ArticlePloS one2013
Variance in brain volume with advancing age: implications for defining the limits of normality.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 22 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed.
- ComBatLS: A Location- and Scale-Preserving Method for Multi-Site Image Harmonization.Human brain mapping · 2025Article
- ComBatLS: A location- and scale-preserving method for multi-site image harmonization.bioRxiv : the preprint server for biology · 2024Article
- Personalized estimates of brain cortical structural variability in individuals with Autism spectrum disorder: the predictor of brain age and neurobiology relevance.Molecular autism · 2023Article
- Turning Back the Clock: A Retrospective Single-Blind Study on Brain Age Change in Response to Nutraceuticals Supplementation vs. Lifestyle Modifications.Brain sciences · 2023Article
- Dimensions of cognitive reserve and their predictive power of cognitive performance and decline in the elderly.Frontiers in dementia · 2023Article
- Characterization of the angular gyrus in an older adult population: a multimodal multilevel approach.Brain structure & function · 2023Article
- Age-related brain atrophy is not a homogenous process: Different functional brain networks associate differentially with aging and blood factors.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years.Human brain mapping · 2022Article
- Resting-state networks in the course of aging-differential insights from studies across the lifespan vs. amongst the old.Pflugers Archiv : European journal of physiology · 2021Review
- When your brain looks older than expected: combined lifestyle risk and BrainAGE.Brain structure & function · 2021Article
- Non-parametric MRI Brain Atlas for the Polish Population.Frontiers in neuroinformatics · 2021Article
- Generalizing Longitudinal Age Effects on Brain Structure - A Two-Study Comparison Approach.Frontiers in human neuroscience · 2021Article
- Generalizing age effects on brain structure and cognition: A two-study comparison approach.Human brain mapping · 2019Article
- Person-Based Brain Morphometric Similarity is Heritable and Correlates With Biological Features.Cerebral cortex (New York, N.Y. : 1991) · 2019Article
- Brain structural differences between 73- and 92-year olds matched for childhood intelligence, social background, and intracranial volume.Neurobiology of aging · 2018Article
- Article
- ENIGMA and the individual: Predicting factors that affect the brain in 35 countries worldwide.NeuroImage · 2017Review
- Whole Brain Magnetic Resonance Image Atlases: A Systematic Review of Existing Atlases and Caveats for Use in Population Imaging.Frontiers in neuroinformatics · 2017Review
- A Complex Interplay of Vitamin B1 and B6 Metabolism with Cognition, Brain Structure, and Functional Connectivity in Older Adults.Frontiers in neuroscience · 2017Article
- Statistical estimation of physiological brain age as a descriptor of senescence rate during adulthood.Brain imaging and behavior · 2015Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors.
Funding
Abstract
backgroundStatistical models of normal ageing brain tissue volumes may support earlier diagnosis of increasingly common, yet still fatal, neurodegenerative diseases. For example, the statistically defined distribution of normal ageing brain tissue volumes may be used as a reference to assess patient volumes. To date, such models were often derived from mean values which were assumed to represent the distributions and boundaries, i.e. percentile ranks, of brain tissue volume. Since it was previously unknown, the objective of the present study was to determine if this assumption was robust, i.e. whether regression models derived from mean values accurately represented the distributions and boundaries of brain tissue volume at older ages. MATERIALS AND
methodsWe acquired T1-w magnetic resonance (MR) brain images of 227 normal and 219 Alzheimer's disease (AD) subjects (aged 55-89 years) from publicly available databanks. Using nonlinear regression within both samples, we compared mean and percentile rank estimates of whole brain tissue volume by age.
resultsIn both the normal and AD sample, mean regression estimates of brain tissue volume often did not accurately represent percentile rank estimates (errors=-74% to 75%). In the normal sample, mean estimates generally underestimated differences in brain volume at percentile ranks below the mean. Conversely, in the AD sample, mean estimates generally underestimated differences in brain volume at percentile ranks above the mean. Differences between ages at the 5(th) percentile rank of normal subjects were ~39% greater than mean differences in the AD subjects.
conclusionsWhile more data are required to make true population inferences, our results indicate that mean regression estimates may not accurately represent the distributions of ageing brain tissue volumes. This suggests that percentile rank estimates will be required to robustly define the limits of brain tissue volume in normal ageing and neurodegenerative disease.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.