Longitudinal changes in grey and white matter during adolescence
Introduction
Adolescence is defined as the developmental period of transition from childhood to adulthood and is characterized by maturation of cognitive abilities and complex behavioral features (Spear, 2000). Major advances in learning through education are made during adolescence and obvious physical, hormonal, emotional, and social changes occur. By contrast, changes in brain structure during adolescence are more subtle. In the grey matter (GM), these changes take the form of increased myelination of cortico-cortical connections (Nielsen, 1963, Yakovlev and Lecours, 1967) or synaptic “pruning” (Huttenlocher, 1979) or both. Increases in the diameter and myelination of the axons forming the fiber tracts, alongside increased neuronal size and glia proliferation, contribute to the monotonic increase in white matter (WM) volume or density during childhood and adolescence revealed by analysis of magnetic resonance imaging (MRI) scans (Giedd et al., 1999, Paus et al., 1999). Understanding changes in brain structures and the relationship between changes in GM and WM structures during adolescence is an important goal not only to understand normal brain development but also to aid in the study of abnormal neurodevelopment in disorders such as schizophrenia and bipolar disorder (Giedd, 2004, Paus et al., 2008).
Over the past decade, the availability of automated computational techniques for analyzing structural MRI data of the brain has led to a plethora of studies documenting changes during normal childhood and adolescence. These studies are in general agreement that GM volume decreases and WM volume increases during this age range (Barnea-Goraly et al., 2005, Giorgio et al., 2008, Lebel et al., 2008, Paus et al., 1999, Reiss et al., 1996). The literature on changes in WM microstructure, measured using diffusion tensor imaging (DTI), shows a consistent pattern of increased fractional anisotropy (FA) across childhood and adolescence (Ashtari et al., 2007, Barnea-Goraly et al., 2005, Bonekamp et al., 2006, Eluvathingal et al., 2007, Giorgio et al., 2008, Lebel et al., 2008, Muetzel et al., 2008, Nagy et al., 2004, Schmithorst et al., 2002). However, previous DTI studies have been cross-sectional, and few have focused on the late adolescent period. Inconsistent findings reflect the need for more targeted studies and highlight the importance of longitudinal studies to enable the reconstruction of the dynamic course and anatomical sequence of the developing brain (Toga et al., 2006).
In general, FA is a quantitative measure of WM organization and structural integrity, but the specific nature of the developmental changes that contribute to the observed changes is unknown. Some fundamental phenomena that could illuminate this also remain to be elucidated. For example, it is unclear whether increases in FA are due to greater diffusivity along the main diffusion axis (Ashtari et al., 2007) or reduced diffusivity along the axes perpendicular to it (Bhagat and Beaulieu, 2004, Bonekamp et al., 2006, Eluvathingal et al., 2007, Giorgio et al., 2008, Snook et al., 2005, Suzuki et al., 2003) or a combination of the two.
Here, we present an analysis of longitudinal data obtained during late adolescence. We analyzed T1-weighted brain images to examine changes in GM and WM volumes and diffusion images to examine changes in WM microstructure. The aims of this study were to (i) replicate and extend previous findings from cross-sectional studies, (ii) explore changes in GM and WM volumes by using a more sensitive longitudinal design, and (iii) examine the nature of the changes in WM microstructure.
To our knowledge, this is the first study to examine within-subject longitudinal changes in diffusion data in healthy adolescents. It also combines analyses of different data types obtained in the same individuals. In fact, we used two whole-brain approaches to measure changes in brain structure: a voxel-based morphometry (VBM)-style analysis to measure changes in GM and WM volumes (Good et al., 2001) and tract-based spatial statistics (TBSS (Smith et al., 2006)) to examine changes in diffusion data. We paid particular attention to diffusion changes in two specific WM pathways, the arcuate fasciculus (AF) and the corticospinal tract (CST). These two pathways had previously been shown to have an increase in WM density in a large cross-sectional study of 4- to 19-year-old subjects (Paus et al., 1999).
Section snippets
Materials and methods
MRI data were acquired at two time points in a group of 24 healthy adolescents (10 males, 14 females; 21 right-handed, 3 left-handed). The median age at baseline was 15.3 years, range was 13.5–18.8 years, and mean was 15.7 ± 1.4 years. This group was selected because the age spread was fairly evenly distributed. All subjects were likely to be in a similar phase of brain reorganization, although, with differing ages, subjects would be at different points along any developmental trajectory.
Correlations between changes in grey matter volume and age over time
A significant (corrected p < 0.05) decrease in GM volume with increasing age was found in five clusters (Fig. 2). The largest one encompassed many cortical areas extending from the medial parieto-occipital cortex to bilateral superior and inferior lateral parietal areas including the parietal opercular cortex. In the right hemisphere, this cluster also encompassed central opercular and superior temporal cortex extending to portions of the inferior occipitotemporal cortex and the right cerebellar
Discussion
We scanned 24 adolescents aged between 13.5 and 18.8 years and rescanned, on average, 2.5 years later. We found evidence for decreased grey and increased white matter volumes across many different brain regions. Furthermore, we found that FA, which reflects white matter microstructure, increased during the observation period in many fiber tracts mainly due to an increase in diffusivity along the main axis of these tracts. We discuss below each of these patterns of change, their
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