Individual differences in cognitive performance can be partially explained by genetic variations (Barnes et al. 2011 ). The AATn polymorphism of the CNR1 gene, which codes for CB1, have been related to cognitive function: procedural learning (Ruiz‐Contreras et al. 2011 ), attention (Stadelmann et al. 2011 ) and working memory (Ruiz‐Contreras et al. 2013 ). Although the CNR1 gene has other polymorphisms, rs1049353 is the only one on coding region, but it is a synonymous SNP; others belongs to an untranslated region and their functionality are unknown. Also, many of these SNPs have a high bias allele frequency in many populations. We selected the rs2180619 which is at −3068 base pairs from exon 1 (Zhang et al. 2004 ), probably as a part of the promoter region of the CNR1 gene. It is possible CB1 expression might change as a function of rs2180619 genotype. Although the physiological role of this SNP has not been reported; ‘ in silico ’ data suggests that GG genotype is related to lower levels of CB1 receptor expression (Lazary et al. 2009 ). Nonetheless, psychiatric phenotypes have been associated to this SNP: GG polymorphism for the rs2180619 is more frequent in subjects with substance‐use disorders (Zhang et al. 2004 ) and, by interacting with the SS genotype of the promoter region of the serotonin transporter, the GG subjects were fourfold at risk for high anxiety (Lazary et al. 2009 ). Thus, G allele could be a risk factor for ‘psychopathological conditions’. However, this allele is also present in healthy subjects; and GG genotype might be related to a differential performance in cognitive function compared to the AA genotype. We hypothesize that the GG genotype might be related to lower cognitive performance in a task which evaluates working memory load and attentional control, in comparison to the AA genotype in healthy subjects.

Attentional control and working memory are both goal‐directed abilities that influence our cognitive performance (Barnes et al. 2011 ). When attention is attracted by irrelevant information, working memory accuracy decreases (Gazzaley 2011 ); on the other hand, working memory load affects the subsequent attentional processes required to perform rapid serial visual presentation tasks (Gil‐Gómez de Liaño et al. 2013 ). Goal‐directed attention facilitates subsequent processing of relevant information, reducing reaction times and augmenting accuracy (Lepsien et al. 2011 ; Kuo et al. 2012 ), indicating reduced processing of irrelevant information. The ability to pay attention to relevant visual information and simultaneously ignore what is irrelevant depends on complex neuronal networks which lead to an enhancement and suppression of fronto‐parietal and visual association cortical activity (Chadick & Gazzaley 2011 ). The enhancement and suppression responses change as a function of age (Gazzaley et al. 2005 b) or working memory load (Rissman et al. 2009 ). However, individual differences have been also reported in healthy young participants (Zanto & Gazzaley 2009 ).

For the attentional control and working memory load task, dependent measures were reaction times and d ' that was subjected to a mixed anova; the genotype (AA, AG and GG) was the between‐group factor; and each experimental condition (Remember faces, Remember scenes, Remember both faces and scenes, and Passive view) was the within‐subjects factor. The Unequal N Tukey–Kramer Honestly Significant Difference post hoc test was used. Analyses considered control of the false discovery rate (FDR) for multiple comparisons at a significance threshold of P ≤ 0.03 (Benjamini et al. 2001 ).

Because the Mexican population resulted from the admixture of mainly European (Spaniard) and Native American populations, we assessed the ancestry on a subset of individuals to evaluate if the results could be confounded by population stratification. A genotyping of a panel of 10 ancestry informative markers (AIMs: rs963170, rs1861498, rs3340, rs4130405, rs1980888, rs1487214, rs726391, rs2078588, rs724729 and rs1877751) was performed using Taq‐Man assays (ABI Prism 7900HT Sequence Detection System; Applied Biosystems) in a random subsample of AA ( n = 26) and GG ( n = 26) subjects. Ten duplicate samples were used for each ancestry informative marker as a genotyping control and no discordant genotypes were observed.

