This study examined whether individuals who put themselves at high risk for stimulant dependence by using stimulants occasionally, show behavioral and/or neural processing differences in risk-taking decision making situations and yielded three main findings. First, OSU did not differ from healthy comparison subjects on their preference for risky versus safe options. Second, OSU showed attenuation of brain activation in areas that are important for risk processing as well as reduced neural differentiation of risky and safe options in brain areas essential for cognitive control mechanisms and bodily representation of risk. Third, THC use did not modulate these findings, but excessive co-use had additional effects on neural activation, which could contribute to poorer processing of risk.

In line with our hypothesis based on stimulant dependent individuals [39, 45, 59, 60], OSU exhibited insula and DLPFC attenuation across safe and risky decision making. Moreover, OSU relative to CS showed lower sgACC and striatal activation during risky decisions, but smaller IFG deactivation during safe decisions. OSU with greater lifetime stimulant use exhibited lower dACC and posterior insula activation during risky decision making. Finally, higher amounts of THC co-use were associated with a less pronounced deactivation and less neural differentiation of risky and safe options within the striatum, insula and prefrontal cortex. OSU who adjusted behavior towards lowered risk as a response to monetary losses resembled CS [26, 28, 29, 61] by exhibiting dorsal striatum, IFG, and dACC activation during decision making more than OSU who engaged in continued risk. Taken together, these results support the hypothesis that individuals even at very early stages in their stimulant use show aberrant risk-related brain activation towards recruiting brain areas less that are important for cognitive control or interoceptive processing. Attenuated neural differentiation of risky and safe options may lead an individual to process risky options and/or associated outcomes differently. This blunted neural response especially in brain areas essential for cognitive control mechanisms may make it difficult for OSU to refrain from risky decisions.

Given that the present study design was cross-sectional and did not include subjects prior to any stimulant use in a follow-up design, we cannot strictly conclude that these differences precede the onset of stimulant use. Nevertheless, because OSU had minimal exposure to stimulants and the majority of brain differences were not affected by THC use, it is most likely that these differences are not a consequence of extended stimulant use. Taken together, we identified brain activation patterns in OSU typical for chronic users [38–40, 45, 60, 62, 63] at stages where subjects–in this case high functioning students in challenging academic situations–and their environment, e.g. school, work and health care system, may not be aware of this heightened risk as overt behavioral impairments are not yet prominent. Given the minimal exposure to neurotoxic substances in our sample, we hypothesize that these may have preceded stimulant initiation. Longitudinal studies starting in stimulant naïve individuals are needed to verify this hypothesis.

Behaviorally, OSU performed comparably to CS, which is at odds with our prior investigation using the risky gains task in a small sample of OSU [23]. One possible explanation for this contradiction is the fact that only students without evidence for ADHD or antisocial personality disorder were included into the current investigation. The absence of behavioral differences is in line with our previous findings of absent or only subtle cognitive impairments on standard neuropsychological tests [64, 65] and other neuroimaging tasks [66, 67] in this sample. The absence of behavioral alterations at early stages of stimulant use suggests that cognitive impairments may increase with greater use of drugs [22, 68] as research has highlighted behavioral impairments in chronic users. Nevertheless, neural differences emerged between OSU and CS despite the absence of behavioral impairments in OSU, suggesting that OSU and CS differ in the process arriving at decisions. Specifically, OSU presented an attenuated neural differentiation of risky and safe decisions, thus seemed less sensitive to adverse consequences of risk taking. This finding extends recent results of our group showing a blunted neural response to risk in the absence of performance differences to be indicative of relapse to stimulant use [50].

OSU displayed a pronounced attenuation of dorsal striatum, ACC, prefrontal and insular activation to both risky and safe decisions. Drawing on findings in healthy subjects and stimulant dependence [26, 27, 36, 37, 44, 69], these results suggest that neural decision making impairments in OSU relate to dysfunctions in all aspects of decision making. First, OSU showed attenuated recruitment of prefrontal cortex, ACC, ventral striatum and left anterior insula. These areas are, among others, crucial for various cognitive rather than motivational/emotional aspects of decision making, e.g. discerning reward values of available choices, maintaining task objectives in short term memory, calculation of risk prediction error or choice-outcome contingency learning. Thus, these findings are similar to findings observed in stimulant dependent subjects. Specifically, chronic cocaine and methamphetamine dependent patients in contrast to non-users have for instance been shown to exhibit DLPFC and SFG hypoactivation for instance during delay discounting tasks, which require subjects to weigh alternatives with immediate or short-term outcomes against decisions with higher, but delayed pay offs while making decisions during hard compared to easy trials [39, 62] as well as DLPFC reductions during decision making [45, 60]. Prior work also demonstrates IFG reductions in stimulant dependent individuals during decision making [40–43]. Our findings now suggest that decision making related attenuation of prefrontal recruitment is prominent at very early stages of stimulant use, suggestive of a neural pattern potentially promoting initiation of stimulant use.

