OPINION ARTICLE published: 27 May 2013 HUMAN NEUROSCIENCE doi: 10.3389/fnhum.2013.00223 The value of the dual systems model of adolescent risk-taking

Nicole M. Strang*, Jason M. Chein and Laurence Steinberg

Department of Psychology, Temple University, Philadelphia, PA, USA *Correspondence: [email protected] Edited by: Russell A. Poldrack, University of Texas at Austin, USA Reviewed by: Russell A. Poldrack, University of Texas at Austin, USA Sarah Helfinstein, University of Texas at Austin, USA

In recent years, a perspective on adolescent make three main points: (1) that the data 10- to 30-year-olds, participants’ self- risk-taking derived from developmen- do not support the DS model because report indicated a peak in sensation- tal neuroscience has become increasingly there are too few studies assessing the seeking during mid- popular. This perspective, referred to as relationship between development in each (Steinberg et al., 2009), and on a gam- the “dual systems model” (Somerville brain system and patterns of “real-world” bling task, participants’ behavior was et al., 2010; Steinberg, 2010)orsome- behavior; (2) that activation of the socioe- most influenced by rewarding stimuli times the “maturational imbalance the- motional system is sometimes associated during this same age period (Cauffman ory” (Casey et al., 2011), posits that with adaptive functioning, that activation et al., 2010). In contrast, impulse con- increased risk-taking during adolescence of the cognitive control system is some- trol increases gradually and linearly, and is due to a combination of heightened times associated with maladaptive func- the peak in performance on tasks mea- reward sensitivity and immature impulse tioning, and that these pieces of evidence suring capabilities like planning and control, which are tied to the develop- are contrary to the DS model; and (3) that response inhibition occurs subsequent ment of two brain systems that undergo patterns of brain development are more to the peak in reward sensitivity. This significant change during this age period, complex than those described by the DS linear trajectory has been demonstrated but that develop along different timeta- theory. in self-reports of impulsive behavior bles. One system, which has been called As proponents of the DS perspective in several large-scale studies (Steinberg the “socioemotional” incentive process- on adolescent risk taking, we welcome the et al., 2009; Harden and Tucker-Drob, ing system (Steinberg, 2010; Chein et al., opportunity to respond to the Pfeifer and 2011). Additionally there is compelling 2011) or “ventral affective system” (Pfeifer Allen critique. While, we agree that pre- evidence from behavioral studies of cog- and Allen, 2012), is localized mainly sentations of the model have sometimes nitive control, which demonstrate that in the ventral and ventrome- oversimplified the evidence or overlooked performance improves gradually over the dial . The second system, inconsistencies in the literature, we believe course of adolescence and does not peak referred to as the “cognitive control” sys- that the framework continues to offer until late adolescence (Luna, 2009; Albert tem (Steinberg, 2010; Chein et al., 2011) a useful model for understanding risky and Steinberg, 2011). Furthermore, both or “prefrontal control system” (Pfeifer and behavior in adolescence. In the absence of (Verdejo-García et al., 2008) Allen, 2012), is localized mainly in lat- an alternative theoretical account, which and reward/sensation-seeking (Galvan eral prefrontal, parietal, and anterior cin- Pfeifer and Allen do not offer, the DS et al., 2007; Romer, 2010) are correlated gulate cortices (Wager and Smith, 2003; model provides a useful heuristic for the with self-reported risk-taking. Owen et al., 2005). Briefly, the dual systems formulation of testable hypotheses. Importantly, the brain systems pre- (DS) perspective posits that risk-taking Pfeifer and Allen (2012) make sev- sumed to mediate these constructs fol- during mid-adolescence is the product of eral excellent points about the model’s low similar developmental trajectories. the heightened reactivity of the socioe- limitations and the challenges of map- The remodeling of dopaminergic pathways motional system against a backdrop of ping neuroimaging findings onto specific connecting the ventral striatum to the PFC still maturing cognitive control. With fur- theoretical claims. However, in our view, is most pronounced shortly after puberty, ther maturation, the socioemotional sys- there are three main shortcomings in their justbeforetheriseinrewardsensitivity tem becomes less reactive and the cognitive critique. First and foremost, the authors (Spear, 2009; Luciana and Collins, 2012). control system becomes stronger and more fail to acknowledge that there is con- In contrast, the prefrontal and parietal cor- efficient. Together, these changes lead to siderable behavioral evidence consistent tices, which are thought to support age- an increase in risk taking during adoles- with the predictions of the DS model. related improvements in cognitive control cence followed by a decrease in risk taking Reward sensitivity follows an inverted U- (Luna and Sweeney, 2001; Bunge et al., as individuals move into adulthood. shaped curve (Steinberg et al., 2009; 2002; Astle and Scerif, 2009; Luna et al., A recent article (Pfeifer and Allen, Romer, 2010; Harden and Tucker-Drob, 2010),areamongthelastbrainregionsto 2012) critiques the DS model. The authors 2011). In a large behavioral study of mature (Huttenlocher, 1990; Giedd et al.,