Saliva was collected from each participant through the Oragene DNA Self‐Collection Kit (DNA Genotek Inc., Kanata, Ontario, Canada). Genomic deoxyribonucleic acid was isolated employing the Prep‐IT‐L2P DNA Purification Protocol (DNA Genotek Inc.). DNA integrity was verified by electrophoresis in 0.8% agarose gels. Their concentrations and purity were quantified by sample retention system NanoDrop‐1000 Spectrophotometer (Thermo Fisher Scientific Inc., Wilmington, DE, USA). Genotypes for the rs2180619 were determined by Allelic discrimination with allele specific Taqman® probes (Genotyping Assay ID: C__15841551_10, Applied Biosystems, Foster City, CA, USA). Samples including NTCs were analyzed by duplicate and the results were replicated at 100% with quality value over 98%. Genotypes were confirmed comparing the allelic discrimination plot with its amplification plot.

Subjects performed a working memory task described earlier (Gazzaley et al. 2005 a,b) which can be used to test the effect of distractors (irrelevant information for a goal‐directed behavior) and the effect of working memory load on performance. There were four experimental conditions, in which four stimuli, two scenes and two faces, were randomly displayed as cue stimuli (each one presented for 800 milliseconds). A 9000 milliseconds delay period, where a plus sign was displayed as a fixation point (vertical and horizontal visual angle: 0.74°), was followed by an image of a scene, a face or an arrow (depending on the experimental condition) as the probe stimulus. Experimental conditions varied in the instructions given to the subjects: (1) Remember faces/ignore scenes; (2) Remember scenes/ignore faces; (3) Remember faces and scenes; (4) Passive view. In the first two conditions, subjects were instructed to remember one type of stimulus and ignore the other one (irrelevant information); therefore, attentional control was evaluated here. In the third condition, performance under a high load of working memory was tested, because subject had to keep both types of stimuli, faces and scenes, in their memory. In these three conditions, subjects indicated if the probe stimulus was one of the cue stimuli presented or not. For the Passive View condition, subjects answer about the direction of the arrow, so no working memory is involved in this condition (Fig. S1, Supporting Information). Each trial began with a plus sign, which was displayed for 3000 mseg. Each condition was presented in separate blocks of 30 trials, the probe stimulus was one of the cue stimuli in 50% of the trials; in the Passive View condition, the arrow pointed left in 50% of the trials.

Five hundred and twenty‐five gray scale pictures were presented, 263 were scenes and 262 were faces with neutral expressions. Our group created this battery bank of pictures. All images were standardized to measure 225 pixels high and 173 pixels wide (vertical visual angle = 3.4°, horizontal visual angle = 2.8°). Half of the scene images were outdoor scenes and the other half, indoor scenes. Half of the face images were of female and the other half, male. All images were novel and never were repeated throughout the tasks. Also, two images of arrows were used, one pointing to left and the other to the right (vertical visual angle = 0.57°, horizontal visual angle = 1.7°).

One hundred and sixty‐four healthy young Mexican‐Mestizo subjects participated in this study (100 women and 64, men; mean age: 22.86 years, SD = 2.72, years of schooling: 15.88, SD = 1.78). Only subjects born in Mexico whose parents and grandparents identified themselves as Mexican‐Mestizo were included. All of them were right‐handed [according to the Edinburgh Inventory, (Oldfield 1971 )], and with normal‐to‐corrected vision. According to a structured interview, subjects reported be free of any neurological or psychiatric illnesses at the time of the experiment and before in their lifetime, as well as their first‐degree relatives. Participants did not have history of drug addiction; also, they had not consumed any illicit drug for recreational purposes in the year before of the experiment. At the time of the experimental session, subjects did not consume any medication. We rejected subjects with moderate or severe symptoms of depression or anxiety, detected by the Depression and Anxiety Beck inventories. All subjects responded the Wechsler Adult Intelligence Scale‐Vocabulary subscale. Experiments were performed at 10, 12, 14 or 16 h, in order to avoid diurnal effects (Monk et al. 1997 ). Our research was endorsed by UNAM's School of Medicine's Research and Ethics Committee. Subjects signed an informed consent form, upon receiving a complete description of the research procedures. This sample was different as those we reported in our previous researches (Ruiz‐Contreras et al. 2011 ; Ruiz‐Contreras et al. 2013 ).

