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Area of Science:

  • Neuroimaging
  • Neuroscience
  • Aging Research

Background:

  • Inconsistent findings exist regarding age-related gray matter changes from structural MRI studies.
  • Variability may stem from sample size, tissue segmentation, spatial normalization, and statistical modeling.
  • Adjusting for global gray matter volume is crucial for accurate regional analysis.

Purpose of the Study:

  • To investigate the impact of methodological choices on assessing age-related gray matter changes using voxel-based morphometry (VBM).
  • To analyze gray matter volume changes in a large, evenly distributed adult sample (ages 18-77).
  • To compare different global adjustment methods for regional analyses.

Main Methods:

  • Voxel-based morphometry (VBM) applied to structural MRI scans from 420 adults (18-77 years).
  • Improved segmentation using multiple tissue classes and age-appropriate templates.
  • Enhanced registration with DARTEL (diffeomorphic algorithm) over constrained warp.
  • Comparison of global adjustment methods: no adjustment, Local Covariation, Global Scaling, and Local Scaling.

Main Results:

  • Replicated general age-related gray matter decline across the brain, with rapid loss in frontal cortex and central sulcus.
  • Methodological improvements enhanced segmentation and registration accuracy.
  • Global adjustment methods significantly altered regionally-specific age-related decline estimates.
  • Local Covariation explained more age-related variance than Global Scaling on average.

Conclusions:

  • Methodological choices, particularly global adjustment strategies, critically influence VBM findings on aging.
  • Explicitly stating assumptions in VBM analyses is essential for valid inferences.
  • Local Covariation may offer a more robust approach for analyzing age-related gray matter changes compared to Global Scaling.