A decade of changes in brain volume and cognition

  • Rowa Aljondi
  • Cassandra SzoekeEmail author
  • Chris Steward
  • Paul Yates
  • Patricia Desmond
Original Research


Brain atrophy can occur several decades prior to onset of cognitive impairments. However, few longitudinal studies have examined the relationship between brain volume changes and cognition over a long follow-up period in healthy elderly women. In the present study we investigate the relationship between whole brain and hippocampal atrophy rates and longitudinal changes in cognition, including verbal episodic memory and executive function, in older women. We also examine whether baseline brain volume predicts subsequent changes in cognitive performance over a 10-year period. A total of 60 individuals from the population-based Women’s Healthy Ageing Project with a mean age at baseline of 59 years underwent 3T MRI. Of these, 40 women completed follow-up cognitive assessments, 23 of whom had follow-up MRI scans. Linear regression analysis was used to examine the relationship between brain atrophy and changes in verbal episodic memory and executive function over a 10-year period. The results show that baseline measurements of frontal and temporal grey matter volumes predict changes in verbal episodic memory performance, whereas hippocampal volume at baseline is associated with changes in executive function performance over a 10-year period of follow-ups. In addition, higher whole brain and hippocampal atrophy rates are correlated with a decline in verbal episodic memory. These findings indicate that in addition to atrophy rate, smaller regional grey matter volumes even 10 years prior is associated with increased rates of cognitive decline. This study suggests useful neuroimaging biomarkers for the prediction of cognitive decline in healthy elderly women.


Normal aging Elderly women Brain atrophy Hippocampal atrophy Episodic memory Executive function 



We would like to acknowledge the contribution of the participants and their supporters who have contributed their time and commitment for over 20 years to the University. A full list of all researchers contributing to the project and the membership of our Scientific Advisory Board is available at


This study is funded by the National Health and Medical Research Council (NHMRC Grants 547500, 1032350 & 1062133), Ramaciotti Foundation, Australian Healthy Ageing Organisation, the Brain Foundation, the Alzheimer’s Association (NIA320312), Australian Menopausal Society, Bayer Healthcare, Shepherd Foundation, Scobie and Claire Mackinnon Foundation, Collier Trust Fund, J.O. & J.R. Wicking Trust, Mason Foundation and the Alzheimer’s Association of Australia. Inaugural funding was provided by VicHealth and the NHMRC. The Principal Investigator of WHAP (CSz) is supported by the National Health and Medical Research Council.

Compliance with ethical standards

Conflict of interest

Prof. Szoeke has provided clinical consultancy and been on scientific advisory committees for the Australian Commonwealth Scientific and Industrial Research Organisation, Alzheimer’s Australia, University of Melbourne and other relationships which are subject to confidentiality clauses. She has been a named Chief Investigator on investigator driven collaborative research projects in partnership with Pfizer, Merck, Bayer and GE. She has been an investigator on clinical trials with Lundbeck within the last 2 years. Dr. Desmond has been supported by the Royal Melbourne Hospital and the National Health and Medical Research Council of Australia. Other authors report no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Supplementary material

