ArticleFrontiers in aging neuroscience2016
Statistical Approaches for the Study of Cognitive and Brain Aging.
Article in Frontiers in aging neuroscience, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Statistical Methods in Aging Research: Improving Current Practices and Embracing Emerging Approaches.Annual review of statistics and its application · 2026Article
- Interpretable machine learning for precision cognitive aging.Frontiers in computational neuroscience · 2025Article
- Longitudinal changes in brain-derived neurotrophic factor (BDNF) but not cytokines contribute to hippocampal recovery in anorexia nervosa above increases in body mass index.Psychological medicine · 2024Article
- A Subtype Perspective on Cognitive Trajectories in Healthy Aging.Brain sciences · 2024Article
- Differential longitudinal changes of hippocampal subfields in patients with anorexia nervosa.Psychiatry and clinical neurosciences · 2024Article
- Differential alterations of amygdala nuclei volumes in acutely ill patients with anorexia nervosa and their associations with leptin levels.Psychological medicine · 2023Article
- Toward precision medicine using a "digital twin" approach: modeling the onset of disease-specific brain atrophy in individuals with multiple sclerosis.Scientific reports · 2023Article
- Toward Precision Medicine Using a "Digital Twin" Approach: Modeling the Onset of Disease-Specific Brain Atrophy in Individuals with Multiple Sclerosis.Research square · 2023Article
- Medial Temporal Lobe Subregional Atrophy in Aging and Alzheimer's Disease: A Longitudinal Study.Frontiers in aging neuroscience · 2021Article
- Multi-scale network regression for brain-phenotype associations.Human brain mapping · 2020Article
- Proper timing for the evaluation of neonatal brain white matter development: a diffusion tensor imaging study.European radiology · 2019Article
- Age dependency of risk factors for cognitive decline.BMC geriatrics · 2018Article
- Cognitive Aging and the Hippocampus in Older Adults.Frontiers in aging neuroscience · 2016Article
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7 authors.
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Abstract
Neuroimaging studies of cognitive and brain aging often yield massive datasets that create many analytic and statistical challenges. In this paper, we discuss and address several limitations in the existing work. (1) Linear models are often used to model the age effects on neuroimaging markers, which may be inadequate in capturing the potential nonlinear age effects. (2) Marginal correlations are often used in brain network analysis, which are not efficient in characterizing a complex brain network. (3) Due to the challenge of high-dimensionality, only a small subset of the regional neuroimaging markers is considered in a prediction model, which could miss important regional markers. To overcome those obstacles, we introduce several advanced statistical methods for analyzing data from cognitive and brain aging studies. Specifically, we introduce semiparametric models for modeling age effects, graphical models for brain network analysis, and penalized regression methods for selecting the most important markers in predicting cognitive outcomes. We illustrate these methods using the healthy aging data from the Active Brain Study.
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