What are the changes that you have experienced from childhood to adolescence?

Adolescence is a period of significant development that begins with the onset of puberty1 and ends in the mid-20s. Consider how different a person is at the age of 12 from the person he or she is at age 24. The trajectory between those two ages involves a profound amount of change in all domains of development—biological, cognitive, psychosocial, and emotional. Personal relationships and settings also change during this period, as peers and romantic partners become more central and as the adolescent moves into and then beyond secondary school or gains employment.

Importantly, although the developmental plasticity that characterizes the period makes adolescents malleable, malleability is not synonymous with passivity. Indeed, adolescents are increasingly active agents in their own developmental process. Yet, as they explore, experiment, and learn, they still require scaffolding and support, including environments that bolster opportunities to thrive. A toxic environment makes healthy adolescent development challenging. Ultimately, the transformations in body, brain, and behavior that occur during adolescence interact with each other and with the environment to shape pathways to adulthood.

Each stage of life depends on what has come before it, and young people certainly do not enter adolescence with a “blank slate.” Rather, adolescent development is partly a consequence of earlier life experiences. However, these early life experiences are not determinative, and the adaptive plasticity of adolescence marks it as a window of opportunity for change through which mechanisms of resilience, recovery, and development are possible. (Chapter 3 discusses this life-course perspective on development in detail.) This chapter explores three key domains of adolescent development: puberty, neurobiological development, and psychosocial development. Within each domain, we highlight processes that reflect the capacity for adaptive plasticity during adolescence and beyond, marking adolescence as a period of unique opportunity for positive developmental trajectories.

NEUROBIOLOGICAL DEVELOPMENT

Adolescence is a particularly dynamic period of brain development, second only to infancy in the extent and significance of the neural changes that occur. The nature of these changes—in brain structures, functions, and connectivity—allows for a remarkable amount of developmental plasticity unique to this period of life, making adolescents amenable to change.4 These normative developments are required to prepare the brain so it can respond to the demands and challenges of adolescence and adulthood, but they may also increase vulnerability for risk behavior and psychopathology (Paus et al., 2008; Rudolph et al., 2017). To understand how to take advantage of this versatile adolescent period, it is first important to recognize how and where the dynamic changes in the brain are taking place; shows structures and regions of the brain that have been the focus of adolescent developmental neuroscience.

FIGURE 2-2

Brain areas important to adolescent development. SOURCE: iStock.com/James Kopp.

In the following sections, we summarize current research on structural and functional brain changes taking place over the course of adolescence. Our summary begins with a focus on morphological changes in gray and white matter, followed by a discussion of structural changes in regions of the brain that have particular relevance for adolescent cognitive and social functioning. We then discuss current theoretical perspectives that attempt to account for the associations between neurobiological, psychological, and behavioral development in adolescence.

Notably, the field of adolescent neuroscience has grown quickly over the past several decades. Advances in technology continue to provide new insights into neurobiological development; however, there is still a lack of agreed-upon best practices, and different approaches (e.g., in equipment, in statistical modeling) can result in different findings (Vijayakumar et al., 2018). Our summary relies on the most recent evidence available and, per the committee's charge, we focus on neurobiological changes that make adolescence a period of unique opportunity for positive development. This is not intended to be an exhaustive review of the literature; moreover, studies tend to use “typically” developing adolescents, which limits our ability to comment on whether or how these processes may change for young people with developmental delays or across a broader spectrum of neurodiversity.

High Plasticity Marks the Window of Opportunity

Studies of adolescent brain development have traditionally focused on two important processes: changes in gray matter and changes in myelin. Gray matter is comprised of neural cell bodies (i.e., the location of each nerve cell's nucleus), dendrites, and all the synapses, which are the connections between neurons. Thus, increases or decreases in gray matter reflect changes in these elements, representing, for instance, the formation or disappearance of synapsis (also known as “synaptogenesis” and “synaptic pruning”). New learning and memories are stored in dynamic synaptic networks that depend equally on synapse elimination and synapse formation. That is, unused connections and cells must be pruned away as the brain matures, specializes, and tailors itself to its environment (Ismail et al., 2017).