Mean and SEM of the reaction time during the measurement of attentional control. Only GG subjects significantly increased their reaction time when they had to ignore faces (Remember Scenes), and when they had to pay attention to them (Remember faces), suggesting a diminished ability to ignore irrelevant information. AA n = 40, AG n = 92 or GG n = 32. * P = 0.03.

In order to evaluate attentional control, a comparison of reaction times was performed between Remember faces and Remember scenes conditions. In both conditions subjects had to ignore an irrelevant stimulus (scenes and faces, respectively) in order to solve the task. We tested the hypothesis that GG participants were less able to ignore distractor stimuli than the AA participants. A mixed anova with genotype (AA, AG, GG) per experimental condition (Remember faces vs. Remember scenes) revealed a significant interaction ( F 2,161 = 3.58, P = 0.0300, η 2 = 0.04, power = 0.66). Post hoc analysis showed that reaction times were not different among genotypes for responding in each experimental condition. Nevertheless, reaction times were slower for the Remember Scenes (ignoring faces) condition contrasted to the Remember faces condition in GG subjects (Fig. 3 ).

Mean and SEM of the accuracy in the attentional control and working memory task, depending on the experimental condition. Significant differences were observed between GG and AA genotypes only in the high load working memory condition (Remember Both), where the performance was worse in GG subjects. AA n = 40, AG n = 92 or GG n = 32. * P = 0.017.

A performance difference among genotypes was found, evidenced by d ′ measures ( F 2,161 = 3.99, P = 0.0203, η 2 = 0.05, power = 0.71). GG participants had lower performance in the task as a whole (all conditions) compared to AA participants (Fig. 1 ). Also, a significant interaction was observed between genotypes and experimental condition ( F 6,483 = 2.61, P = 0.0170, η 2 = 0.03, power = 0.85). Post hoc analysis revealed that a significant reduction in accuracy was observed for the GG participants compared to the AA participants only in the ‘Remember both’ condition (Fig. 2 ); no differences were found between AG and AA or GG participants.

The demographic characteristics of the sample as a function of the rs2180619 are shown in Table 1 . No differences were found in any of these variables ( P > 0.05, see Table 1 ). Neither one of the allelic frequencies differed in our sample (A: 0.52, G: 0.48, χ 2 1 = 0.25, P = 0.62) nor did genotypic frequencies (AA: 0.24, AG: 0.56, GG: 0.20, χ 2 2 = 0.23, P = 0.89). Both the genotypes for the rs2180619 and the AIMs were within the Hardy–Weinberg equilibrium.

Discussion

Our results show that individual differences in attentional control and working memory performance varied as a function of the genotypes of the rs2180619 of the CNR1 gene. We obtained three main findings. First, GG subjects had less accuracy in general performance in the working memory task (Fig. 1). Second, having two copies of the G allele, was associated with less efficiency when the subject had to maintain a high load of elements in working memory (i.e. four stimuli vs. two faces or two scenes), but not when load was low (i.e. two faces or two scenes). Third, reaction times between three genotypes did not differ among experimental conditions. However, reaction times differed in GG subjects only when they had to inhibit distractors, in order to pay attention to, and remember, relevant stimuli (attentional control): higher reaction times when subject had to ignore faces than when they had to remember them. This result might indicate that, in contrast to A carriers, GG subjects are more vulnerable to distractor information (i.e. faces in Remember Scenes condition), although it does not necessarily compromise their accuracy. It has been reported that faces, when presented as distractors, elicit higher amplitudes for N170 and P2a components of the event‐related potentials, as well as earlier latencies for faces than scenes when they are presented as distractors, suggesting that when faces are acting as distractors, they capture the subjects' attention (Carretié et al. 2012). Our behavioral results showed that GG subjects are vulnerable to distraction when faces are present, but not the other genotypes.