11682_2018_9887_MOESM1_ESM.docx (15 kb)
ESM 1 (DOCX 14 kb)


  1. Apostolova, L. G., Green, A. E., Babakchanian, S., Hwang, K. S., Chou, Y.-Y., Toga, A. W., & Thompson, P. M. (2012). Hippocampal atrophy and ventricular enlargement in normal aging, mild cognitive impairment and Alzheimer’s disease. Alzheimer Disease and Associated Disorders, 26(1), 17–27.CrossRefPubMedPubMedCentralGoogle Scholar
  2. Archer, H., Kennedy, J., Barnes, J., Pepple, T., Boyes, R., Randlesome, K., Clegg, S., Leung, K., Ourselin, S., & Frost, C. (2010). Memory complaints and increased rates of brain atrophy: risk factors for mild cognitive impairment and Alzheimer’s disease. International Journal of Geriatric Psychiatry, 25(11), 1119–1126.CrossRefPubMedGoogle Scholar
  3. Bourisly, A. K., El-Beltagi, A., Cherian, J., Gejo, G., Al-Jazzaf, A., & Ismail, M. (2015). A voxel-based morphometric magnetic resonance imaging study of the brain detects age-related gray matter volume changes in healthy subjects of 21–45 years old. The Neuroradiology Journal, 28(5), 450–459.CrossRefPubMedPubMedCentralGoogle Scholar
  4. Burgess, N., Maguire, E. A., & O’Keefe, J. (2002). The human hippocampus and spatial and episodic memory. Neuron, 35(4), 625–641.CrossRefPubMedGoogle Scholar
  5. Burgmans, S., Van Boxtel, M., Smeets, F., Vuurman, E., Gronenschild, E., Verhey, F., Uylings, H., & Jolles, J. (2009). Prefrontal cortex atrophy predicts dementia over a six-year period. Neurobiology of Aging, 30(9), 1413–1419.CrossRefPubMedGoogle Scholar
  6. Cardenas, V., Chao, L., Studholme, C., Yaffe, K., Miller, B., Madison, C., Buckley, S., Mungas, D., Schuff, N., & Weiner, M. (2011). Brain atrophy associated with baseline and longitudinal measures of cognition. Neurobiology of Aging, 32(4), 572–580.CrossRefPubMedGoogle Scholar
  7. Carlson, M. C., Xue, Q.-L., Zhou, J., & Fried, L. P. (2009). Executive decline and dysfunction precedes declines in memory: the women’s health and aging study II. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 64(1), 110–117.CrossRefGoogle Scholar
  8. Carmichael, O., Mungas, D., Beckett, L., Harvey, D., Farias, S. T., Reed, B., Olichney, J., Miller, J., & DeCarli, C. (2012). MRI predictors of cognitive change in a diverse and carefully characterized elderly population. Neurobiology of Aging, 33(1), 83–95.CrossRefPubMedGoogle Scholar
  9. Cherbuin, N., Anstey, K. J., Réglade-Meslin, C., & Sachdev, P. S. (2009). In vivo hippocampal measurement and memory: a comparison of manual tracing and automated segmentation in a large community-based sample. PLoS One, 4(4), e5265.CrossRefPubMedPubMedCentralGoogle Scholar
  10. Clark, M. S., Dennerstein, L., Elkadi, S., Guthrie, J. R., Bowden, S. C., & Henderson, V. W. (2004a). Normative data for tasks of executive function and working memory for Australian-born women aged 56–67. Australian Psychologist, 39(3), 244–250.CrossRefGoogle Scholar
  11. Clark, M. S., Dennerstein, L., Elkadi, S., Guthrie, J. R., Bowden, S. C., & Henderson, V. W. (2004b). Normative verbal and non-verbal memory test scores for Australian women aged 56–67. Australian and New Zealand Journal of Psychiatry, 38(7), 532–540.PubMedGoogle Scholar
  12. Cover, K. S., van Schijndel, R. A., van Dijk, B. W., Redolfi, A., Knol, D. L., Frisoni, G. B., Barkhof, F., Vrenken, H., & Initiative, A.s.D.N. (2011). Assessing the reproducibility of the SienaX and Siena brain atrophy measures using the ADNI back-to-back MP-RAGE MRI scans. Psychiatry Research: Neuroimaging, 193(3), 182–190.CrossRefPubMedGoogle Scholar
