Sensitive periods of substance abuse: Early risk for the transition to dependence (2017)

Chloe J. Jordan^* and Susan L. Andersen

Early adolescent substance use dramatically increases the risk of lifelong substance use disorder (SUD). An adolescent sensitive period evolved to allow the development of risk-taking traits that aid in survival; today these may manifest as a vulnerability to drugs of abuse. Early substance use interferes with ongoing neurodevelopment to induce neurobiological changes that further augment SUD risk. Although many individuals use drugs recreationally, only a small percentage transition to SUD. Current theories on the etiology of addiction can lend insights into the risk factors that increase vulnerability from early recreational use to addiction. Building on the work of others, we suggest individual risk for SUD emerges from an immature PFC combined with hyper-reactivity of reward salience, habit, and stress systems. Early identification of risk factors is critical to reducing the occurrence of SUD. We suggest preventative interventions for SUD that can be either tailored to individual risk profiles and/or implemented broadly, prior to the sensitive adolescent period, to maximize resilience to developing substance dependence. Recommendations for future research include a focus on the juvenile and adolescent periods as well as on sex differences to better understand early risk and identify the most efficacious preventions for SUD.

4.1. Evidence for sensitive periods of substance abuse in humans

Evidence indicates that drug exposure beginning in early adolescence can increase the risk of SUD long-term (Chambers et al., 2003; Grant, 1998). Predisposing risk factors, including impulsivity, exposure to early adversity, or other pre-existing conditions (such as attention deficit hyperactivity disorder [ADHD] and conduct disorder) may lead to early-onset drug use if not addressed (Enoch, 2011; Mannuzza et al., 2008; Verdejo-Garcia et al., 2008). However, individuals with ADHD who receive early treatment show the same age-related elevated rates of SUD as age-matched community controls (Mannuzza et al., 2008; Steinhausen and Bisgaard, 2014; Wilens et al., 2003). In other words, medication does not seem to increase risk of substance use when initiated early (Molina et al., 2013; Volkow and Swanson, 2008). While these former results have been shown in longitudinal studies, cross-sectional studies demonstrate a different relationship between impulsivity and marijuana use, such that early-onset use (<16 years of age) may be associated with elevated impulsivity (Gruber et al., 2014). Epidemiology studies further indicate that adolescent use of alcohol, marijuana, and cocaine adolescent increase the risk of substance dependence (Wagner and Anthony, 2002). Findings such as these raise more questions—does early drug use lead to impulsivity? Do different drugs have different long-term effects on the brain and subsequent SUD vulnerability? The prospective ABCD initiative of the NIH (abcdstudy.org) will help answer some of these issues surrounding early drug exposure.

Disentangling the cause-and-effect of SUD from individual risk factors is difficult due to shared neural substrates. Adolescent networks that underlie impulsivity risk factors are the same as those affected by illicit drugs (Nees et al., 2012; Schneider et al., 2012; Stanger et al., 2013; Whelan et al., 2012). The prefrontal cortex (PFC) does not mature fully until late adolescence or early adulthood (Arain et al., 2013; Barnea-Goraly et al., 2005; Durston et al., 2001; Giedd et al., 1999; Sowell et al., 1999; see Section 5.1), and is pivotal for underlying SUD risk. Substance use during adolescence can induce changes in PFC activity and PFC projections to subcortical regions that persist in adulthood (Squeglia et al., 2009). Brain regions that are influenced by drug exposure depend on their state of maturation when drug exposure occurs (Andersen, 2005; Andersen and Navalta, 2011). For example, adolescent marijuana users show reduced cortical thickness in middle, superior frontal and insular cortices, but increased thickness in more posterior cortical regions such as the superior temporal and inferior parietal cortices, compared to non-users (Lopez-Larson et al., 2011). Moreover, early-onset marijuana use (<16 years) is associated with reduced white matter fiber tract integrity in the corpus callosum compared to later-onset marijuana use (>16 years; Gruber et al., 2014).

4.2. Evidence for sensitive periods of substance abuse in animals

Animal studies have demonstrated that timing of drug exposure matters. Periods of increased vulnerability to stimulant use are evident in rodent models as further evidence for a sensitive adolescent period to substance abuse (Adriani et al., 2004; Baskin et al., 2015; Brandon et al., 2001, 2003; Harvey et al., 2011; Jordan et al., 2014, 2016; Kuhn, 2015; Ruedi-Bettschen et al., 2006; Schramm-Sapyta et al., 2009; Smith, 2003; Wong et al., 2013). For example, in animal models of ADHD, which is often comorbid with SUD in humans (Mannuzza et al., 2008; Steinhausen and Bisgaard, 2014), treatment with stimulant drugs during adolescence (post-natal days [P] 28–55) enhanced the rate to acquire cocaine self-administration, and increases the efficacy and motivating influence of cocaine reinforcement (Baskin et al., 2015; Harvey et al., 2011; Jordan et al., 2014). Gulley and Juraska (2013) provide further review on the long-term effects of adolescent drug exposure.

One mechanism by which adolescent drug exposure may increase the risk of SUD is by altering the developmental trajectory of the PFC and its connections with subcortical regions. In rodents, cocaine exposure in adolescence, but not adulthood, produces a long-lasting attenuation of medial PFC (mPFC) GABAergic activity and parvalbumin cell expression that remains evident in adulthood (Cass et al., 2013). Moreover, binge-like alcohol exposure in adolescent rats reduces adult hippocampus, thalamus, dorsal striatum (STR), and cortex volumes compared to littermate controls (Gass et al., 2014; see Gulley and Juraska, 2013 for further review). Taken together, evidence from both humans and rodents indicates that substance use during the sensitive adolescent period can further exacerbate vulnerability to developing SUD, with long-term impact on cortical and subcortical development.

4.3. Prevention measures: promoting invulnerability to substance abuse

With respect to substance abuse and dependence, an individual may also experience periods of relative invulnerability to the long-term effects of drugs, such as during the juvenile or prepubertal periods (Andersen, 2003, 2005; Stanis and Andersen, 2014). Studies both in humans (Biederman et al., 1999; Mannuzza et al., 2008; Wilens et al., 2003) and in rodents (Adriani et al., 2006b; Andersen et al., 2002a; Bolanos et al., 2003; Carlezon et al., 2003; Thanos et al., 2007) suggest that childhood or prepubertal exposure to stimulants reduces the rewarding properties of drugs of abuse and may protect against SUD later in life. In pre-pubertal children stimulants do not produce rewarding effects (Rapoport et al., 1978). Moreover, in pre-pubertal children exposure to methylphenidate produces an enduring increase in methylphenidate-stimulated blood flow in the STR and thalamus, with no significant change observed in adult-exposed subjects (Schrantee et al., 2016). Similar brain changes were evident in rodent males that were exposed pre-pubertally (P20-35) to methylphenidate (Andersen et al., 2008a). Under these drug exposure conditions, exposure to methylphenidate induced aversions to cocaine-associated environments in a place preference paradigm that is evident in adulthood (Andersen et al., 2002a; Carlezon et al., 2003, but see Crawford et al., 2011). In animals, pre-pubertally established ‘aversions’ to cocaine manifest as a deactivation of the amygdala in response to cocaine-conditioned odors (Lowen et al., 2015; discussed further in Section 5.2). Exposure to psychostimulants may also affect brain morphometry in regions relevant for SUD. In a longitudinal study of cerebral cortex thickness, psychostimulant treatment normalized the ADHD-associated excess cortical thinning during adolescence (Shaw et al., 2007, 2009; van der Marel et al., 2014). Age-dependent effects of methylphenidate treatment on brain morphometry in animals depend on the age of exposure, with a greater impact on corpus callosum white matter and striatal volume following adolescent exposure compared to adults (van der Marel et al., 2014). Together, these data suggest that there is a pre-pubertal window of invulnerability to stimulants, and exposure to stimulants during this window may be protective against the rewarding effects of drugs later in life.

The juvenile period may represent an opportunity to institute preventative interventions for SUD. Pharmacotherapeutic interventions, such as pre-pubertal methylphenidate exposure, can reduce the rewarding properties of drugs later in life (Adriani et al., 2006a; Andersen et al., 2002a; Brenhouse et al., 2009; Carlezon et al., 2003; Thanos et al., 2007). However, caution must be exercised as pharmacotherapies are not without side effects, and variables such as age, sex and duration of treatment can negatively impact SUD vulnerability (Baskin et al., 2015; Brandon et al., 2001, 2003; Brenhouse et al., 2009; Harvey et al., 2011; Jordan et al., 2014; Lambert and Hartsough, 1998; Steinhausen and Bisgaard, 2014). In particular, there is a greater need for research in females. Preclinical research suggests that females experience different long-term effects following pre-pubertal (Brenhouse et al., 2009), pubertal, or even adult exposure to drugs (Dow-Edwards, 2010).

In contrast to pharmacotherapies, behavioral interventions can be broadly applied to young populations with little concern for side effects, and can also be combined with medication to further increase efficacy. We propose that the prevailing theories of the etiology of SUD can inform effective interventions for at-risk individuals. Below we review four SUD theories and suggest behavioral interventions (Table 1) that can be implemented alone or in combination to address specific risk factors for the transition to substance dependence.

 

Table 1

Summary of substance dependence etiology and relevance to adolescents.

5.1. Executive immaturity in adolescence

Substance use disorder is thought to arise in part from a reduced ability to inhibit or control the desire to pursue the rewarding effects of drugs, known as an executive function deficit (Hester et al., 2010). Brain regions associated with executive function include the dorsolateral PFC, the dorsomedial PFC (Curtis and D’Esposito, 2003), the pre-supplementary motor area (Lau et al., 2006) and the ventrolateral PFC (Ridderinkhof et al., 2004; Fig. 2). In the adult brain, the PFC plays an important inhibitory role on subcortical reward and motivational systems (Arnsten and Rubia, 2012; Tekin and Cummings, 2002), including interactions with the striatum (STR) and subthalamic nucleus (STN; Diamond, 2013; Fig. 2).

 

Fig. 2

Neural circuitry underlying adolescent vulnerability to substance use disorder (SUD). Current theories on the etiology of SUD indicate addiction results from an executive function deficit (A), increased incentive salience of drug-related cues (B), and …

5.2. Incentive salience and sensitization

A second theory on the etiology of substance dependence describes a key process in addiction: incentive salience, or the “wanting” or motivated desire attributed by the brain to a rewarding stimulus in the environment (Berridge and Arnsten, 2013; Berridge, 2007, 2009a). During the transition from substance use to dependence, greater incentive salience is attributed to drug-related cues than to other reinforcing environmental cues or conditions (e.g., food, social cues, etc). Thus, over time, motivation to pursue the drug eclipses other needs and drug cues increasingly drive behavior. The salience network has been identified by resting state connectivity fMRI studies, and includes dorsal ACC, OFC, and insular cortex with their strong connectivity to subcortical and limbic structures (Seeley et al., 2007). Other important nodes within the salience network include subcortical sites for emotion, home-ostatic regulation, and reward (see Fig. 2; Ongur and Price, 2000; Seeley et al., 2007). The amygdala in particular plays an integral role in encoding salience, and also maintains conditioned effects after repeated pairing of internal drug sensations with external environmental stimuli (Chang et al., 2012; Meil and See, 1997; Szalay et al., 2013). Over time, conditioned drug cues gain further salience by activating cortical sites. In turn, cortical sites impinge upon reward-associated regions of the NAc, which is associated with wanting of the drug, and the STR, which is associated with habitual drug-seeking/taking behavior.

