The brain undergoes profound development across childhood and adolescence, including continuous changes in brain morphology, connectivity, and functioning that are, in part, dependent on one's... Show moreThe brain undergoes profound development across childhood and adolescence, including continuous changes in brain morphology, connectivity, and functioning that are, in part, dependent on one's experiences. These neurobiological changes are accompanied by significant changes in children's and adolescents' cognitive learning. By drawing from studies in the domains of reading, reinforcement learning, and learning difficulties, we present a brief overview of methodological approaches and research designs that bridge brain- and behavioral research on learning. We argue that ultimately these methods and designs may help to unravel questions such as why learning interventions work, what learning computations change across development, and how learning difficulties are distinct between individuals. Show less
Ma, I.; Westhoff, B.; Duijvenvoorde, A.C.K. van 2022
Adolescence is a key life phase for developing well-adjusted social behaviour. An essential component of well-adjusted social behaviour is the ability to update our beliefs about the... Show moreAdolescence is a key life phase for developing well-adjusted social behaviour. An essential component of well-adjusted social behaviour is the ability to update our beliefs about the trustworthiness of others based on gathered information. Here, we examined how adolescents (n = 157, 10–24 years) sequentially sampled information about the trustworthiness of peers and how they used this information to update their beliefs about others’ trustworthiness. Our Bayesian computational modelling approach revealed an adolescence-emergent increase in uncertainty of prior beliefs about others’ trustworthiness. As a consequence, early to mid-adolescents (ages 10–16) gradually relied less on their prior beliefs and more on the gathered evidence when deciding to sample more information, and when deciding to trust. We propose that these age-related differences could be adaptive to the rapidly changing social environment of early and mid-adolescents. Together, these findings contribute to the understanding of adolescent social development by revealing adolescent-emergent flexibility in prior beliefs about others that drives adolescents’ information sampling and trust decisions. Show less
The overarching goal of this thesis was to examine the behavioral, computational, and neural mechanisms underlying social learning in adolescence. The first aim was to examine developmental... Show moreThe overarching goal of this thesis was to examine the behavioral, computational, and neural mechanisms underlying social learning in adolescence. The first aim was to examine developmental patterns across adolescence of two forms of social learning: (1) learning about other people, specifically, whether they are (un)cooperative and (un)trustworthy, and (2) learning for other people (prosocial learning) to know what actions may benefit or help others. I made use of multiple experimental paradigms based on well-known economic games and/or probabilistic reinforcement learning paradigms to assess these forms of social learning. Secondly, I aimed to examine underlying mechanisms and factors that account for age-related and individual differences in social learning. Applying computational modeling and functional neuroimaging as additional tools contributed to a better understanding of the underlying mechanisms and how these develop across adolescence. The findings in this thesis converge to early-to-mid adolescence as a key developmental period for developing well-adjusted social behaviors, and especially in the cooperative domain there are pronounced improvements. These studies make an important contribution to the literature on social development and learning, and may eventually contribute to interventions targeted at promoting well-adjusted behavior in typically developing adolescents, as well as youth with maladaptive social tendencies. Show less
Learning which of our behaviors benefit others contributes to forming social relationships. An important period for the development of (pro)social behavior is adolescence, which is characterized by... Show moreLearning which of our behaviors benefit others contributes to forming social relationships. An important period for the development of (pro)social behavior is adolescence, which is characterized by transitions in social connections. It is, however, unknown how learning to benefit others develops across adolescence and what the underlying cognitive and neural mechanisms are. In this functional neuroimaging study, we assessed learning for self and others (i.e., prosocial learning) and the concurring neural tracking of prediction errors across adolescence (ages 9-21, N = 74). Participants performed a two-choice probabilistic reinforcement learning task in which outcomes resulted in monetary consequences for themselves, an unknown other, or no one. Participants from all ages were able to learn for themselves and others, but learning for others showed a more protracted developmental trajectory. Prediction errors for self were observed in the ventral striatum and showed no age-related differences. However, prediction error coding for others showed an age-related increase in the ventromedial prefrontal cortex. These results reveal insights into the computational mechanisms of learning for others across adolescence, and highlight that learning for self and others show different age-related patterns. Show less
Westhoff, B.; Molleman, L.; Viding, E.; Bos, W. van den; Duijvenvoorde, A.C.K. van 2020