On the other hand, working memory performance was also differentially related to rs2180619 genotypes. Lower accuracy was observed in GG subjects compared to AA subjects. Particularly, a high load of information only affects GG subjects' accuracy. A working memory network has been proposed, involving the participation of the left dorsolateral prefrontal cortex, parietal cortex, temporal cortex and cerebellum, which augment their activity as the load of information held in working memory increases (Bossong et al. 2012). The activity of this working memory network is reduced when an agonist of CB1R is administered, revealing the functional role of the eCB in working memory in humans.

Both attentional control and working memory performance in this study are less proficient in GG subjects as compared to AA subjects. Importantly, as is shown in Table 1, AA, AG and GG subjects did not differ in demographic and other characteristics, such as age, years of schooling or depression or anxiety levels measured by Beck inventories. Thus, the differences among genotypes are not explained by any of these factors.

The physiological effect of the rs2180619 of the CNR1 gene is unknown, however, it has been previously suggested, by ‘in silico’ data that the GG genotype is related to lower levels of CB1 receptor expression (Lazary et al. 2009), risk behaviors such as addiction (Zhang et al. 2004), and anxiety (Lazary et al. 2009). GG participants do not present addiction or high anxiety levels, but were susceptible to distraction. Nonetheless, experimental work is needed to know the physiological effect of GG vs. AA polymorphisms. One way to assess its physiological effect could be measuring the CB1 expression in AA vs. GG subject by means of positron emission tomography; or doing this evaluation in post‐mortem brains, and segregated by genotype of rs2180619. Our hypothesis is that GG subjects express lower levels of CB1, in contrast to AA subjects. This hypothesis agrees with previous evidence of an impairment of working memory in knock‐out mice for CB1 (Varvel & Lichtman 2002). Also, it is known that attention (D'Souza et al. 2012; Solowij et al. 2002) and working memory (Bossong et al. 2012) is impaired in marijuana users, in which a reduction in the expression of the CB1R was reported (Hirvonen et al. 2012). In attention deficit/hyperactivity disorder (ADHD) patients, hypoactivity of the fatty acid amide hydrolase in plasma levels is observed in comparison to healthy volunteers (Centonze et al. 2009), suggesting a higher amount of the endocannabinoid anandamide and a reduction in CB1R (however, no evidence of brain expression of CB1R exists at this time on ADHD subjects). Also, in an ADHD mice model with point‐mutation of the dopamine transporter, there is a loss of CB1R response to a cannabinoid agonist to change the frequency of spontaneous inhibitory postsynaptic currents, which controls GABAergic transmission in the striatum (Castelli et al. 2011). Therefore, because the reduction in CB1R expression or function is associated to a reduction in working memory and attention performance, we propose the hypothesis that in GG subjects (of the rs2180619 of the CNR1) express lower levels of CB1R.

Some limitations of our study must be addressed. First, the level of expression of the CB1R in the brain is unknown as a function of the rs2180619 genotypes, though it is crucial to describing the functional relation of this polymorphism of the CNR1 gene. Second, it is possible that rs2180619 would be interacting with other SNPs of the CNR1 or with other genes. Haplotype studies are necessary to associate cognitive performance with CNR1 gene.

In conclusion, our results show that individual differences in attentional control and working memory performance are related to genotypes of the rs2180619 of the CNR1 gene: GG subjects performed at lower levels than AA subjects. These results further support the participation of the eCB, particularly, of CB1R in the attentional control and working memory networks regulating cognitive performance in human subjects.