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Download METHODS Subjects Thirty-two healthy male volunteers were
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METHODS Subjects Thirty-two healthy male volunteers were recruited for this study. One tested positive on the opiate urine screening, while another participant only completed one session. Therefore, the final number of participants was 30 (mean age = 26.7, SD = 4.7 years). To account for data loss of one task, an additional group of seven healthy males were recruited, yielding a total N of 23 for the ‘liking’ task (mean age = 25.5, SD = 4.8 years). During a pre-testing phone screening interview, none of the participants reported a history of depression or other major psychiatric illness, none were on medication, and none had multiple complex allergies. AUDIT (Alcohol Use Disorders Identification Test) and DUDIT (Drug Use Disorders Identification Test) were used to assess drug and alcohol consumption among participants1, 2. Volunteers reported consuming an average of 5.5 alcoholic drinks per week. Of the 37 participants included, 27 reported previous use of cannabinoids, 12 during the last year. Previous use of other drugs was reported as follows: amphetamines (seven participants), stimulants (cocaine, crack; nine participants), hallucinogens (ecstasy, LSD; nine participants) and opiates (one participant, three others had used prescribed morphine). None of the participants reported prior drug dependence or addiction, and none had taken morphine in any form for at least two years prior to testing3. All participants had normal or corrected-to-normal vision. Genotyping using predesigned TaqMan single nucleotide polymorphism (SNP) genotyping assays for the A118G SNP of the mu opioid receptor gene (OPRM1) as previously described4 revealed that there were 27 AA carriers and ten AG carriers in the sample. Stimuli and Apparatus For the purposes of this study, we developed a new database of face stimuli (The Oslo Face Database), consisting of color photographs of 187 young individuals (103 females). Three full-frontal view photographs were taken for each individual: one picture with direct gaze, and two pictures with averted gaze (one looking ~50 degrees to the left and one looking ~50 degrees to the right). For each set of photographs, the models assumed a neutral, emotionless facial expression. Subsequently, each image was edited with Adobe Photoshop such that only models’ heads remained visible. In a separate experiment, 41 participants (21 females, mean age = 24.7; SD = 9.2) rated attractiveness of all images from the database on a visual analog scale ranging from very unattractive to very attractive. Three attractiveness categories were calculated separately for each face gender based on the ratings from male participants only: The less attractive (female faces mean = 3.0±0.4, male faces mean = 3.0±0.3), attractive (female faces mean = 4.9±0.2, male faces mean = 4.2±0.2), and the most attractive category (female faces mean = 5.8±0.5, male faces mean = 4.9±0.3). Due to the lack of high ratings for the male faces, we matched female faces from the attractive category to male faces from the most attractive category. Photographs of 20 females and 20 males were selected from each of the three attractiveness categories. A total of 240 images were used, depicting 60 females and 60 males with both direct and averted (half to the left and half to the right) gaze. Forty unique images depicting 10 females and 10 males (3 most attractive, 4 attractive and 3 less attractive of each sex) with both direct and averted gaze were presented in each task, and no images were repeated across tasks or sessions. The direction of the averted gaze was counterbalanced. The order of presentation was pseudorandomized and counterbalanced. 1 Each image (19.5 × 19.5 cm) was presented on a computer screen located about 70 cm in front of the participant, with a resolution of 1680 x 1050 pixels. Models’ heads in the images subtended about 9.8 x 13 degrees of visual angle. Luminance-matched gray baseline images with a fixation cross were created for each of the facial stimuli. Procedure Participants were tested on three different days with a minimum inter-session interval of seven days, and asked to refrain from eating an hour before test onset. The test interval (60-150 min after drug intake) was chosen to coincide with the maximum plasma concentration of per-oral morphine5 and naltrexone6. Each session lasted approximately three hours and the participants were reimbursed 400-500 NOK (about USD 80) per session, depending on their performance in an independent monetary reward task performed as part of the