Executive cognitive functions and impulsivity as correlates of risk taking and problem behavior in preadolescents
Introduction
Early initiation of drugs and other risk behaviors portends dysfunctional developmental outcomes. For example, youth who initiate drug use prior to age 14 exhibit the highest rates of lifetime drug use and substance use disorder (SUD) (Grant & Dawson, 1998). Early users of drugs also tend to engage in other externalizing behaviors, such as aggressive behavior and rule breaking that place them at risk for poor developmental trajectories (McGue et al., 2006, Moffitt, 1993, Moffitt, 1996, Moffitt and Caspi, 2001). Early intervention may be able to alter these trajectories toward a healthier course. We examine and test neuropsychological explanations for these early manifestations of problem behavior to help identify potential points of intervention.
Hypotheses concerning the antecedent conditions and causes of youth drug abuse and other risk behaviors generally refer to one or more concepts related to what various researchers call self-control, self-regulation, behavior control, or impulsivity. There is the potential for confusion among these concepts, partly because of inconsistencies in terminology between laboratories, and partly because the concepts themselves have yet to be fully understood and differentiated from one another. In the present study, we distinguish between a set of mental abilities called executive cognitive functions (ECFs), on the one hand, and a set of self-reported personality traits broadly called impulsivity, on the other. ECFs include working memory, cognitive control, and reward processing, abilities that will be described in greater detail shortly. Impulsivity includes traits of sensation seeking and the tendency to act without thinking or planning.
One hypothesis put forth by Tarter and colleagues (Aytaclar et al., 1999, Tarter et al., 2003) points to a syndrome of early externalizing behaviors as well as poor ECF, a pattern they call “neurobehavioral disinhibition”, as the source of early risk taking. They find that youth with high levels of this pattern at ages 10–12 years exhibit high levels of drug use in late adolescence (age 19). They place particular emphasis on ECF as one source of the risk (Aytaclar et al., 1999). Moffitt and colleagues also emphasize early neuropsychological deficits as the source of risk for development of a conduct-disordered trajectory that persists into adulthood. However, they also note the importance of impulsivity for this trajectory (Caspi et al., 1995, White et al., 1994).
Despite evidence for a range of behavioral and cognitive deficits as the precursors of early drug use and risk taking, the precise nature of the deficit has not been isolated (see Zucker, Donovan, Masten, Mattson, & Moss, 2008 and Zucker, 2006, for reviews). Indeed, poor ECF in preadolescence may not correlate with contemporaneous risk behavior. Aytaclar et al. (1999) found that some ECFs at ages 10–12 predicted drug use two years later. However, Tarter et al. (2003) found that ECF assessed at ages 10–12 did not predict subsequent drug use at age 16 or correlate with risk for drug use based on parental drug use history, while other indicators, such as externalizing behaviors, were much better predictors. It was not until age 19 that early ECF was a predictor of drug use and SUD. In neither of these studies was drug use assessed at the same time as ECF (ages 10–12), and in both cases the samples were drawn to contrast high versus lower risk youth rather than more general community populations.
Nigg et al. (2004) examined an extensive battery of ECFs in relation to drug use in boys ages 12–15. The ECFs that were studied did not appear to lie on a single dimension, and there was no evidence of relations between early drug use and the various ECF indices. A study of later drug use in the same sample of boys and a smaller sample of girls at ages 15–17 revealed a small correlation between performance on a response inhibition task (stop signal reaction time paradigm) and use of alcohol and other drugs (Nigg et al., 2006). However, the sample was drawn primarily from families with a history of drug abuse, and the ECF-drug use relation did not emerge until mid adolescence. It is not possible therefore to rule out the hypothesis that early drug use influences ECF rather than the other way around. Furthermore, the relation was only observed for one of many ECF tasks, making it difficult to determine the generality of the finding. Hence, little is known about the relation between ECF and risk taking in preadolescent community samples, and what evidence there is suggests that ECF is not strongly related to early initiation of risky behavior.
Other research has examined the relation between ECF and risk taking tendencies during childhood and adolescence (Crone and van der Molen, 2004, Hooper et al., 2004, Lamm et al., 2006, Overman et al., 2004). However, this research tends to use proxies for risk taking, such as the Iowa Gambling Task (IGT) (Bechara, Damasio, Damasio, & Anderson, 1994), rather than actual initiation of drug use or other risky behavior. This task as well as others test the ability to process and keep track of reward contingencies and are often treated as an index of ECF in itself. We refer to these tasks as measures of reward processing because they tend to be associated with orbitofrontal functioning (Fellows and Farah, 2005, Wallis, 2007). However, this research indicates that working memory as well as other aspects of ECF, such as ability to exert cognitive and behavioral control, is not related to reward processing in youth.
