Neural processing of win-contingent audiovisual cues during virtual gambling: An fMRI cross-over study

Neural processing of win-contingent audiovisual cues during virtual gambling: An fMRI cross-over study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Neural processing of win-contingent audiovisual cues during virtual gambling: An fMRI cross-over study Lisa Jil Krause, Ronald Fischer, Falk Kiefer, Tagrid Leménager, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9001151/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Rationale: Over the last 30 years, the global incidence and prevalence of gambling disorder (GD) have risen, with particularly high risk associated with slot machine gambling. Win‑contingent audiovisual stimuli are considered a key mechanism that may promote risky decision-making during gambling. Objectives: This study aimed to investigate whether win‑conting­­ent audiovisual cues modulate risky decision-making and neural responses during a virtual slot-machine task in healthy volunteers. Methods: In a randomized cross-over design, N = 20 right-handed healthy volunteers completed a virtual slot-machine paradigm with and without win-contingent audiovisual cues. We compared risky versus safe choices and rational versus irrational decisions and examined differential fMRI (functional magnetic resonance imaging) activation during decision and feedback phases using flexible factorial models. This study was pre-registered in the German clinical trials database: DRKS00021178 on 03.04.2020. Results: Win‑contingent audiovisual cues did not significantly affect the frequency of high-risk versus low-risk choices or rational versus irrational decisions. In the feedback phase, wins (vs. losses and near wins) elicited robust activation in hippocampal, parietal, frontal and insular regions. Compared with the uncued version, the cued version was associated with reduced activation in temporal, thalamic, parietal and insular cortices during win feedback, particularly for rational decisions. Conclusion: Win‑contingent audiovisual cues modulated neural responses to gambling outcomes in healthy individuals, but did not alter observable choice behavior, suggesting preserved cognitive control despite cue-induced changes in reward- and salience-related networks. FMRI Pathological gambling decision-making win-contingent cues Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Over the last 30 years, the global incidence and prevalence of gambling disorders (GD) has increased. The risk for GD is particularly high, when using gambling and slot machines [19, 22]. Characteristics such as high availability, high event and payout frequency, increasable stakes and winnings create the illusion of control over the game outcome and increase the possibility of excessive gambling and risky decisions. The occurrence of near wins, where one reel is one position away from a jackpot, similarly promotes GD behavior via activation of similar frontostriatal circuits like actual monetary gains do [11, 22, 29]. Another mechanism to increase the addictive potential of slot machines is the delivery of choices and wins with audiovisual cues such as sounds and colorful lights and symbols. These cues have shown to affect the decision-making of healthy individuals towards more risky decisions [4, 26, 31]. In people with GD the cerebral reward system shows an increase in responsiveness (“cue reactivity”) to gambling-related stimuli, especially in the ventral striatum, as an important part of the limbic system [12, 22]. In the frontostriatal regions, such as the striatum and prefrontal cortex, reduced activation during cue exposure, gambling simulations, impulse control and anticipation of winning was found [13, 20]. Reduced connectivity between the two areas is thought to play a role in cue-induced craving [20]. However, few studies used real-world gambling paradigms. Recent reviews (Linnet 2020 and Clark 2019) stressed the relevance of such tasks due to their external validity and their capacity to demonstrate hyperreactivity in the striatum, midbrain, and medial and prefrontal cortex in people with GD. In addition, the review advocated for further research using realistic gambling tasks to investigate outcome anticipation and its role in the learning process in GD [5, 15]. Thus, to further elucidate the processing of win‑contingent audiovisual stimuli, we investigated the neurobiological basis of these cues in a realistic virtual slot-machine paradigm in healthy volunteers. Specifically, we tested whether win‑contingent cues (i) increase risky decision-making and (ii) alter neural responses during decision-making and outcome processing, with a particular focus on regions implicated in GD such as the insula, striatum and prefrontal cortex. Methods Study design This randomized cross-over study compared the effects of a virtual slot machine paradigm with win-contingent cues (henceforth “cued version”) to a parallel version without win-contingent