ArticleNeurobiology of aging2015
Cross-sectional versus longitudinal estimates of age-related changes in the adult brain: overlaps and discrepancies.
Article in Neurobiology of aging, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 2 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
42 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Age-related differences in hippocampal subfield volumes across the human lifespan: A meta-analysis.Hippocampus · 2023Pooled it
- Genetic variants associated with longitudinal changes in brain structure across the lifespan.Nature neuroscience · 2022Pooled it
- Long-Term Effects of a 5-Year Randomized Controlled Exercise Trial on Brain Volumes and Cognitive Function in Older Adults: A 4-Year Post-Intervention Follow-Up Study.Sports medicine (Auckland, N.Z.) · 2026Trial
- Trial
- Long-term reliability and stability of parameterized resting state EEG: evidence from a five-year follow-up.Cerebral cortex (New York, N.Y. : 1991) · 2026Article
- Cerebellar growth is associated with domain-specific cerebral maturation and socio-linguistic behavior.Nature communications · 2026Article
- Cortical mean diffusivity detects early age-related changes and associates with cognition and plasma biomarkers.Brain communications · 2026Article
- Mesoscale connectivity of the human hippocampus and fimbria revealed by ex vivo diffusion MRI.NeuroImage · 2025Article
- Early-Life Adversity Predicts Markers of Aging-Related Neuroinflammation, Neurodegeneration, and Cognitive Impairment in Women.Annals of neurology · 2025Article
- Computational memory capacity predicts aging and cognitive decline.Nature communications · 2025Article
- Review
- Harnessing BDNF Signaling to Promote Resilience in Aging.Aging and disease · 2024Review
- Revisiting adolescence as a sensitive period for sociocultural processing.Neuroscience and biobehavioral reviews · 2024Review
- DAT1 and BDNF polymorphisms interact to predict Aβ and tau pathology.Neurobiology of aging · 2024Article
- Characterization of Brain Volume Changes in Aging Individuals With Normal Cognition Using Serial Magnetic Resonance Imaging.JAMA network open · 2023Article
- Brain volumetrics across the lifespan of the rhesus macaque.Neurobiology of aging · 2023Article
- Traumatic stress load and stressor reactivity score associated with accelerated gray matter maturation in youths indexed by normative models.Molecular psychiatry · 2023Article
- Greater cognitive reserve is related to lower cortical excitability in healthy cognitive aging, but not in early clinical Alzheimer's disease.Frontiers in human neuroscience · 2023Article
- Modular community structure of the face network supports face recognition.Cerebral cortex (New York, N.Y. : 1991) · 2022Article
- The MRi-Share database: brain imaging in a cross-sectional cohort of 1870 university students.Brain structure & function · 2021Article
Corrections and comments
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2 authors.
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Abstract
The healthy adult brain undergoes tissue volume decline with age, but contradictory findings abound regarding rate of change. To identify a source of this discrepancy, we present contrasting statistical approaches to estimate hippocampal volume change with age based on 200 longitudinally-acquired magnetic resonance imaging in 70 healthy adults, age 20-70 years, who had 2-5 magnetic resonance imaging collected over 6 months to 8 years. Linear mixed-effects modeling using volume trajectories over age for each subject revealed significantly negative slopes with aging after a linear decline with a suggestion of acceleration in older individuals. By contrast, general linear modeling using either the first observation only of each subject or all observations treated independently (thereby disregarding trajectories) indicated no significant correlation between volume and age. Entering a quadratic term into the linear model yielded a biologically plausible function that was not supported by longitudinal analysis. The results underscore the importance of analyses that incorporate the trajectory of individuals in the study of brain aging.
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