White matter, on the other hand, is comprised of myelin. Myelin is the fatty sheath around the long projections, or axons, that neurons use to communicate with other neurons. The fatty myelin insulates the axonal “wire” so that the signal that travels down it can travel up to 100 times faster than it can on unmyelinated axons (Giedd, 2015). With myelination, neurons are also able to recover quickly from firing each signal and are thereby able to increase the frequency of information transmission (Giedd, 2015). Not only that, myelinated neurons can more efficiently integrate information from other input neurons and better coordinate their signaling, firing an outgoing signal only when information from all other incoming neurons is timed correctly (Giedd, 2015). Thus, the increase in white matter is representative of the increase in quality and speed of neuron-to-neuron communication throughout adolescence. This is comparable to upgrading from driving alone on a single-lane dirt road to driving on an eight-lane paved expressway within an organized transportation/transit authority system, since it increases not only the amount of information trafficked throughout the brain but also the brain's computational power by creating more efficient connections.

Recent advances in neuroimaging methods have greatly enhanced our understanding of adolescent brain development over the past three decades. In the mid-2000s developmental neuroscientists described differential changes in gray matter (i.e., neurons) and white matter (i.e., myelin) over the course of adolescence. Specifically, gray-matter volume was believed to follow an inverted-U shape, peaking in different regions at different ages and declining over the course of late adolescence and adulthood (Lenroot and Giedd, 2006). In contrast, cortical white matter, which reflects myelin growth, was shown to increase steadily throughout adolescence and into early adulthood, reflecting increased connectivity among brain regions (Lenroot and Giedd, 2006). The proliferation of neuroimaging studies, particularly longitudinal studies following children over the course of adolescence, has enabled researchers to examine these processes in more detail and across a larger number of participants (Vijayakumar et al., 2018).

Analyses of about 850 brain scans from four samples of participants ranging in age from 7 to 29 years (average = 15.2 years) confirm some previous trends, disconfirm others, and highlight the complexity in patterns of change over time. Researchers found that gray-matter volume was highest in childhood, decreased across early and middle adolescence, and began to stabilize in the early twenties; this pattern held even after accounting for intracranial and whole brain volume (Mills et al., 2016). Additional studies of cortical volume have also documented the highest levels occurring in childhood with decreases from late childhood throughout adolescence; the decrease appears to be due to the thinning of the cortex (Tamnes et al., 2017). Importantly, this finding contrasts with the “inverted-U shape” description of changes in gray-matter volume and disconfirms previous findings of a peak during the onset of puberty (Mills et al., 2016).

For white-matter volume, on the other hand, researchers found that across samples, increases in white-matter volume occurred from childhood through mid-adolescence and showed some stabilizing in late adolescence (Mills et al., 2016). This finding generally confirms patterns observed in other recent studies, with the exception that some researchers have found continued increases in white-matter volume into early adulthood (versus stabilizing in late adolescence; e.g., Aubert-Broche et al., 2013). shows these recent findings related to gray and white matter.

FIGURE 2-3

Cortical gray- and white-matter volume, ages 5 to 30. NOTES: Age in years is measured along the x-axis and brain measure along the y-axis (raw values (mm3). Best fitting models are represented by the solid lines. Dashed lines represent 95-percent confidence (more...)

