

    PubMed  PubMed Central  Google Scholar 

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

    Google Scholar 

  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).

    PubMed  Google Scholar 

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

    PubMed  PubMed Central  Google Scholar 

  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).

    PubMed  Google Scholar 

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

    PubMed  Google Scholar 

  66. Anthony, M. & Lin, F. A. Systematic review for functional neuroimaging studies of cognitive reserve across the cognitive aging spectrum. Arch. Clin. Neuropsychol. https://doi.org/10.1093/arclin/acx125 (2017).

    Article  PubMed Central  Google Scholar 

  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).

    PubMed  PubMed Central  Google Scholar 

  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).

    PubMed  PubMed Central  Google Scholar 

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

    PubMed  PubMed Central  Google Scholar 

  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).

    CAS  PubMed  PubMed Central  Google Scholar 

  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).

    PubMed  PubMed Central  Google Scholar 

  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).

    PubMed  Google Scholar 

  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).

    PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  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).

    CAS  PubMed  Google Scholar 

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

    CAS  PubMed  Google Scholar 

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

    PubMed  Google Scholar 

  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).

    Google Scholar 

  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).

    Google Scholar 

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

    PubMed  Google Scholar 

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

    PubMed  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  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).

    PubMed  PubMed Central  Google Scholar 

  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).

    PubMed  Google Scholar 

  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).

    PubMed  Google Scholar 

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

    PubMed  PubMed Central  Google Scholar 

  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).

    PubMed  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  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).

    Google Scholar 

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

    Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  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).

    PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

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

    PubMed  Google Scholar 

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

    PubMed  PubMed Central  Google Scholar 

  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).

    CAS  PubMed  Google Scholar 

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

    PubMed  PubMed Central  Google Scholar 

  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).

    PubMed  PubMed Central  Google Scholar 

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

    PubMed  Google Scholar 

  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).

    Google Scholar 

  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).

    CAS  PubMed  PubMed Central  Google Scholar 

  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).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  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).

    CAS  PubMed  PubMed Central  Google Scholar 

  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).

    PubMed  PubMed Central  Google Scholar 

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

    PubMed  Google Scholar 

  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).

    Google Scholar 

  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).

    CAS  PubMed  PubMed Central  Google Scholar 

  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).

    PubMed  Google Scholar 

  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).

    PubMed  Google Scholar 

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Acknowledgements

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.

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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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Correspondence to Roberto Cabeza.

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Cabeza, R., Albert, M., Belleville, S. et al. Maintenance, reserve and compensation: the cognitive neuroscience of healthy ageing. Nat Rev Neurosci 19, 701–710 (2018). https://doi.org/10.1038/s41583-018-0068-2

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