2006
DOI: 10.1016/j.neubiorev.2006.07.001
|View full text |Cite
|
Sign up to set email alerts
|

Differential aging of the brain: Patterns, cognitive correlates and modifiers

Abstract: Deciphering the secret of successful aging depends on understanding the patterns and biological underpinnings of cognitive and behavioral changes throughout adulthood. That task is inseparable from comprehending the workings of the brain, the physical substrate of behavior. In this review, we summarize the extant literature on age-related differences and changes in brain structure, including postmortem and noninvasive magnetic resonance imaging (MRI) studies. Among the latter, we survey the evidence from volum… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

62
838
9
10

Year Published

2007
2007
2023
2023

Publication Types

Select...
8
2

Relationship

1
9

Authors

Journals

citations
Cited by 1,014 publications
(919 citation statements)
references
References 227 publications
62
838
9
10
Order By: Relevance
“…In contrast to supratentorial fiber systems, the two infratentorial systems examined (pontocerebellar and cerebellar hemisphere bundles) showed no signs of aging whatsoever, a finding consistent with a fiber tracking study of children and young adults (Liston et al, 2006) and a region-of-interest study of adult aging (Yoon et al, 2007). As has been speculated, demonstrated, and replicated with region-of-interest and voxel-based analyses (for reviews, Minati et al, 2007;Moseley, 2003;Pfefferbaum and Sullivan, 2005a;Pfefferbaum, 2003, 2007;Wozniak and Lim, 2006), these patterns of normal aging provide support for subtle disruption of frontal systems in explaining age-related decline in selective cognitive and motor functions (Craik and Salthouse, 2008;Fazekas et al, 2005;Raz and Rodrigue, 2006). Degradation of anterior commissural fibers may curtail deployment of bilateral compensatory mechanisms to enhance performance when age-related decline reduces performance efficiency by the preferred gray matter system (c.f., Dennis and Cabeza, 2008).…”
Section: Discussionsupporting
confidence: 70%
“…In contrast to supratentorial fiber systems, the two infratentorial systems examined (pontocerebellar and cerebellar hemisphere bundles) showed no signs of aging whatsoever, a finding consistent with a fiber tracking study of children and young adults (Liston et al, 2006) and a region-of-interest study of adult aging (Yoon et al, 2007). As has been speculated, demonstrated, and replicated with region-of-interest and voxel-based analyses (for reviews, Minati et al, 2007;Moseley, 2003;Pfefferbaum and Sullivan, 2005a;Pfefferbaum, 2003, 2007;Wozniak and Lim, 2006), these patterns of normal aging provide support for subtle disruption of frontal systems in explaining age-related decline in selective cognitive and motor functions (Craik and Salthouse, 2008;Fazekas et al, 2005;Raz and Rodrigue, 2006). Degradation of anterior commissural fibers may curtail deployment of bilateral compensatory mechanisms to enhance performance when age-related decline reduces performance efficiency by the preferred gray matter system (c.f., Dennis and Cabeza, 2008).…”
Section: Discussionsupporting
confidence: 70%
“…In our study, the MTR decreases in the frontal white matter and basal forebrain were likely to be related to vascular pathology because they were negatively correlated with diffusion (ADC, Table 4), a measure that is known to be sensitive to capillary expansion, swelling of perivascular spaces, and vascular insults (Moseley, 2002;Pfefferbaum et al, 2003;Raz and Rodrigue, 2006;Wozniak and Lim, 2006). Previous studies of WM tract integrity have reported reduced FA in healthy elderly subjects most prominently in FWM and the corpus callosum (Head et al, 2004;Pfefferbaum et al, 2005;Salat et al, 2005;.…”
Section: Discussionmentioning
confidence: 55%
“…AlsoFin this specific sampleFthe whole brain was larger in the depressed subjects than in the comparison subjects. Thus, we chose to use the volume of the primary visual cortex (the calcarine area) to control for individual variations in brain size, as this is one of the regions with minimal inter-subject variation as well as with minimal agerelated variation (Raz and Rodrigue, 2006).…”
Section: Methodsmentioning
confidence: 99%