Age-related networks of regional covariance in MRI gray matter: Reproducible multivariate patterns in healthy aging

Abstract

Healthy aging is associated with brain volume reductions that involve the frontal cortex, but also affect other brain regions. We sought to identify an age-related network pattern of MRI gray matter using a multivariate statistical model of regional covariance, the Scaled Subprofile Model (SSM) with voxel based morphometry (VBM) in 29 healthy adults, 23-84 years of age (Group 1). In addition, we evaluated the reproducibility of the age-related gray matter pattern derived from a prior SSM VBM study of 26 healthy adults, 22-77 years of age (Group 2;Alexander et al., 2006) in relation to the current sample and tested the ability of the network analysis to extract an age-related pattern from both cohorts combined. The SSM VBM analysis of Group 1 identified a regional pattern of gray matter atrophy associated with healthy aging (R 2 =0.64, p<0.000001) that included extensive reductions in bilateral dorsolateral and medial frontal, anterior cingulate, insula/perisylvian, precuneus, parietotemporal, and caudate regions with areas of relative preservation in bilateral cerebellum, thalamus, putamen, mid cingulate, and temporal pole regions. The age-related SSM VBM gray matter pattern, previously reported for Group 2, was highly expressed in Group 1 (R 2 =0.52, p<0.00002). SSM analysis of the combined cohorts extracted a common age-related pattern of gray matter showing reductions involving bilateral medial frontal, insula/perisylvian, anterior cingulate and, to a lesser extent, bilateral dorsolateral prefrontal, lateral temporal, parietal, and caudate brain regions with relative preservation in bilateral cerebellum, temporal pole, and right thalamic regions. The results suggest that healthy aging is associated with a regionally distributed

Network-level structural covariance in the developing brain

“…Previous studies have documented age-dependent patterns of regional cortical thickness in healthy children (18,50), and structural changes have been associated with practice and learning (51)(52)(53) as well as with aging and disease (54,55). A comprehensive, datadriven approach to human connectomic mapping (56) may provide a framework for understanding normal childhood development as well as neurodevelopmental (31) and age-related disorders (14) that impact network function.…”

A Transverse and Longitudinal MR Imaging Voxel-Based Morphometry Study in Patients with Primary Cervical Dystonia

“…The GM volume decrease observed in healthy subjects during aging that diffusely affects the cerebral cortex may preferentially involve the associative neocortex, particularly the prefrontal and temporal regions [25][26][27][28] and the medial frontal cortex. 28 Although the GM changes detected in subcortical and cortical areas may be secondary to our patients' involuntary neck movements, this possibility seems unlikely. When they underwent the VBM studies, all the patients with CD were under optimal treatment with botulinum toxin, a therapy that significantly improves the severity of the involuntary neck movements.…”

Structural covariance of neostriatal and limbic regions in patients with obsessive–compulsive disorder

“…3,4 Such factors range from genetic 5 and other developmental influences [6][7][8] to aging effects. 9,10 Other aspects related to the basic principles of brain organ ization, such as the existence of functional connectivity, or cor related spontaneous activity across time between distant struc tures, may also influence the patterns of structural covariance. 2 Structural covariance is observed between the regions of the different resting state functional networks.…”