test battery. The experimental procedures were approved by the Regional Ethics Committee (2011/1337/REK sør-øst D). At the end of the last session, participants were debriefed and asked to guess the identity of the drug received in each session. On average, participants identified the drug received correctly 34% of the time, indicating successful blinding. Drug administration. Morphine is a selective μ-opioid receptor agonist and the most widely chosen analgesic for moderate to severe pain7. To minimize subjective drug effects we chose 10 mg per oral morphine (Morfin®, Nycomed Pharma, Asker, Norway). Naltrexone is a non-selective opioid antagonist with a high affinity to μ- and κ-opioid receptors. It is used in the treatment of drug and alcohol addiction to block the effects of exogenous opioids (e.g. heroine) or to reduce drug/alcohol craving. We used 50 mg per oral naltrexone (Adepend, Orpha-Devel, Purkersdorf, Austria), a standard dosage that has been used with only minor side-effects in several previous studies 8, 9. Placebo pills were cherry-flavored breath mints visually matched to morphine and naltrexone pills. A small amount of the flavored placebo pills were added to the drug dosages to avoid any recognition of medication taste. Time Line. After giving written consent, participants were asked to submit a urine sample for opiate screening (MOP Opiate300 Test Strip; SureScreen Diagnostics Ltd, Derby, UK). After completing state-relevant questionnaires (including measures of mood: happiness, anxiety, irritability, feeling good), and if the drug toxicology was negative, participants received one of the three drugs. In each of the three testing sessions, the ‘liking’ and ‘wanting’ tasks were run as parts of a larger study. Task orders were pseudo-randomized and counterbalanced between participants. Throughout each test session, participants completed the mood checklist four times: (1) before drug administration (session baseline), (2) 60 min after ingestion, before testing began, (3) ~40 min into testing, and (4) after completion of all tasks. To ensure the study results were not due to reduced motor functions in either of the drug conditions, the participants completed the BRAIN test Bradykinesia Akinesia Incoordination task, 10 at 40 minutes into the testing session. ‘Wanting’ Task. Participants were instructed to manipulate the duration of each facial image presentation according to their own wish, by repeatedly pressing one button to make the current trial last longer (‘keep’ press), or another button to make it end sooner (‘change’ press); the more button presses, the more the duration could be manipulated. A visual meter with a moving stripe 2 indicated how much time was left of each trial, and also worked as a visual indicator of how much the participants were manipulating the trial duration. The total duration of the experiment was fixed to 3.65 minutes. Trials were separated by a 2-second break, and without the participant's manipulation the experiment was set to consist of 31 trials of 5 seconds each. On average, participants completed 30.2 trials per each session of the task. Viewing time and the number of ‘keep’ and ‘change’ button presses for each image were recorded. MatLab software R2012a (Mathworks, Natic, USA) was used to present the stimuli and collect participants' responses. ‘Liking’ Task. After presentation of a fixation point for 2 seconds, a facial image was presented on the computer screen for 5 seconds. This was followed by presentation of a visual analog scale for a maximum of 10 seconds. Participants were requested to rate how attractive each face was on a scale ranging from very unattractive to very attractive. After the response (or when 10 seconds elapsed), another fixation image was presented, followed by another facial image, and then by the visual analog scale, etc. E-Prime 2.0® software (Psychology Software Tools Inc., Pittsburg, PA, USA) was used to present the stimuli and collect subjects’ responses in the ‘liking’ task. Data from 14 participants were excluded from analysis due to a software problem (recording responses in EPrime). Subsequently, an additional group of seven healthy males were pre-screened and tested using exactly the same experimental paradigm. Therefore, the final sample size for the ‘liking’ task was 23. Data analysis Viewing times and 2.5-SD-trimmed ‘keep’ or ‘change’ button-press data from the ‘wanting’ task, and attractiveness ratings from the ‘liking’ task were analyzed with multiple regressions using a linear multilevel/mixed models analysis, based on a maximum likelihood approach11 in SPSS. Drug (morphine, naltrexone, or placebo), Gaze Direction (direct or averted gaze), and