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1999; Bitan et al., 2006). The value of examine brain-behavior relations through older adolescents permits individuals to the DS theory is that it provides an inte- individual differences analyses. We note, make more informed decisions, but it also grated account for the observed changes in however, that real-world behaviors are enables them to ruminate, sometimes to risk-taking, in the psychological constructs undoubtedly subserved by interacting and a degree that may lead to or exacerbate presumed to contribute to risk-taking, and distributed brain networks, not just indi- depression. in the structural and functional neural vidual brain regions, and there is not cur- Third, Pfeifer and Allen (2012) point changes presumed to contribute to the rently a consensus on an analytic approach out that there are findings that run counter psychological changes. for exploring correlations between acti- to predictions derived from the DS model. Pfeifer and Allen (2012) are correct that vations in interactive networks and con- It is hard to think of any theory of human there are few studies that assess, within comitant behavior. Moreover, real-world development for which there are no incon- the same experimental sample, correla- risk-taking is influenced by a wide array sistent findings; a complete absence of tions among real-world behavior, associ- of contextual variables that cannot be con- inconsistency in the literature is an unre- ated psychological functioning, and the trolled in the lab. alistic criterion against which to evalu- presumed structural and functional neu- Second, the authors mischaracterize the ate a theory’s utility. Over time, findings ral substrates of these phenomena—but DS model as built on the assumption that that are inconsistent with other studies or this is surely not a shortcoming unique activation of the socioemotional system is with predictions derived from a particu- to this area of inquiry. Indeed, the neu- always maladaptive and activation of the lar theory inevitably arise. In evaluating roimaging literature as a whole includes cognitive control system is always adaptive; these instances, the chief considerations very few studies with an adequate sam- to our knowledge no such assertions have should be (1) whether the inconsistencies ple to support strong conclusions about ever been made by proponents of the DS in the theory can be explained through brain-behavior correlations, and serious view. Perhaps this assertion arises in the more nuanced analyses or by refining the objections have been raised about the popular press, but we don’t believe it is theory; (2) whether the putative incon- potential for spurious conclusions to arise a characteristic of scientific writings that sistencies are incompatible with what the when small sample sizes are used (Yarkoni, employ this framework. The DS model theory actually predicts, rather than with 2009; Vul and Pashler, 2012). Even when is agnostic with respect to whether the mischaracterizations of the theory; and (3) a substantial correlation actually exists developmental changes in brain structure whether there are so many inconsistencies between brain activation in some particu- or function produce desirable or unde- that the theory is no longer useful. lar region and behavior in the population, sirable consequences. Even, if the neural The question of whether reward sen- an atypically large fMRI sample is needed changes of adolescence impel individu- sitivity is heightened during adolescence for a fair chance of detecting the effect als to take more risks, not all risk tak- illustrates the first of these points nicely. [e.g., With a correlation of r = 0.5, 60 par- ing is undesirable; indeed, one of the While, it had once appeared as if findings ticipants would be needed to give an 80% central propositions of the framework is onthisissuewerealloverthemap(with chance of detecting the effect at a statistical that the heightened risk taking seen dur- some studies finding adolescent hypersen- threshold of p < 0.001 (Yarkoni, 2009)]. ing adolescence is an evolutionarily adap- sitivity to reward, some finding adolescent Given that developmental MRI studies tive phenomenon. The hyper-responsivity hyposensitivity, and others finding no age almost universally have sample sizes of to reward that characterizes adolescents differences), an accumulation of evidence fewer than 40 participants per age group, relative to children and adults in many has made it clear that adolescents most evaluating the DS model based on how studies of reward processing (Ernst et al., often evince a greater response to reward- well-individual differences in brain acti- 2005; Galvan et al., 2006; Geier et al., ing stimuli as compared to adults (Ernst vation predict real world behaviors is an 2010; van Leijenhorst et al., 2010a,b; et al., 2005; Galvan et al., 2006; Geier unreasonable criterion. It is fair to say Chein et al., 2011; Christakou et al., 2011; et al., 2010; van Leijenhorst et al., 2010a,b; that the DS model has seldom been tested Padmanabhan et al., 2011; Smith et al., Chein et al., 2011; Christakou et al., 2011; in predictions of real world behavior, but 2011; Somerville et al., 2011)isnei- Padmanabhan et al., 2011; Smith et al., untested is not the same as inaccurate. ther inherently maladaptive nor inherently 2011; Somerville et al., 2011). Further, Pointing out that two different aspects adaptive; to quote an overused colloquial- recent analyses have shown that consid- of development (brain and behavior) fol- ism,“itiswhatitis.”Insomeindividuals eration of the stage of the reward pro- low similar trajectories is, admittedly, not this may lead to maladaptive sensation- cessing under examination (Galvan, 2010; evidence that one trajectory causes the seeking, or drug use, or unprotected sex. Geier et al., 2010)mayprovideanexpla- other, but neither is it merely argument by In others, it may lead to more intense nation for those few studies (Bjork et al., analogy, as Pfeifer and Allen (2012) assert. attempts to win the admiration of others, 2004, 2011) that find a different pattern of Itstrikesusasmorethancoincidentalthat earn money, or do well in school. Rewards results. patterns of behavior in adolescence fol- come in many forms, some socially val- The second issue regarding inconsis- low a developmental course matching that ued, and others undesirable. Similarly, we tencies is illustrated by Pfeifer and Allen’s observed in brain systems presumed to find no descriptions of the DS theory (2012) assertion that the DS theory pre- undergird these behaviors. As it becomes which assert that more cognitive control dicts that one should see greater activa- possible and more common to collect data is always more adaptive. The improved tion of prefrontal regions with age. This from larger samples, it will be possible to ability to imagine the future seen among is not a prediction that comes from the