cues (henceforth “uncued version”) on neural brain activation during feedback (win, loss near win) and on decisions during the gambling task (choice of the high- versus low-risk gambling bet). Two test blocks (cued and uncued test block) were conducted per person, each with and without win-contingent audiovisual stimuli, 30 trials of 41 seconds each per block, totaling 23.5 minutes per block with a randomized sequence of the two paradigm versions. The study was a pilot trial that enrolled a total of 20 healthy individuals. The study was approved by the local ethics committee (Heidelberg University), conducted in accordance to the Declaration of Helsinki and pre-registered (German clinical trials database: DRKS00021178). Participants provided written informed consent. All study procedures were conducted at the Central Institute of Mental Health in Mannheim, Germany. Participants A total of N = 20 right-handed healthy volunteers were recruited though public advertisements, on the Central Institute of Mental Health Website and on social media. Participants were required to be between the ages of 18 and 65 with sufficient eyesight to participate either with contact lenses or MRI-compatible glasses. Only participants with a negative COVID-19 test, a breath alcohol of 0.0%, and a negative drug urine test and negative pregnancy test were enrolled. Before enrollment, a medical history was recorded and participants were screened for psychiatric disorders via Structured Clinical Interview for DSM-5 (SCID) [3]. Severe somatic, neurological, and psychiatric illnesses, including current manic or severe depressive episodes and schizoaffective disorders, led to exclusion from the study. Exceptions were nicotine dependence and affective disorders associated with the use of antidepressants if their dose was unchanged for at least 30 days. The use of other psychotropic drugs also led to exclusion from the study. All participants were screened for GD via the ICD-10 and DSM-5 diagnostic criteria and the Gamblers‘ Believe Questionnaire (GBQ) and South Oaks Gambling Screen (SOGS) [1, 10, 27, 32]. One participant was removed from the study, due to indications for multiple psychiatric comorbidities during the screening process. Primary outcome measures Slot machine paradigm As our slot machine paradigm, we used a modified version of the Vancouver Gambling Task (VGT) [25], a virtual slot machine, with the two paradigm versions, one with and one win-contingent audiovisual stimuli (“cued”) and one without (from here on “uncued”), the order of presentation (i.e. first cued or uncued version) of the versions was randomized (see Fig. 1 and Fig. 9 in the supplementary information for a more detailed depiction). Figure 1 Design of the virtual gambling paradigm: uncued and cued version The two different gambling paradigm versions during the win output, on the left the uncued version, on the right the cued version with the strongest stimuli and the highest reward magnitude. (Einsatz: German for stake, Gewinn: reward magnitude, Spielstand: score) This paradigm has been successfully used and validated in prior independent studies [2]. Instead of real money, each participant started with a virtual account of 30 points and was told that they could earn or lose points during the game. The aim was to earn as many points as possible to receive the highest possible voucher as compensation for participation. Each paradigm version consisted of 30 trial runs (10 wins, 10 near wins, 10 losses). The sequence of the wins and losses was predetermined and the same in both paradigms, this pseudo-randomization ensuring parallelism, and with an oversampling of wins in the beginning to facilitate cue-outcome learning. The paradigm consisted of three phases per trial run: decision, anticipation, and feedback phase. Figure 2 Design of the virtual gambling paradigm: phases of the gambling paradigm The 3 phases of each trial run in an uncued trial: decision phase with the stakes, the win probability and the reward magnitude for the high-risk and low-risk game option, anticipation phase with the wheels turning and feedback phase with the display of a win with the new score (Einsatz: German for stake, Gewinn: reward magnitude, Chance: win probability, Spielstand: score, Leider verloren: loss) In the decision phase, the participants were given the task of choosing one of two game options with different risk profiles, one of them being a low-risk option, the other a high-risk option. The risk profiles differed in winning probability, stake, and total win, with the riskier option having higher stakes, higher wins, and lower probabilities of winning. Based on the different expected value (EV) ratios, we classified the choices as rational, when they aligned with risk profile favored by the EV ratio [25]. The EV Ratio was calculated as shown by Sharp et al. (2012) In three trial runs per version, both risk profiles were rational choices, in order to investigate risky decision-making