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    • Rubia and Luna et al summarize the changes in brain

    2018-11-15

    Rubia (2013) and Luna et al. (2010) summarize the changes in THZ1 Hydrochloride activation that occur in cortex from childhood to later adulthood. Their summaries indicate increasing connectivity within cognitive control networks as children age, which may contribute to greater cognitive control during adolescence. This conclusion is consistent with recent studies indicating that brain networks involved in cognitive control versus default mode become more segregated during adolescence (Baum et al., 2017; Dosenbach et al., 2010; Fair et al., 2008; Satterthwaite et al., 2013), but conversely become less segregated during later adulthood, thereby displaying an inverted-U shaped pattern of interconnectivity across the lifespan (Betzel et al., 2014; Chan et al., 2014). Furthermore, Chan et al. (2014) found that reduced network segregation at any adult age was associated with an important marker of age-related cognitive decline, namely weaker verbatim memory. As summarized by Betzel et al. (2014), on the one hand, functional connectivity (FC) over the lifespan within resting state networks (RSNs) “decreased with age, affecting higher-order control and attention networks. On the other hand, FC tended to increase between RSNs, especially among components of the dorsal attentional network, the saliency/ventral attention networks and visual and attention networks and the somatomotor network.” (p. 352). These changes are consistent with a brain that grows in cognitive ability during adolescence but that increasingly relies on between-network connections as adulthood progresses into aging. For most adults, the ability to exert cognitive control or behavioral inhibition eventually declines as indexed by tasks that challenge response speed and attentional skills (e.g., stop-signal and WM) (Lindenberger, 2014). However, older adults have greater ability to draw from experience, which is consistent with growing connectivity between networks.
    Beyond imbalance during adolescence Despite the valuable insights spurred by imbalance models, it time to move beyond these models to consider the role that experience plays in healthy adolescent development. One potentially fruitful direction in future research would be to compare measures of gist learning and decision making to measures that capture the development of wisdom (Sunstein, 2008; see also, Reyna, 2008; Reyna and Huettel, 2014). Such a direct comparison would test Reyna and Brainerd’s (2011) fuzzy-trace theory, which predicts that decision-making shifts from relying on lower-level (verbatim) representations that encourage risk taking to more abstract (gist) representations that support healthier decisions to categorically avoid catastrophic risks (but to take risks when they offer the possibility of a categorically superior outcome relative to less risky options). In this regard, the theory has already successfully predicted self-reported real-world risky behaviors using gist measures (e.g., Broniatowski et al., 2015; Fraenkel et al., 2012; Mills et al., 2008; Reyna et al., 2011; Reyna and Mills, 2014; Wolfe et al., 2015). Another promising direction for future research is to examine the relation between executive functions such as WM and the decline in maladaptive risk taking with age. As the consequences of exploratory risk taking accumulate in experience, those with stronger WM should be able to incorporate those experiences more effectively in decisions entailing maladaptive risk. Preliminary evidence for this prediction has been observed in a study of late adolescent risk for drug addiction. Those with stronger WM ability were more able to avoid advancing to drug dependence apart from differences in impulsive tendencies (Khurana et al., 2017). Our model also suggests that we look at risk taking more broadly than just examining behaviors with adverse consequences. For example, Romer et al. (2016) showed that both sensation seeking and parts of the BAS were related to risk behaviors that are considered adaptive, such as entering scholastic competitions and engaging in sports (see also Hansen and Breivik, 2001). Many of the risky behaviors that adolescents pursue involve potential social conflicts with parents or peers (Weber et al., 2002), and these and other forms of risk behavior are also likely to increase during adolescence and should be considered in our models.