Learning to successfully navigate social environments is a critical developmental goal, predictive of long-term wellbeing. However, little is known about how people learn to adjust to different... Show moreLearning to successfully navigate social environments is a critical developmental goal, predictive of long-term wellbeing. However, little is known about how people learn to adjust to different social environments, and how this behaviour emerges across development. Here, we use a series of economic games to assess how children, adolescents, and young adults learn to adjust to social environments that differ in their level of cooperation (i.e., trust and coordination). Our results show an asymmetric developmental pattern: adjustment requiring uncooperative behaviour remains constant across adolescence, but adjustment requiring cooperative behaviour improves markedly across adolescence. Behavioural and computational analyses reveal that age-related differences in this social learning are shaped by age-related differences in the degree of inequality aversion and in the updating of beliefs about others. Our findings point to early adolescence as a phase of rapid change in cooperative behaviours, and highlight this as a key developmental window for interventions promoting well-adjusted social behaviour. Show less
Westhoff, B.; Koele, I.J.; Groep, I.H. van de 2020
When you think about learning, you probably think about things you are taught at school. But have you ever realized you use a different type of learning as well, on a daily basis? This type of... Show moreWhen you think about learning, you probably think about things you are taught at school. But have you ever realized you use a different type of learning as well, on a daily basis? This type of learning is called social learning, and it has to do with the people around you. That is, you learn from and about others by watching and interacting with them. For example, seeing someone else’s mistakes may teach you to avoid falling into the same trap. Although social learning happens very often, you may not yet know much about it. However, social learning is very important because it helps us to learn more efficiently and to determine how best to behave around others. In this article, we introduce two different types of social learning, and explain how your brain plays an important role. Show less
Adolescence is the transitional period between childhood and adulthood, characterized by substantial changes in reward-driven behavior. Although reward-driven behavior is supported by subcortical... Show moreAdolescence is the transitional period between childhood and adulthood, characterized by substantial changes in reward-driven behavior. Although reward-driven behavior is supported by subcortical-medial prefrontal cortex (PFC) connectivity, the development of these circuits is not well understood. Particularly, while puberty has been hypothesized to accelerate organization and activation of functional neural circuits, the relationship between age, sex, pubertal change, and functional connectivity has hardly been studied. Here, we present an analysis of resting-state functional connectivity between subcortical structures and the medial PFC, in 661 scans of 273 participants between 8 and 29 years, using a three-wave longitudinal design. Generalized additive mixed model procedures were used to assess the effects of age, sex, and self-reported pubertal status on connectivity between subcortical structures (nucleus accumbens, caudate, putamen, hippocampus, and amygdala) and cortical medial structures (dorsal anterior cingulate, ventral anterior cingulate, subcallosal cortex, frontal medial cortex). We observed an age-related strengthening of subcortico-subcortical and cortico-cortical connectivity. Subcortical-cortical connectivity, such as, between the nucleus accumbens-frontal medial cortex, and the caudate-dorsal anterior cingulate cortex, however, weakened across age. Model-based comparisons revealed that for specific connections pubertal development described developmental change better than chronological age. This was particularly the case for changes in subcortical-cortical connectivity and distinctively for boys and girls. Together, these findings indicate changes in functional network strengthening with pubertal development. These changes in functional connectivity may maximize the neural efficiency of interregional communication and set the stage for further inquiry of biological factors driving adolescent functional connectivity changes. Show less
Adolescence is the transitional period between childhood and adulthood, characterized by substantial changes in reward-driven behavior. Although reward-driven behavior is supported by subcortical... Show moreAdolescence is the transitional period between childhood and adulthood, characterized by substantial changes in reward-driven behavior. Although reward-driven behavior is supported by subcortical-medial prefrontal cortex (PFC) connectivity, the development of these circuits is not well understood. Particularly, while puberty has been hypothesized to accelerate organization and activation of functional neural circuits, the relationship between age, sex, pubertal change, and functional connectivity has hardly been studied. Here, we present an analysis of resting-state functional connectivity between subcortical structures and the medial PFC, in 661 scans of 273 participants between 8 and 29 years, using a three-wave longitudinal design. Generalized additive mixed model procedures were used to assess the effects of age, sex, and self-reported pubertal status on connectivity between subcortical structures (nucleus accumbens, caudate, putamen, hippocampus, and amygdala) and cortical medial structures (dorsal anterior cingulate, ventral anterior cingulate, subcallosal cortex, frontal medial cortex). We observed an age-related strengthening of subcortico-subcortical and cortico-cortical connectivity. Subcortical-cortical connectivity, such as, between the nucleus accumbens-frontal medial cortex, and the caudate-dorsal anterior cingulate cortex, however, weakened across age. Model-based comparisons revealed that for specific connections pubertal development described developmental change better than chronological age. This was particularly the case for changes in subcortical-cortical connectivity and distinctively for boys and girls. Together, these findings indicate changes in functional network strengthening with pubertal development. These changes in functional connectivity may maximize the neural efficiency of interregional communication and set the stage for further inquiry of biological factors driving adolescent functional connectivity changes. Show less