under these circumstances. The anticipation phase consisted of the three wheels of the virtual slot machine turning. For the feedback phase, the wheel stopped turning, displaying the outcome of the trial run and the new score after the potential win was added and the stake subtracted. There were then three scenarios: win (all three reels showing the same symbol), “pure” loss (all three reels showed different symbols), and near win. This is a monetary loss in which the first two reels show the same symbol, but the last reel is one position away from the winning position [11]. For the cued paradigm version the outcome was accompanied by audiovisual stimuli of varying intensity depending on the reward magnitude, as used by [4]. The uncued version did not display any of these additional stimuli, as shown in Fig. 1. To ensure that the different phases were of the same length for all measurements, a maximum duration of 16 s was set for the anticipation phase. If the test subjects decided earlier, a fixation cross was displayed for the remaining time. If no decision was made during this period, the last decision was replicated by the program. Behavioral data In addition to the fMRI data, the participants' decisions regarding the choice of game options were also analyzed in SPSS (Statistical Package for the Social Sciences, SPSS Inc., Chicago, IL, USA; Release 29.0.0). Descriptive statistics were generated for high- and low-risk decisions, as well as rational and irrational decisions. The main effect of the game versions (with versus without win contingent audiovisual stimuli) was analyzed using a general linear model with the game version as a fixed factor, the order of presentation of the game versions as a covariate, as well as their interaction, and the proportion of high-risk decisions, rational decisions and high-risk decisions in trials with an EV ratio of 0 as the dependent variable. Data acquisition fMRI All fMRI measurements were performed on the same Siemens MAGNETOM 3 Tesla whole-body-tomograph (MAGNETOM PRIMSA fit , Siemens, Erlangen, Germany). A total of 60 T2*-weighted echo-planar images (EPI) were acquired during the slot machine task using the CMRR multi-band EPI sequence [18, 24] (TR = 0.869 s, TE = 38 ms, flip angle = 58°, 60 interleaved slices, slice thickness = 2.4 mm, voxel dimensions = 2.4 x 2.4 x 2.4 mm 3 , FOV = 210 x 210mm 2 , 88 x 88 matrix, AP phase-encoding, multi-band factor 6, bandwidth 1832 Hz/Px, MB LeakBlock Kernel, weak raw filter, prescan normalization, excite pulse duration 7ms). Field map images were acquired with a standard Siemens dual gradient echo sequence (TR = 0.698 s, TE1 = 5.19 ms, TE2 = 7.65 ms, flip angle = 54°, 64 interleaved slices, slice thickness = 2.4 mm, voxel dimensions 2.4 x 2.4 x 2.4 mm 3 , FOV = 210 x 210mm 2 , 88 x 88 matrix, AP phase-encoding, bandwidth 279 Hz/Px). The paradigm was run using the Presentation® software (version 9.9, Neurobehavioral Systems, Inc., Albany, CA, USA). Auditory stimuli were delivered via the MRI-compatible Opto Acoustics OptoActiveTM II ANC headphones. Before the start of the paradigm, a T1-weighted MPRAGE data set was also acquired on the 3 T MRI with a 12-channel head coil to visualize brain morphology (TR = 2.00 s, TE = 2.03 ms, flip angle = 8°, 208 slices, slice thickness = 1 mm, voxel dimensions 1 x 1 x 1 mm 3 , FOV = 256 x 256 mm 2 , AP phase-encoding, bandwidth 240 Hz/Px). The slices were oriented sagittal, and the acquisition was performed in ascending order. Data analysis fMRI pre-processing The pre-processing and statistical analysis of the fMRI data was performed using the statistical parametric mapping software (SPM12, Wellcome Department of Imaging Neuroscience, University College London, London, UK) for Matlab. The initial six scans of each trial were discarded, to account for possible effects of magnetic saturation. Spatial correction of all images was performed on the first remaining data set to compensate for subject movement during the trial. The structural T2* EPI-MPRage image was normalized to a standard EPI template (MNI brain) using a 12-parameter affine transformation with additional nonlinear components. For quality control, the movement parameters of the test subjects were checked for movement artifacts. A single run was excluded in the case of an abrupt translational movement of more than 2 mm and > 2° in rotational movements. Here, strong movements were excluded, which have a negative influence on the accuracy of the localization of neuronal activations. In addition, the normalization was checked for plausibility and the occurrence of artefacts such as ghost artefacts. fMRI first level processing First level analyses of mean activation during cued and uncued blocks were computed for each participant in SPM12. For modelling the experimental conditions (cued and uncued) a general linear model (GLM) was used. The resulting contrast images of all participants were included in a second-level analysis to identify