The widely held belief about a peak in cortical gray matter around puberty followed by declines throughout adolescence was based on the best available evidence at the time. New studies show steady declines in cortical volume beginning in late childhood and continuing through middle adolescence. While the decrease in volume is largely due to cortical thinning rather than changes in surface area, there appear to be complex, regionally specific associations between cortical thickness and surface area that change over the course of adolescence (Tamnes et al., 2017). Discrepant findings can be attributed to a number of factors including head motion during brain imaging procedures (more common among younger participants), different brain imaging equipment, and different approaches to statistical modeling (Tamnes et al., 2017; Vijayakumar et al., 2018). There do appear to be converging findings regarding overall directions of change; however, inconsistencies in descriptions of trajectories, peaks, and regional changes will likely continue to emerge as researchers work toward agreed-upon best practices (Vijayakumar et al., 2018). Importantly, though, as Mills and colleagues (2016, p. 279) point out, it is critical to acknowledge that “it is not possible to directly relate developmental changes in morphometric MRI measures to changes in cellular or synaptic anatomy” (also see Mills and Tamnes, 2014). In other words, patterns of change in overall gray- or white-matter volume do not provide insight into the specific ways in which neural connections (e.g., synapses, neural networks) may change within the adolescent brain.

In fact, some neural circuity, consisting of networks of synaptic connections, is extremely malleable during adolescence, as connections form and reform in response to a variety of novel experiences and stressors (Ismail et al., 2017; Selemon, 2013). Gray-matter reduction in the cortex is associated with white-matter organization, indicating that cortical thinning seen in adulthood may be a result of both increased connectivity of necessary circuitry and pruning of unnecessary synapses (Vandekar et al., 2015). Thus, adolescent brains can modulate the strength and quality of neuronal connections rapidly to allow for flexibility in reasoning and for leaps in cognition (Giedd, 2015).

Structural Changes in the Adolescent Brain

Two key neurodevelopmental processes are most reliably observed during adolescence. First, there is evidence of significant change and maturation in regions of the prefrontal cortex (PFC) involved in executive functioning and cognitive and impulse control capabilities (Crone and Steinbeis, 2017; Steinberg, 2005). In other words, areas of the brain that support planning and decision-making develop significantly during the second decade of life. Second, there is evidence of improved connectivity5 within and between the cortical (i.e., outer) and subcortical (i.e., inner) regions of the brain. Moreover, in both the cortical and subcortical regions, there are age-related and hormone-related changes in neural activity and structure, such as increased volume and connectivity (Gogtay et al., 2004; Østby et al., 2009; Peper and Dahl, 2013; Wierenga et al., 2014).

Over the course of adolescence, regions of the PFC undergo protracted development and significant remodeling. Cortical circuits, especially those that inhibit behavior, continue to develop, enhancing adolescents' capacity for self-regulation (Caballero and Tseng, 2016). Compared to adults, adolescents have a significantly less mature cortical system and tend to utilize these regions less efficiently, and this impacts their top-down cognitive abilities including planning, working memory, impulsivity control, and decision-making (Casey and Caudle, 2013). Ongoing development of structures and connections within the cortical regions corresponds to more efficient balancing of inputs and outputs as adolescents interact with the world.

Changes within subcortical brain regions are also reflected in adolescent capabilities. For instance, increased volume in certain subregions of the hippocampus may predict greater capacity for memory recall and retention in adolescents (Tamnes et al., 2014). Adolescents also display heightened activity in the hippocampus, compared with adults, and differential reward processing in the striatum, which is part of the basal ganglia and plays an important role in motivation and perception of reward. This neural activity may explain their increased sensitivity to rewards and contribute to their greater capacity for learning and habit formation, particularly when incentivized by positive outcomes (Davidow et al., 2016; Sturman and Moghaddam, 2012).

Another subcortical structure, the amygdala, undergoes significant development during puberty and gains new connections to other parts of the brain, such as the striatum and hippocampus (Scherf et al., 2013). The amygdala modulates and integrates emotional responses based on their relevance and impact in context. In conjunction with the amygdala's substantial development, adolescents show higher amygdala activity in response to threat cues6 than do children or adults (Fuhrmann et al., 2015; Hare et al., 2008; Pattwell et al., 2012). Consequently, they are prone to impulsive action in response to potential threats7 (Dreyfuss et al., 2014). Changes in the hippocampus and amygdala may be responsible for suppressing fear responses in certain contexts (Pattwell et al., 2011). Such fearlessness can be adaptive for adolescents as they explore new environments and make important transitions—such as entering college or starting a new job away from home. Children and adults do not tend to show the same kind of fear suppression as adolescents, suggesting that this is unique to this stage of development (Pattwell et al., 2011).