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DS theory. The expected relationships clarity regarding the relationship between Bjork, J. M., Smith, A. R., Chen, G., and Hommer, between age and activation depend on the age-related improvements in cognitive D. W. (2011). Psychosocial problems and recruit- task demands. The DS model predicts that control and brain activation will emerge as ment of incentive neurocircuitry: exploring indi- vidual differences in healthy adolescents. Dev. when a task and the method of analysis methods for assessing structural and func- Cogn. Neurosci. 1, 570–577. provide an index of the tendency to engage tional connectivity improve (Dosenbach Bunge, S. A., Dudukovic, N. M., Thomason, M. E., cognitive control, PFC activation should et al., 2010). Vaidya, C. J., and Gabrieli, J. D. (2002). Immature be weaker on average among adolescents Having new tools to investigate the rela- contributions to cognitive control relative to adults. This is generally what tionship between brain and behavior may in children: evidence from fMRI. 33, 301–311. one finds, for instance, if one examines the allow us to make important advances, but Casey, B. J., Jones, R. M., and Somerville, L. H. (2011). subset of studies exploring age-dependent in the absence of a testable theory we Braking and accelerating of the adolescent brain. PFC activation during working memory can’t expect that much will be learned. We J. Res. Adolesc. 21, 21–33. task performance, as reviewed by Crone believe the DS model still serves an impor- Cauffman, E., Shulman, E. P., Steinberg, L., Claus, E., and Dahl (2012), for which the majority of tant purpose, in that it yields specific and Banich, M. T., Graham, S., et al. (2010). Age dif- ferences in affective decision making as indexed studies demonstrate a pattern of increasing testable predictions. We further, contend by performance on the Iowa Gambling Task. Dev. PFC activity with age. In contrast, when a that there are fewer caveats and contradic- Psychol. 46, 193–207. task and the associated method of analy- tory findings than have been implied by Chein, J. M., Albert, D., O’Brien, L., Uckert, K., and sis provide an index of the efficiency with Pfeifer and Allen (2012), and indeed that Steinberg, L. (2011). Peers increase adolescent risk taking by enhancing activity in the brain’s reward which control is achieved, then PFC acti- there are many other sources of affirma- circuitry. Dev. Sci. 14, F1–F10. vationwouldbeexpectedtobegreateron tive evidence for the DS model. Because Christakou, A., Brammer, M., and Rubia, K. (2011). average for adolescents relative to adults. the DS model took its original form from Maturation of limbic corticostriatal activation Of course, determining whether, a specific behavioralscienceitistobeexpectedthat and connectivity associated with developmental approach provides an index of tendency the model is not yet fully specified with changes in temporal discounting. Neuroimage 54, 1344–1354. or efficiency is not a simple undertaking respect to patterns of brain function. There Crone, E. A., and Dahl, R. E. (2012). Understanding because even subtly varying factors (e.g., is a complex mapping between psycho- adolescence as a period of social-affective engage- proportion of targets to lures, degree of logical constructs and their neural under- ment and goal flexibility. Nat. Rev. Neurosci. 13, proactive interference, stimulus, and feed- pinnings, and we anticipate that further 636–650. back timing, shape of assumed hemody- specification of the model will become Dosenbach, N. U. F., Nardos, B., Cohen, A. L., Fair, D. A., Power, J. D., Church, J. A., et al. namic model, etc.) are known to affect possible as the field develops refined ways (2010). Prediction of individual brain maturity how a task functions. Engaging in care- to integrate behavioral and neuroscien- using fMRI. Science 329, 1358–1361. ful task analysis, garnering support from tific sources of evidence. We welcome fur- Ernst, M., Nelson, E. E., Jazbec, S., McClure, E. B., converging methodologies (e.g., behavior, ther attempts to confirm, or disconfirm, Monk, C. S., Leibenluft, E., et al. (2005). ERP, computational modeling), and run- aspects of the DS model, as well as the and in responses to receipt and omission of gains in adults and adolescents. ning larger sample sizes to allow greater introduction of alternative theories that Neuroimage 25, 1279–1291. exploration of brain-behavior relation- might better account for the phenomenol- Galvan, A. (2010). Adolescent development of the ships, might be useful ways to overcome ogy of adolescent risk behavior. reward system. Front. Hum. Neurosci. 4:6. doi: this challenge. 10.3389/neuro.09.006.2010 Galvan,A.,Hare,T.,Voss,H.,Glover,G.,andCasey, There is behavioral evidence that is ACKNOWLEDGMENTS B. J. (2007). Risk-taking and the adolescent brain: consistent with the DS model’s prediction Funding relevant to development of this whoisatrisk?Dev. 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