Structural and functional neuroimaging of late-life depression: a coordinate-based meta-analysis

Brain Imaging Behav. 2022 Feb;16(1):518-531. doi: 10.1007/s11682-021-00494-9. Epub 2021 Jul 31.


Several neuroimaging studies have investigated localized aberrations in brain structure, function or connectivity in late-life depression, but the ensuing results are equivocal and often conflicting. Here, we provide a quantitative consolidation of neuroimaging in late-life depression using coordinate-based meta-analysis by searching multiple databases up to March 2020. Our search revealed 3252 unique records, among which we identified 32 eligible whole-brain neuroimaging publications comparing 674 patients with 568 controls. The peak coordinates of group comparisons between the patients and the controls were extracted and then analyzed using activation likelihood estimation method. Our sufficiently powered analysis on all the experiments, and more homogenous subsections of the data (patients > controls, controls > patients, and functional imaging experiments) revealed no significant convergent regional abnormality in late-life depression. This inconsistency might be due to clinical and biological heterogeneity of LLD, as well as experimental (e.g., choice of tasks, image modalities) and analytic flexibility (e.g., preprocessing and analytic parameters), and distributed patterns of neural abnormalities. Our findings highlight the importance of clinical/biological heterogeneity of late-life depression, in addition to the need for more reproducible research by using pre-registered and standardized protocols on more homogenous populations to identify potential consistent brain abnormalities in late-life depression.

Keywords: Activation likelihood estimation; Functional magnetic resonance imaging; Late-life depression; Positron emission tomography; Voxel-based morphometry.

Publication types

  • Meta-Analysis
  • Review

MeSH terms

  • Brain / diagnostic imaging
  • Depression*
  • Functional Neuroimaging
  • Humans
  • Magnetic Resonance Imaging*
  • Neuroimaging