A Neurodevelopmental Perspective on Risk-Taking

In recent years, researchers have worked to reconcile contemporary neuroscience findings with decades of behavioral research on adolescents. There has been a particular emphasis on understanding “risky” behavior through the lens of developmental neuroscience. Risk-taking can be driven by a tendency for sensation-seeking, in which individuals exhibit an increased attraction toward novel and intense sensations and experiences despite their possible risks (Steinberg, 2008; Zuckerman and Kuhlman, 2000). This characteristic is heightened during adolescence and is strongly associated with reward sensitivity and drive (Cservenka et al., 2013) as well as the rise in dopamine pathways from the subcortical striatum to the PFC (Wahlstrom et al., 2010). Ironically, as executive function improves, risk-taking based on sensation-seeking also rises, likely due to these strengthened dopamine pathways from the striatum to the PFC regions (Murty et al., 2016; Wahlstrom et al., 2010). Despite these stronger sensation-seeking tendencies, however, by mid-adolescence most youth are able to perform cognitive-control tasks at the same level as adults, signaling their capacity for executive self-control (Crone and Dahl, 2012).

Risk-taking can also be driven by impulsivity, which includes the tendency to act without thinking about consequences (impulsive action) or to choose small, immediate rewards over larger, delayed rewards (impulsive choice) (Romer et al., 2017). Impulsive action, which is based on insensitivity to risk, is a form of risk-taking that peaks during early adolescence and is inversely related to working memory ability (Romer et al., 2011). It may also be a consequence of asynchronous limbic-PFC maturation, which is described below. Notably, impulsive actions are seen most frequently in a subgroup of adolescents with pre-existing impairment in self-control and executive function (Bjork and Pardini, 2015). In contrast, impulsive choice behaviors, which are made under conditions of known risks and rewards, do not peak in adolescence. Instead, impulsive choice declines from childhood to adulthood, reflecting the trend of increasing, prefrontal-regulated executive functions throughout adolescence (van den Bos et al., 2015). Interestingly, when given the choice between two risky options with ambiguous reward guarantees, adolescents are more inclined to explore the riskier option than are adults (Levin and Hart, 2003), showing a greater tolerance for ambiguities in reward and stronger exploratory drive (Tymula et al., 2012).

Theoretical models have emerged to explain how neurobiological changes map onto normative “risk” behaviors in adolescence. While some argue that these models and accompanying metaphors may be overly simplistic (e.g., Pfeifer and Allen, 2012), the models are nevertheless utilized frequently to guide and interpret research (e.g., Steinberg et al., 2018). We briefly discuss two of them here: the “dual systems” model and the “imbalance” model.

The “dual systems” model (Shulman et al., 2016; Steinberg, 2008) represents “the product of a developmental asynchrony between an easily aroused reward system, which inclines adolescents toward sensation seeking, and still maturing self-regulatory regions, which limit the young person's ability to resist these inclinations” (Steinberg et al., 2018). The “reward system” references subcortical structures, while the “self-regulatory regions” refer to areas like the PFC. Proponents of the dual-systems model point to recent findings on sensation seeking and self-regulation from a study of more than 5,000 young people spanning ages 10 to 30 across 11 countries. A similar pattern emerged across these settings. In 7 of 11 countries there was a peak in sensation seeking in mid-to-late adolescence (around age 19) followed by a decline. Additionally, there was a steady rise in self-regulation during adolescence; self-regulation peaked in the mid-20s in four countries and continued to rise in five others. The researchers note that there were more similarities than differences across countries and suggest that the findings provide strong support for a dual-systems account of sensation seeking and self-regulation in adolescence.