  13. Crivello, F., Tzourio-Mazoyer, N., Tzourio, C., & Mazoyer, B. (2014). Longitudinal assessment of global and regional rate of grey matter atrophy in 1,172 healthy older adults: modulation by sex and age. PLoS One, 9(12), e114478.CrossRefPubMedPubMedCentralGoogle Scholar
  14. Davatzikos, C., & Bryan, R. N. (1996). Using a deformable surface model to obtain a shape representation of the cortex. Medical Imaging, IEEE Transactions on, 15(6), 785–795.CrossRefGoogle Scholar
  15. Delis, D. C., Kramer, J. H., Kaplan, E., & Ober, B. A. (1987). CVLT, California verbal learning test: adult version: manual. San Antonio: Psychological Corporation.Google Scholar
  16. den Heijer, T., van der Lijn, F., Koudstaal, P. J., Hofman, A., van der Lugt, A., Krestin, G. P., Niessen, W. J., & Breteler, M. M. (2010). A 10-year follow-up of hippocampal volume on magnetic resonance imaging in early dementia and cognitive decline. Brain, 133(4), 1163–1172.CrossRefGoogle Scholar
  17. Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., Buckner, R. L., Dale, A. M., Maguire, R. P., & Hyman, B. T. (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage, 31(3), 968–980.CrossRefPubMedGoogle Scholar
  18. Destrieux, C., Fischl, B., Dale, A., & Halgren, E. (2010). Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature. NeuroImage, 53(1), 1–15.CrossRefPubMedPubMedCentralGoogle Scholar
  19. Driscoll, I., Davatzikos, C., An, Y., Wu, X., Shen, D., Kraut, M., & Resnick, S. (2009). Longitudinal pattern of regional brain volume change differentiates normal aging from MCI. Neurology, 72(22), 1906–1913.CrossRefPubMedPubMedCentralGoogle Scholar
  20. Duarte, A., Hayasaka, S., Du, A., Schuff, N., Jahng, G.-H., Kramer, J., Miller, B., & Weiner, M. (2006). Volumetric correlates of memory and executive function in normal elderly, mild cognitive impairment and Alzheimer’s disease. Neuroscience Letters, 406(1), 60–65.CrossRefPubMedPubMedCentralGoogle Scholar
  21. Durand-Dubief, F., Belaroussi, B., Armspach, J., Dufour, M., Roggerone, S., Vukusic, S., Hannoun, S., Sappey-Marinier, D., Confavreux, C., & Cotton, F. (2012). Reliability of longitudinal brain volume loss measurements between 2 sites in patients with multiple sclerosis: comparison of 7 quantification techniques. American Journal of Neuroradiology, 33(10), 1918–1924.CrossRefPubMedGoogle Scholar
  22. Elkadi, S., Clark, M. S., Dennerstein, L., Guthrie, J. R., Bowden, S. C., & Henderson, V. W. (2006a). Normative data for Australian midlife women on category fluencyand a short form of the Boston naming test. Australian Psychologist, 41(1), 37–42.CrossRefGoogle Scholar
  23. Elkadi, S., Clark, M. S., Dennerstein, L., Guthrie, J. R., Bowden, S. C., & Henderson, V. W. (2006b). Normative visuospatial performance in Australian midlife women. Australian Psychologist, 41(1), 43–47.CrossRefGoogle Scholar
  24. Farzan, A., Mashohor, S., Ramli, A. R., & Mahmud, R. (2015). Boosting diagnosis accuracy of Alzheimer’s disease using high dimensional recognition of longitudinal brain atrophy patterns. Behavioural Brain Research, 290, 124–130.CrossRefPubMedGoogle Scholar
  25. Fischl, B. (2012). FreeSurfer. NeuroImage, 62(2), 774–781.CrossRefPubMedPubMedCentralGoogle Scholar
  26. Fischl, B., Sereno, M. I., & Dale, A. M. (1999). Cortical surface-based analysis: II: inflation, flattening, and a surface-based coordinate system. NeuroImage, 9(2), 195–207.CrossRefPubMedGoogle Scholar