differences between the paradigm versions. fMRI second level processing As recommended for crossover studies flexible factorial models were used for both within-subject analyses (period and paradigm version) and between-subject analyses, as well as for the interaction of version*period in order to asses sequence effects[9]. A cluster-extent corrected threshold of familywise error (FWE) of pFWE < .05 was set as the statistical threshold for all analyses. Results Sample characteristics The sample characteristics and sociodemographic data of the n = 20 healthy participants are shown in Table 1 , as well as the results of the psychometric questionnaires. Table 1 Sample characteristics Questionnaire Total Mean (SD) Minimum [possible min] Maximum [possible max] Cut-off Age (years) 28.05 (10.57) Gender W:M 12:8 SOGS 0.25 (0.72) 0 [0] 3 [20] > 5 pathological > 2 problematic GUQ mean 1.17 (0.67) 1 [1] 4 [6] GBQ 6.15 (0.95) 7 [7] 4 [1] Mean cognitive distortion < 4.5 Desire scale 1.20 (0.89) 1 [1] 5 [11] Intention scale 1.30 (0.98) 1 [1] 5 [11] Negative Feelings scale 1.20 (0.62) 1 [1] 3 [11] Positive expectation scale 1.70 (1.89) 1 [1] 8 [11] Abstinence intention scale 6.00 (4.27) 11 [11] 1 [11] Realism 6.58 (2.67) 2 [1] 11 [1] FTND 0 (0) 0 [0] 0 [10] BDI 5.30 (6.20) 0 [0] 21 [63] > 13 mild, > 19 moderate, > 25 severe STAI 36.05 (9.11) 24 [20] 60 [80] > 39–40 BIS AI 15.85 (2.72) 12 [8] 20 [32] BIS MI 21.00 (2.41) 16 [11] 25 [44] BIS NI 18.43 (2.14) 15 [11] 23 [44] BIS total 5.29 (3.76) 47 [34] 61 [136] SPSRQ punishment 11.00 (3.84) 4 [0] 18 [24] SPSRQ reward 8.10 (4.25) 1 [0] 15 [24] SPSRQ total 18.10 (6.63) 9 [0] 32 [48] Sample characteristics and psychometric data of the participants. n = 20; Item Realism: n = 19; GBQ: inverse scale. GUQ: Gambling Urge Questionnaire, FTND: Fagerstrøm Test for Nicotine Dependence, BDI: Beck Depression Inventory, BIS: Baratt Impulsiveness Scale, AI: Attentional Impulsiveness, MI: Motor Impulsiveness, NI: Nonplanning Impulsiveness, SPSRQ: Sensitivity to Punishment and Reward Questionnaire Effect of win-contingent cues on decision-making Across both task versions, participants showed comparable rates of high-risk choices and rational decisions, with no significant main effects of win-contingent audiovisual cues or cue-by-order interactions on behavioral outcomes.​ The proportion of high-risk choices did not differ between the cued and uncued versions, neither across all trials nor in trials with an ambiguous expected value ratio (EVR = 0). Likewise, the frequency of rational versus irrational choices was comparable between versions, and no significant interaction with task order emerged (Table 2 and Table 1 in Supplementary material).​ Participants frequently chose options that did not maximize expected value in both task versions, which is consistent with previous reports of suboptimal EV-based choices in gambling-like tasks among healthy individuals. Table 2 Effects of task version and task order on decision-making behavior during virtual gambling Source Dependent variable F Significance p η² Task version (cued versus uncued) High-risk .008 .929 .000 High-risk EVR = 0 .032 .860 .001 Rational 2.388 .132 .066 Task period High-risk 1.366 .251 .039 High-risk EVR = 0 5.217 .029 .133 Rational 2.248 .143 .062 Interaction task version x period High-risk .000 .990 .000 High-risk EVR = 0 .215 .646 .006 Rational 1.991 .167 .055 The task version and task period showed no significant effect on the occurrence of high-risk or rational decisions. GLM univariate, sample size n = 19, EVR = 0: EV ratio = 0, thus favoring neither of the two winning options, rational: choice of the option conforming to the expected value; task order = order in which the game versions were played Neural response during the feedback phase of cued versus uncued trials As a reference for the following differences for the paradigm versions, we investigated the neural activation patterns during the uncued paradigm version. In the uncued version, wins (vs. losses and near wins) elicited increased activation in the hippocampi, superior parietal and frontal regions, insula and thalamus, consistent with robust engagement of memory, attentional and salience networks during rewarding outcomes (Flexible factorial model, contrast: win > loss + near win in the uncued paradigm version, p < .001, cluster-extent corrected pFWE < .05, n = 19, see Table 3 and Fig. 3). Comparing the cued an uncued paradigm versions with the aforementioned uncued paradigm as the baseline, we computed multiple contrasts to investigate the influence of win-contingent audiovisual cues on neural activation patterns. Regarding win > loss + near win, this contrast showed no significant additional neural activations in the cued version compared to the uncued trial (Flexible factorial model, contrast: win > loss + near win in the cued > uncued paradigm, p < .001, cluster-extent corrected pFWE < .05, n = 19). When directly contrasting the brain activation patterns during the cued