Other factors such as gender and family history of AUDs may moderate this relationship

Cognitive theories attempting to explain adolescent risk-taking as the result of underdeveloped decision-making skills have found little, if any support, as studies demonstrate that adolescents show an adequate understanding of the steps involved in the decision-making process, such as weighing pros and cons. In fact, children as young as 4 years old have some understanding of consequence probabilities and adolescents and adults show equal levels of awareness of the consequences associated with risky behaviors . In some cases, adolescents may even overestimate their personal vulnerability to risk consequences compared to adults . Further, interventions designed to provide adolescents with information about the risks of substance use, drinking and driving, and unprotected sex have proved largely unsuccessful and have done little to change adolescents’ actual behavior . Simplified theories of “immature cognitive abilities” in adolescence are also inconsistent with a developmental perspective, as the increase in cognitive sophistication from childhood to adolescence would imply a decrease in risk-taking behaviors with age, rather than an increase . Steinberg proposes an alternative view of adolescent risk-taking behavior that is rooted in developmental neuroscience. Specifically, heightened risk-taking in adolescence is described as the product of a “competition” between a socioemotional network that is sensitive to social and emotional stimuli , and a cognitive control network that is responsible for regulating executive functions such as planning, organization, response inhibition, and self-regulation. The socioemotional network relies on limbic and paralimbic structures such as the amygdala, ventral striatum, orbitofrontal cortex,cannabis plant growing ventromedial prefrontal cortex, and superior temporal sulcus, while the cognitivecontrol network consists of lateral prefrontal and parietal cortices as well as the anterior cingulate . During adolescence, the brain undergoes significant structural, functional, neurochemical, and hormonal changes that directly impact the development of the socioemotional and cognitive control networks, among other regions.

Specifically, synaptic pruning and myelination processes result in reduced gray matter volume and increased white matter volume by late adolescence/early adulthood . Increases in white matter during adolescence are associated with greater structural connectivity and faster, more efficient neural communication between brain regions . Evidence from neuroimaging studies note that dramatic changes occur in the brain’s dopaminergic system at puberty, primarily in prefrontal and striatal regions . Specifically, dopamine activity shows substantial decreases in the nucleus accumbens, an important region of the ventral striatum well known for its role in reward processing. Dopamine has been implicated as a primary mechanism of affective and motivational regulation and is linked to the socioemotional network ; thus, the sudden decrease in this neurochemical creates a “dopamine void” which may compel adolescents to seek out novel and risky behaviors to compensate . Changes in brain regions associated with the cognitive control network also take place in adolescence, including gray matter decreases and white matter increases in the prefrontal cortex, and an overall increase in synaptic connections among cortical and subcortical regions of the brain . In contrast to the acute changes that occur to socioemotional regions with puberty, changes in the cognitive control network are gradual and typically continue into the mid-twenties. As a result of timing differences in the developmental brain changes that occur during adolescence, there appears to be a “timing gap” between the maturation of the socioemotional network and the maturation of the cognitive control network. Greater motivational drives for novel and rewarding experiences combined with an immature cognitive control network may predispose adolescents to risky behavior, including substance use. This becomes especially relevant under conditions of high emotional arousal , where the socioemotional network is likely to become highly activated and the cognitive control network must “work harder” to override it . While neurochemical modifications and other developmental brain changes may contribute to adolescents’ increased propensity for risk-taking , it is paradoxical, as the brain may be especially vulnerable to the insult of alcohol during this critical time . A handful of studies have shown a deleterious effect of heavy alcohol use on adolescents’ neuropsychological performance in varied domains, including visuospatial abilities , verbal and non-verbal retention , attention and information processing , and language and academic achievement .

Female adolescent alcohol users have also shown deficits on tasks of executive functioning, specifically those involving in planning, abstract reasoning, and problem-solving . Post-drinking effects, such as hangover severity and withdrawal symptoms have been demonstrated to be important predictors of alcohol-related neurocognitive impairment, as greater self reported withdrawal symptoms have been linked with poorer visuospatial functioning and poorer verbal and non-verbal retention . Longitudinal studies have examined whether observed neurocognitive deficits in this population represent premorbid risk factors for use or consequences of heavy alcohol use. In one study, after controlling for recent alcohol use, age, education, practice effects, and baseline neuropsychological functioning, substance use over an 8-year follow-up period significantly predicted neuropsychological functioning at Year 8. Specifically, adolescents who reported continued heavy drinking and greater alcohol hangover or withdrawal symptoms showed impairment on tasks of attention and visuospatial functioning compared to non-using adolescents . These findings were replicated in a prospective study that characterized at-risk adolescents prior to initiating alcohol use. For females, initiation of alcohol use over the follow-up period was associated with worsening visuospatial functioning, while greater hangover symptoms over the follow-up period predicted poorer sustained attention in males . Taken together, these studies suggest that heavy drinking during adolescence is associated with deficits in cognitive performance, which likely result from, rather than predate, alcohol use.Specifically, evidence suggests that females may be more vulnerable to the negative impact of heavy alcohol use in adolescence , and a positive family history of AUDs has been associated with worse neurocognitive performance in adolescent heavy alcohol users, particularly in language and attention domains . Structural magnetic resonance imaging studies provide evidence for anatomical brain abnormalities in adolescents with histories of heavy lifetime alcohol use, compared to their non-using peers.