Research with adults has found that some components of ECF, working memory and reversal learning, are related to performance in the IGT (Bechara et al., 1998, Bechara and Martin, 2004). However, this relation has only been observed in persons who are drug dependent or who suffered brain lesions that affect decision making. Nevertheless, in commenting on these findings, Bechara and Martin (2004) noted that “the integrity of decision making seems to be dependent on the intactness of working memory—that is, the participant's decision making is affected by having an abnormal working memory” (p. 160). In their research, Farah and Fellows (2005) found that both working memory capacity and reversal learning deficits may underlie performance on this task.
Other research with normal subjects has found evidence that working memory capacity influences performance on reward processing tasks. A study by Finn (2002) found that working memory affected the performance of young adults on a task requiring learning of cues to reward. In addition, Hinson and colleagues (Hinson et al., 2002, Hinson et al., 2003) as well as Shamosh et al. (2008) find that reduced working memory capacity increases the tendency to choose smaller immediate rewards over larger but delayed rewards. Hence, there is some suggestion that weak working memory may interfere with optimal performance on reward processing tasks that involve the need to inhibit responses that previously led to reward or that currently lead to non-optimal reward.
Another major correlate of risky behavior in adolescents is a set of relatively stable personality traits under the rubric of impulsivity (S.B.G. Eysenck and Eysenck, 1977, Eysenck and Eysenck, 1978, Patton et al., 1995, Verdejo-Garcia et al., 2008, Whiteside and Lynam, 2001, Zuckerman, 2006). These traits are regarded as under the control of both the prefrontal cortex (PFC) and the subcortical motivational systems to which it is linked (Chambers and Potenza, 2003, Chambers et al., 2003, Cloninger, 1987, Cloninger, 1988, Zuckerman, 2006). Research in both humans and animals suggests that impulsivity is multidimensional (Evenden, 1999, Whiteside and Lynam, 2001) and that some of its manifestations grow in strength during adolescence (Casey et al., 2008, Chambers and Potenza, 2003, Chambers et al., 2003, Spear, 2000a). In particular, sensation seeking, the attraction to novel and exciting experiences peaks during adolescence (Romer and Hennessy, 2007, Zuckerman, 2006), likely reflecting enhanced dopamine release to the ventral striatum and prefrontal cortex (Chambers et al., 2003, Spear, 2000a, Spear, 2000b). Based on this increase, one would expect early risk takers to exhibit higher levels of sensation seeking, a pattern confirmed in one study of early drug use initiation (Crawford, Pentz, Chou, Li, & Dwyer, 2003).
Other forms of impulsivity may also correlate with early risk behavior. For example, tendencies to act without thinking have been studied under the rubric of poor behavioral control (Block et al., 1988, Wong et al., 2006) or as part of novelty seeking in Cloninger's system (1988). This research indicates that early levels of poor behavioral control foreshadow later drug use, findings consistent with models put forth by Cloninger (1988), Tarter et al. (2003), and Moffitt (1993). Indeed, early manifestations of poor behavioral control might reflect the effects of the same mechanisms that underlie sensation seeking. However, less is known about how closely sensation seeking and poor behavioral control correlate during preadolescence when many risk behaviors first emerge.
Several theories of cortical and subcortical brain development focus on the relative imbalance between subcortical reward systems that mature more rapidly than slowly developing frontal control systems, resulting in poor control over impulsive behavior during adolescence (Casey et al., 2008, Nelson et al., 2002, Steinberg, 2008). These models base their predictions on structural brain imaging studies showing that dorsal and frontal brain areas exhibit a slower course of pruning and myelination than ventral and occipital areas (Gogtay et al., 2004; Sowell et al., 2003). Indeed, these studies indicate that complete maturation of these frontal areas does not occur until the third decade of life. Based on these models, one would expect that ECF would have only limited ability to control impulsive behavior tendencies in early adolescence. Nevertheless, models of neurobehavioral risk for SUD (Moffitt, 1993, Nigg et al., 2004, Tarter et al., 2003) anticipate that ECF and impulsivity will be inversely related. Consistent with this expectation, an intervention to improve working memory ability in children ages 7–12 with ADHD found that the resulting improvements in ECF were accompanied by reductions in parent reports of impulsive tendencies (Klingberg et al., 2005).
Impulsivity may also play a role in the manifestation of various types of externalizing problems that have also been associated with drug use and other risky behaviors in childhood and adolescence. Indeed, sensation seeking and poor behavioral control are major characteristics of externalizing behaviors (Caspi et al., 1995, White et al., 1994). In addition, externalizing problems tend to correlate moderately with internalizing symptoms in children and adolescents (Achenbach, 1991, Krueger et al., 1998), perhaps reflecting overlapping genetic influences (Kendler, Aggen, Jacobson, & Neale, 2003). Given that both externalizing and internalizing problems in childhood foreshadow later drug use in adolescence (Zucker et al., 2008, Zuckerman, 2006), we anticipate that impulsivity would be an important source of those symptoms. Nevertheless, externalizing problems may be related to risk taking apart from their relation to impulsivity as suggested by models such as Tarter's neurobehavioral disinhibition approach.