Second, OSU were also characterized by attenuated activation of the dACC, a brain area crucial for detection of conflict and action selection. Moreover, OSU presented attenuated rACC and sgACC activation, which have been related to motivational and learning-related aspects of goal-directed behavior [32–34]. Our findings in OSU extend prior work in chronic users, where cocaine dependent patients showed reduced ACC activation across risky and safe conditions while gambling [38]. Multi-substance abusers also exhibited attenuated ACC activation, which correlated with a greater number of risky decisions [19]. Third, attenuation of striatal, sgACC and insula activation support the notion that OSU experience risk as less aversive than CS as revealed by research on non-users with different risk preferences [70]. The attenuation also suggests a diminished linkage of risk with positive and negative outcomes in OSU. Risk-outcome associations, however, are essential for successful behavioral adjustment in terms of subsequent avoidance of punishment. Prior work in chronic substance users revealed diminished caudate activation to a variety of non-drug rewards [46, 47], findings summarized as the ‘reward deficiency syndrome’ hypothesis. Our findings of attenuated insula activation in a substantial sample of OSU are in line with previous decision making studies in cocaine dependent patients [40], relapsing methamphetamine dependent individuals [63], and OSU [71], whereas multi-substance abusers showed greater insula activation to higher number of risky choices [19]. Together, these patterns of neural attenuation in OSU in brain regions required for successful goal-directed decision making and generation of an interoceptive awareness to generate internal alarm signals to avoid risk may in the end promote continued risk-taking like drug use.

Secondary analyses verified that THC, which was substantially consumed by some of our participants, did not directly influence these activation patterns. While THC is known to promote cognitive and neural impairments [72–74], co-use of THC was not an exclusion criterion, as research shows that more than half of stimulant using students consume THC [4]. The onset of THC use in our sample typically preceded stimulant initiation. THC had additive neural effects, in that OSU with heavy THC use were characterized by a lacking differentiation of risky and safe options in related brain areas critical for decision making (e.g. right anterior insula and DLPFC), supporting studies revealing dose-dependent THC effects on decision making and brain activation [18].

Importantly, higher lifetime stimulant use was associated with diminished risk-taking activation in dACC and posterior insula after controlling for THC co-use. Our dACC findings demonstrate that OSU with relatively more uses show more pronounced neural decision making alterations in areas associated with cognitive control functions like response selection, proactive performance monitoring and conflict monitoring [30], findings consistent with research in chronic users [75–77]. The posterior insula has been shown to play a crucial role in the generation of interoceptive awareness [36]. The present finding of reduced activation in those OSU with higher lifetime uses may thus reflect diminished bodily representations of risk. The perception of (external and) internal alarm signals is crucial for the avoidance of risky behavior. While we cannot ultimately differentiate whether OSU with initially more pronounced brain functional alterations consumed more stimulants in a self-medication approach or whether repeated exposure to neurotoxic substances resulted in changes in neural activation patterns, dose-dependency and self-medication hypotheses find support in previous research showing that more frequent cocaine use leads to more pronounced dACC hypoactivations [78] whereas acute administration of cocaine fosters normalization of ACC hypoactivity [79]. To summarize, our dose-related findings suggest that both an attenuation of cognitive control mechanisms and bodily awareness foster prolonged exposure to risk as neither cognitive nor internal alarm signals support inhibition of prepotent responses.

Our results focusing on performance following losses revealed that OSU who took lower risks after monetary losses were characterized by a successful recruitment of brain structures CS employ to monitor conflict (dACC) and link outcomes with choices (dorsal striatum). On the contrary, OSU who repeatedly engaged in risk by selecting risky options showed a diminished activation of the sgACC, which is crucial for motivational aspects of decision making. OSU also presented alterations of dorsal striatum activation. With the dorsal striatum being engaged in mechanisms avoiding choices associated with losses, the findings suggest an attenuated emotional representation of risk, which may make it difficult for stimulant users to avoid risky choices. They may expose themselves to continued risk (e.g. in terms of continued substance use), which in the end might lead to a higher likelihood to transition to dependence. Cognitive-behavioral, pharmacological and/or neurofunctional trainings aimed at enhancing activation in those target areas might enable individuals to re-gain control over risk taking.