  27. Fischl, B., van der Kouwe, A., Destrieux, C., Halgren, E., Ségonne, F., Salat, D. H., Busa, E., Seidman, L. J., Goldstein, J., & Kennedy, D. (2004). Automatically parcellating the human cerebral cortex. Cerebral Cortex, 14(1), 11–22.CrossRefPubMedGoogle Scholar
  28. Fjell, A. M., Walhovd, K. B., Fennema-Notestine, C., McEvoy, L. K., Hagler, D. J., Holland, D., Brewer, J. B., & Dale, A. M. (2009). One-year brain atrophy evident in healthy aging. The Journal of Neuroscience, 29(48), 15223–15231.CrossRefPubMedPubMedCentralGoogle Scholar
  29. Fjell, A. M., Sneve, M. H., Storsve, A. B., Grydeland, H., Yendiki, A., & Walhovd, K. B. (2015). Brain events underlying episodic memory changes in aging: a longitudinal investigation of structural and functional connectivity. Cerebral Cortex, 26(3), 1272–1286.CrossRefPubMedPubMedCentralGoogle Scholar
  30. Fleischman, D. A., Yu, L., Arfanakis, K., Han, S. D., Barnes, L. L., Arvanitakis, Z., Boyle, P. A., & Bennett, D. A. (2013). Faster cognitive decline in the years prior to MR imaging is associated with smaller hippocampal volumes in cognitively healthy older persons. Frontiers in Aging Neuroscience, 5, 21.CrossRefPubMedPubMedCentralGoogle Scholar
  31. Frisoni, G. B., Fox, N. C., Jack, C. R., Scheltens, P., & Thompson, P. M. (2010). The clinical use of structural MRI in Alzheimer disease. Nature Reviews Neurology, 6(2), 67–77.CrossRefPubMedPubMedCentralGoogle Scholar
  32. Guo, J., Isohanni, M., Miettunen, J., Jääskeläinen, E., Kiviniemi, V., Nikkinen, J., Remes, J., Huhtaniska, S., Veijola, J., & Jones, P. (2016). Brain structural changes in women and men during midlife. Neuroscience Letters, 615, 107–112.CrossRefPubMedPubMedCentralGoogle Scholar
  33. Hackert, V., den Heijer, T., Oudkerk, M., Koudstaal, P., Hofman, A., & Breteler, M. (2002). Hippocampal head size associated with verbal memory performance in nondemented elderly. NeuroImage, 17(3), 1365–1372.CrossRefPubMedGoogle Scholar
  34. Henneman, W., Sluimer, J., Barnes, J., Van Der Flier, W., Sluimer, I., Fox, N., Scheltens, P., Vrenken, H., & Barkhof, F. (2009). Hippocampal atrophy rates in Alzheimer disease added value over whole brain volume measures. Neurology, 72(11), 999–1007.CrossRefPubMedPubMedCentralGoogle Scholar
  35. Hua, X., Hibar, D. P., Lee, S., Toga, A. W., Jack, C. R., Weiner, M. W., Thompson, P. M., & Initiative, A.s.D.N. (2010). Sex and age differences in atrophic rates: an ADNI study with n= 1368 MRI scans. Neurobiology of Aging, 31(8), 1463–1480.CrossRefPubMedPubMedCentralGoogle Scholar
  36. Jack, C., Shiung, M., Weigand, S., O’Brien, P., Gunter, J., Boeve, B., Knopman, D., Smith, G., Ivnik, R., & Tangalos, E. (2005). Brain atrophy rates predict subsequent clinical conversion in normal elderly and amnestic MCI. Neurology, 65(8), 1227–1231.CrossRefPubMedPubMedCentralGoogle Scholar
  37. Johnson, J. K., Lui, L.-Y., & Yaffe, K. (2007). Executive function, more than global cognition, predicts functional decline and mortality in elderly women. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 62(10), 1134–1141.CrossRefPubMedCentralGoogle Scholar
  38. Johnson, K. A., Fox, N. C., Sperling, R. A., & Klunk, W. E. (2012). Brain imaging in Alzheimer disease. Cold Spring Harbor Perspectives in Medicine, 2(4), a006213.CrossRefPubMedPubMedCentralGoogle Scholar
  39. Kramer, J. H., Mungas, D., Reed, B. R., Wetzel, M. E., Burnett, M. M., Miller, B. L., Weiner, M. W., & Chui, H. C. (2007). Longitudinal MRI and cognitive change in healthy elderly. Neuropsychology, 21(4), 412–418.CrossRefPubMedPubMedCentralGoogle Scholar