5.2.2. Evidence from animals

In contrast to executive function, incentive salience can be readily assessed during the brief adolescent period. Adolescents attribute greater incentive salience to rewarding stimuli, including drug-related cues, compared to juveniles or adults. Adolescent rodents form preferences for environments associated with lower doses of cocaine than juveniles or adults (Badanich et al., 2006; Brenhouse et al., 2008; Zakharova et al., 2009b) are more resistant to extinction of cocaine-associated cues, and reinstate cocaine place preferences to a greater degree than adults (Brenhouse et al., 2010; Brenhouse and Andersen, 2011). Young adolescent rodents also form place preferences for nicotine-associated environments after a single drug-environment pairing, whereas late adolescent and adult rats may not form preferences even after repeated pairings (Adriani et al., 2002; Belluzzi et al., 2004; Vastola et al., 2002). Similarly, self-administration paradigms show that, compared to adults, adolescent rats acquire cocaine self-administration faster (Perry et al., 2007), earn more cocaine infusions, are more resistant to extinction and more readily reinstate cocaine seeking (Anker and Carroll, 2010; Wong et al., 2013; Wong and Marinelli, 2016). Furthermore, adolescent male and female rats self-administer more nicotine than adults (Levin et al., 2003, 2007), and adolescent male rats self-administer greater amounts of heroin than adults (Doherty and Frantz, 2012). Together, these findings suggest that heightened incentive or motivational salience during adolescence contributes to important characteristics of substance dependence, including augmented drug seeking, extinction resistance, and relapse behaviors.

Developing circuitry and dopaminergic markers may help to explain heightened incentive salience during adolescence (Brenhouse et al., 2008; Sonntag et al., 2014). Lesion and inactivation studies demonstrate the importance of the NAc in encoding the initial salience of the primary reward-related cue, while the BLA appears necessary for maintaining salience encoding over time (Chang et al., 2012; Szalay et al., 2013). The attribution of motivational salience to drug-related cues is mediated by elevated D1 receptor expression on excitatory input from the PFC to the NAc (Kalivas et al., 2005; Robinson and Berridge, 1993b; Sonntag et al., 2014). Over time, salient drug-related cues release dopamine in the NAc even in the absence of drug taking (Ito et al., 2002; Willuhn et al., 2010).

Altered PFC ←–→ BLA and PFC → NAc connectivity in adolescence provide additional mechanisms by which reward-related cues acquire heightened incentive salience, relative to the juvenile or adult periods. The density of axonal projections increases with age in BLA → PFC (Cunningham et al., 2002, 2008) and PFC → NAc (Brenhouse et al., 2008) pathways until late adolescence/young adulthood. Within the BLA itself, dendritic spine density, length, and complexity increase locally from the juvenile period through late adolescence, and stabilize in adulthood (Koss et al., 2014). Dendritic density also increases on long-range projections from the BLA → mPFC from the juvenile period through adulthood (Johnson et al., 2016). Inhibitory GABAergic interneurons in the mPFC are a primary target of BLA projections (Cunningham et al., 2008), suggesting growing BLA → mPFC projections closes a sensitive period of development for the PFC. Excitatory BLA projections increase cortical interneuron excitation and ultimately augment PFC inhibitory tone, which may have downstream effects on driving NAc and other subcortical activity. Axonal projections from the PFC → BLA prune after adolescence (Cressman et al., 2010), suggesting further fine-tuning of activity.

Pharmacological changes also occur during adolescence that help to explain age differences in salience attribution (Brenhouse and Andersen, 2011). For example, our work (Andersen and Teicher, 2000; Teicher et al., 1995), and others (Tarazi et al., 1998) shows that dopamine receptors are transiently overproduced and pruned over the course of adolescence in a regional- and sex-dependent manner that seems to be independent of pubertal hormone increases (Andersen et al., 1997a,b, 2002b). More specifically, dopamine D1 and D2 receptors in the STR rise to higher levels in males than females during adolescence, and D1 remains higher in males during adulthood despite some pruning (Andersen et al., 1997b). In contrast, dopamine D1 and D2 receptors in the NAc do not show this same pattern, suggesting NAc plasticity may be more adaptive to changing needs of the reward system (Teicher et al., 1995).

Dopamine receptors in the mPFC are also differentially expressed across transitions between childhood, adolescence, and adulthood (Andersen et al., 1997a,b; Lyss et al., 1999; Teicher et al., 1998). For example, D2 receptors switch from inhibitory to excitatory on parvalbumin interneurons in the mPFC during adolescence (Tseng and O’Donnell, 2007). Notably, developing signaling mechanisms are not uniform across brain regions, as initially reported in non-human primates (Lidow et al., 1991). Rather, signaling mechanisms within individual circuit develop independently. For example, we find that D1 receptors are overproduced on glutamatergic, but not GABAergic, neurons in the mPFC → NAc projections (Brenhouse et al., 2008). Elevated D1 on excitatory mPFC projection neurons is associated with increased drug seeking, taking, and drug-cue salience, as well as addiction-related behaviors such as novelty seeking, sexual activity, preferences for sweet taste, and impulsivity (Freund et al., 2016; Nair et al., 2011; Sanchez et al., 2003; Sonntag et al., 2014). As suggested by Fig. 3, we predict that subjects with elevated motivational salience at an early age may be most vulnerable to developing SUD.

 

Fig. 3

Risk for the transition to substance use disorder (SUD). Substance use before age 14 is associated with the greatest risk of developing substance abuse or dependence later in life. However, while many individuals try drugs, only a small percentage transition …

Taken together, these findings suggest that increases in PFC ←–→ BLA and PFC → NAc signaling and connectivity during adolescence may underlie elevated incentive salience of drug-related cues. We propose that theory of incentive salience helps capture the early phases of adolescent drug experimentation, while vulnerability to habit development (Section 5.3) reflects underlying risk to the transition to addiction.

5.3. Habit formation

An alternative theory proposes that addiction reflects a shift in the neural control of behavior from a goal-directed learning mechanism to a habit-based mechanism (Everitt et al., 2008). Goal-directed learning and decision making describes choices made based upon environmental input and the affective value of the expected outcome (Hogarth and Chase, 2011; Voon et al., 2015). In contrast, habit formation maintains behaviors regardless of motivation or goals (Judah et al., 2013; Rothman et al., 2009), such that behaviors are initiated more or less “automatically” (Gardner et al., 2012). In substance users, drug seeking is driven initially by desire for the rewarding effects of the drug, a goal-directed behavior. After repeated drug pairings with the environment, drug-associated cues become behavioral triggers that ultimately lead to compulsive and habitual abuse. As use transitions to abuse, projections from limbic to associative to sensorimotor cortex gradually recruit involvement from the ventromedial striatum to progressively greater involvement of the dorsomedial to the dorsolateral striatal regions (Fig. 2; Belin and Everitt, 2008; Burton et al., 2015; Everitt and Robbins, 2013; Gremel and Cunningham, 2008; Haber et al., 2006).

5.4. Stress reactivity and negative reinforcement

Recent evidence suggests that stress facilitates the attribution of incentive salience and the recruitment of habit-related circuitry during learning, which further augment vulnerability to addiction (Dias-Ferreira et al., 2009; Sadowski et al., 2009; Schwabe et al., 2008, 2011; Taylor et al., 2014). A fourth theory on the etiology SUD proposes that compulsive substance use critically involves negative reinforcement, or the removal of an aversive (physically or psychologically uncomfortable) affective state, such as stress. Over time, the hedonic effects caused by drug activation of the brain’s reward system are increasingly countered by an up-regulation of an anti-reward system (opponent-process counter-adaptation; Koob and Le Moal, 2001). The process drives formation of a new allo-static state in the reward set point (i.e., an increase in what is perceived as rewarding) such that increasingly greater amounts of reinforcement are needed to maintain functioning, leading to further substance abuse and the development of SUD. Higher allo-static reward set points can additionally be driven by prenatal or early life stress (Hanson et al., 2016). Exposure to stressors may therefore represent important risk factors for the transition from early substance use to dependence in young individuals.

This work was supported by the National Institutes of Drug Abuse DA-10543 and DA-026485 (to SLA) and by the John A. Kaneb Young Investigator Award (to CJJ). We thank Dr. Heather Brenhouse for the data presented in Fig. 3A.

Declaration of interest

The authors do not have any competing interests with the present review.