In summary, findings demonstrate that individuals at very early stages of stimulant use, similar to stimulant dependent individuals, show attenuated neural processing of risk and particularly less pronounced neural differentiation of risky and safe options. Given minimal exposure to stimulants in our sample, these deficiencies may have preceded stimulant initiation and might serve as vulnerability markers to allow for early intervention. While not directly linked, neural deficiencies were potentially promoted by THC use as particularly excessive THC users showed attenuated neural differentiation of risky and safe options in related but distinct networks. Through this mechanism, early THC use may have lowered the threshold for stimulant initiation. Stimulant use was associated with aberrant activation in brain areas crucial for cognitive and motivational aspects of goal-directed decision making. In conjunction with diminished bodily representations of risk weakening internal warning signals, these characteristics might foster continued risk-taking and thus increase likelihood for prolonged consumption and transition to dependence. Critical next steps will be the concrete delineation of risk factors for the stimulant-using individual and longitudinal studies preferably starting with individuals prior to any substance use. Such studies might confirm the hypothesized scenario of neural activation patterns encouraging continued substance use.

This study has some limitations. First, our study design was cross-sectional and not completely prospective; we included stimulant using individuals with very limited exposure to stimulants lacking clinically significant stimulant-related problems. This design makes it difficult to differentiate between pre-existing characteristics and effects of repeated exposure to drugs. Nevertheless, the mean number of stimulant exposure was minimal, making neurotoxic effects of stimulants less likely while supporting the hypothesis of a neural vulnerability predisposing to stimulant initiation. Research in stimulant naïve subjects at high risk for stimulant use (e.g. young first degree relatives of stimulant dependent individuals) may separate a genetic vulnerability for stimulant related problems from factors associated with occasional use. Second, co-use of THC did not serve as an exclusion criterion to allow for a representative sample of stimulant using young individuals [4]. While the current design did not include a subgroup of non-stimulant using THC users, we approached a potential THC effect by split group analyses and revealed that THC did not directly influence effects. THC had additive neural effects attenuating neural differentiation of risky and safe responses. Longitudinal studies including individuals prior to any substance use and the comparison with pure THC users are warranted to tease apart effects of THC and stimulants. We specifically excluded stimulant using and comparison subjects with a lifetime history (diagnosis or treatment) of ADHD and conduct disorder, both of which known to contribute to the propensity of substance use [80]. These strict exclusion criteria may also explain why we could not replicate previous findings of Leland and Paulus [23] administering the very same task to a smaller sample of OSU. Taken together, we feel confident that our results of attenuated neural representation of risk-related decision making in OSU delineate precursors of stimulant use problems. Future analyses will focus on the concrete predictive value for the stimulant-using individual. Third, the task was set up in a way that there was no inherent advantage of selecting safe or risky options to lead to similar monetary wins across subjects. While participants were instructed that holding out for 40 or 80 were “risky options”, this implementation did not encourage contingency learning, as no underlying optimal strategy was reinforced. Lastly, it needs to be discussed whether predetermined temporal aspects of our task may have influenced results. In this regard, it is important to point out that potential differences in individual response times are unlikely to have affected our results. The time window during which subjects needed to collect a value displayed on the screen was set to 1s, so that potentially slow responding subjects were able to collect a given amount. On the other hand, this window of opportunity (see [23] for a more detailed discussion) added a certain time pressure to our task, so that waiting was disadvantageous. One might also argue that our behavioral options not only differed on risk domain but also on waiting domain, as subjects always had to wait longer to gain higher rewards, which increased the chances of higher losses. Hence, results could technically also be driven by differences in subjects’ willingness to wait, particularly given that OSU and CS differed on some self-reported measures of impulsiveness. Our results (see S1 Table) however verify, that group differences of brain activation were not explained by differences in self-reported impulsivity. In addition, our task was set up in a way that longer waiting would have resulted in monetary losses. Groups did not differ on the number of missed trials so that we are confident, that our results are not related to a differential willingness to wait.