Page 250 - Like me, or else... - Michelle Achterberg

Chapter 9
only the development of these networks, but also how the environment shapes the maturation of these connections.
Neuroimaging in childhood: Pitfalls and possibilities
With the emergence of functional neuroimaging only two decades ago, the field of developmental cognitive neuroscience can still be considered relatively young and acquisition methods and analysis techniques are rapidly improving. Several prior developmental neuroimaging findings have been called into question after studies showed that these findings were largely influenced by age-related differences in head motion (Satterthwaite et al., 2013), highlighting the need for an in-depth investigation of factors that can influence scan quality in children. In chapter 7 I therefore provide an overview of MRI scan quantity and quality in a large developmental twin sample and investigated the genetic and environmental influences on head motion. Overall, scan quantity was high (88% of participants completed all runs), while scan quality decreased with increasing session length. Scanner related distress was negatively associated with scan quantity, but not with scan quality. In line with previous studies, behavioral genetic analyses showed that genetics explained part of the variation in head motion, with heritability estimates of 29-65%. Additionally, the results revealed that subtle head motion - after exclusion of excessive head motion- showed lower heritability estimates (0–14%), indicating that findings of motion-corrected and quality- controlled MRI data are less confounded by genetic factors. Moreover, shared environmental influences played a larger role (15–33%) in the variation in quality- controlled head motion, suggesting that head motion can be influenced by participant instruction and age-appropriate scanner adjustments. This is specifically important for neuroimaging studies across different age-ranges, as this can minimize the confounding factor of age-related differences in head motion on findings regarding brain development.
Brain connectivity as predictor of emotion regulation
As was explained in the section on neurocognitive development models, the ability to regulate emotions and control impulses increases considerably during adolescence, the transition phase between childhood and adulthood. In chapter 8 I tested the hypothesis that this form of emotion regulation is driven by increased maturation of frontostriatal circuitry using a fiber-tracking approach combined with longitudinal imaging. Given the novelty of this approach, here I made use of a classic and often used paradigm to study impulse control; the delay discounting paradigm (Peper et al., 2013). The delay discounting task estimates the preference to choose for a direct small reward over a delayed larger reward. In total, 192 healthy volunteers between 8 and 26 years underwent diffusion tensor imaging scanning and completed the delay discounting task twice,
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