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Regional Brain Changes in Aging Healthy Adults: General Trends, Individual Differences and Modifiers
Open accessAbstract
Brain aging research relies mostly on cross-sectional studies, which infer true changes from age differences. We present longitudinal measures of five-year change in the regional brain volumes in healthy adults. Average and individual differences in volume changes and the effects of age, sex and hypertension were assessed with latent difference score modeling. The caudate, the cerebellum, the hippocampus and the association cortices shrunk substantially. There was minimal change in the entorhinal and none in the primary visual cortex. Longitudinal measures of shrinkage exceeded cross-sectional estimates. All regions except the inferior parietal lobule showed individual differences in change. Shrinkage of the cerebellum decreased from young to middle adulthood, and increased from middle adulthood to old age. Shrinkage of the hippocampus, the entorhinal cortices, the inferior temporal cortex and the prefrontal white matter increased with age. Moreover, shrinkage in the hippocampus and the cerebellum accelerated with age. In the hippocampus, both linear and quadratic trends in incremental age-related shrinkage were limited to the hypertensive participants. Individual differences in shrinkage correlated across some regions, suggesting common causes. No sex differences in age trends except for the caudate were observed. We found no evidence of neuroprotective effects of larger brain size or educational attainment.
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“Possibly, at some level, the burden of pathology becomes great enough to overcome this protective mechanism, resulting in rapid cognitive decline31,53.”
From Maintenance, reserve and compensation: the cognitive neuroscience of healthy ageing (2018) · cites this paper as [53]
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“Because longitudinal studies show that posterior association regions, e.g., inferior parietal lobule, are just as sensitive to aging as prefrontal regions (Raz et al., 2005)”
From Aging white matter and cognition: Differential effects of regional variations in diffusion properties on memory, executive functions, and speed (2009) · cites this paper as Raz et al., 2005
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“Most have revealed prominent GM loss in prefrontal regions [40,59,65,71,76] with smaller but significant decline in other regions, notably in mesial temporal areas.”
From Voxel-based mapping of brain gray matter volume and glucose metabolism profiles in normal aging (2009) · cites this paper as [65]
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“Although a longitudinal PET-MR combined study would obviously be of considerable interest, the advantage of this approach relative to cross-sectional designs has been occasionally [40,65], but not consistently [27,75], shown.”
From Voxel-based mapping of brain gray matter volume and glucose metabolism profiles in normal aging (2009) · cites this paper as [65]
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Cites
Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975) · Journal of Psychiatric Research · doi:10.1016/0022-3956(75)90026-6 · Cited by 88,282
The CES-D Scale: A Self-Report Depression Scale for Research in the General Population
Radloff, L. S. (1977) · Applied Psychological Measurement · doi:10.1177/014662167700100306 · Cited by 53,267
(1998) · Cited by 36,049
The assessment and analysis of handedness: The Edinburgh inventory
Oldfield, R. C. (1971) · Neuropsychologia · doi:10.1016/0028-3932(71)90067-4 · Cited by 35,900
Intraclass correlations: Uses in assessing rater reliability.
Shrout, P. E., & Fleiss, J. L. (1979) · Psychological Bulletin · doi:10.1037/0033-2909.86.2.420 · Cited by 24,532
Wasserman, S. S., Hedges, L. V., & Olkin, I. (1988) · Journal of Educational Statistics · doi:10.2307/1164953 · Cited by 10,377
Parallel organization of functionally segregated circuits linking basal ganglia and cortex
Alexander, G. E., DeLong, M. R., & Strick, P. L. (1986) · Annual Review of Neuroscience · doi:10.1146/annurev.ne.09.030186.002041 · Cited by 8,527
"General Intelligence," Objectively Determined and Measured
Spearman, C. (1904) · The American Journal of Psychology · doi:10.2307/1412107 · Cited by 6,207
Brain development during childhood and adolescence: a longitudinal MRI study
Giedd, J. N., Blumenthal, J., Jeffries, N. O., Castellanos, F. X., Liu, H., Zijdenbos, A., Paus, T., Evans, A. C., & Rapoport, J. L. (1999) · Nature Neuroscience · doi:10.1038/13158 · Cited by 5,552
Blessed, G., Tomlinson, B. E., & Roth, M. (1968) · British Journal of Psychiatry · doi:10.1192/bjp.114.512.797 · Cited by 4,117
Flagged first, then by citations
Research works printed but not linked: 1
- Hedges L, Olkin I (1985) Statistical methods for meta-analysis. Orlando, FL: Academic Press.