A second model, the “imbalance” model, shifts the focus away from an orthogonal, dual systems account and instead emphasizes patterns of change in neural circuitry across adolescence. This fine-tuning of circuits is hypothesized to occur in a cascading fashion, beginning within subcortical regions (such as those within the limbic system), then strengthening across regions, and finally occurring within outer areas of the brain like the PFC (Casey et al., 2016). This model corresponds with observed behavioral and emotional regulation—over time, most adolescents become more goal-oriented and purposeful, and less impulsive (Casey, 2015). Proponents of the imbalance model argue that it emphasizes the “dynamic and hierarchical development of brain circuitry to explain changes in behavior throughout adolescence” (Casey et al., 2016, p. 129). Moreover, they note that research stemming from this model focuses less on studying specific regions of the brain and more on how information flows within and between neural circuits, as well as how this flow of information shifts over the course of development (e.g., “temporal changes in functional connectivity within and between brain circuits,” p. 129).

Rethinking the “Mismatch” Between the Emotional and Rational Brain Systems

Regardless of whether one of these two models more accurately represents connections between adolescent neurobiological development and behavior, both perspectives converge on the same point: fundamental areas of the brain undergo asynchronous development throughout adolescence. Moreover, adolescent behavior, especially concerning increased risk-taking and still-developing self-control, has been notably attributed to asynchronous development within and between subcortical and cortical regions of the brain. The former drives emotion, and the latter acts as the control center for long-term planning, consideration of outcomes, and level-headed regulation of behavior (Galván et al., 2006; Galván, 2010; Mueller et al., 2017; Steinbeis and Crone, 2016). Thus, if connections within the limbic system develop faster than those within and between the PFC region,8 the imbalance may favor a tendency toward heightened sensitivity to peer influence, impulsivity, risk-taking behaviors, and emotional volatility (Casey and Caudle, 2013; Giedd, 2015; Mills et al., 2014).

Indeed, adolescents are more impulsive in response to positive incentives than children or adults, although they can suppress these impulses when large rewards are at stake. Adolescents are also more sensitive than children or adults to the presence of peers and to other environmental cues, and show a heightened limbic response to threats (Casey, 2015). As the cortical regions continue to develop and activity within and across brain regions becomes more synchronized, adolescents gain the capacity to make rational, goal-directed decisions across contexts and conditions.

The idea of asynchrony or “mismatch” between the pace of subcortical development and cortical development implies that these developmental capacities are nonoptimal. Yet, even though they are associated with impulsivity and risk-taking, we should not jump to the conclusion that the gap in maturation between the emotion and control centers of the brain is without developmental benefit. As Casey (2015, p. 310) notes, “At first glance, suggesting that a propensity toward motivational or emotional cues during adolescence is adaptive may seem untenable. However, a heightened activation into action by environmental cues and decreased apparent fear of novel environments during this time may facilitate evolutionarily appropriate exploratory behavior.” While an adolescent's “heart over mind” mentality may compromise judgment and facilitate unhealthy behaviors, it can also spawn creativity and exploration. Novelty seeking can be a boon to adolescents, spurring them to pursue exciting, new directions in life (Spear, 2013).

If properly monitored and cushioned by parents and the community, adolescents can learn from missteps and take advantage of what can be viewed as developmental opportunities. Indeed, because adolescents are more sensitive to rewards and their decision-making ability may skew more toward seeking the positive benefits of a choice and less toward avoiding potential risks, this tendency can enhance learning and drive curiosity (Davidow et al., 2016). To avoid stereotyping all adolescents as “underdeveloped” or “imbalanced,” it is important to recognize the nuances in the different types of risk-taking behavior and to counterbalance a focus on negative outcomes by observing the connections between risk-taking and exploration, curiosity, and other attributes of healthy development (Romer et al., 2017).

