br SES language and brain structure The
SES, language, and brain structure The brain undergoes significant changes over the course of development (Johnson et al., 2016). Synaptic density increases rapidly in the first few years of life, during which time neurons form connections and become organized into specialized functional regions. Synapses undergo an extended period of adjustment and pruning, and AZD2281 cost become increasingly myelinated through early adulthood. Importantly, this process has been shown to be experience-dependent (Fox et al., 2010). Although structural MRI is generally insensitive to specific neuronal processes like axonal pruning and myelination, it is nevertheless useful as a method to quantify large-scale morphometric changes in vivo, including the measurement of such variables as regional volume, cortical thickness, and surface area. Each of these measures change nonlinearly over the course of development. Indeed, measures of brain structure have been found to be correlated with differences in cognition and are posited to be sensitive to experience-dependent neural plasticity (Galván, 2010; Johnson et al., 2016; Noble et al., 2015). Two primary models based on the animal literature have been used to understand socioeconomic differences within the cognitive neuroscience of SES. The first suggests that being deprived of meaningful stimulation causes early proliferation and pruning, resulting in global inefficiencies. The second suggests that living in particularly stressful conditions blunts autonomic reactivity and alters neural systems involved in emotional processing, thus inhibiting fear learning. In this context, theorists have posited that lower-SES children have been raised in environments in which they have been deprived of stimulation and subject to chronic stressors, both of which may negatively affect their development (McLaughlin et al., 2014). A number of researchers in the field of the cognitive neuroscience of SES have now studied brain structure in probing cognitive differences between lower- and higher-SES children. For example, in attempting to elucidate the effects of SES on disparities in neurocognitive development, Noble et al. (2012) examined regional volumes in a sample of 5- to 17-year-olds from lower- and higher-SES backgrounds. Previous work demonstrated that higher-SES children outperformed their economically disadvantaged peers on neurocognitive tasks thought to assess the functioning of the brain’s language system (Noble et al., 2007). Thus, Noble and colleagues attempted to examine more directly the neural basis of these SES-associated differences. They examined five neural regions of interest (ROIs) on the basis of their presumed role in the development of language and reading skills: the left superior temporal gyrus (LSTG), left middle temporal gyrus, left inferior temporal gyrus (LITG), left inferior frontal gyrus (LIFG), and left fusiform gyrus. Noble et al. found that, after controlling for age and whole-brain volume, only LITG volume showed a trend-level association with SES. They did, however, find a significant interaction of SES and age in both the LIFG and LSTG. Whereas in the lower-SES children volumes of both ROIs were negatively related to age, this relation was reversed in the higher-SES children, who showed a positive relation between ROI volumes and age. In interpreting this finding, Noble et al. (2012) drew on preexisting research regarding the impact of SES on development, relying on evidence that the early language environment is poorer in impoverished homes. They suggested that language deprivation is compounded throughout children’s lives, citing Hart and Risley (1995), who measured children’s language input only until they were three years of age. Next, Noble et al. turned to a separate body of research suggesting that lower-SES children perform more poorly on neurocognitive assessments of language than do their higher-SES peers (Noble et al., 2007). Integrating these findings, Noble et al. reasoned that because higher-SES children are posited to have more advanced language skills, presumably due to compounding differences in the home language environment, and because the higher-SES children in their sample had increasing LIFG and LSTG volume with greater age, the late increase of volume in these ROIs (compared to a decrease among the lower-SES children) must be indicative of superior language development in the higher-SES children. Noble et al. then suggested that this difference arises due to an extended period of neurodevelopment, specifically that pruning occurs over a longer timeframe, which gives these children a prolonged period of plasticity that aids in learning (Noble et al., 2012). It is important to note that Noble et al. do not present any evidence concerning the language experience and home environment of the children in their study; there are no direct correlations presented among their neuroimaging findings, children’s language experience, and language performance.