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Lee, J. K., Fandakova, Y., Johnson, E. G., Cohen, N. J., Bunge, S. A., & Ghetti, S. (2020) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2019.100741 · Cited by 70
Understanding the cause of sporadic Alzheimer’s disease
Zetterberg, H., & Mattsson, N. (2014) · Expert Review of Neurotherapeutics · doi:10.1586/14737175.2014.915740 · Cited by 73
Tse, Y. C., Montoya, I., Wong, A. S., Mathieu, A., Lissemore, J., Lagace, D. C., & Wong, T. P. (2014) · Hippocampus · doi:10.1002/hipo.22296 · Cited by 69
Brehmer, Y., Li, S.-C., Straube, B., Stoll, G., von Oertzen, T., Müller, V., & Lindenberger, U. (2008) · Psychology and Aging · doi:10.1037/0882-7974.23.2.227 · Cited by 69
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Age‐related changes in the ease of dynamical transitions in human brain activity
Ezaki, T., Sakaki, M., Watanabe, T., & Masuda, N. (2018) · Human Brain Mapping · doi:10.1002/hbm.24033 · Cited by 55
Albinet, C. T., Mandrick, K., Bernard, P. L., Perrey, S., & Blain, H. (2014) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2014.00272 · Cited by 65
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Mueller, S. G., Ng, P., Neylan, T., Mackin, S., Wolkowitz, O., Mellon, S., Yan, X., Flory, J., Yehuda, R., Marmar, C. R., et al. (2015) · Psychiatry Research: Neuroimaging · doi:10.1016/j.pscychresns.2015.09.006 · Cited by 61
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Santos, A., Resmini, E., Crespo, I., Pires, P., Vives-Gilabert, Y., Granell, E., Valassi, E., Gómez-Anson, B., Martínez-Momblán, M. A., Mataró, M., et al. (2014) · European Journal of Endocrinology · doi:10.1530/eje-14-0371 · Cited by 60
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Willette, A. A., Bendlin, B. B., McLaren, D. G., Canu, E., Kastman, E. K., Kosmatka, K. J., Xu, G., Field, A. S., Alexander, A. L., Colman, R. J., et al. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.03.015 · Cited by 55
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Lim, H. K., Hong, S. C., Jung, W. S., Ahn, K. J., Won, W. Y., Hahn, C., Kim, I. S., & Lee, C. U. (2013) · American Journal of Neuroradiology · doi:10.3174/ajnr.a3293 · Cited by 52
Hypertension is associated with reduced hippocampal connectivity and impaired memory
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Use it and boost it with physical and mental activity.