1. Adriani W, et al. Peculiar vulnerability to nicotine oral self-administration in mice during early adolescence. Neuropsychopharmacology. 2002;27:212–224. [PubMed]
2. Adriani W, et al. Behavioral and neurochemical vulnerability during adolescence in mice: studies with nicotine. Neuropsychopharmacology. 2004;29:869–878. [PubMed]
3. Adriani W, et al. Methylphenidate administration to adolescent rats determines plastic changes on reward-related behavior and striatal gene expression. Neuropsychopharmacology. 2006a;31:1946–1956. [PubMed]
4. Adriani W, et al. Short-term effects of adolescent methylphenidate exposure on brain striatal gene expression and sexual/endocrine parameters in male rats. Ann. N. Y. Acad. Sci. 2006b;1074:52–73. [PubMed]
5. Aguiar AS, Jr., et al. Downhill training upregulates mice hippocampal and striatal brain-derived neurotrophic factor levels. J. Neural Transm. (Vienna) 2008;115:1251–1255. [PubMed]
6. Alarcon G, et al. Developmental sex differences in resting state functional connectivity of amygdala sub-regions. Neuroimage. 2015;115:235–244. [PMC free article] [PubMed]
7. American Psychiatric Association . Diagnostic and Statistical Manual of Mental Disorders. 5th ed. American Psychiatric Association; Washington, DC.: 2013.
8. Andersen SL, Gazzara RA. The ontogeny of apomorphine-induced alterations of neostriatal dopamine release: effects on spontaneous release. J. Neurochem. 1993;61:2247–2255. [PubMed]
9. Andersen SL, Navalta CP. Annual Research Review: new frontiers in developmental neuropharmacology: can long-term therapeutic effects of drugs be optimized through carefully timed early intervention? J. Child Psychol. Psychiatry. 2011;52:476–503. [PMC free article] [PubMed]
10. Andersen SL, Teicher MH. Sex differences in dopamine receptors and their relevance to ADHD. Neurosci. Biobehav. Rev. 2000;24:137–141. [PubMed]
11. Andersen SL, Teicher MH. Delayed effects of early stress on hippocampal development. Neuropsychopharmacology. 2004;29:1988–1993. [PubMed]
12. Andersen SL, Teicher MH. Stress, sensitive periods and maturational events in adolescent depression. Trends Neurosci. 2008;31:183–191. [PubMed]
13. Andersen SL, Teicher MH. Desperately driven and no brakes: developmental stress exposure and subsequent risk for substance abuse. Neurosci. Biobehav. Rev. 2009;33:516–524. [PMC free article] [PubMed]
14. Andersen SL, Dumont NL, Teicher MH. Developmental differences in dopamine synthesis inhibition by (+/−)-7-OH-DPAT. Naunyn. Schmiedebergs Arch. Pharmacol. 1997a;356:173–181. [PubMed]
15. Andersen SL, et al. Sex differences in dopamine receptor overproduction and elimination. Neuroreport. 1997b;8:1495–1498. [PubMed]
16. Andersen SL, et al. Altered responsiveness to cocaine in rats exposed to methylphenidate during development. Nat. Neurosci. 2002a;5:13–14. [PubMed]
17. Andersen SL, et al. Pubertal changes in gonadal hormones do not underlie adolescent dopamine receptor overproduction. Psychoneuroendocrinology. 2002b;27:683–691. [PubMed]
18. Andersen SL, et al. Juvenile methylphenidate modulates reward-related behaviors and cerebral blood flow by decreasing cortical D3 receptors. Eur. J. Neurosci. 2008a;27:2962–2972. [PubMed]
19. Andersen SL, et al. Preliminary evidence for sensitive periods in the effect of childhood sexual abuse on regional brain development. J. Neuropsychiatry Clin. Neurosci. 2008b;20:292–301. [PMC free article] [PubMed]
20. Andersen SL. Changes in the second messenger cyclic AMP during development may underlie motoric symptoms in attention deficit/hyperactivity disorder (ADHD). Behav. Brain Res. 2002;130:197–201. [PubMed]
21. Andersen SL. Trajectories of brain development: point of vulnerability or window of opportunity? Neurosci. Biobehav. Rev. 2003;27:3–18. [PubMed]
22. Andersen SL. Stimulants and the developing brain. Trends Pharmacol. Sci. 2005;26:237–243. [PubMed]
23. Andersen SL. Exposure to early adversity: points of cross-species translation that can lead to improved understanding of depression. Dev. Psychopathol. 2015;27:477–491. [PMC free article] [PubMed]
24. Andrzejewski ME, et al. A comparison of adult and adolescent rat behavior in operant learning extinction, and behavioral inhibition paradigms. Behav. Neurosci. 2011;125:93–105. [PubMed]
25. Anker JJ, Carroll ME. Reinstatement of cocaine seeking induced by drugs, cues, and stress in adolescent and adult rats. Psychopharmacology (Berl.) 2010;208:211–222. [PMC free article] [PubMed]
26. Arain M, et al. Maturation of the adolescent brain. Neuropsychiatr. Dis. Treat. 2013;9:449–461. [PMC free article] [PubMed]
27. Arnsten AF, Rubia K. Neurobiological circuits regulating attention, cognitive control, motivation, and emotion: disruptions in neurodevelopmental psychiatric disorders. J. Am. Acad. Child Adolesc. Psychiatry. 2012;51:356–367. [PubMed]
28. Averbeck BB, et al. Estimates of projection overlap and zones of convergence within frontal-striatal circuits. J. Neurosci. 2014;34:9497–9505. [PMC free article] [PubMed]
29. Badanich KA, Adler KJ, Kirstein CL. Adolescents differ from adults in cocaine conditioned place preference and cocaine-induced dopamine in the nucleus accumbens septi. Eur. J. Pharmacol. 2006;550:95–106. [PubMed]
30. Bailey J, Penhune VB. A sensitive period for musical training: contributions of age of onset and cognitive abilities. Ann. N. Y. Acad. Sci. 2012;1252:163–170. [PubMed]
31. Bardo MT, Compton WM. Does physical activity protect against drug abuse vulnerability? Drug Alcohol Depend. 2015;153:3–13. [PubMed]
32. Bardo MT, Donohew RL, Harrington NG. Psychobiology of novelty seeking and drug seeking behavior. Behav. Brain Res. 1996;77:23–43. [PubMed]
33. Barnea-Goraly N, et al. White matter development during childhood and adolescence: a cross-sectional diffusion tensor imaging study. Cereb. Cortex. 2005;15:1848–1854. [PubMed]
34. Baskin BM, Dwoskin LP, Kantak KM. Methylphenidate treatment beyond adolescence maintains increased cocaine self-administration in the spontaneously hypertensive rat model of attention deficit/hyperactivity disorder. Pharmacol. Biochem. Behav. 2015;131:51–56. [PMC free article] [PubMed]
35. Beckmann JS, Bardo MT. Environmental enrichment reduces attribution of incentive salience to a food-associated stimulus. Behav. Brain Res. 2012;226:331–334. [PMC free article] [PubMed]
36. Belin D, Everitt BJ. Cocaine seeking habits depend upon dopamine-dependent serial connectivity linking the ventral with the dorsal striatum. Neuron. 2008;57:432–441. [PubMed]
37. Belin D, et al. High impulsivity predicts the switch to compulsive cocaine-taking. Science. 2008;320:1352–1355. [PMC free article] [PubMed]
38. Bellis MA, et al. Predictors of risky alcohol consumption in schoolchildren and their implications for preventing alcohol-related harm. Subst. Abuse Treat. Prev. Policy. 2007;2:15. [PMC free article] [PubMed]
39. Belluzzi JD, et al. Age-dependent effects of nicotine on locomotor activity and conditioned place preference in rats. Psychopharmacology (Berl.) 2004;174:389–395. [PubMed]
40. Bereczkei T, Csanaky A. Evolutionary pathway of child development: lifestyles of adolescents and adults from father-absent families. Hum. Nat. 1996;7:257–280. [PubMed]
41. Berridge CW, Arnsten AF. Psychostimulants and motivated behavior: arousal and cognition. Neurosci. Biobehav. Rev. 2013;37:1976–1984. [PubMed]
42. Berridge KC. The debate over dopamine’s role in reward: the case for incentive salience. Psychopharmacology (Berl.) 2007;191:391–431. [PubMed]
43. Berridge KC. Wanting and liking: observations from the neuroscience and psychology laboratory. Inquiry (Oslo) 2009a;52:378. [PMC free article] [PubMed]
44. Berridge KC. ‘Liking’ and ‘wanting’ food rewards: brain substrates and roles in eating disorders. Physiol. Behav. 2009b;97:537–550. [PMC free article] [PubMed]
45. Biederman J, et al. Pharmacotherapy of attention-deficit/hyperactivity disorder reduces risk for substance use disorder. Pediatrics. 1999;104:e20. [PubMed]
46. Biegel GM, et al. Mindfulness-based stress reduction for the treatment of adolescent psychiatric outpatients: a randomized clinical trial. J. Consult. Clin. Psychol. 2009;77:855–866. [PubMed]
47. Bjork JM, et al. Incentive-elicited brain activation in adolescents: similarities and differences from young adults. J. Neurosci. 2004;24:1793–1802. [PubMed]
48. Bjorklund DF, Pellegrini AD. Child development and evolutionary psychology. Child Dev. 2000;71:1687–1708. [PubMed]
49. Bogin B, Smith BH. Evolution of the human life cycle. Am. J. Hum. Biol. 1996;8:703–716. [PubMed]
50. Bolanos CA, et al. Methylphenidate treatment during pre- and periadolescence alters behavioral responses to emotional stimuli at adulthood. Biol. Psychiatry. 2003;54:1317–1329. [PubMed]
51. Bowen S, et al. Mindfulness-based relapse prevention for substance use disorders: a pilot efficacy trial. Subst. Abuse. 2009;30:295–305. [PMC free article] [PubMed]
52. Brandon CL, et al. Enhanced reactivity and vulnerability to cocaine following methylphenidate treatment in adolescent rats. Neuropsychopharmacology. 2001;25:651–661. [PubMed]
53. Brandon CL, Marinelli M, White FJ. Adolescent exposure to methylphenidate alters the activity of rat midbrain dopamine neurons. Biol. Psychiatry. 2003;54:1338–1344. [PubMed]
54. Brenhouse HC, Andersen SL. Delayed extinction and stronger reinstatement of cocaine conditioned place preference in adolescent rats compared to adults. Behav. Neurosci. 2008;122:460–465. [PMC free article] [PubMed]
55. Brenhouse HC, Andersen SL. Developmental trajectories during adolescence in males and females: a cross-species understanding of underlying brain changes. Neurosci. Biobehav. Rev. 2011;35:1687–1703. [PMC free article] [PubMed]
56. Brenhouse HC, Sonntag KC, Andersen SL. Transient D1 dopamine receptor expression on prefrontal cortex projection neurons: relationship to enhanced motivational salience of drug cues in adolescence. J. Neurosci. 2008;28:2375–2382. [PMC free article] [PubMed]
57. Brenhouse HC, et al. Juvenile methylphenidate exposure and factors that influence incentive processing. Dev. Neurosci. 2009;31:95–106. [PMC free article] [PubMed]
