Elsevier

NeuroImage

Volume 52, Issue 1, 1 August 2010, Pages 172-185
NeuroImage

Differentiating maturational and aging-related changes of the cerebral cortex by use of thickness and signal intensity

https://doi.org/10.1016/j.neuroimage.2010.03.056Get rights and content

Abstract

Cortical thickness decreases from childhood throughout life, as estimated by magnetic resonance imaging (MRI). This monotone trajectory does not reflect the fundamentally different neurobiological processes underlying morphometric changes in development versus aging. We hypothesized that intracortical gray matter (GM) and subjacent white matter (WM) T1-weighted signal intensity would distinguish developmental and age-related changes in the cortex better than thickness. Intracortical GM and subjacent WM signal intensity and cortical thickness was measured across the brain surface in a healthy life span sample (n = 429, 8–85 years). We also computed the relaxation rate of T2* (R2*) from multiecho sequences and mapped intracortical GM and subjacent WM values to the surface to delineate age-related variability in R2* and to adjust the T1 signal intensity for possible confounds of accumulated iron. While monotone age-related reductions in thickness were found, both intracortical GM and subcortical WM signal intensity showed inverted U patterns with peaks from eight to approximately 30 years of age. The spatial pattern of intracortical neurodevelopment followed a posterior–anterior gradient, with earliest maturation of occipital visual cortices and most protracted in superior frontal regions. From 50 s and 60 s, substantial signal reductions were observed in several regions, including the insula, cingulate, and inferior temporal gyrus. R2* showed similar patterns but peaked much later than the T1-weighted signal intensity measures. The results are presented as animations yielding detailed depictions of the dynamic regional variability in cortical neurodevelopment and aging and demonstrate that cortical thickness and T1-weighted signal intensity are sensitive to different cortical maturational and aging-related processes.

Introduction

Delineating normal life span development of the cerebral cortex provides indispensible knowledge informing the interpretation of the deviating courses related to developmental and age-related diseases (Tau and Peterson, 2010). Alterations in cortical volume and thickness have been mapped in vivo in development (Giedd et al., 1999, Gogtay et al., 2004, Shaw et al., 2008, Sowell et al., 2003, Sowell et al., 2004, Tamnes et al., 2010) and aging (Fjell et al., 2009, Good et al., 2001, Jernigan et al., 2001, Raz et al., 2004, Salat et al., 2004, Westlye et al., 2009b) using magnetic resonance imaging (MRI). Accumulating evidence is converging on decreases in cortical thickness and volume from late childhood. Although the neurobiological underpinnings of the morphometric changes are not established, it is likely that fundamentally different processes induce cortical thinning in development and the atrophy seen in adulthood (Sowell et al., 2003). The maturational cortical thinning may be caused by regressive use-dependent selective synapse elimination (Bourgeois and Rakic, 1993, Huttenlocher and Dabholkar, 1997) in combination with progressive proliferation of myelin into the neuropil (Shaw et al., 2008, Sowell et al., 2001, Yakovlev and Lecours, 1967). These processes refine local and distributed network connectivity and enhance the efficiency and synchronicity of signal transmission (Tau and Peterson, 2010). Cortical thinning is thus regarded an early maturational marker. In contrast, adult cortical thinning has been attributed to degenerative shrinkage of large neurons (Terry et al., 1987), loss of myelinated axonal fibers (Nairn et al., 1989), deafferentation (Bertoni-Freddari et al., 2002), and reduction in synaptic density (Morrison and Hof, 1997).

Cortical thickness fails to distinguish between maturational and aging-related neurobiological processes. However, by mapping intracortical T1-weighted signal intensity, we may differentiate the neurobiological processes associated with development from those associated with aging. T1-weighted signal intensity reflects the underlying tissue proton relaxation times, which is related to degree of myelination (Barbier et al., 2002, Clark et al., 1992, Eickhoff et al., 2005, Walters et al., 2003). Signal intensity alterations may provide an independent biomarker of structural alterations in development, aging, and disease (Salat et al., 2009, Westlye et al., 2009b).

The aim of this study was to track cortical GM and subcortical WM development and aging by surface-based mapping of cortical and subcortical T1-weighted signal intensity and R2* as well as cortical thickness in 429 participants aged 8–85 years. We anticipated signal intensity increases from childhood through adolescence and decline in the latter half of life. Since signal intensity is related to tissue myeloarchitecture, we expected cortical trajectories similar to those demonstrated in white matter microstructural maturation, with increases well into adulthood (Lebel et al., 2008, Westlye et al., in press). This stands in contrast to the monotone cortical thinning from childhood. In line with evidence of a maturational posterior–anterior gradient (Gogtay et al., 2004), we expected early maturation of sensorimotor areas including visual cortices, followed by association areas and last in higher-order frontal and posterior parietal cortices. Following an inverse ontogenetic course in aging (Courchesne et al., 2000, Raz, 2000), we expected earliest decline in frontoparietal cortices and latest in sensorimotor areas.

Several biophysical variables influence the T1-weighted signal. Changes in T2 and T2* relaxation secondary to iron depositions may modulate the T1-weighted signal intensity, even on strongly T1-weighted acquisitions like the MP-RAGE sequence used in the present study. Therefore, possible confounding effects of bioaccumulated iron, with consequent reduction in T2* relaxation times, were controlled by including T2* relaxation rate (R2*) computed from multiecho sequences as additional covariates in the statistical models. Since R2* also may index relevant age-related biophysical variability, we delineated the age trajectories for intracortical GM and subjacent WM R2* across the life span.

Section snippets

Subjects

The sample was drawn from the first wave of two ongoing longitudinal research projects at the Center for the Study of Human Cognition at the University of Oslo, namely, Neurocognitive Development and Cognition and Plasticity through the Lifespan and is overlapping with the sample in Westlye et al. (in press). The studies were approved by the Regional Ethical Committee of Southern Norway (REK-Sør). Participants were recruited through newspaper ads and among students and employees at the

Quadratic effects of age

Supplementary Fig. 2 shows statistical p maps (p < .01) from GLMs testing for quadratic effects of age on intracortical GM and subcortical WM T1-weighted signal intensity and intracortical GM R2* while regressing out linear effects of age and sex. Widespread negative quadratic effects (inverse U curves) of age were observed across measures.

Intracortical GM T1-weighted signal intensity

Fig. 1A shows color-coded surface mappings of the timing of maximum cortical GM T1-weighted signal intensity (after removal of ICV-related variance per

Discussion

Cortical thinning in development and aging are caused by different neurobiological processes, but this cannot be monitored in vivo by use of imaging-derived cortical thickness measures alone. Here, we show that signal intensity obtained from heavily T1-weighted MRI scans is a promising biomarker of cortical age-related changes. In contrast to cortical thickness, T1-weighted signal intensity showed nonmonotone relationships with age, with strong maturational increases, a relatively stable

Disclosure statement

Anders M. Dale is a founder and holds equity in CorTechs Labs, Inc, and also serves on the Scientific Advisory Board. The terms of this arrangement have been reviewed and approved by the University of California, San Diego, in accordance with its conflict of interest policies. All other authors state that there are no actual or potential conflicts of interest. Appropriate approval and procedures were used concerning human subjects participating in the study.

Acknowledgments

This study was supported by the Norwegian Research Council (grant 177404/W50 to K.B.W. and 175066/D15 to A.M.F.) and the University of Oslo to K.B.W. and A.M.F. The authors wish to express their gratitude to three anonymous reviewers for constructive comments on an earlier version of the article.

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