Facial Attractiveness Level (most attractive, attractive, and less attractive) were included as main factors. Session Number, Stimulus Order, OPRM1 group (AA or GA carriers), and Image Set as control variables. Planned contrasts were run to elucidate the specific questions central to our hypotheses. Reported effect sizes (Cohen’s d) were calculated based on the t statistic extracted from the contrast specified within the mixed models analysis and using the following formula: d = ( t*2 ) / ( sqrt(df)), where df=N-1. SUPPLEMENTARY RESULTS Main effects of drug on viewing time in the ‘wanting’ task. Both morphine and naltrexone treatment decreased the average viewing time of female faces with around 200 ms compared to placebo (main effect of Drug, F(2,1208)=3.6, p=0.026; average viewing time: morphine M = 4.58±0.08, placebo M = 4.79±0.08, and naltrexone M = 4.55±0.07). As reported in the main text, analysis of button press data revealed that these opioid-related decreases were driven by different ‘wanting’ behavior, such that the expected pattern of ‘wanting’ increases with morphine and decreases with naltrexone emerged when analysis was constricted to keep button presses for the most attractive female faces. Effects of gaze direction of faces on ‘liking’ and ‘wanting’. Gaze affected viewing preferences in the ‘wanting’ task, specifically increasing motivation to view the most attractive faces with direct 3 gaze (Attractiveness*Gaze Direction interaction (F (2, 1208) = 5.27, p = 0.005)). There were no significant interactions between Gaze Direction and Drug (all Fs < 0.79). As expected, there was a trend for the participants to rate female faces with direct gaze as more attractive than faces with averted gaze (main effect of Gaze Direction, F (1, 1314) = 3.27, p = 0.071). Effects of controlling for variability in the A118G SNP of OPRM1. The pattern of finding and statistics/ effect sizes remained the same for both the liking and wanting analyses with and without the genetic information in the model. Effects of drug manipulations on mood. ANOVA tests were employed to evaluate the effect of drugs for all mood types with Drug (morphine, placebo, naltrexone), Mood Type (happy, anxious, irritated, feeling good), and Time of Mood Check (before drug administration, 60 min after ingestion, ~40 min into testing, after completion of all tasks). Neither morphine, nor naltrexone treatment significantly affected mood (Drug main effects/interactions): Fs≤1.29, ps≥0.22). Motor coordination test. In this this test, participants were asked to use their dominant index finger to alternate between two keybord keys, 15 cm apart, as quicky and accurately as possible. The dysmetria score (DS) is a weighted score of number of incorrect presses corrected for speed. The repeated-measures ANOVA of the Dysmetria x Drug showed no significant effect of drug: F (2, 58) = 0.91, p = 0.38, p2 =0.03). This result indicates that the differences in performance on the test across drug conditions were unlikely to result from significant decreases in motor or eye-hand coordination. Plasma levels of drugs and their metabolites. Participants provided a blood sample at the end of each experiment session. Analyses were performed at The Norwegian Institute of Public Health, Division of Forensic Medicine and Drug Abuse Research, using a high-performance liquid chromatography–tandem mass spectrometry method12 to identify plasma levels of morphine and its two major metabolites: morphine-3-glucuronide (M3G) and morphine-6-glucuronide (M6G); and naltrexone and its major metabolite, 6-β-naltrexol (6βN). The results are presented in Supplementary Table 1. Supplementary Table 1. Plasma levels of morphine, naltrexone and major metabolites ~150 min after oral drug ingestion Mean (ng/ML) Morphine M3G M6G Naltrexone 6βN SD 0.155 0.032 0.009 0.157 0.016 0.041 0.010 0.003 0.038 0.009 SUPPLEMENTARY DISCUSSION 4 The current study provides evidence for the opioid system involvement in mediating motivational responses for the social stimuli. In relation to stimulus specificity, it raises a question of whether a similar pattern of opioid system modulation would be obtained for other, non-social, rewards. Since facial attractiveness is processed by the same opioid-driven limbic reward system as other types of rewards13,14,15, we believe that the current findings could generalize to non-human rewarding stimuli as well. The data from rodent studies cited in the manuscript offer support for this assumption. Specifically, when using food stimuli, MOR agonism increases and antagonism decreases preference specifically for the most palatable option16. 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