58. Brenhouse HC, Dumais K, Andersen SL. Enhancing the salience of dullness: behavioral and pharmacological strategies to facilitate extinction of drug-cue associations in adolescent rats. Neuroscience. 2010;169:628–636. [PMC free article] [PubMed]
59. Brenhouse HC, Lukkes JL, Andersen SL. Early life adversity alters the developmental profiles of addiction-related prefrontal cortex circuitry. Brain Sci. 2013;3:143–158. [PMC free article] [PubMed]
60. Brown JD, Siegel JM. Exercise as a buffer of life stress: a prospective study of adolescent health. Health Psychol. 1988;7:341–353. [PubMed]
61. Burton AC, Nakamura K, Roesch MR. From ventral-medial to dorsal-lateral striatum: neural correlates of reward-guided decision-making. Neurobiol. Learn. Mem. 2015;117:51–59. [PMC free article] [PubMed]
62. Cain ME, Green TA, Bardo MT. Environmental enrichment decreases responding for visual novelty. Behav. Processes. 2006;73:360–366. [PMC free article] [PubMed]
63. Callaghan BL, et al. The international society for developmental psychobiology Sackler symposium: early adversity and the maturation of emotion circuits—a cross-species analysis. Dev. Psychobiol. 2014;56:1635–1650. [PMC free article] [PubMed]
64. Carlezon WA, Jr., Mague SD, Andersen SL. Enduring behavioral effects of early exposure to methylphenidate in rats. Biol. Psychiatry. 2003;54:1330–1337. [PubMed]
65. Casey BJ, Jones RM. Neurobiology of the adolescent brain and behavior: implications for substance use disorders. J. Am. Acad. Child Adolesc. Psychiatry. 2010;49:1189–1201. [PMC free article] [PubMed]
66. Casey BJ, Getz S, Galvan A. The adolescent brain. Dev. Rev. 2008;28:62–77. [PMC free article] [PubMed]
67. Casey B, Jones RM, Somerville LH. Braking and accelerating of the adolescent brain. J. Res. Adolesc. 2011;21:21–33. [PMC free article] [PubMed]
68. Cass DK, et al. Developmental disruption of gamma-aminobutyric acid function in the medial prefrontal cortex by noncontingent cocaine exposure during early adolescence. Biol. Psychiatry. 2013;74:490–501. [PMC free article] [PubMed]
69. Chaddock L, et al. Basal ganglia volume is associated with aerobic fitness in preadolescent children. Dev. Neurosci. 2010;32:249–256. [PMC free article] [PubMed]
70. Chambers RA, Taylor JR, Potenza MN. Developmental neurocircuitry of motivation in adolescence: a critical period of addiction vulnerability. Am. J. Psychiatry. 2003;160:1041–1052. [PMC free article] [PubMed]
71. Chang SE, Wheeler DS, Holland PC. Roles of nucleus accumbens and basolateral amygdala in autoshaped lever pressing. Neurobiol. Learn. Mem. 2012;97:441–451. [PMC free article] [PubMed]
72. Clark DB, Lesnick L, Hegedus AM. Traumas and other adverse life events in adolescents with alcohol abuse and dependence. J. Am. Acad. Child Adolesc. Psychiatry. 1997;36:1744–1751. [PubMed]
73. Cobb S. Presidential Address-1976: social support as a moderator of life stress. Psychosom. Med. 1976;38:300–314. [PubMed]
74. Colorado RA, et al. Effects of maternal separation, early handling, and standard facility rearing on orienting and impulsive behavior of adolescent rats. Behav. Processes. 2006;71:51–58. [PubMed]
75. Congdon E, et al. Measurement and reliability of response inhibition. Front. Psychol. 2012;3:37. [PMC free article] [PubMed]
76. Connor-Smith JK, et al. Responses to stress in adolescence: measurement of coping and involuntary stress responses. J. Consult. Clin. Psychol. 2000;68:976–992. [PubMed]
77. Cook SC, Wellman CL. Chronic stress alters dendritic morphology in rat medial prefrontal cortex. J. Neurobiol. 2004;60:236–248. [PubMed]
78. Crawford CA, et al. Early methylphenidate exposure enhances cocaine self-administration but not cocaine-induced conditioned place preference in young adult rats. Psychopharmacology (Berl.) 2011;213:43–52. [PMC free article] [PubMed]
79. Cressman VL, et al. Prefrontal cortical inputs to the basal amygdala undergo pruning during late adolescence in the rat. J. Comp. Neurol. 2010;518:2693–2709. [PMC free article] [PubMed]
80. Cruz FC, et al. Maternal separation stress in male mice: long-term increases in alcohol intake. Psychopharmacology (Berl.) 2008;201:459–468. [PMC free article] [PubMed]
81. Cui M, et al. Enriched environment experience overcomes the memory deficits and depressive-like behavior induced by early life stress. Neurosci. Lett. 2006;404:208–212. [PubMed]
82. Cunningham MG, Bhattacharyya S, Benes FM. Amygdalo-cortical sprouting continues into early adulthood: implications for the development of normal and abnormal function during adolescence. J. Comp. Neurol. 2002;453:116–130. [PubMed]
83. Cunningham MG, Bhattacharyya S, Benes FM. Increasing Interaction of amygdalar afferents with GABAergic interneurons between birth and adulthood. Cereb. Cortex. 2008;18:1529–1535. [PubMed]
84. Curtis CE, D’Esposito M. Persistent activity in the prefrontal cortex during working memory. Trends Cognit. Sci. 2003;7:415–423. [PubMed]
85. Darwin CR. The descent of man, and selection in relation to sex. 1 st Edition John Murray; London: 1871.
86. Diamond A, Lee K. Interventions shown to aid executive function development in children 4 to 12 years old. Science. 2011;333:959–964. [PMC free article] [PubMed]
87. Diamond A. Executive functions. Annu. Rev. Psychol. 2013;64:135–168. [PMC free article] [PubMed]
88. Dias-Ferreira E, et al. Chronic stress causes frontostriatal reorganization and affects decision-making. Science. 2009;325:621–625. [PubMed]
89. Dickinson A. Actions and habits: the development of behavioural autonomy. Philos. Trans. R Soc. Lond. B Biol. Sci. 1985;308:67–78.
90. Doherty JM, Frantz KJ. Heroin self-administration and reinstatement of heroin-seeking in adolescent vs: adult male rats. Psychopharmacology (Berl.) 2012;219:763–773. [PubMed]
91. Dow-Edwards D. Sex differences in the effects of cocaine abuse across the life span. Physiol. Behav. 2010;100:208–215. [PMC free article] [PubMed]
92. Duncan DF. Life stress as a precursor to adolescent drug dependence. Int. J. Addict. 1977;12:1047–1056. [PubMed]
93. Durston S, et al. Anatomical MRI of the developing human brain: what have we learned? J. Am. Acad. Child Adolesc. Psychiatry. 2001;40:1012–1020. [PubMed]
94. de Bruijn GJ, van den Putte B. Adolescent soft drink consumption, television viewing and habit strength: investigating clustering effects in the Theory of Planned Behaviour. Appetite. 2009;53:66–75. [PubMed]
95. de Wit H. Impulsivity as a determinant and consequence of drug use: a review of underlying processes. Addict. Biol. 2009;14:22–31. [PMC free article] [PubMed]
96. Eagle DM, Baunez C. Is there an inhibitory-response-control system in the rat? Evidence from anatomical and pharmacological studies of behavioral inhibition. Neurosci. Biobehav. Rev. 2010;34:50–72. [PMC free article] [PubMed]
97. El Rawas R, et al. Environmental enrichment decreases the rewarding but not the activating effects of heroin. Psychopharmacology (Berl.) 2009;203:561–570. [PubMed]
98. Enoch MA. The role of early life stress as a predictor for alcohol and drug dependence. Psychopharmacology (Berl.) 2011;214:17–31. [PMC free article] [PubMed]
99. Ernst M, et al. Amygdala and nucleus accumbens in responses to receipt and omission of gains in adults and adolescents. Neuroimage. 2005;25:1279–1291. [PubMed]
100. Ernst M, Pine DS, Hardin M. Triadic model of the neurobiology of motivated behavior in adolescence. Psychol. Med. 2006;36:299–312. [PMC free article] [PubMed]
101. Ernst M. The triadic model perspective for the study of adolescent motivated behavior. Brain Cognit. 2014;89:104–111. [PMC free article] [PubMed]
102. Eshel N, et al. Neural substrates of choice selection in adults and adolescents: development of the ventrolateral prefrontal and anterior cingulate cortices. Neuropsychologia. 2007;45:1270–1279. [PMC free article] [PubMed]
103. Everitt BJ, Robbins TW. From the ventral to the dorsal striatum: devolving views of their roles in drug addiction. Neurosci. Biobehav. Rev. 2013;37:1946–1954. [PubMed]
104. Everitt BJ, Robbins TW. Drug addiction: updating actions to habits to compulsions ten years on. Annu. Rev. Psychol. 2016;67:23–50. [PubMed]
105. Everitt BJ, et al. Review: neural mechanisms underlying the vulnerability to develop compulsive drug-seeking habits and addiction. Philos. Trans. R Soc. Lond. B Biol. Sci. 2008;363:3125–3135. [PMC free article] [PubMed]
106. Fareri DS, Tottenham N. Effects of early life stress on amygdala and striatal development. Dev. Cognit. Neurosci. 2016;19:233–247. [PMC free article] [PubMed]
107. Farrell MR, et al. Sex-specific effects of early life stress on social interaction and prefrontal cortex dendritic morphology in young rats. Behav. Brain Res. 2016;310:119–125. [PubMed]
108. Ferron C, et al. Sport activity in adolescence: associations with health perceptions and experimental behaviours. Health Educ. Res. 1999;14:225–233. [PubMed]
109. Francis DD, et al. Environmental enrichment reverses the effects of maternal separation on stress reactivity. J. Neurosci. 2002;22:7840–7843. [PubMed]
110. Freund N, et al. When the party is over: depressive-like states in rats following termination of cortical D1 receptor overexpression. Psychopharmacology (Berl.) 2016;233:1191–1201. [PMC free article] [PubMed]
111. Fuchs RA, Branham RK, See RE. Different neural substrates mediate cocaine seeking after abstinence versus extinction training: a critical role for the dorsolateral caudate-putamen. J. Neurosci. 2006;26:3584–3588. [PMC free article] [PubMed]
112. Gabard-Durnam LJ, et al. The development of human amygdala functional connectivity at rest from 4 to 23 years: a cross-sectional study. Neuroimage. 2014;95:193–207. [PMC free article] [PubMed]
113. Galvan A, et al. Earlier development of the accumbens relative to orbitofrontal cortex might underlie risk-taking behavior in adolescents. J. Neurosci. 2006;26:6885–6892. [PubMed]
114. Galvan A. Adolescent development of the reward system. Front. Hum. Neurosci. 2010;4:6. [PMC free article] [PubMed]
115. Ganella DE, Kim JH. Developmental rodent models of fear and anxiety: from neurobiology to pharmacology. Br. J. Pharmacol. 2014;171:4556–4574. [PMC free article] [PubMed]
116. Garavan H, et al. Cue-induced cocaine craving: neuroanatomical specificity for drug users and drug stimuli. Am. J. Psychiatry. 2000;157:1789–1798. [PubMed]