The “mismatch” model provides one way of understanding adolescents' capacity for self-control and involvement in risky behavior. A better model of adolescent neurobiological development, some argue, is a “lifespan wisdom model,” prioritizing the significance of experience on brain maturation that can only be gained through exploration (Romer et al., 2017). Indeed, growing evidence shows that adolescents have a distinctive ability for social and emotional processing that allows them to adapt readily to the capricious social contexts of adolescence, and equips them with flexibility in adjusting their motivations and prioritizing new goals (Crone and Dahl, 2012; Nigg and Nagel, 2016).

Despite differences between neurobiological models, there is agreement that distinctions between adolescent and adult behaviors necessitate policies and opportunities intended to address adolescent-specific issues. With their heightened neurocognitive capacity for change, adolescents are in a place of both great opportunity and vulnerability. Key interventions during this period may be able to ameliorate the impact of negative experiences earlier in life, providing many adolescents with a pivotal second chance to achieve their full potential and lead meaningful, healthy, and successful lives (Guyer et al., 2016; see also Chapter 3).

Cognitive Correlates of Adolescent Brain Development

Reflective of the ongoing changes in the brain described above, most teens become more efficient at processing information, learning, and reasoning over the course of adolescence (Byrnes, 2003; Kuhn, 2006, 2009). The integration of brain regions also facilitates what is called “cognitive control,” the ability to think and plan rather than acting impulsively (Casey, 2015; Casey et al., 2016; Steinberg, 2014).

Changes in components of cognitive control, such as response selection/inhibition and goal selection/maintenance, along with closely associated constructs such as working memory, increase an individual's capacity for self-regulation of affect and behavior (Ochsner and Gross, 2005). Importantly, each of these aspects of cognitive control appears to have distinct developmental trajectories, and each may be most prominently associated with distinct underlying regions of the cortex (Crone and Steinbeis, 2017). For example, although the greatest developmental improvements in response inhibition and interference control may be observed prior to adolescence, improvements in flexibility, error monitoring, and working memory are more likely to occur throughout the second decade of life (Crone and Steinbeis, 2017). This suggests different developmental trajectories, whereby more basic, stimulus-driven cognitive control processes develop earlier than do more complex cognitive control processes, which rely on internal and abstract representation (Crone and Steinbeis, 2017; Dumontheil et al., 2008).

Those functions that do continue to show significant developmental change during adolescence seem to especially rely on the capacity for abstract representation, which is a capacity that has been found to undergo a distinctive increase during adolescence (Dumontheil, 2014). The capacity for abstract representation can relate to both temporal and relational processes, that is, to both long-term goals and to past or future events (temporal) and to representing higher-order relationships between representations (relational) as distinct from simple stimulus features (Dumontheil, 2014). From early through late adolescence (into adulthood), this increase in abstract thinking ability makes teens better at using evidence to draw conclusions, although they still have a tendency to generalize based on personal experience—something even adults do. Adolescents also develop greater capacity for strategic problem-solving, deductive reasoning, and information processing, due in part to their ability to reason about ideas that may be abstract or untrue; however, these skills require scaffolding and opportunities for practice (Kuhn, 2009).

Recent research on cognitive development during adolescence has focused on both cognitive and emotional (or “affective”) processing, particularly to understand how these processes interact with and influence each other in the context of adolescent decision making. First, the capacity for abstract representation and for affective engagement with such representations (Davey et al., 2008) increases the capacity for self-regulation of emotions in order to achieve a goal (Ochsner and Gross, 2005). Indeed, the capacity to regulate a potent, stimulus-driven, short-term response may rely on the ability to mentally represent and affectively engage with a longer-term goal. Furthermore, such stimulus-driven, affective influences on cognitive processing, including on decision making, risk-taking, and judgment, change significantly over the course of adolescence (Hartley and Somerville, 2015; Steinberg, 2005).

Beyond individual capacities for cognitive regulation, the social and emotional context for cognitive processing matters a great deal. The presence of peers and the value of performing a task influence how motivating certain contexts may be and the extent to which cognitive processing is recruited (Johnson et al., 2009). Moreover, there is increasing evidence that some of these changes in cognitive and affective processing are linked to the onset of puberty (Crone and Dahl, 2012). Researchers have found that adolescents do better than young adults on learning and memory tasks when the reward systems of the brain are engaged (Davidow et al., 2016).