  40. Lemaitre, H., Goldman, A. L., Sambataro, F., Verchinski, B. A., Meyer-Lindenberg, A., Weinberger, D. R., & Mattay, V. S. (2012). Normal age-related brain morphometric changes: nonuniformity across cortical thickness, surface area and gray matter volume? Neurobiology of Aging, 33(3), 617. e1–617. e9.CrossRefGoogle Scholar
  41. Maclaren, J., Han, Z., Vos, S. B., Fischbein, N., & Bammer, R. (2014). Reliability of brain volume measurements: a test-retest dataset. Scientific Data, 1, 140037.CrossRefPubMedPubMedCentralGoogle Scholar
  42. Maillet, D., & Rajah, M. N. (2013). Association between prefrontal activity and volume change in prefrontal and medial temporal lobes in aging and dementia: a review. Ageing Research Reviews, 12(2), 479–489.CrossRefPubMedGoogle Scholar
  43. Mak, E., Su, L., Williams, G. B., Watson, R., Firbank, M., Blamire, A. M., & O’Brien, J. T. (2015). Longitudinal assessment of global and regional atrophy rates in Alzheimer’s disease and dementia with Lewy bodies. NeuroImage: Clinical, 7, 456–462.CrossRefGoogle Scholar
  44. McDonald, C. R., Gharapetian, L., McEvoy, L. K., Fennema-Notestine, C., Hagler, D. J., Holland, D., Dale, A. M., & Initiative, A.s.D.N. (2012). Relationship between regional atrophy rates and cognitive decline in mild cognitive impairment. Neurobiology of Aging, 33(2), 242–253.CrossRefPubMedGoogle Scholar
  45. Morey, R. A., Petty, C. M., Xu, Y., Hayes, J. P., Wagner, H. R., Lewis, D. V., LaBar, K. S., Styner, M., & McCarthy, G. (2009). A comparison of automated segmentation and manual tracing for quantifying hippocampal and amygdala volumes. NeuroImage, 45(3), 855–866.CrossRefPubMedGoogle Scholar
  46. Morey, R. A., Selgrade, E. S., Wagner, H. R., Huettel, S. A., Wang, L., & McCarthy, G. (2010). Scan–rescan reliability of subcortical brain volumes derived from automated segmentation. Human Brain Mapping, 31(11), 1751–1762.PubMedPubMedCentralGoogle Scholar
  47. Morrison, J. H., & Baxter, M. G. (2012). The ageing cortical synapse: hallmarks and implications for cognitive decline. Nature Reviews Neuroscience, 13(4), 240–250.CrossRefPubMedPubMedCentralGoogle Scholar
  48. Mungas, D., Harvey, D., Reed, B., Jagust, W., DeCarli, C., Beckett, L., Mack, W., Kramer, J., Weiner, M., & Schuff, N. (2005). Longitudinal volumetric MRI change and rate of cognitive decline. Neurology, 65(4), 565–571.CrossRefPubMedPubMedCentralGoogle Scholar
  49. Nyberg, L., Lövdén, M., Riklund, K., Lindenberger, U., & Bäckman, L. (2012). Memory aging and brain maintenance. Trends in Cognitive Sciences, 16(5), 292–305.CrossRefPubMedGoogle Scholar
  50. Oosterman, J. M., Vogels, R. L., van Harten, B., Gouw, A. A., Scheltens, P., Poggesi, A., Weinstein, H. C., & Scherder, E. J. (2008). The role of white matter hyperintensities and medial temporal lobe atrophy in age-related executive dysfunctioning. Brain and Cognition, 68(2), 128–133.CrossRefPubMedGoogle Scholar
  51. Papp, K. V., Kaplan, R. F., Springate, B., Moscufo, N., Wakefield, D. B., Guttmann, C. R., & Wolfson, L. (2014). Processing speed in normal aging: effects of white matter hyperintensities and hippocampal volume loss. Aging, Neuropsychology, and Cognition, 21(2), 197–213.CrossRefGoogle Scholar
  52. Persson, J., Pudas, S., Lind, J., Kauppi, K., Nilsson, L.-G., & Nyberg, L. (2012). Longitudinal structure–function correlates in elderly reveal MTL dysfunction with cognitive decline. Cerebral Cortex, 22(10), 2297–2304.CrossRefPubMedGoogle Scholar
