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Deriving and Testing the Validity of Cognitive Reserve Candidates

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Biomarkers for Preclinical Alzheimer’s Disease

Part of the book series: Neuromethods ((NM,volume 137))

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Abstract

Empirical support has established cognitive reserve (CR) well as a concept since its inception three decades ago, and most brain researchers subscribe to some version of CR as a collection of subject factors that influence cognitive performance beyond simple brain structural health. We give a simple but precise analytic recipe to test requirements for any plausible cognitive reserve candidate based on brain imaging. Gradations of partial fulfillment of some but not all of these requirements are possible.

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References

  1. Verghese J, Lipton RB, Katz MJ et al (2003) Leisure activities and the risk of dementia in the elderly. N Engl J Med 348(25):2508–2516

    Article  PubMed  Google Scholar 

  2. Hu G, Sarti C, Jousilahti P et al (2005) Leisure time, occupational, and commuting physical activity and the risk of stroke. Stroke 36(9):1994–1999

    Article  PubMed  Google Scholar 

  3. Rovio S, Kareholt I, Helkala EL et al (2005) Leisure-time physical activity at midlife and the risk of dementia and Alzheimer's disease. Lancet Neurol 4(11):705–711. https://doi.org/10.1016/S1474-4422(05)70198-8

    Article  PubMed  Google Scholar 

  4. Helzner EP, Scarmeas N, Cosentino S et al (2007) Leisure activity and cognitive decline in incident Alzheimer disease. Arch Neurol 64(12):1749–1754

    Article  PubMed  Google Scholar 

  5. Akbaraly TN, Portet F, Fustinoni S et al (2009) Leisure activities and the risk of dementia in the elderly: results from the Three-City Study. Neurology 73(11):854–861. https://doi.org/10.1212/WNL.0b013e3181b7849b

    Article  CAS  PubMed  Google Scholar 

  6. Scarmeas N, Levy G, Tang MX et al (2001) Influence of leisure activity on the incidence of Alzheimer’s disease. Neurology 57(12):2236–2242

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Valenzuela MJ, Sachdev P, Wen W et al (2008) Lifespan mental activity predicts diminished rate of hippocampal atrophy. PLoS One 3(7):e2598. https://doi.org/10.1371/journal.pone.0002598

    Article  PubMed  PubMed Central  Google Scholar 

  8. Gates N, Valenzuela M (2010) Cognitive exercise and its role in cognitive function in older adults. Curr Psychiatry Rep 12(1):20–27. https://doi.org/10.1007/s11920-009-0085-y

    Article  PubMed  Google Scholar 

  9. Bonaiuto S, Rocca W, Lippi A (1990) Impact of education and occupation on prevalence of Alzheimer’s disease (AD) and multi-infarct dementia (MID) in Appignano, Macerata Province, Italy. Neurology 40(suppl 1):346

    Google Scholar 

  10. Cohen CI (1994) Education, occupation, and Alzheimer’s disease. JAMA 272(18):1405. Author reply 1406

    Article  CAS  PubMed  Google Scholar 

  11. Gun RT, Korten AE, Jorm AF et al (1997) Occupational risk factors for Alzheimer disease: a case-control study. Alzheimers Dis Assoc Disord 11(1):21–27

    Article  CAS  Google Scholar 

  12. Helmer C, Letenneur L, Rouch I et al (2001) Occupation during life and risk of dementia in French elderly community residents. J Neurol Neurosurg Psychiatry 71(3):303–309

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Anttila T, Helkala EL, Kivipelto M et al (2002) Midlife income, occupation, APOE status, and dementia: a population-based study. Neurology 59(6):887–893

    Article  CAS  PubMed  Google Scholar 

  14. Ravaglia G, Forti P, Maioli F et al (2002) Education, occupation, and prevalence of dementia: findings from the Conselice study. Dement Geriatr Cogn Disord 14(2):90–100

    Article  PubMed  Google Scholar 

  15. Finkel D, Andel R, Gatz M et al (2009) The role of occupational complexity in trajectories of cognitive aging before and after retirement. Psychol Aging 24(3):563–573. https://doi.org/10.1037/a0015511

