Cited by 271Dementia and Cognitive Impairment ResearchCognitive Abilities and TestingNeural and Behavioral Psychology Studies

A voxel-based morphometric study to determine individual differences in gray matter density associated with age and cognitive change over time

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Tisserand, D. J.·2004·Cerebral Cortex

Abstract

Voxel-based morphometry (VBM) was used to examine the relation between age and gray matter density cross-sectionally and to study the association between gray matter density and longitudinal decline in performance on cognitive tests in healthy, non-demented elderly individuals. Participants were neuropsychologically tested at baseline and again after 3 years. Thirty-seven subjects (mean age 72.5 years) who showed a decline in cognitive test performance at follow-up were compared with 38 individually matched control subjects (mean age 71.8 years) whose performance did not change over time. Magnetic resonance imaging scans were acquired at follow-up and individual differences in regional gray matter density were examined with VBM. The largest age effects were found in various regions in the prefrontal cortex, the (medial) temporal lobes and the striate cortex. Longitudinal cognitive decline was associated with decreased gray matter density in prefrontal areas, the (medial) temporal lobes and the posterior parietal cortex. These findings suggest that prefrontal and temporal cortical regions are of particular relevance both in aging and age-related cognitive decline in healthy elderly individuals.

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  • Studies using ROI or VBM have yielded contradictory results regarding whether the hippocampus is preserved or deteriorates with aging.

    “In spite of the objectivity of this method, studies led to somewhat contradictory results regarding the hippocampus: some authors have found this structure to be preserved with aging [29,31], whereas others have reported structural deterioration [38,81,84,87].”

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Research works printed but not linked: 3

  1. Collins DL, Evans AC (1999) ANIMAL: automatic nonlinear image matching and anatomical labeling. In: Brain warping (Toga AW, ed.), pp. 133-142. San Diego, CA: Academic Press.
  2. De Bie SE (1987) Standaardvragen 1987: Voorstellen voor unifor- mering van vraagstellingen naar achtergrondkenmerken en inter- views [Standard questions 1987: proposal for uniformisation of questions regarding background variables and interviews], 2nd edn. Leiden, The Netherlands: Leiden University Press.
  3. Evans AC, Collins DL, Holmes CJ (1996) Computational approaches to quantifying human neuroanatomical variability. In: Brain mapping: the methods (Toga AW, Mazziotta JC, eds), pp. 343-361. San Diego, CA: Academic Press.

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Authors
Tisserand, D. J.
Affiliations
Baycrest Centre for Geriatric Care (CA)
Corresponding author
Tisserand, D. J.
Venue
Cerebral Cortex
Published
2004-04-27
Volume
14
Issue
9
Pages
966-973
ISSN
  • 1047-3211 (ISSN-L)
  • 1460-2199
OpenAlex
W2105250545
Cited by
271
References
62
Citations by year
2025: 1 · 2024: 7 · 2023: 11 · 2022: 9 · 2021: 7 · 2020: 5 · 2019: 14 · 2018: 16 · 2017: 11 · 2016: 14 · 2015: 14 · 2014: 15 · 2013: 14 · 2012: 15
FWCI
9.33
Type
journal article
Language
en
Open access
Locations
  • Cerebral Cortex (publishedVersion)
  • PubMed (publishedVersion)
  • Research Publications (Maastricht University) (publishedVersion, other-oa)
  • Research Publications (Maastricht University) (submittedVersion, other-oa)
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
Keywords
gray matter density, brain aging, age-related cognitive decline, healthy older adults, prefrontal cortex, medial temporal lobe, posterior parietal cortex, longitudinal cognitive change, individual differences, neuroimaging of aging
MeSH terms
Adult, Aged, Aged, 80 and over, Aging, Cerebral Cortex, Cognition, Female, Humans, Individuality, Magnetic Resonance Imaging, Male, Middle Aged, Time Factors, Chi-Square Distribution, Linear Models, Statistics, Nonparametric

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