  53. Raz, N., Lindenberger, U., Rodrigue, K. M., Kennedy, K. M., Head, D., Williamson, A., Dahle, C., Gerstorf, D., & Acker, J. D. (2005). Regional brain changes in aging healthy adults: general trends, individual differences and modifiers. Cerebral Cortex, 15(11), 1676–1689.CrossRefPubMedGoogle Scholar
  54. Rémy, F., Mirrashed, F., Campbell, B., & Richter, W. (2005). Verbal episodic memory impairment in Alzheimer’s disease: a combined structural and functional MRI study. NeuroImage, 25(1), 253–266.CrossRefPubMedGoogle Scholar
  55. Resnick, S. M., Pham, D. L., Kraut, M. A., Zonderman, A. B., & Davatzikos, C. (2003). Longitudinal magnetic resonance imaging studies of older adults: a shrinking brain. Society for Neuroscience, 23(8), 3295–3301.Google Scholar
  56. Reuter, M., Schmansky, N. J., Rosas, H. D., & Fischl, B. (2012). Within-subject template estimation for unbiased longitudinal image analysis. NeuroImage, 61(4), 1402–1418.CrossRefPubMedPubMedCentralGoogle Scholar
  57. Rusinek, H., De Santi, S., Frid, D., Tsui, W.-H., Tarshish, C. Y., Convit, A., & de Leon, M. J. (2003). Regional brain atrophy rate predicts future cognitive decline: 6-year longitudinal MR imaging study of normal aging 1. Radiology, 229(3), 691–696.CrossRefPubMedGoogle Scholar
  58. Schmidt, R., Ropele, S., Enzinger, C., Petrovic, K., Smith, S., Schmidt, H., Matthews, P. M., & Fazekas, F. (2005). White matter lesion progression, brain atrophy, and cognitive decline: the Austrian stroke prevention study. Annals of Neurology, 58(4), 610–616.CrossRefPubMedGoogle Scholar
  59. Sluimer, J. D., van der Flier, W. M., Karas, G. B., Fox, N. C., Scheltens, P., Barkhof, F., & Vrenken, H. (2008). Whole-brain atrophy rate and cognitive decline: longitudinal MR study of memory clinic patients 1. Radiology, 248(2), 590–598.CrossRefPubMedGoogle Scholar
  60. Smith, S. M., Zhang, Y., Jenkinson, M., Chen, J., Matthews, P., Federico, A., & De Stefano, N. (2002). Accurate, robust, and automated longitudinal and cross-sectional brain change analysis. NeuroImage, 17(1), 479–489.CrossRefPubMedGoogle Scholar
  61. Smith, S. M., Rao, A., De Stefano, N., Jenkinson, M., Schott, J. M., Matthews, P. M., & Fox, N. C. (2007). Longitudinal and cross-sectional analysis of atrophy in Alzheimer’s disease: cross-validation of BSI, SIENA and SIENAX. NeuroImage, 36(4), 1200–1206.CrossRefPubMedGoogle Scholar
  62. Söderlund, H., Nyberg, L., & Nilsson, L. G. (2004). Cerebral atrophy as predictor of cognitive function in old, community-dwelling individuals. Acta Neurologica Scandinavica, 109(6), 398–406.CrossRefPubMedGoogle Scholar
  63. Szoeke, C. E. I., Robertson, J. S., Rowe, C. C., Yates, P., Campbell, K., Masters, C. L., Ames, D., Dennerstein, L., & Desmond, P. (2013). The women’s healthy ageing project: fertile ground for investigation of healthy participants ‘at risk’ for dementia. International Review of Psychiatry, 25(6), 726–737.CrossRefPubMedGoogle Scholar
  64. Szoeke, C., Coulson, M., Campbell, S., & Dennerstein, L. (2016). Cohort profile: women’s healthy ageing project (WHAP)-a longitudinal prospective study of Australian women since 1990. Women’s Midlife Health, 2(1), 5.CrossRefGoogle Scholar
  65. Takao, H., Hayashi, N., & Ohtomo, K. (2011). Effect of scanner in longitudinal studies of brain volume changes. Journal of Magnetic Resonance Imaging, 34(2), 438–444.CrossRefPubMedGoogle Scholar