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Spencer, R. M. C., & Riggins, T. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2123415119 · Cited by 41
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Self-citationWhitman, E. T., Elliott, M. L., Knodt, A. R., Abraham, W. C., Anderson, T. J., Cutfield, N. J., Hogan, S., Ireland, D., Melzer, T. R., Ramrakha, S., et al. (2025) · Nature Aging · doi:10.1038/s43587-025-00897-z · Cited by 37
Zhang, H., Sachdev, P. S., Wen, W., Crawford, J. D., Brodaty, H., Baune, B. T., Kochan, N. A., Slavin, M. J., Reppermund, S., Kang, K., et al. (2016) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2015.10.008 · Cited by 32
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Müller, P., Schmicker, M., & Müller, N. G. (2017) · Zeitschrift für Gerontologie und Geriatrie · doi:10.1007/s00391-017-1202-x · Cited by 25
Structural inequality and temporal brain dynamics across diverse samples
Baez, S., Hernandez, H., Moguilner, S., Cuadros, J., Santamaria‐Garcia, H., Medel, V., Migeot, J., Cruzat, J., Valdes‐Sosa, P. A., Lopera, F., et al. (2024) · Clinical and Translational Medicine · doi:10.1002/ctm2.70032 · Cited by 21
Chisholm, N. C., Packard, A. R., Koss, W. A., & Juraska, J. M. (2012) · Endocrinology · doi:10.1210/en.2012-1412 · Cited by 21
Caloric restriction and aging but not overexpression of SOD1 affect hippocampal volumes in mice
Rutten, B. P. F., Brasnjevic, I., Steinbusch, H. W. M., & Schmitz, C. (2010) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2010.08.002 · Cited by 15
Linnet, E., & Roser, M. E. (2012) · Psychology and Aging · doi:10.1037/a0024905 · Cited by 14
Hausman, H. K., Alexander, G. E., Cohen, R., Marsiske, M., DeKosky, S. T., Hishaw, G. A., O'Shea, A., Kraft, J. N., Dai, Y., Wu, S., et al. (2023) · Brain Stimulation · doi:10.1016/j.brs.2023.05.021 · Cited by 13
Episodic Memory in Healthy Older Adults: The Role of Prefrontal and Parietal Cortices
Rajah, M. N., Maillet, D., & Grady, C. L. (2015) · The Wiley Handbook on the Cognitive Neuroscience of Memory · doi:10.1002/9781118332634.ch17 · Cited by 9
Healthy heart, healthy brain: hypertension affects cognitive functioning in older age
Scullin, M. K., Le, D. T., & Shelton, J. T. (2017) · Translational Issues in Psychological Science · doi:10.1037/tps0000131 · Cited by 11
Heckner, M. K., Cieslik, E. C., Eickhoff, S. B., Camilleri, J. A., Hoffstaedter, F., & Langner, R. (2020) · doi:10.1101/2020.07.15.204941
Metadata
- Authors
- Raz, N., Lindenberger, U., Rodrigue, K. M., Kennedy, K. M., Head, D., Williamson, A., Dahle, C., Gerstorf, D., & Acker, J. D.
- Affiliations
- Wayne State University (US)
- Max Planck Society (DE)
- University of Washington (US)
- University of Memphis (US)
- Baptist Memorial Hospital (US)
- Corresponding author
- Raz, Naftali
- ORCID
- Venue
- Cerebral Cortex
- Publisher
- Oxford University Press (OUP)
- Published
- 2005-02-09
- Volume
- 15
- Issue
- 11
- Pages
- 1676-1689
- ISSN
- 1047-3211 (ISSN-L)
- 1460-2199
- OpenAlex
- W2103069600
- Cited by
- 2,875
- References
- 61
- Citations by year
- 2026: 90 · 2025: 115 · 2024: 138 · 2023: 108 · 2022: 144 · 2021: 198 · 2020: 171 · 2019: 188 · 2018: 170 · 2017: 192 · 2016: 171 · 2015: 172 · 2014: 174 · 2013: 163 · 2012: 139
- FWCI
- 35.53
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Cerebral Cortex (publishedVersion)
- PubMed (publishedVersion)
- Max Planck Institute for Plasma Physics (submittedVersion)
- Max Planck Digital Library (submittedVersion, other-oa)
- MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
- Funders
- Wayne State University
- National Institute on Aging (AG-11230)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Social Sciences › Psychology › Developmental and Educational Psychology › Aging and Gerontology Research
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
- Keywords
- brain aging, individual differences, hippocampus, cerebellum, caudate nucleus, entorhinal cortex, inferior parietal lobule, hypertension, sex differences, educational attainment, neuroprotection, healthy older adults
- MeSH terms
- Adult, Age Factors, Aged, Aged, 80 and over, Aging, Body Constitution, Brain, Female, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Organ Size, Sensitivity and Specificity, Sex Factors, Reproducibility of Results, Imaging, Three-Dimensional
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