117. Gardner B, Lally P, Wardle J. Making health habitual: the psychology of ‘habit-formation’ and general practice. Br. J. Gen. Pract. 2012;62:664–666. [PMC free article] [PubMed]
118. Gass JT, et al. Adolescent alcohol exposure reduces behavioral flexibility, promotes disinhibition, and increases resistance to extinction of ethanol self-administration in adulthood. Neuropsychopharmacology. 2014;39:2570–2583. [PMC free article] [PubMed]
119. Giedd JN, et al. Brain development during childhood and adolescence: a longitudinal MRI study. Nat. Neurosci. 1999;2:861–863. [PubMed]
120. Gluckman PD, Hanson MA. Evolution, development and timing of puberty. Trends Endocrinol. Metab. 2006;17:7–12. [PubMed]
121. Goff B, et al. Reduced nucleus accumbens reactivity and adolescent depression following early-life stress. Neuroscience. 2013;249:129–138. [PMC free article] [PubMed]
122. Goldman PS, Alexander GE. Maturation of prefrontal cortex in the monkey revealed by local reversible cryogenic depression. Nature. 1977;267:613–615. [PubMed]
123. Goldstein RZ, Volkow ND. Dysfunction of the prefrontal cortex in addiction: neuroimaging findings and clinical implications. Nat. Rev. Neurosci. 2011;12:652–669. [PMC free article] [PubMed]
124. Grace AA, et al. Regulation of firing of dopaminergic neurons and control of goal-directed behaviors. Trends Neurosci. 2007;30:220–227. [PubMed]
125. Grant BF, Dawson DA. Age of onset of drug use and its association with DSM-IV drug abuse and dependence: results from the National Longitudinal Alcohol Epidemiologic Survey. J. Subst. Abuse. 1998;10:163–173. [PubMed]
126. Grant BF. Age at smoking onset and its association with alcohol consumption and DSM-IV alcohol abuse and dependence: results from the National Longitudinal Alcohol Epidemiologic Survey. J. Subst. Abuse. 1998;10:59–73. [PubMed]
127. Gremel CM, Cunningham CL. Roles of the nucleus accumbens and amygdala in the acquisition and expression of ethanol-conditioned behavior in mice. J. Neurosci. 2008;28:1076–1084. [PubMed]
128. Gruber SA, et al. Worth the wait: effects of age of onset of marijuana use on white matter and impulsivity. Psychopharmacology (Berl.) 2014;231:1455–1465. [PMC free article] [PubMed]
129. Grusser SM, et al. Cue-induced activation of the striatum and medial prefrontal cortex is associated with subsequent relapse in abstinent alcoholics. Psychopharmacology (Berl.) 2004;175:296–302. [PubMed]
130. Gulley JM, Juraska JM. The effects of abused drugs on adolescent development of corticolimbic circuitry and behavior. Neuroscience. 2013;249:3–20. [PMC free article] [PubMed]
131. Gustafsson L, Ploj K, Nylander I. Effects of maternal separation on voluntary ethanol intake and brain peptide systems in female Wistar rats. Pharmacol. Biochem. Behav. 2005;81:506–516. [PubMed]
132. Guyer AE, et al. Striatal functional alteration in adolescents characterized by early childhood behavioral inhibition. J. Neurosci. 2006;26:6399–6405. [PubMed]
133. Guyer AE, et al. A developmental examination of amygdala response to facial expressions. J. Cognit. Neurosci. 2008;20:1565–1582. [PMC free article] [PubMed]
134. Haber SN, Fudge JL, McFarland NR. Striatonigrostriatal pathways in primates form an ascending spiral from the shell to the dorsolateral striatum. J. Neurosci. 2000;20:2369–2382. [PubMed]
135. Haber SN, et al. Reward-related cortical inputs define a large striatal region in primates that interface with associative cortical connections, providing a substrate for incentive-based learning. J. Neurosci. 2006;26:8368–8376. [PubMed]
136. Hammerslag LR, Gulley JM. Age and sex differences in reward behavior in adolescent and adult rats. Dev. Psychobiol. 2014;56:611–621. [PMC free article] [PubMed]
137. Hanson JL, et al. Cumulative stress in childhood is associated with blunted reward-related brain activity in adulthood. Soc. Cognit. Affect. Neurosci. 2016;11:405–412. [PMC free article] [PubMed]
138. Harrell JS, et al. Smoking initiation in youth: the roles of gender, race, socioeconomics, and developmental status. J. Adolesc. Health. 1998;23:271–279. [PubMed]
139. Harvey RC, et al. Methylphenidate treatment in adolescent rats with an attention deficit/hyperactivity disorder phenotype: cocaine addiction vulnerability and dopamine transporter function. Neuropsychopharmacology. 2011;36:837–847. [PMC free article] [PubMed]
140. Hawkins JD, Catalano RF, Miller JY. Risk and protective factors for alcohol and other drug problems in adolescence and early adulthood: implications for substance abuse prevention. Psychol. Bull. 1992;112:64–105. [PubMed]
141. Hawley P. The evolution of adolescence and the adolescence of evolution: the coming of age of humans and the theory about the forces that made them. J. Res. Adolesc. 2011;21:307–316.
142. Hester R, Garavan H. Executive dysfunction in cocaine addiction: evidence for discordant frontal, cingulate, and cerebellar activity. J. Neurosci. 2004;24:11017–11022. [PubMed]
143. Hester R, Lubman DI, Yucel M. The role of executive control in human drug addiction. Curr. Top. Behav. Neurosci. 2010;3:301–318. [PubMed]
144. Hogarth L, Chase HW. Parallel goal-directed and habitual control of human drug-seeking: implications for dependence vulnerability. J. Exp. Psychol. Anim. Behav. Process. 2011;37:261–276. [PubMed]
145. Holzel BK, et al. Investigation of mindfulness meditation practitioners with voxel-based morphometry. Soc. Cognit. Affect. Neurosci. 2008;3:55–61. [PMC free article] [PubMed]
146. Holzel BK, et al. Mindfulness practice leads to increases in regional brain gray matter density. Psychiatry Res. 2011;191:36–43. [PMC free article] [PubMed]
147. Hostinar CE. The Impacts of Social Support and Early Life Stress on Stress Reactivity in Children and Adolescents. University of Minnesota Digital Conservancy. 2013
148. Houben K, Wiers RW, Jansen A. Getting a grip on drinking behavior: training working memory to reduce alcohol abuse. Psychol. Sci. 2011;22:968–975. [PubMed]
149. Humensky JL. Are adolescents with high socioeconomic status more likely to engage in alcohol and illicit drug use in early adulthood? Subst. Abuse Treat. Prev. Policy. 2010;5:19. [PMC free article] [PubMed]
150. Huot RL, et al. Development of adult ethanol preference and anxiety as a consequence of neonatal maternal separation in Long Evans rats and reversal with antidepressant treatment. Psychopharmacology (Berl.) 2001;158:366–373. [PubMed]
151. Ito R, et al. Dopamine release in the dorsal striatum during cocaine-seeking behavior under the control of a drug-associated cue. J. Neurosci. 2002;22:6247–6253. [PubMed]
152. Jasinska AJ, et al. Factors modulating neural reactivity to drug cues in addiction: a survey of human neuroimaging studies. Neurosci. Biobehav. Rev. 2014;38:1–16. [PMC free article] [PubMed]
153. Johnson JS, Newport EL. Critical period effects in second language learning: the influence of maturational state on the acquisition of English as a second language. Cognit. Psychol. 1989;21:60–99. [PubMed]
154. Johnson TR, et al. Neural processing of a cocaine-associated odor cue revealed by functional MRI in awake rats. Neurosci. Lett. 2013;534:160–165. [PMC free article] [PubMed]
155. Johnson CM, et al. Long-range orbitofrontal and amygdala axons show divergent patterns of maturation in the frontal cortex across adolescence. Dev. Cognit. Neurosci. 2016;18:113–120. [PMC free article] [PubMed]
156. Jonkman S, Pelloux Y, Everitt BJ. Differential roles of the dorsolateral and midlateral striatum in punished cocaine seeking. J. Neurosci. 2012;32:4645–4650. [PubMed]
157. Jordan CJ, et al. Cocaine-seeking behavior in a genetic model of attention-deficit/hyperactivity disorder following adolescent methylphenidate or atomoxetine treatments. Drug Alcohol Depend. 2014;140:25–32. [PMC free article] [PubMed]
158. Jordan CJ, et al. Adolescent D-amphetamine treatment in a rodent model of ADHD: Pro-cognitive effects in adolescence without an impact on cocaine cue reactivity in adulthood. Behav. Brain Res. 2016;297:165–179. [PMC free article] [PubMed]
159. Judah G, Gardner B, Aunger R. Forming a flossing habit: an exploratory study of the psychological determinants of habit formation. Br. J. Health Psychol. 2013;18:338–353. [PubMed]
160. Kalinichev M, et al. Long-lasting changes in stress-induced corticosterone response and anxiety-like behaviors as a consequence of neonatal maternal separation in Long-Evans rats. Pharmacol. Biochem. Behav. 2002;73:131–140. [PubMed]
161. Kalivas PW, Volkow N, Seamans J. Unmanageable motivation in addiction: a pathology in prefrontal-accumbens glutamate transmission. Neuron. 2005;45:647–650. [PubMed]
162. Kendig MD, et al. Chronic restricted access to 10% sucrose solution in adolescent and young adult rats impairs spatial memory and alters sensitivity to outcome devaluation. Physiol. Behav. 2013;120:164–172. [PubMed]
163. Khurana A, et al. Working memory ability predicts trajectories of early alcohol use in adolescents: the mediational role of impulsivity. Addiction. 2013;108:506–515. [PMC free article] [PubMed]
164. Kilpatrick DG, et al. Risk factors for adolescent substance abuse and dependence: data from a national sample. J. Consult. Clin. Psychol. 2000;68:19–30. [PubMed]
165. Kilpatrick DG, et al. Violence and risk of PTSD, major depression, substance abuse/dependence, and comorbidity: results from the National Survey of Adolescents. J. Consult. Clin. Psychol. 2003;71:692–700. [PubMed]
166. Knudsen EI. Sensitive periods in the development of the brain and behavior. J. Cognit. Neurosci. 2004;16:1412–1425. [PubMed]
167. Koob GF, Le Moal M. Drug addiction, dysregulation of reward, and allostasis. Neuropsychopharmacology. 2001;24:97–129. [PubMed]
168. Koss WA, et al. Dendritic remodeling in the adolescent medial prefrontal cortex and the basolateral amygdala of male and female rats. Synapse. 2014;68:61–72. [PubMed]
169. Kosten TA, Miserendino MJ, Kehoe P. Enhanced acquisition of cocaine self-administration in adult rats with neonatal isolation stress experience. Brain Res. 2000;875:44–50. [PubMed]
170. Kosten TA, et al. Neonatal isolation enhances acquisition of cocaine self-administration and food responding in female rats. Behav. Brain Res. 2004;151:137–149. [PubMed]
