CommentaryNeuroanatomical aging: Universal but not uniform
Section snippets
Patterns in brain aging
At least two premises must be met for MRI techniques to be informative: (1) there must be a set of identifiable regularities that can be identified by means of such techniques and (2) these regularities must be of some significance for human functioning. During the last 15 years some inconsistencies have been reported in brain aging research, but the first premise has partly been shown to hold true. Two relatively large new morphometric studies, Allen et al., and ours, Walhovd et al. ([1], [30]
Neuroanatomical aging in a neuropsychological perspective: how does it add up?
We agree with Allen et al. [1] in that data on volumetric brain aging ultimately should help us understand normal age-related changes in cognition from a biological perspective. As noted above, this is a premise, which must be fulfilled for MRI techniques to be truly informative in aging. However, in view of the age functions observed for structures such as the hippocampus, which is assumed to support memory capacity, this seems to be a highly complex task. De facto, sharply curvilinear or
References (32)
- et al.
Normal neuroanatomical variation due to age: the major lobes and a parcellation of the temporal region
Neurobiol Aging.
(2005) Age-related myelin breakdown: a developmental model of cognitive decline and Alzheimer's disease
Neurobiol Aging
(2004)- et al.
Model of subcortical functions in language: current status
J Neurolinguistics
(1997) - et al.
Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain
Neuron
(2002) - et al.
A voxel-based morphometric study of ageing in 465 normal adult human brains
NeuroImage
(2001) - et al.
Effects of age on tissues and regions of the cerebrum and cerebellum
Neurobiol Aging
(2001) - et al.
White matter mapping is needed
Neurobiol Aging
(2004) - et al.
Age changes on tests of fluid and crystallized ability for women and men on the Kaufman Adolescent and Adult Intelligence Test (KAIT) at ages 17–94 years
Arch Clin Neuropsychol
(1996) - et al.
Neural circuitry of judgment and decision mechanisms
Brain Res Rev
(2005) - et al.
Unsolved problems in comparing brain sizes in homo sapiens
Brain Cogn
(1998)
The microvascular frontal-subcortical syndrome of aging
Neurobiol Aging
Speech and language disturbances due to subcortical lesions
Brain Lang
Correction for intracranial volume in analysis of whole brain atrophy in multiple sclerosis: the proportion vs. residual method
NeuroImage
Preservation of hippocampal volume throughout adulthood in healthy men and women
Neurobiol Aging
Relationship between hippocampal volume and memory ability in healthy individuals across the lifespan: review and meta-analysis
Neuropsychologia
Effects of age on volumes of cortex, white matter and subcortical structures
Neurobiol Aging.
Cited by (22)
NEUROIMAGING IN DEMENTIAS
2016, Revista Medica Clinica Las CondesThe impact of aging on gray matter structural covariance networks
2012, NeuroImageCitation Excerpt :It has been well established that healthy aging is associated with anatomical changes in the brain. Although the majority of magnetic resonance imaging (MRI) studies have shown that significant anatomical variability exists within the senior population (Raz and Rodrigue, 2006; Walhovd et al., 2005), a common pattern of atrophy in the prefrontal cortex (Lemaitre et al., 2012; Raz et al., 1997, 2005; Tisserand et al., 2002, 2004) and the medial temporal lobe (Bigler et al., 2002; Du et al., 2006; Tisserand et al., 2004) has been consistently reported when comparing older and younger adults. In particular, these anatomical changes have been associated with an age-related decline in executive functions (Cardenas et al., 2011; Du et al., 2006) and episodic memory (Pardo et al., 2007; Petersen et al., 2000; Rusinek et al., 2003), respectively.
FreeSurfer
2012, NeuroImageCitation Excerpt :It has been used to improve our understanding of an array of neurological disorders (Becker et al., 2008; Desikan et al., 2010a,b; Dickerson et al., 2009; Gold et al., 2005; Kuperberg et al., 2003; Manoach et al., 2007; Milad et al., 2005; Oliveira et al., 2010; Rauch et al., 2005; Rosas et al., 2002, 2005, 2006, 2010; Sabuncu et al., 2011; Sailer et al., 2003; Stufflebeam et al., 2011), the genetic basis of neuroanatomical variability and change (Kremen et al., 2010; Panizzon et al., 2009), as well as healthy development (Isaacs et al., 2008; Martinussen et al., 2005) and aging (Fjell et al., 2005, 2006; Salat et al., 2004, 2005a, 2005b, 2009; Walhovd et al., 2004, 2005a, 2005b, 2006).
Normal age-related brain morphometric changes: Nonuniformity across cortical thickness, surface area and gray matter volume?
2012, Neurobiology of AgingCitation Excerpt :In vivo studies using Magnetic Resonance Imaging (MRI) have consistently shown an age-related decrease in GM and WM volume concomitant with an increase in CSF volume (Courchesne et al., 2000; Good et al., 2001; Lemaitre et al., 2005; Raz et al., 1997; Smith et al., 2007; Walhovd et al., 2005). Studies looking at the effect of age using either manual drawing of regions of interest (ROI) (Allen et al., 2005; Raz et al., 1997; Raz et al., 2004) or automated/semi-automated methods, such as voxel-based morphometry (VBM) (Good et al., 2001; Smith et al., 2007; Tisserand et al., 2002) have reported regionally variable vulnerability to aging across the whole brain (Raz et al., 2006; Walhovd et al., 2005). The literature related to regional heterogeneity in age-related changes in brain morphometry can be grouped into two categories based on the regions involved.
Consistent neuroanatomical age-related volume differences across multiple samples
2011, Neurobiology of AgingCitation Excerpt :Cerebellum: Five studies have found negative age relationships for total cerebellar volume, cerebellar GM, cerebellar WM, or other cerebellar compartments (Jernigan et al., 2001; Liu et al., 2003; Luft et al., 1999; Raz et al., 2001; Sullivan et al., 2000; Walhovd et al., 2005a). In one study, no effects on cerebellar WM (Sullivan et al., 2000) were found, in contrast to a more recent study (Walhovd et al., 2005b). One study observed that the age changes were best described by an exponential fit (Luft et al., 1999).
Age-related differences in regional brain volumes: A comparison of optimized voxel-based morphometry to manual volumetry
2009, Neurobiology of AgingCitation Excerpt :However, when manually measured intracranial volume was used as a covariate, the sex differences all but disappeared. This finding reinforces the recommendation to use an extra-cerebral index such as manually or semi-automatically traced intracranial vault volume as a covariate for head size correction (Walhovd et al., 2005). In the context of an aging brain study, the possibility of sexually dimorphic age trajectories warrants attention.