The hippocampus appears to be one area of potential vulnerability, as decreased bilateral hippo campal volumes have been observed in adolescents meeting criteria for AUDs, with smaller hippo campi related to earlier onset and longer duration of the disorder . Nagel, Schweinsburg, Phan, and Tapert found similar results, with smaller left hippo campal volumes observed in heavy alcohol-using adolescents compared to controls, even after excluding teens with co-occurring Axis I disorders. Hippo campal volume did not correlate with degree of alcohol use in this study, suggesting that between-group differences may be reflective of premorbid factors, and not solely the result of heavy alcohol use. Another area of the brain that may be especially vulnerable to the effects of heavy alcohol use in adolescence is the prefrontal cortex. As a key component of both the cognitive control and socioemotional networks, this region is important to the study of risk-taking. In a sample of adolescents with co-occurring psychiatric and AUDs, DeBellis and colleagues found significantly smaller prefrontal cortex volumes in alcohol users compared to controls. These findings were replicated by Medina and colleagues in a sample of alcohol dependent adolescents without psychiatric disorders; however,vertical grow rack system a significant group by gender interaction was observed. Specifically, alcohol dependent females showed smaller prefrontal cortex and white matter volumes than female controls, and alcohol dependent males showed larger prefrontal and white matter volumes than male controls. In a cortical thickness study of adolescent binge drinkers, Squeglia, Sorg, and colleagues found alcohol use by gender interactions in four left frontal brain regions, where female binge drinkers had thicker cortices than female controls and male binge drinkers had thinner cortices than male controls. Thicker frontal cortices corresponded with poorer visuospatial, inhibition, and attention abilities for females and worse attention abilities for males, providing further evidence that females may be especially vulnerable to brain changes brought on by heavy alcohol use in adolescence. Diffusion tensor imaging studies have yielded corroborating evidence of altered brain development in adolescent heavy alcohol users. In one study, adolescents with histories of binge drinking showed decreased white matter integrity in 18 major fiber tract pathways, specifically in the frontal, cerebellar, temporal, and parietal regions . Another study found reduced white matter integrity in the corpus callosum of youth with AUDs, particularly in the posterior aspect . In addition, reduced white matter integrity in this region was related to longer durations of heavy drinking, larger quantities of recent alcohol consumption, and greater alcohol withdrawal symptoms .

There is evidence that poorer white matter integrity may be both a consequence of adolescent alcohol use and a predisposing risk factor for use. Specifically, in a study of 11- to 15-year-old alcohol naïve youth, Herting, Schwartz, Mitchell, & Nagel, found that youth with a positive family history of AUDs had poorer white matter integrity in several brain regions, along with slower reaction time on a task of delay discounting, when compared to youth without a family history of AUDs. In addition, Jacobus, Thayer, Trim, Bava, and Tapert found that poorer white matter integrity measured in 16- to 19-year old adolescents was related to more self-reported substance use and delinquency/aggression at an 18-month follow-up. In fMRI studies, altered neural processing has been observed in heavy drinking adolescents during cognitive tasks of spatial working memory , verbal encoding, and visual working memory . Tapert and colleagues found that adolescents with a history of heavy drinking over the past 1-2 years showed increased blood oxygen level-dependent response in bilateral parietal regions during a SWM task, but decreased BOLD activation in the occipital and cerebellar regions compared to lighter drinkers. In addition, BOLD activation abnormalities were associated with more withdrawal, hangover symptoms, and greater lifetime alcohol consumption. Similarly, in a study of verbal encoding, Schweinsburg, McQueeny, Nagel, Eyler, and Tapert showed that adolescent binge drinkers had more BOLD response in the right superior frontal and bilateral posterior parietal regions but less BOLD response in the occipital cortex, compared to non-drinkers. Control adolescents also showed significant activation in the left hippocampus during novel encoding, whereas binge drinkers did not. A 2011 follow-up to this investigation found increased dorsal frontal and parietal BOLD response among 16- to 18-year-old binge drinkers, and decreased inferior frontal response during verbal encoding . Squeglia, Pulido, and colleagues found comparable results during a VWM task, in that heavy drinking adolescents showed more BOLD response compared to matched controls in right inferior parietal, right middle and superior frontal, and left medial frontal regions, but less BOLD response in left middle occipital regions. Notably, this investigation included a longitudinal component with a separate sample of adolescents in which the brain areas showing group differences in BOLD response to the VWM task were identified as ROIs. Adolescents were scanned at baseline before they ever used alcohol or drugs and then scanned again at a 3-year follow-up time point. Adolescents from this sample who transitioned into heavy drinking during the follow-up period showed less BOLD response to the VWM task compared to continuous non-drinkers in frontal and parietal regions at baseline; in addition, BOLD response in these regions increased significantly over the follow-up period for the heavy drinkers, while controls’ BOLD response did not change significantly over time. Finally, less BOLD activation at baseline predicted subsequent substance use, above and beyond age, family history of AUDs, and baseline externalizing behaviors. Taken together, results from these studies suggest that the adolescent brain is indeed sensitive to the insult of excessive alcohol use, and structural alterations and neural reorganization may result from continued heavy drinking. In turn, this altered brain development may trigger cognitive, emotional, and behavioral changes, leading to further alcohol use and other risk-taking behaviors. As the majority of fMRI studies of adolescent alcohol users to date are cross sectional in nature, it is difficult to determine whether the observed neural abnormalities predate the onset of alcohol use, or are consequences of alcohol use. However, results of the Squeglia, Pulido et al. study suggest that a combination of both explanations may be most accurate. Specifically, neural functioning differences may be evident prior to the initiation of drinking, but early alcohol use may also change the trajectory of normative brain development observed in adolescence, leading to less efficient neural processing over time.

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