171. Kosten TA, Zhang XY, Kehoe P. Heightened cocaine and food self-administration in female rats with neonatal isolation experience. Neuropsychopharmacology. 2006;31:70–76. [PubMed]
172. Kreek MJ, et al. Genetic influences on impulsivity, risk taking, stress responsivity and vulnerability to drug abuse and addiction. Nat. Neurosci. 2005;8:1450–1457. [PubMed]
173. Kremers SP, van der Horst K, Brug J. Adolescent screen-viewing behaviour is associated with consumption of sugar-sweetened beverages: the role of habit strength and perceived parental norms. Appetite. 2007;48:345–350. [PubMed]
174. Kuhn C. Emergence of sex differences in the development of substance use and abuse during adolescence. Pharmacol. Ther. 2015;153:55–78. [PMC free article] [PubMed]
175. Lacy RT, et al. Exercise decreases speedball self-administration. Life Sci. 2014;114:86–92. [PMC free article] [PubMed]
176. Lakes KD, Hoyt WT. Promoting self-regulation through school-based martial arts training. Appl. Dev. Psychol. 2004;25:283–302.
177. Lambert NM, Hartsough CS. Prospective study of tobacco smoking and substance dependencies among samples of ADHD and non-ADHD participants. J. Learn. Disabil. 1998;31:533–544. [PubMed]
178. Lau H, Rogers RD, Passingham RE. Dissociating response selection and conflict in the medial frontal surface. Neuroimage. 2006;29:446–451. [PubMed]
179. Laviola G, et al. Beneficial effects of enriched environment on adolescent rats from stressed pregnancies. Eur. J. Neurosci. 2004;20:1655–1664. [PubMed]
180. Lazar SW, et al. Meditation experience is associated with increased cortical thickness. Neuroreport. 2005;16:1893–1897. [PMC free article] [PubMed]
181. Letchworth SR, et al. Progression of changes in dopamine transporter binding site density as a result of cocaine self-administration in rhesus monkeys. J. Neurosci. 2001;21:2799–2807. [PubMed]
182. Levin ED, et al. Adolescent-onset nicotine self-administration modeled in female rats. Psychopharmacology (Berl.) 2003;169:141–149. [PubMed]
183. Levin ED, et al. Adolescent vs: adult-onset nicotine self-administration in male rats: duration of effect and differential nicotinic receptor correlates. Neurotoxicol. Teratol. 2007;29:458–465. [PMC free article] [PubMed]
184. Lidow MS, Goldman-Rakic PS, Rakic P. Synchronized overproduction of neurotransmitter receptors in diverse regions of the primate cerebral cortex. Proc. Natl. Acad. Sci. U. S. A. 1991;88:10218–10221. [PMC free article] [PubMed]
185. Liston C, et al. Stress-induced alterations in prefrontal cortical dendritic morphology predict selective impairments in perceptual attentional set-shifting. J. Neurosci. 2006;26:7870–7874. [PubMed]
186. Liu HS, et al. Dorsolateral caudate nucleus differentiates cocaine from natural reward-associated contextual cues. Proc. Natl. Acad. Sci. U. S. A. 2013;110:4093–4098. [PMC free article] [PubMed]
187. Lomanowska AM, et al. Inadequate early social experience increases the incentive salience of reward-related cues in adulthood. Behav. Brain Res. 2011;220:91–99. [PubMed]
188. Lopez-Larson MP, et al. Altered prefrontal and insular cortical thickness in adolescent marijuana users. Behav. Brain Res. 2011;220:164–172. [PMC free article] [PubMed]
189. Lowen SB, et al. Cocaine-conditioned odor cues without chronic exposure: implications for the development of addiction vulnerability. Neuroimage Clin. 2015;8:652–659. [PMC free article] [PubMed]
190. Lukas SE, et al. Extended-release naltrexone (XR-NTX) attenuates brain responses to alcohol cues in alcohol-dependent volunteers: a bold FMRI study. Neuroimage. 2013;78:176–185. [PubMed]
191. Lupien SJ, et al. Effects of stress throughout the lifespan on the brain, behaviour and cognition. Nat. Rev. Neurosci. 2009;10:434–445. [PubMed]
192. Lyss PJ, et al. Degree of neuronal activation following FG-7142 changes across regions during development. Brain Res. Dev. Brain Res. 1999;116:201–203. [PubMed]
193. Maas LC, et al. Functional magnetic resonance imaging of human brain activation during cue-induced cocaine craving. Am. J. Psychiatry. 1998;155:124–126. [PubMed]
194. Manjunath NK, Telles S. Improved performance in the Tower of London test following yoga. Indian J. Physiol. Pharmacol. 2001;45:351–354. [PubMed]
195. Mannuzza S, et al. Age of methylphenidate treatment initiation in children with ADHD and later substance abuse: prospective follow-up into adulthood. Am. J. Psychiatry. 2008;165:604–609. [PMC free article] [PubMed]
196. Marais L, Stein DJ, Daniels WM. Exercise increases BDNF levels in the striatum and decreases depressive-like behavior in chronically stressed rats. Metab. Brain Dis. 2009;24:587–597. [PubMed]
197. Marek S, et al. The contribution of network organization and integration to the development of cognitive control. PLoS Biol. 2015;13:e1002328. [PMC free article] [PubMed]
198. Marin MT, Planeta CS. Maternal separation affects cocaine-induced locomotion and response to novelty in adolescent but not in adult rats. Brain Res. 2004;1013:83–90. [PubMed]
199. Mason M, et al. Time-varying effects of a text-based smoking cessation intervention for urban adolescents. Drug Alcohol Depend. 2015;157:99–105. [PMC free article] [PubMed]
200. Matthews K, et al. Repeated neonatal maternal separation alters intravenous cocaine self-administration in adult rats. Psychopharmacology (Berl.) 1999;141:123–134. [PubMed]
201. Matthews M, et al. Reduced presynaptic dopamine activity in adolescent dorsal striatum. Neuropsychopharmacology. 2013;38:1344–1351. [PMC free article] [PubMed]
202. McEwen BS, Gianaros PJ. Central role of the brain in stress and adaptation: links to socioeconomic status health, and disease. Ann. N. Y. Acad. Sci. 2010;1186:190–222. [PMC free article] [PubMed]
203. Mechelli A, et al. Neurolinguistics: structural plasticity in the bilingual brain. Nature. 2004;431:757. [PubMed]
204. Mehta MA, et al. Hyporesponsive reward anticipation in the basal ganglia following severe institutional deprivation early in life. J. Cognit. Neurosci. 2010;22:2316–2325. [PubMed]
205. Meil WM, See RE. Lesions of the basolateral amygdala abolish the ability of drug associated cues to reinstate responding during withdrawal from self-administered cocaine. Behav. Brain Res. 1997;87:139–148. [PubMed]
206. Mendle J, et al. Associations between early life stress, child maltreatment, and pubertal development among girls in foster care. J. Res. Adolesc. 2011;21:871–880. [PMC free article] [PubMed]
207. Michaels CC, Easterling KW, Holtzman SG. Maternal separation alters ICSS responding in adult male and female rats: but morphine and naltrexone have little affect on that behavior. Brain Res. Bull. 2007;73:310–318. [PubMed]
208. Mitchell MR, et al. Adolescent risk taking, cocaine self-administration, and striatal dopamine signaling. Neuropsychopharmacology. 2014;39:955–962. [PMC free article] [PubMed]
209. Moffett MC, et al. Maternal separation and handling affects cocaine self-administration in both the treated pups as adults and the dams. J. Pharmacol. Exp. Ther. 2006;317:1210–1218. [PubMed]
210. Moffett MC, et al. Maternal separation alters drug intake patterns in adulthood in rats. Biochem. Pharmacol. 2007;73:321–330. [PMC free article] [PubMed]
211. Molina BS, et al. Adolescent substance use in the multimodal treatment study of attention-deficit/hyperactivity disorder (ADHD) (MTA) as a function of childhood ADHD, random assignment to childhood treatments, and subsequent medication. J. Am. Acad. Child Adolesc. Psychiatry. 2013;52:250–263. [PMC free article] [PubMed]
212. Moll GH, et al. Age-associated changes in the densities of presynaptic monoamine transporters in different regions of the rat brain from early juvenile life to late adulthood. Brain Res. Dev. Brain Res. 2000;119:251–257. [PubMed]
213. Mueller SC, et al. Early-life stress is associated with impairment in cognitive control in adolescence: an fMRI study. Neuropsychologia. 2010;48:3037–3044. [PMC free article] [PubMed]
214. Munakata Y, et al. A unified framework for inhibitory control. Trends Cognit. Sci. 2011;15:453–459. [PMC free article] [PubMed]
215. Myers B, et al. Central stress-integrative circuits: forebrain glutamatergic and GABAergic projections to the dorsomedial hypothalamus medial preoptic area, and bed nucleus of the stria terminalis. Brain Struct. Funct. 2014;219:1287–1303. [PMC free article] [PubMed]
216. Nair SG, et al. Role of dorsal medial prefrontal cortex dopamine D1-family receptors in relapse to high-fat food seeking induced by the anxiogenic drug yohimbine. Neuropsychopharmacology. 2011;36:497–510. [PMC free article] [PubMed]
217. Naneix F, et al. Parallel maturation of goal-directed behavior and dopaminergic systems during adolescence. J. Neurosci. 2012;32:16223–16232. [PubMed]
218. National, Institute of Drug Abuse [18 Sept. 2016];Principles of Adolescent Substance Use Disorder Treatment: A Research-Based Guide. 2014 Available at. https://www.drugabuse.gov/publications/principles-adolescent-substance-use-disorder-treatment-research-based-guide/introduction.
219. National Institute of Drug Abuse [9 Nov. 2016];Trends and Statistics. 2015 Available at. https://www.drugabuse.gov/related-topics/trends-statistics.
220. Nees F, et al. Determinants of early alcohol use in healthy adolescents: the differential contribution of neuroimaging and psychological factors. Neuropsychopharmacology. 2012;37:986–995. [PMC free article] [PubMed]
221. Newcomb MD, Harlow LL. Life events and substance use among adolescents: mediating effects of perceived loss of control and meaninglessness in life. J. Pers. Soc. Psychol. 1986;51:564–577. [PubMed]
222. Newman LA, McGaughy J. Adolescent rats show cognitive rigidity in a test of attentional set shifting. Dev. Psychobiol. 2011;53:391–401. [PubMed]
223. Ogbonmwan YE, et al. The effects of post-extinction exercise on cocaine-primed and stress-induced reinstatement of cocaine seeking in rats. Psychopharmacology (Berl.) 2015;232:1395–1403. [PMC free article] [PubMed]
224. Ongur D, Price JL. The organization of networks within the orbital and medial prefrontal cortex of rats monkeys and humans. Cereb. Cortex. 2000;10:206–219. [PubMed]
225. Parent AS, et al. Early developmental actions of endocrine disruptors on the hypothalamus, hippocampus, and cerebral cortex. J. Toxicol. Environ. Health B Crit. Rev. 2011;14:328–345. [PMC free article] [PubMed]
