ReviewImaging brain development: The adolescent brain
Highlights
► Developmental neuroimaging has undergone rapid expansion in the past 15 years. ► MRI and fMRI studies point to adolescence as a period of neural development. ► Activity patterns within the social brain network change during adolescence. ► Several areas of research will expand and mature in the next two decades.
Introduction
Half a century ago, very little was known about how the human brain develops and it is unlikely scientists expected that at the turn of the millennium it would be possible to look inside the brains of living humans of all ages and track changes in brain structure and function across development. In the second half of the twentieth century, interest in brain development rapidly increased. Most research in this field relied on non-human animal brains. Data on human brain development were rare because of the scarcity of post-mortem human brains of different ages. It is only in the past 15 years or so, because of advances in imaging techniques, that research has revealed a great deal about the development of the living human brain across the lifespan. Technical advances in neuroimaging methods, in particular, magnetic resonance imaging (MRI) and functional MRI (fMRI), have revolutionized what we know about how the human brain develops and have facilitated the rapid expansion of this young research field.
In this paper, I first review early histological studies on the development of the brain. In the next section, I outline recent advances that have made it possible to study the development of the living human brain. In the third section, I review recent MRI studies on structural development in the living human brain. Next, I briefly discuss fMRI developmental imaging studies on the social brain during adolescence. Finally, I look ahead and speculate on some of the key questions for the next 20 years of developmental neuroimaging.
Ground-breaking experiments on animals, starting in the 1950s, showed that, soon after birth, sensory regions of the brain go through sensitive periods during which environmental stimulation appears to be crucial for normal brain development and normal perceptual development to occur (Hubel and Wiesel, 1962, Wiesel and Hubel, 1965). Early in postnatal development, the brain begins to form new synapses, so that at some point in early development the synaptic density greatly exceeds adult levels. This process of synaptogenesis lasts up to several months or years, depending on the species of animal, and is followed by a period of synaptic pruning (Cragg, 1975). Which synapses survive and which are selectively eliminated is partly experience-dependent (Changeux and Danchin, 1976, Low and Cheng, 2006). Much of what we know about how the brain develops comes from animal research. For example, research carried out in rhesus monkeys demonstrated that synaptic densities in visual cortex reach maximal levels two to four months after birth, after which time pruning begins (Bourgeois et al., 1994, Rakic, 1995, Rakic et al., 1986, Woo et al., 1997, Zecevic and Rakic, 2001). Synaptic densities gradually decline to adult levels at around three years, around the time rhesus monkeys reach sexual maturity.
In the late 1960s and 1970s research on post-mortem human brains revealed that some brain areas, in particular the prefrontal cortex, continue to develop well beyond early childhood (Huttenlocher, 1979, Huttenlocher et al., 1982, Yakovlev and Lecours, 1967). First, it was found that the myelination of axons follows a chronologic sequence, and that the last cortical areas to be myelinated are the association areas, the prefrontal cortex (PFC) among them, where the process of myelination continues for years, well into adolescence (Yakovlev and Lecours, 1967). Second, post-mortem human brain data suggested that synaptic reorganisation continues throughout childhood and adolescence in certain brain regions (Webb et al., 2001). Histological studies of human prefrontal cortex have shown that there is a proliferation of synapses in the subgranular layers of the prefrontal cortex during early and mid-childhood, followed by a plateau phase and a subsequent elimination and reorganisation of prefrontal synaptic connections during adolescence (Huttenlocher, 1979). This finding has recently been supported and expanded by a larger scale study of prefrontal synaptic spine development in 32 post-mortem human brains of different ages across the lifespan (aged one week to 91 years; Petanjek et al., 2011). This study demonstrated that prefrontal dendritic spine density increases in childhood, resulting in numbers that exceed adult levels two- or three-fold by puberty, and then decreases gradually after puberty (Fig. 1). The elimination of synaptic spines continued beyond adolescence throughout the third decade of life, providing evidence for astonishingly protracted dendritic reorganisation in the human prefrontal cortex.
In the past decade or so, the field of developmental cognitive neuroscience has undergone unprecedented expansion, mostly due to technological advances in neuroimaging techniques. There has been a year-on-year increase in the number of papers reporting studies using paediatric neuroimaging published since 1996, as shown in Fig. 2. There have been high profile books (e.g. Johnson, 2004), special issues of several scientific journals and conferences, as well as a new journal (Developmental Cognitive Neuroscience), dedicated to this growing field (see Blakemore et al., 2010a).