Sensation seeking and poor behavioral control have been implicated in the initiation and continuation of a wide range of risky behaviors in adolescents (Verdejo-Garcia et al., 2008, Zuckerman, 2006). Indeed, risk behaviors tend to cluster in adolescents such that initiation of one behavior is related to initiation of others (Biglan and Cody, 2003, McGue et al., 2006). Hence, we expected that we would observe early initiation of several behaviors that place youth at risk for adverse outcomes. In particular, we have already reported the high rate of gambling for money that we have observed in the present cohort (Hurt, Giannetta, Brodsky, Shera, & Romer, 2008). Unlike most studies of ECF and other risk factors, we examined the general tendency to engage in risk taking using a variety of risky behaviors as markers of this pattern.
In this first wave of a prospective study, we examined a range of ECFs, forms of impulsivity, and externalizing and associated internalizing problems as correlates of general risk taking tendencies in a community sample of pre-adolescents ages 10–12. We also assessed a wide range of risky behaviors, including drug use, gambling, and fighting. Our interest in studying the inter-relationships among several different forms of ECF, impulsivity, externalizing behavior, and risk behavior led us to adopt structural equation modeling (SEM) as the analytic strategy (Kaplan, 2000). This approach permits one to measure factors common to different assessments that nevertheless reflect the same theoretic processes and to test hypothesized relationships between those factors. The method also permits tests of alternative models for explaining relationships between factors (see Miyake, Friedman, Rettinger, Shah, & Hegarty, 2001, for a similar approach).
Based on theories of adolescent neurobiological vulnerability to drug use and dependence (Moffitt, 1993, Tarter et al., 2003) as well as models of adolescent brain development (Casey et al., 2008, Chambers et al., 2003, Steinberg, 2008), we expected impulsivity as assessed by both sensation seeking and failure to think before acting to be positively related to early initiation of risk behaviors and to externalizing and internalizing problems. We also expected ECFs, especially working memory ability and indicators of reward processing, to be inversely related to impulsivity, early initiation of risk behaviors, and externalizing/internalizing problems. In addition, based on Tarter's model, we expected externalizing problems to be related to risk taking apart from impulsivity.
Section snippets
Method
Participants in this multi-cohort longitudinal study were enrolled at ages 10–12 years. This report included data on the 387 youth who completed the first of four planned annual assessments. Seventy percent of the subjects attended 7 Philadelphia schools where onsite enrollment occurred. The remaining 30% attended other Philadelphia area schools and were recruited through flyers distributed at schools and posted in local venues such as libraries. Parental consent and youth assent were obtained
Results
Table 1 presents the intercorrelations between the various measures analyzed in this study as well as their relations with male gender and age. For each measure, means and standard deviations are listed in the last rows of the table. Male youth tended to exhibit better cognitive control on the Flanker task but not on the Stroop, to perform worse on one reward processing task (reversal learning), to engage in more risk behaviors, to have fewer internalizing behavior problems, and to have higher
Discussion
This study of a community sample of pre-adolescent youth identified early initiators of several risk behaviors described by a single factor, confirming the existence of a general risk-taking tendency at this early age. We also found evidence for a general tendency toward impulsive behavior defined by both sensation seeking and lack of thinking and planning when acting. Furthermore, consistent with our expectations concerning the importance of impulsivity as a precursor to early risk behavior,
Acknowledgments
This work was supported by NIDA RO1 DA 18913-01, NICHD 3P30 HD26979, and GCRC RR00240.
References (127)
- et al.
Evaluation of behavioral measures of risk taking propensity with inner city adolescents
Behaviour Research and Therapy
(2005) - et al.
Association between hyperactivity and executive cognitive functioning in childhood and substance use in early adolescence
Journal of the American Academy of Child and Adolescent Psychiatry
(1999) The role of emotion in decision-making: Evidence from neurological patients with orbitofrontal damage
Brain and Cognition
(2004)- et al.
Insensitivity to future consequences following damage to human prefrontal cortex
Cognition
(1994) - et al.
Decision-making deficits, linked to a dysfunctional ventromedial prefrontal cortex, revealed in alcohol and stimulant abusers
Neuropsychologia
(2001) - et al.
Activation of prefrontal cortex in children during a nonspatial working memory task with functional MRI
Neuroimage
(1995) - et al.
The adolescent brain
Developmental Review
(2008) - et al.
Using deformable surfaces to segment 3-D images and infer differential structures
Computer, Vision, Graphics, Image Process: Image Understand.
(1992) - et al.
Working memory and intelligence are highly related constructs, but why?
Intelligence
(2008) - et al.
Common regions of the human frontal lobe recruited by diverse cognitive demands
Trends in Neurosciences
(2000)