226. Patrick ME, et al. Socioeconomic status and substance use among young adults: a comparison across constructs and drugs. J. Stud. Alcohol Drugs. 2012;73:772–782. [PMC free article] [PubMed]
227. Patton GC, et al. Puberty and the onset of substance use and abuse. Pediatrics. 2004;114:e300–6. [PMC free article] [PubMed]
228. Peeters M, et al. Weaknesses in executive functioning predict the initiating of adolescents’ alcohol use. Dev. Cognit. Neurosci. 2015;16:139–146. [PubMed]
229. Perry JL, et al. Acquisition of i: v. cocaine self-administration in adolescent and adult male rats selectively bred for high and low saccharin intake. Physiol. Behav. 2007;91:126–133. [PMC free article] [PubMed]
230. Peterson AB, Abel JM, Lynch WJ. Dose-dependent effects of wheel running on cocaine-seeking and prefrontal cortex Bdnf exon IV expression in rats. Psychopharmacology (Berl.) 2014;231:1305–1314. [PubMed]
231. Phillips GD, et al. Isolation rearing enhances the locomotor response to cocaine and a novel environment: but impairs the intravenous self-administration of cocaine. Psychopharmacology (Berl.) 1994;115:407–418. [PubMed]
232. Ploj K, Roman E, Nylander I. Long-term effects of maternal separation on ethanol intake and brain opioid and dopamine receptors in male Wistar rats. Neuroscience. 2003;121:787–799. [PubMed]
233. Pool E, et al. Measuring wanting and liking from animals to humans: a systematic review. Neurosci. Biobehav. Rev. 2016;63:124–142. [PubMed]
234. Porrino LJ, et al. Cocaine self-administration produces a progressive involvement of limbic, association, and sensorimotor striatal domains. J. Neurosci. 2004;24:3554–3562. [PubMed]
235. Potvin S, et al. Cocaine and cognition: a systematic quantitative review. J. Addict. Med. 2014;8:368–376. [PubMed]
236. Pruessner JC, et al. Dopamine release in response to a psychological stress in humans and its relationship to early life maternal care: a positron emission tomography study using [11C]raclopride. J. Neurosci. 2004;24:2825–2831. [PubMed]
237. Quas JA, et al. The symphonic structure of childhood stress reactivity: patterns of sympathetic, parasympathetic, and adrenocortical responses to psychological challenge. Dev. Psychopathol. 2014;26:963–982. [PMC free article] [PubMed]
238. Radley JJ, et al. Chronic behavioral stress induces apical dendritic reorganization in pyramidal neurons of the medial prefrontal cortex. Neuroscience. 2004;125:1–6. [PubMed]
239. Rapoport JL, et al. Dextroamphetamine: cognitive and behavioral effects in normal prepubertal boys. Science. 1978;199:560–563. [PubMed]
240. Ridderinkhof KR, et al. Neurocognitive mechanisms of cognitive control: the role of prefrontal cortex in action selection, response inhibition, performance monitoring, and reward-based learning. Brain Cognit. 2004;56:129–140. [PubMed]
241. Robins LN. The natural history of adolescent drug use. Am. J. Public Health. 1984;74:656–657. [PMC free article] [PubMed]
242. Robinson TE, Berridge KC. The neural basis of drug craving: an incentive-sensitization theory of addiction. Brain Res. Brain Res. Rev. 1993a;18:247–291. [PubMed]
243. Robinson TE, Berridge KC. The neural basis of drug craving: an incentive-sensitization theory of addiction. Brain Res. Brain Res. Rev. 1993b;18:247–291. [PubMed]
244. Roman E, Ploj K, Nylander I. Maternal separation has no effect on voluntary ethanol intake in female Wistar rats. Alcohol. 2004;33:31–39. [PubMed]
245. Romeo RD, McEwen BS. Stress and the adolescent brain. Ann. N. Y. Acad. Sci. 2006;1094:202–214. [PubMed]
246. Romeo RD. The teenage brain: the stress response and the adolescent brain. Curr. Dir. Psychol. Sci. 2013;22:140–145. [PMC free article] [PubMed]
247. Rothman AJ, Sheeran P, Wood W. Reflective and automatic processes in the initiation and maintenance of dietary change. Ann. Behav. Med. 2009;1(38 Suppl):S4–17. [PubMed]
248. Romeo RD, et al. Adolescence and the ontogeny of the hormonal stress response in male and female rats and mice. Neurosci. Biobehav. Rev. 2016;70:206–216. [PMC free article] [PubMed]
249. Ruedi-Bettschen D, et al. Early deprivation leads to altered behavioural, autonomic and endocrine responses to environmental challenge in adult Fischer rats. Eur. J. Neurosci. 2006;24:2879–2893. [PubMed]
250. SAMHSA . Results from the 2008 National Survey on Drug Use and Health: National Findings. Office of Applied Studies; Rockville, MD: 2008.
251. SAMHSA . Results from the 2011 National Survey on Drug Use and Health: Summary of National Findings. Substance Abuse and Mental Health Services Administration; Rockville, MD: 2012.
252. SAMHSA . Results from the 2013 National Survey on Drug Use and Health: Detailed Tables. Center for Behavioral Health Statistics and Quality; Rockville, MD: 2014.
253. SAMHSA Behavioral health trends in the United States: Results from the 2014 National Survey on Drug Use and Health (HHS Publication No. SMA 15–4927, NSDUHSeries H-50) 2015.
254. SAMHSA . 2014 National Survey on Drug Use and Health: Detailed Tables. Center for Behavioral Health Statistics and Quality; Rockville, MD: 2015b.
255. Sadowski RN, et al. Effects of stress, corticosterone, and epinephrine administration on learning in place and response tasks. Behav. Brain Res. 2009;205:19–25. [PMC free article] [PubMed]
256. Sanchez CJ, et al. Manipulation of dopamine d1-like receptor activation in the rat medial prefrontal cortex alters stress- and cocaine-induced reinstatement of conditioned place preference behavior. Neuroscience. 2003;119:497–505. [PubMed]
257. Sanchez V, et al. Wheel running exercise attenuates vulnerability to self-administer nicotine in rats. Drug Alcohol Depend. 2015;156:193–198. [PMC free article] [PubMed]
258. Schneider S, et al. Risk taking and the adolescent reward system: a potential common link to substance abuse. Am. J. Psychiatry. 2012;169:39–46. [PubMed]
259. Schramm-Sapyta NL, et al. Are adolescents more vulnerable to drug addiction than adults?: Evidence from animal models. Psychopharmacology (Berl.) 2009;206:1–21. [PMC free article] [PubMed]
260. Schrantee A, et al. Age-dependent effects of methylphenidate on the human dopaminergic system in young vs adult patients with attention-deficit/hyperactivity disorder: a randomized clinical trial. JAMA Psychiatry. 2016;73:955–962. [PMC free article] [PubMed]
261. Schwabe L, Wolf OT. Stress prompts habit behavior in humans. J. Neurosci. 2009;29:7191–7198. [PubMed]
262. Schwabe L, Wolf OT. Stress-induced modulation of instrumental behavior: from goal-directed to habitual control of action. Behav. Brain Res. 2011;219:321–328. [PubMed]
263. Schwabe L, et al. Chronic stress modulates the use of spatial and stimulus-response learning strategies in mice and man. Neurobiol. Learn. Mem. 2008;90:495–503. [PubMed]
264. Schwabe L, Dickinson A, Wolf OT. Stress, habits, and drug addiction: a psychoneuroendocrinological perspective. Exp. Clin. Psychopharmacol. 2011;19:53–63. [PubMed]
265. Schwartz JA, Beaver KM, Barnes JC. The association between mental health and violence among a nationally representative sample of college students from the United States. PLoS One. 2015;10:e0138914. [PMC free article] [PubMed]
266. See RE, Elliott JC, Feltenstein MW. The role of dorsal vs ventral striatal pathways in cocaine-seeking behavior after prolonged abstinence in rats. Psychopharmacology (Berl.) 2007;194:321–331. [PubMed]
267. Seeley WW, et al. Dissociable intrinsic connectivity networks for salience processing and executive control. J. Neurosci. 2007;27:2349–2356. [PMC free article] [PubMed]
268. Seger CA, Spiering BJ. A critical review of habit learning and the Basal Ganglia. Front. Syst. Neurosci. 2011;5:66. [PMC free article] [PubMed]
269. Shaw P, et al. Attention-deficit/hyperactivity disorder is characterized by a delay in cortical maturation. Proc. Natl. Acad. Sci. U. S. A. 2007;104:19649–19654. [PMC free article] [PubMed]
270. Shaw P, et al. Psychostimulant treatment and the developing cortex in attention deficit hyperactivity disorder. Am. J. Psychiatry. 2009;166:58–63. [PMC free article] [PubMed]
271. Sinha R. Chronic stress, drug use, and vulnerability to addiction. Ann. N. Y. Acad. Sci. 2008;1141:105–130. [PMC free article] [PubMed]
272. Sisk CL, Schulz KM, Zehr JL. Puberty: a finishing school for male social behavior. Ann. N. Y. Acad. Sci. 2003;1007:189–198. [PubMed]
273. Smith JL, et al. Deficits in behavioural inhibition in substance abuse and addiction: a meta-analysis. Drug Alcohol Depend. 2014;145:1–33. [PubMed]
274. Smith RF. Animal models of periadolescent substance abuse. Neurotoxicol. Teratol. 2003;25:291–301. [PubMed]
275. Solinas M, et al. Environmental enrichment during early stages of life reduces the behavioral, neurochemical, and molecular effects of cocaine. Neuropsychopharmacology. 2009;34:1102–1111. [PubMed]
276. Somerville LH, Jones RM, Casey BJ. A time of change: behavioral and neural correlates of adolescent sensitivity to appetitive and aversive environmental cues. Brain Cognit. 2010;72:124–133. [PMC free article] [PubMed]
277. Somerville LH, Hare T, Casey BJ. Frontostriatal maturation predicts cognitive control failure to appetitive cues in adolescents. J. Cognit. Neurosci. 2011;23:2123–2134. [PMC free article] [PubMed]
278. Sonntag KC, et al. Viral over-expression of D1 dopamine receptors in the prefrontal cortex increase high-risk behaviors in adults: comparison with adolescents. Psychopharmacology (Berl.) 2014;231:1615–1626. [PMC free article] [PubMed]
279. Sowell ER, et al. In vivo evidence for post-adolescent brain maturation in frontal and striatal regions. Nat. Neurosci. 1999;2:859–861. [PubMed]
280. Spear LP. The adolescent brain and age-related behavioral manifestations. Neurosci. Biobehav. Rev. 2000;24:417–463. [PubMed]
281. Squeglia LM, Jacobus J, Tapert SF. The influence of substance use on adolescent brain development. Clin. EEG Neurosci. 2009;40:31–38. [PMC free article] [PubMed]
282. Stanger C, et al. Neuroeconomics and adolescent substance abuse: individual differences in neural networks and delay discounting. J. Am. Acad. Child Adolesc. Psychiatry. 2013;52:747–755. e6. [PMC free article] [PubMed]