    Article  PubMed  PubMed Central  Google Scholar 

  16. Garibotto V, Borroni B, Sorbi S et al (2012) Education and occupation provide reserve in both ApoE epsilon4 carrier and noncarrier patients with probable Alzheimer’s disease. Neurol Sci 33(5):1037–1042. https://doi.org/10.1007/s10072-011-0889-5

    Article  CAS  PubMed  Google Scholar 

  17. Stern Y, Gurland B, Tatemichi TK et al (1994) Influence of education and occupation on the incidence of Alzheimer’s disease. J Am Med Assoc 271:1004–1010

    Article  CAS  Google Scholar 

  18. Habeck C, Razlighi Q, Gazes Y et al (2016) Cognitive reserve and brain maintenance: orthogonal concepts in theory and practice. Cereb Cortex. https://doi.org/10.1093/cercor/bhw208

  19. Fischl B, Salat DH, Busa E et al (2002) Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 33(3):341–355

    Article  CAS  PubMed  Google Scholar 

  20. Fischl B, van der Kouwe A, Destrieux C et al (2004) Automatically parcellating the human cerebral cortex. Cereb Cortex 14(1):11–22. https://doi.org/10.1093/cercor/bhg087

    Article  PubMed  Google Scholar 

  21. Kennedy KM, Erickson KI, Rodrigue KM et al (2009) Age-related differences in regional brain volumes: a comparison of optimized voxel-based morphometry to manual volumetry. Neurobiol Aging 30(10):1657–1676. https://doi.org/10.1016/j.neurobiolaging.2007.12.020

    Article  PubMed  Google Scholar 

  22. Fjell AM, Westlye LT, Amlien I et al (2009) High consistency of regional cortical thinning in aging across multiple samples. Cereb Cortex 19(9):2001–2012. https://doi.org/10.1093/cercor/bhn232

    Article  PubMed  PubMed Central  Google Scholar 

  23. Ardekani BA, Guckemus S, Bachman A et al (2005) Quantitative comparison of algorithms for inter-subject registration of 3D volumetric brain MRI scans. J Neurosci Methods 142(1):67–76. https://doi.org/10.1016/j.jneumeth.2004.07.014

    Article  PubMed  Google Scholar 

  24. Dale AM, Fischl B, Sereno MI (1999) Cortical surface-based analysis. I Segmentation and surface reconstruction. Neuroimage 9(2):179–194

    Article  CAS  PubMed  Google Scholar 

  25. Fischl B, Dale AM (2000) Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proc Natl Acad Sci U S A 97(20):11050–11055. https://doi.org/10.1073/pnas.200033797

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Jenkinson M, Bannister P, Brady M et al (2002) Improved optimization for the robust and accurate linear registration and motion correction of brain images. NeuroImage 17(2):825–841

    Article  PubMed  Google Scholar 

  27. Power JD, Barnes KA, Snyder AZ et al (2012) Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. NeuroImage 59(3):2142–2154. https://doi.org/10.1016/j.neuroimage.2011.10.018

    Article  PubMed  Google Scholar 

  28. Carp J (2013) Optimizing the order of operations for movement scrubbing: comment on Power et al. NeuroImage 76:436–438. https://doi.org/10.1016/j.neuroimage.2011.12.061

    Article  PubMed  Google Scholar 

  29. Birn RM, Diamond JB, Smith MA et al (2006) Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI. NeuroImage 31(4):1536–1548. https://doi.org/10.1016/j.neuroimage.2006.02.048

    Article  PubMed  Google Scholar 

  30. Power JD, Cohen AL, Nelson SM et al (2011) Functional network organization of the human brain. Neuron 72(4):665–678. https://doi.org/10.1016/j.neuron.2011.09.006

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Correspondence to Yaakov Stern .

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Stern, Y., Habeck, C. (2018). Deriving and Testing the Validity of Cognitive Reserve Candidates. In: Perneczky, R. (eds) Biomarkers for Preclinical Alzheimer’s Disease. Neuromethods, vol 137. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7674-4_4

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  • DOI: https://doi.org/10.1007/978-1-4939-7674-4_4

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7673-7

  • Online ISBN: 978-1-4939-7674-4

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