These changes in cognitive functioning may have adaptive qualities as part of normative adolescent development, even though they also make some individuals more vulnerable to psychopathology, such as depression and anxiety disorders. Notably, the flexibility of the frontal cortical network may be greater in adolescence than in adulthood (Jolles and Crone, 2012). Such flexibility may result in an improved ability to learn to navigate the increasingly complex social challenges that are part of adolescents' social worlds, and as adolescents encounter increasing opportunities for autonomy it may prove to be adaptive. In addition, the ability to shift focus in a highly motivated way could allow more learning, problem solving, and use of creativity (Kleibeuker et al., 2016). Of particular relevance, such emerging abilities may also determine the degree to which an individual can take advantage of new learning opportunities, including mental health–promoting interventions. With the right supports, this capacity for flexibility and adaptability can foster deep learning, complex problem-solving skills, and creativity (Crone and Dahl, 2012; Hauser et al., 2015; Kleibeuker et al., 2012).

Summary

The extensive neurobiological changes in adolescence enable us to reimagine this period as one of remarkable opportunity for growth. Connections within and between brain regions become stronger and more efficient, and unused connections are pruned away. Such developmental plasticity means adolescents' brains are adaptive; they become more specialized in response to environmental demands. The timing and location of the dynamic changes are also important to understand. The onset of puberty, often between ages 10 and 12, brings about changes in the limbic system region resulting in increased sensitivity to both rewards and threats, to novelty, and to peers. In contrast, it takes longer for the cortical regions, implicated in cognitive control and self-regulation, to develop (Steinberg et al., 2018).

Adolescent brains are neither simply “advanced” child brains, nor are they “immature” adult brains—they are specially tailored to meet the needs of this stage of life (Giedd, 2015). Indeed, the temporal discrepancy in the specialization of and connections between cortical and subcortical brain regions makes adolescence unique. The developmental changes heighten sensitivity to reward, willingness to take risks, and the salience of social status, propensities that are necessary for exploring new environments and building nonfamilial relationships. Adolescents must explore and take risks to build the cognitive, social, and emotional skills they will need to be productive adults. Moreover, the unique and dynamic patterns of brain development in adolescence foster flexible problem-solving and learning (Crone and Dahl, 2012). Indeed, adolescence is a seminal period for social and motivational learning (Fuligni, 2018), and this flexibility confers opportunity for adaptability and innovation.

While developmental plasticity in adolescence bears many advantages, as with all aspects of development the environment matters a great deal. The malleable brains of adolescents are not only adaptable to innovation and learning but also vulnerable to toxic experiences, such as resource deprivation, harsh, coercive or antisocial relationships, and exposure to drugs or violence. All of these can “get under the skin” as adolescents develop, or more precisely interact with the brain and body to influence development (see Chapter 3).

What is more, the majority of mental illnesses—including psychotic and substance use disorders—begin by age 24 (Casey, 2015; Giedd, 2015). This means that we have a collective responsibility to ask, “How can we create the kinds of settings and supports needed to optimize development during this period of life?” This goes well beyond simply keeping youth out of harm's way, and instead signals an urgent need to consider how we design the systems with which adolescents engage most frequently to meet their developmental needs. Notably, scholars studying adolescent developmental neuroscience suggest the next generation of research should consider questions that shift from understanding risk to understanding thriving, and context-specific opportunities to promote it. Such questions for the field include, “How does brain development create unique opportunities for learning and problem solving?,” “Is the adolescent brain more sensitive to some features of the social environment than others?,” and “Are trajectories of change [in cognitive control and emotional processing] steeper or quicker during some periods than others, potentially providing key windows for input and intervention?” (Fuligni et al., 2018, p. 151).

What are the changes from childhood to adolescence?

What are the changes experienced during adolescence?

What are the changes and development in adolescence?