  66. Takao, H., Hayashi, N., & Ohtomo, K. (2012). A longitudinal study of brain volume changes in normal aging. European Journal of Radiology, 81(10), 2801–2804.CrossRefPubMedGoogle Scholar
  67. Tisserand, D. J., Van Boxtel, M. P., Pruessner, J. C., Hofman, P., Evans, A. C., & Jolles, J. (2004). A voxel-based morphometric study to determine individual differences in gray matter density associated with age and cognitive change over time. Cerebral Cortex, 14(9), 966–973.CrossRefPubMedGoogle Scholar
  68. Tupler, L. A., Krishnan, K. R. R., Greenberg, D. L., Marcovina, S. M., Payne, M. E., MacFall, J. R., Charles, H. C., & Doraiswamy, P. M. (2007). Predicting memory decline in normal elderly: genetics, MRI, and cognitive reserve. Neurobiology of Aging, 28(11), 1644–1656.CrossRefPubMedGoogle Scholar
  69. Van Petten, C. (2004). Relationship between hippocampal volume and memory ability in healthy individuals across the lifespan: review and meta-analysis. Neuropsychologia, 42(10), 1394–1413.CrossRefPubMedGoogle Scholar
  70. Van Petten, C., Plante, E., Davidson, P. S., Kuo, T. Y., Bajuscak, L., & Glisky, E. L. (2004). Memory and executive function in older adults: relationships with temporal and prefrontal gray matter volumes and white matter hyperintensities. Neuropsychologia, 42(10), 1313–1335.CrossRefPubMedGoogle Scholar
  71. Welsh, K. A., Butters, N., Mohs, R. C., Beekly, D., Edland, S., Fillenbaum, G., & Heyman, A. (1994). The consortium to establish a registry for Alzheimer’s disease (CERAD). Part V. A normative study of the neuropsychological battery. Neurology, 44(4), 609–614.CrossRefPubMedGoogle Scholar
  72. Wenger, E., Mårtensson, J., Noack, H., Bodammer, N. C., Kühn, S., Schaefer, S., Heinze, H. J., Düzel, E., Bäckman, L., & Lindenberger, U. (2014). Comparing manual and automatic segmentation of hippocampal volumes: reliability and validity issues in younger and older brains. Human Brain Mapping, 35(8), 4236–4248.CrossRefPubMedGoogle Scholar
  73. Westman, E., Aguilar, C., Muehlboeck, J.-S., & Simmons, A. (2013). Regional magnetic resonance imaging measures for multivariate analysis in Alzheimer’s disease and mild cognitive impairment. Brain Topography, 26(1), 9–23.CrossRefPubMedGoogle Scholar
  74. Wilson, R. S., Li, Y., Bienias, L., & Bennett, D. A. (2006). Cognitive decline in old age: separating retest effects from the effects of growing older. Psychology and Aging, 21(4), 774–789.CrossRefPubMedGoogle Scholar
  75. Yavuz, B. B., Ariogul, S., Cankurtaran, M., Oguz, K. K., Halil, M., Dagli, N., & Cankurtaran, E. S. (2007). Hippocampal atrophy correlates with the severity of cognitive decline. International Psychogeriatrics, 19(04), 767–777.CrossRefPubMedGoogle Scholar
  76. Ystad, M. A., Lundervold, A. J., Wehling, E., Espeseth, T., Rootwelt, H., Westlye, L. T., Andersson, M., Adolfsdottir, S., Geitung, J. T., & Fjell, A. M. (2009). Hippocampal volumes are important predictors for memory function in elderly women. BioMed Central Ltd, 9, 17.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Rowa Aljondi
    • 1
  • Cassandra Szoeke
    • 2
    • 3
    Email author
  • Chris Steward
    • 1
  • Paul Yates
    • 4
  • Patricia Desmond
    • 1
  1. 1.Department of RadiologyThe University of Melbourne, Royal Melbourne HospitalParkvilleAustralia
  2. 2.Department of Medicine (Royal Melbourne Hospital)The University of MelbourneParkvilleAustralia
  3. 3.Institute for Health and AgeingAustralian Catholic UniversityMelbourneAustralia
  4. 4.Aged Care Services DepartmentAustin HealthHeidelbergAustralia

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