Several different neuroimaging techniques have advanced to the point where they can be used reliably to study human brain development across age. EEG and event-related potentials (ERP) have long been regarded as the neuroimaging methods of choice with babies and young children. They have obvious appeal because of their safety, ease of use, and good temporal resolution. The development of functional near-infrared spectroscopy (fNIRS) is providing a new means to look at cortical activation in infants, since it is non-invasive, relatively low cost and portable (Gervain et al., 2011). However, more than any other advance, the increased use of MRI and fMRI in developmental populations has created new opportunities to track structural and functional changes in the developing human brain. This work has advanced our knowledge of how the human brain develops, and the data from developmental neuroimaging studies have in turn triggered new interest in the changing structure and function of the brain over the lifespan.
Research using MRI to acquire structural images from participants across the lifespan has revealed that the human brain continues to develop for many decades (e.g. Shaw et al., 2008). Age-associated region-specific, linear and non-linear changes in white matter tracts (Giedd et al., 1999, Lebel and Beaulieu, 2011, Ostby et al., 2009, Paus et al., 1999) and cortical grey matter (volume, density, and thickness; Ostby et al., 2009, Paus, 2005, Shaw et al., 2008, Tamnes et al., 2010) have been described in structural MRI studies.
One of the most consistent findings from MRI studies is that there is a steady increase in white matter volume in several brain regions during childhood and adolescence. An early developmental MRI study revealed differences in the density of white and grey matter between the brains of a group of children (average age 9 years) and a group of adolescents (average age 14 years; Sowell et al., 1999). The results showed adolescents had a higher volume of white matter and a lower volume of grey matter in the frontal cortex and parietal cortex compared with the younger group. Increased white matter and decreased grey matter density in the frontal and parietal cortices during adolescence is a finding that has been corroborated by several studies carried out by a number of different research groups with increasingly large numbers of subjects (Barnea-Goraly et al., 2005, Giedd et al., 1996, Giedd et al., 1999, Paus et al., 1999, Pfefferbaum et al., 1994, Reiss et al., 1996, Sowell et al., 1999). In addition, increases in white matter volume are accompanied by progressive changes in MRI measures of white matter integrity, such as the magnetisation-transfer ratio (MTR) in MRI, and fractional anisotropy (FA) in diffusion-tensor MRI (Fornari et al., 2007, Giorgio et al., 2010, Paus et al., 2008). The MTR indexes the efficiency of magnetization exchange between different tissue compartments, and is strongly influenced by the integrity of myelin membranes. FA is the extent to which the diffusion of water molecules in the brain is anisotropic (not equal in all directions), and higher FA values are thought to reflect increasing organization of white matter tracts (due to processes including myelination and axon density), since water molecules will tend to diffuse in parallel with the tracts. Generally, there is evidence for increasing FA during adolescence (see Schmithorst and Yuan, 2010, for review). The increase in white matter seen with age (Fig. 3) has been interpreted as reflecting continued axonal myelination (and/or axonal calibre; Paus et al., 2008) during childhood and adolescence.
Recent DTI evidence for non-linear changes in white matter development has been reported in a longitudinal study of 103 participants from 5 to 32 years (Lebel and Beaulieu, 2011). 10 major white matter tracts were assessed for FA and mean diffusivity (MD; which also corresponds to white matter tract strength). In contrast with earlier studies showing linear increases in white matter volume, this study showed nonlinear development trajectories for FA and MD. FA and MD showed more rapid changes at early ages (increases for FA, decreases for MD), and slower changes or levelling off during young adulthood.
In another pioneering developmental MRI study, emanating from the National Institute of Mental Health paediatric neuroimaging project, Giedd et al. (1999) performed longitudinal MRI scans on 145 healthy participants ranging in age from about four to 22 years. Scans were obtained from each participant at two-year intervals. The volume of grey matter in the frontal lobe increased during late childhood and early adolescence with a peak occurring at around 12 years. This was followed by a decline during adolescence (Fig. 4). Similarly, parietal-lobe grey matter volume increased during childhood to a peak at around 12, followed by decline during adolescence. Grey matter development in the temporal lobes was also non-linear, but the peak was reached later at about 17 years. In another longitudinal study by the same group, participants aged between 4 and 21 were scanned every two years for 8 to 10 years (Gogtay et al., 2004). In terms of cortical grey matter density, sensory and motor brain regions matured earliest, followed by the remainder of the cortex, which matured (in terms of grey matter loss) from posterior to anterior regions. This loss of grey matter occurred last in the superior temporal cortex. A later study analysed cortical thickness and investigated the age of at which peak cortical thickness was reached, and again showed earlier maturation in sensory and motor regions and later maturation in parts of the frontal and temporal lobes (Shaw et al., 2008).
