This is the first study that analyzes the effects of chronic cannabis consumption on a visuomotor rotation task to assess the processes involved in motor adaptation. CCUs displayed impaired adaptation, manifested as lower aiming errors in the VMR task than controls.

Our results are consistent with our hypothesis that chronic cannabis use has an impact on cerebellar-dependent functions and, more specifically, on motor adaptation. The visuomotor adaptation paradigm has been used as a marker of cerebellar damage in ataxic patients, who show impaired implicit learning, putatively, due to disrupted forward internal models [32]. More specifically, cerebellar ataxic patients accumulate fewer aiming errors during the rotation and strategy (RS) phase, indicating a decreased motor adaptation [32]. It is interesting to note that the effect size of the original study with ataxic patients is very sizeable (Cohen’s d = −2.627), while the effect size on CCUs is moderate (Cohen’s d= −0.8). This is not surprising, as the clinical manifestation of cerebellar dysfunction of ataxia is severe, while cannabis-induced cerebellar alterations do not lead to a clinical phenotype (all the participants assessed scored zero on the SARA scale). However, we suggest that our results are clinically meaningful for two reasons: First of all, in several brain disorders, early alterations in the patient’s brain are present even decades before the first clinical symptoms appear [39,40]. Our paper shows an altered performance of CCUs in a visuomotor adaptation task, indicating subtle cerebellar alterations in the users´ brains. These results were obtained after excluding experimental participants under the acute effects of cannabis (on the suggestion of an anonymous reviewer). Interestingly, even though this reduced the sample size (from n = 33 to n = 28), statistical significance, and therefore the underlying effect size, increased (from d = −0.7 to −0.8). Our finding suggests that CCUs adapt less when they are not under the acute effects of cannabis. This deficit might be explained by the hypothesis of CB1 receptor down-regulation due to cannabis use [21]. More specifically, it has been shown that repeated cannabis exposure causes endocytosis of the endocannabinoid receptors, resulting in reduced activity of those receptors in the absence of their exogenous agonist. If this hypothesis explains our results, it would be plausible that acute cannabis use in CCUs may indeed hide an underlying impairment in cerebellar-dependent motor adaptation. Although our results show very subtle alterations compared to ataxic patients, these might be the first signs of a future clinically significant impairment that will only manifest with continuous heavy use [41]. Future longitudinal studies will clarify whether these early cerebellar alterations prelude long-term clinical symptoms. Secondly, it is noteworthy that even though, CCUs show no measurable motor deficits clinically, they share a certain degree of alterations in motor adaptation with cerebellar ataxic patients. Future research will show the reliability of the task as a potential tool for assessing brain alterations, as well as whether the latter are present exclusively in cannabis users or they are part of addiction-induced brain alterations.

Globally, these results indicate that VMR tasks might be a simple, non-invasive and novel way to start exploring a basic cerebellar function in CCUs. The cerebellum is crucial for motor adaptation, among other functions. As implicit learning is an essentialskill for everyday functioning, our findings are the first step towards understanding more complex cerebellar deficits. Our results are in line with the increasingly recognized role of the cerebellum in higher cognitive functions and emotional processes, and a recent review that points out a cerebellar involvement in cannabis addiction [42]. Future research should examine whether there are changes in the performance of users after cessation of use, as well as if this task can capture cerebellar alterations in individuals dependent on other substances, such as tobacco, alcohol, amphetamines, etc.

This study has limitations that have to be taken into consideration when interpreting the results. First of all, the small sample size might have compromised the power of the study, so further studies should increase the sample size and also explicitly indicate in the protocol that participants are required to refrain from cannabis use for at least 6 hours prior to the study. Regardless of the small sample size, the moderate effect size might be due to the fact that CCUs do not show any clinically significant motor deficits (SARA score equals to 0), unlike ataxic patients. Secondly, significant differences were found between groups in terms of educational level. While we propose that educational level should not be an important confounder, due to the implicit nature of the task, tobacco and alcohol use might have had an effect on performance. Indeed, even though an ordinary least-squares analysis showed inexistent correlation with performance in the present study, one should take into account for future studies that reduced adaptationmight arise due to the synergistic effects of all substances, and not exclusively of cannabis. Thirdly, even if the small differences that we found in motor adaptation are representative of cerebellar alterations in CCUs, no causation can be inferred, as the brain differences might have been preceded cannabis use. Future longitudinal studies should clarify this matter. Finally, in previous studies where participants only received end-point position feedback, the systematic aiming error accumulated slowly during the 80 trials of the RS phase. However, we opted for providing participants with continuous feedback, evaluating the angular orientation using the initial part of the trajectory. The increased level of feedback has introduced discrepancies with the literature. First, as intended, it may have accelerated (implicit) adaptation, consistently with Taylor et al. [38], where a different VMR task was used. Indeed, the drift rate in our control group (0.2°/trial) is twice as fast as in Taylor et al. [32] (circa 0.1°/trial). Secondly, it has produced a shift in the maximum peak drift, which here reached 27.2° for the control group whereas in previous experiments it remained near 10° [29,32]. This increased peak drift might be due to fast explicit processes [38], as suggested by the high level of adaptation already manifested in the first block of the RS phase. However, we expect to have minimized the influence of the explicit learning in our main result by reporting the drift rate, which was computed taking into account the median performance for each one of the ten blocks of eight trials of the RS phase. In other words, our measure of drift rate is not affected by the high level of adaptation which had already been reached at the first block of the RS phase. Besides, even though we report a tendency in the after-effects that is consistent with our hypothesis of decreased implicit adaptation in CCUs, the difference only reached trend-level significance (p < 0.09). Hence, the replication of these results with a bigger sample size may be needed to confirm that the difference in performance reported here is due to putatively-cerebellar implicit motor learning. Indeed, a possibility to avoid involving explicit processes would be using newer VMR paradigms more precisely targeted at measuring implicit learning [43].