283. Stanis JJ, Andersen SL. Reducing substance use during adolescence: a translational framework for prevention. Psychopharmacology (Berl.) 2014;231:1437–1453. [PMC free article] [PubMed]
284. Steele CJ, et al. Early musical training and white-matter plasticity in the corpus callosum: evidence for a sensitive period. J. Neurosci. 2013;33:1282–1290. [PubMed]
285. Steinhausen HC, Bisgaard C. Substance use disorders in association with attention-deficit/hyperactivity disorder, co-morbid mental disorders, and medication in a nationwide sample. Eur. Neuropsychopharmacol. 2014;24:232–241. [PubMed]
286. Sturman DA, Moghaddam B. Reduced neuronal inhibition and coordination of adolescent prefrontal cortex during motivated behavior. J. Neurosci. 2011;31:1471–1478. [PMC free article] [PubMed]
287. Sturman DA, Moghaddam B. Striatum processes reward differently in adolescents versus adults. Proc. Natl. Acad. Sci. U. S. A. 2012;109:1719–1724. [PMC free article] [PubMed]
288. Sturman DA, Mandell DR, Moghaddam B. Adolescents exhibit behavioral differences from adults during instrumental learning and extinction. Behav. Neurosci. 2010;124:16–25. [PMC free article] [PubMed]
289. Surbey MK. Parent and offspring strategies in the transition at adolescence. Hum. Nat. 1998;9:67–94. [PubMed]
290. Szalay JJ, Jordan CJ, Kantak KM. Neural regulation of the time course for cocaine-cue extinction consolidation in rats. Eur. J. Neurosci. 2013;37:269–277. [PMC free article] [PubMed]
291. Taliaferro LA, Rienzo BA, Donovan KA. Relationships between youth sport participation and selected health risk behaviors from 1999 to 2007. J. Sch. Health. 2010;80:399–410. [PubMed]
292. Tang YY, et al. Central and autonomic nervous system interaction is altered by short-term meditation. Proc. Natl. Acad. Sci. U. S. A. 2009;106:8865–8870. [PMC free article] [PubMed]
293. Tang YY, et al. Improving executive function and its neurobiological mechanisms through a mindfulness-based intervention: advances within the field of developmental neuroscience. Child Dev. Perspect. 2012;6:361–366. [PMC free article] [PubMed]
294. Tanner JM. Growth at Adolescence. With a General Consideration of the Effects of Hereditary and Environmental Factors upon Growth and Maturation from Birth to Maturity. Blackwell Scientific Oxford; 1962.
295. Tarazi FI, Tomasini EC, Baldessarini RJ. Postnatal development of dopamine D4-like receptors in rat forebrain regions: comparison with D2-like receptors. Brain Res. Dev. Brain Res. 1998;110:227–233. [PubMed]
296. Taylor SB, et al. Chronic stress may facilitate the recruitment of habit- and addiction-related neurocircuitries through neuronal restructuring of the striatum. Neuroscience. 2014;280:231–242. [PMC free article] [PubMed]
297. Teicher MH, Andersen SL, Hostetter JC., Jr. Evidence for dopamine receptor pruning between adolescence and adulthood in striatum but not nucleus accumbens. Brain Res. Dev. Brain Res. 1995;89:167–172. [PubMed]
298. Teicher MH, Dumont NL, Andersen SL. The developing prefrontal cortex: is there a transient interneuron that stimulates catecholamine terminals? Synapse. 1998;29:89–91. [PubMed]
299. Teicher MH, Tomoda A, Andersen SL. Neurobiological consequences of early stress and childhood maltreatment: are results from human and animal studies comparable? Ann. N. Y. Acad. Sci. 2006;1071:313–323. [PubMed]
300. Tekin S, Cummings JL. Frontal-subcortical neuronal circuits and clinical neuropsychiatry: an update. J. Psychosom. Res. 2002;53:647–654. [PubMed]
301. Thanos PK, et al. Effects of chronic oral methylphenidate on cocaine self-administration and striatal dopamine D2 receptors in rodents. Pharmacol. Biochem. Behav. 2007;87:426–433. [PubMed]
302. Thompson AB, et al. Methamphetamine blocks exercise effects on Bdnf and Drd2 gene expression in frontal cortex and striatum. Neuropharmacology. 2015;99:658–664. [PMC free article] [PubMed]
303. Tseng KY, O’Donnell P. Dopamine modulation of prefrontal cortical interneurons changes during adolescence. Cereb. Cortex. 2007;17:1235–1240. [PMC free article] [PubMed]
304. USAA USAA Training Systems: Critical Periods for Optimal Development. 2011.
305. Uhl GR. Molecular genetics of substance abuse vulnerability: remarkable recent convergence of genome scan results. Ann. N. Y. Acad. Sci. 2004;1025:1–13. [PubMed]
306. van der Marel K, et al. Long-term oral methylphenidate treatment in adolescent and adult rats: differential effects on brain morphology and function. Neuropsychopharmacology. 2014;39:263–273. [PMC free article] [PubMed]
307. Vanderschuren LJ, Di Ciano P, Everitt BJ. Involvement of the dorsal striatum in cue-controlled cocaine seeking. J. Neurosci. 2005;25:8665–8670. [PubMed]
308. Vastola BJ, et al. Nicotine-induced conditioned place preference in adolescent and adult rats. Physiol. Behav. 2002;77:107–114. [PubMed]
309. Verdejo-Garcia A, Lawrence AJ, Clark L. Impulsivity as a vulnerability marker for substance-use disorders: review of findings from high-risk research, problem gamblers and genetic association studies. Neurosci. Biobehav. Rev. 2008;32:777–810. [PubMed]
310. Volkow ND, Fowler JS. Addiction, a disease of compulsion and drive: involvement of the orbitofrontal cortex. Cereb. Cortex. 2000;10:318–325. [PubMed]
311. Volkow ND, Swanson JM. Does childhood treatment of ADHD with stimulant medication affect substance abuse in adulthood? Am. J. Psychiatry. 2008;165:553–555. [PMC free article] [PubMed]
312. Volkow ND, et al. Prediction of reinforcing responses to psychostimulants in humans by brain dopamine D2 receptor levels. Am. J. Psychiatry. 1999;156:1440–1443. [PubMed]
313. Volkow ND, et al. Cocaine cues and dopamine in dorsal striatum: mechanism of craving in cocaine addiction. J. Neurosci. 2006;26:6583–6588. [PubMed]
314. Vonmoos M, et al. Cognitive dysfunctions in recreational and dependent cocaine users: role of attention-deficit hyperactivity disorder, craving and early age at onset. Br. J. Psychiatry. 2013;203:35–43. [PubMed]
315. Voon V, et al. Disorders of compulsivity: a common bias towards learning habits. Mol. Psychiatry. 2015;20:345–352. [PMC free article] [PubMed]
316. Wagner FA, Anthony JC. From first drug use to drug dependence; developmental periods of risk for dependence upon marijuana, cocaine, and alcohol. Neuropsychopharmacology. 2002;26:479–488. [PubMed]
317. Weinstock J, Barry D, Petry NM. Exercise-related activities are associated with positive outcome in contingency management treatment for substance use disorders. Addict. Behav. 2008;33:1072–1075. [PMC free article] [PubMed]
318. Werch C, et al. A sport-based intervention for preventing alcohol use and promoting physical activity among adolescents. J. Sch. Health. 2003;73:380–388. [PubMed]
319. Werch CC, et al. A multihealth behavior intervention integrating physical activity and substance use prevention for adolescents. Prev. Sci. 2005;6:213–226. [PubMed]
320. Whelan R, et al. Adolescent impulsivity phenotypes characterized by distinct brain networks. Nat. Neurosci. 2012;15:920–925. [PubMed]
321. White LS. Reducing stress in school-age girls through mindful yoga. J. Pediatr. Health Care. 2012;26:45–56. [PubMed]
322. Wilens TE, et al. Does stimulant therapy of attention-deficit/hyperactivity disorder beget later substance abuse? A meta-analytic review of the literature. Pediatrics. 2003;111:179–185. [PubMed]
323. Wills TA, Vaccaro D, McNamara G. The role of life events, family support, and competence in adolescent substance use: a test of vulnerability and protective factors. Am. J. Community Psychol. 1992;20:349–374. [PubMed]
324. Wills TA, et al. Coping dimensions, life stress, and adolescent substance use: a latent growth analysis. J. Abnorm. Psychol. 2001;110:309–323. [PubMed]
325. Wills TA. Stress and coping in early adolescence: relationships to substance use in urban school samples. Health Psychol. 1986;5:503–529. [PubMed]
326. Willuhn I, et al. Dopamine signaling in the nucleus accumbens of animals self-administering drugs of abuse. Curr. Top. Behav. Neurosci. 2010;3:29–71. [PMC free article] [PubMed]
327. Wilson DM, et al. Timing and rate of sexual maturation and the onset of cigarette and alcohol use among teenage girls. Arch. Pediatr. Adolesc. Med. 1994;148:789–795. [PubMed]
328. Witkiewitz K, Marlatt GA, Walker D. Mindfulness-based relapse prevention for alcohol and substance use disorders. journal of cognitive psychotherapy. Int. Q. 2005;19:212–228.
329. Wong WC, Marinelli M. Adolescent-onset of cocaine use is associated with heightened stress-induced reinstatement of cocaine seeking. Addict. Biol. 2016;21:634–645. [PMC free article] [PubMed]
330. Wong WC, et al. Adolescents are more vulnerable to cocaine addiction: behavioral and electrophysiological evidence. J. Neurosci. 2013;33:4913–4922. [PMC free article] [PubMed]
331. Yurgelun-Todd DA, Killgore WD. Fear-related activity in the prefrontal cortex increases with age during adolescence: a preliminary fMRI study. Neurosci. Lett. 2006;406:194–199. [PubMed]
332. Zakharova E, et al. Social and physical environment alter cocaine conditioned place preference and dopaminergic markers in adolescent male rats. Neuroscience. 2009a;163:890–897. [PMC free article] [PubMed]
333. Zakharova E, Wade D, Izenwasser S. Sensitivity to cocaine conditioned reward depends on sex and age. Pharmacol. Biochem. Behav. 2009b;92:131–134. [PMC free article] [PubMed]
334. Zehr JL, et al. Dendritic pruning of the medial amygdala during pubertal development of the male Syrian hamster. J. Neurobiol. 2006;66:578–590. [PubMed]
335. Zgierska A, et al. Mindfulness meditation for substance use disorders: a systematic review. Subst. Abus. 2009;30:266–294. [PMC free article] [PubMed]
336. Zlebnik NE, Carroll ME. Prevention of the incubation of cocaine seeking by aerobic exercise in female rats. Psychopharmacology (Berl.) 2015;232:3507–3513. [PMC free article] [PubMed]
337. Zlebnik NE, Anker JJ, Carroll ME. Exercise to reduce the escalation of cocaine self-administration in adolescent and adult rats. Psychopharmacology (Berl.) 2012;224:387–400. [PMC free article] [PubMed]
338. Zlebnik NE, Saykao AT, Carroll ME. Effects of combined exercise and progesterone treatments on cocaine seeking in male and female rats. Psychopharmacology (Berl.) 2014;231:3787–3798. [PMC free article] [PubMed]