An early MRI study by a different group demonstrated a sharp acceleration in grey matter loss between childhood and adolescence in the dorsal prefrontal cortex and the parietal cortex (Sowell et al., 2001). The regions exhibiting the most robust decrease in grey matter density (e.g. the dorsal prefrontal cortex) also exhibited the most robust increase in white matter density. This study revealed that the loss of grey matter in the frontal cortex continued up to the age of 30. A further MRI study of participants ages 7 to 87 revealed a reduction in grey matter density in the dorsal prefrontal, parietal and temporal cortices, accompanied by an increase in white matter, which continued up to the age of 60 (Sowell et al., 2003).
The MRI results demonstrating non-linear developmental changes in grey matter in various brain regions throughout adolescence have been interpreted in several ways. First, age-related decreases in grey matter volume shown in MRI studies have been proposed to be predominantly due to intracortical myelination and increased axonal calibre (Giorgio et al., 2010, Paus et al., 2008, Perrin et al., 2008). This would result in an increase in the volume of tissue that is classified as white matter (and a net reduction in grey matter) in MRI scans. A second explanation is that the grey matter changes reflect the synaptic reorganisation that occurs during puberty and adolescence (Huttenlocher, 1979, Petanjek et al., 2011). Thus, speculatively, the increase in grey matter apparent at around the age of puberty onset (Giedd et al., 1999) might reflect a wave of synaptic proliferation at this time, while the gradual decrease in grey matter density that occurs in certain brain regions during adolescence has been attributed to synaptic pruning (Giedd et al., 1999, Gogtay et al., 2004, Sowell et al., 2001). Although changes in synaptic density are likely to be accompanied by changes in glia and other cellular components (Theodosis et al., 2008), whether such changes would be visible as volumetric changes in MRI scans is debated (see Paus et al., 2008).
Developmental functional imaging, using fMRI, has rapidly expanded in the past decade. In this section I focus on development of the social brain in adolescence as an example of research in this burgeoning field.
The social brain is defined as the network of brain regions involved in understanding other people. It includes the network that is involved in theory of mind, or mentalising, the process that enables us to understand other people's actions in terms of the underlying mental states that drive them (Frith and Frith, 2007). For example, we interpret another person reaching towards a coffee pot in terms of a desire for coffee, rather than the mechanical forces used in such an action. Over the past 20 years, a large number of neuroimaging studies in adults have shown remarkable consistency in identifying the brain regions that are involved in mentalising. These studies have employed a wide range of stimuli including stories, sentences, words, cartoons and animations, each designed to elicit the attribution of mental states (see Lieberman, 2012-this issue, Amodio and Frith, 2006, Gilbert et al., 2010). In each case, the mentalising task resulted in the activation of a network of regions including the posterior superior temporal sulcus (pSTS)/temporo-parietal junction (TPJ), the anterior temporal cortex (ATC) including the temporal poles and the medial prefrontal cortex (MPFC; see Burnett and Blakemore, 2009, for evidence that these regions function as a network).
Recent meta-analyses of MPFC activation by different mentalising tasks indicate that the peak activation lies within the anterior dorsal MPFC (dMPFC; Amodio and Frith, 2006, Gilbert et al., 2006). This region is activated when one thinks about psychological states, regardless of whether these psychological states are applied to oneself (Johnson et al., 2002, Lieberman, 2012-this issue, Lou et al., 2004, Ochsner et al., 2004, Van Overwalle, 2009, Vogeley et al., 2001), one's mother (Ruby and Decety, 2004), imagined people (Goel et al., 1995) or animals (Mitchell et al., 2005). Frith has proposed that the dMPFC is involved in the necessary decoupling of mental states from physical reality, whereas the pSTS/TPJ is involved in predicting what movement a conspecific is about to make (Frith, 2007; although see Saxe, 2006, for alternative viewpoint).
Section snippets
fMRI studies of mentalising during adolescence
While many studies over the past 30 years have investigated the development of mentalising in infancy and childhood, pointing to step-wise changes in social cognitive abilities during the first five years of life (Frith and Frith, 2007), recently experimental studies have focused on the development of the social brain beyond childhood. Recent cognitive neuroscience studies have focused on adolescence as a period of profound social cognitive change. Adolescence is defined as the period of life
Conclusion
In this paper, I have reviewed MRI and fMRI studies on structural and functional changes in the adolescent brain. The ability to see inside the developing human brain and to track developmental changes, both in terms of structure and function, is relatively recent. The past 15 years has seen an explosion in the number of studies using neuroimaging techniques to investigate maturational changes in the human brain. These studies point to adolescence as a period of continued neural development. The
Acknowledgments
SJB has a Royal Society University Research Fellowship and is also funded by the Wellcome Trust and the Leverhume Trust. The author is grateful to BJ Casey, I. Dumontheil, H. Hillebrandt, E. Kilford, and K. Mills, for comments on earlier drafts of the manuscript.
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