task version to the uncued task we revealed higher brain activation for the cued version. Compared to the reference (the uncued trial), less brain activation was found in the superior temporal lobe, the right thalamus cuneus and left precuneus and both inferior parietal lobules when comparing the uncued version to the cued version. Regions that were found in both the reference and this contrast were both hippocampi, the insula and superior frontal gyri (flexible factorial model, contrast: win > loss + near-win for cued < uncued trial, p < .001, cluster-extent corrected pFWE < 0.05, n = 19, Table 3 and Fig. 3). For rational choices, a similar pattern emerged, with significantly less activation in thalamic, temporal, occipital and parietal cortices in rational decision for win > loss + near win in uncued compared to cued trials. Regions corresponding with the reference were hippocampal and insular cortices as well as the right lingual gyrus (Flexible factorial model, contrast: win > loss + near win in the cued < uncued paradigm version for rational decisions, p < .001, cluster-extent corrected pFWE loss + near win in comparison to the trial without stimuli (flexible factorial model, contrast: win > loss + near win for cued > uncued trial for rational decisions, p < .001, cluster-extent corrected pFWE loss + near win in the uncued paradigm version Cluster size t max MNI coordinates [x, y, z] Brain structure 442 6.22 -32 -28 -12 Left hippocampus, parahippocampal gyrus, fusiform gyrus 4386 6.08 -28 -30 48 Left superior parietal lobule, superior frontal gyrus, precentral gyrus, inferior parietal lobule, supramarginal gyrus, middle frontal gyrus 380 5.97 24 22 -18 Right olfactory cortex, superior frontal orbitofrontal cortex, insula, parahippocampal gyrus, gyrus rectus, inferior frontal orbitofrontal cortex 968 5.57 -12 -4 -6 Right hippocampus, thalamus, parahippocampal gyrus 1113 5.44 10 -90 8 Left cuneus, calcarine cortex, right superior occipital gyrus, lingual gyrus 403 4.95 24 -4 48 Right middle frontal gyrus, precentral gyrus, superior frontal gyrus 208 4.83 -16 -58 28 Left superior occipital gyrus, calcarine cortex, middle occipital gyrus Neural activation patterns win > loss + near win in the cued < uncued paradigm version 1949 6.53 -14 -44 -12 Left hippocampus, fusiform gyrus, superior temporal gyrus, inferior frontal gyrus, opercular part, right thalamus, vermis 3357 6.31 -10 -40 -34 Left middle occipital gyrus, cuneus, cerebellum, right hippocampus, cerebellum, cuneus 1755 5.47 24 -58 8 Right inferior parietal lobule, cuneus, paracentral lobule, middle cingulate gyrus, middle occipital gyrus, lingual gyrus 404 5.37 -22 -44 54 Left precuneus, inferior parietal lobule, postcentral gyrus, superior parietal lobule 748 5.33 36 14 6 Right amygdala, precentral gyrus, insula, rolandic operculum, superior temporal pole, inferior frontal gyrus, opercular part 335 5.14 10 12 30 Left anterior cingulate gyrus, middle cingulate gyrus, right anterior cingulate gyrus, middle cingulate gyrus, superior frontal gyrus Neural activation patterns win > loss + near win in the cued < uncued paradigm version 1653 6.32 -10 -40 -34 Right hippocampus, cerebellum, left cerebellum, vermis 949 6.28 -12 -44 -14 Left hippocampus, fusiform gyrus, cerebellum, thalamus, right thalamus, vermis 714 5.22 -18 -70 32 Left middle occipital gyrus, superior occipital gyrus, cuneus, right cuneus 478 5.20 38 14 6 Right amygdala, inferior frontal gyrus, opercular part, superior temporal pole, insula 427 5.12 24 -58 8 Right cuneus, lingual gyrus 537 4.78 -38 2 2 Left superior temporal gyrus, superior temporal pole, inferior frontal gyrus, opercular part, middle temporal gyrus, insula 266 4.29 14 -70 58 Right precuneus Significant neural activation patterns, Flexible factorial model, contrasts: win > loss + near win in the uncued paradigm version, win > loss + near win in the cued loss + near win in the cued < uncued paradigm version for rational decisions, p < .001, cluster-extent corrected pFWE < .05, n = 19 Neural activation patterns in the feedback phase Depiction of the neural activation patterns, the scale represents the gradation of the t-values. Flexible factorial model, contrasts: a. win > loss + near win in the uncued paradigm version, b. win > loss + near win in the cued loss + near win in the cued < uncued paradigm version for rational decisions, p < .001, cluster-extent corrected pFWE < .05, n = 19 Neural response during the decision phase of cued versus uncued trials As a reference for the comparison between neural activation during high-risk versus low-risk trials, we investigated the neural response during the uncued paradigm version. During the decision phase, high-risk (vs. low-risk) choices in the uncued version engaged frontoparietal and occipital regions, including right angular gyrus, insula, cuneus and bilateral frontal areas (flexible factorial model, contrast: high-risk > low-risk for uncued trial, p <. 001, cluster-extent corrected pFWE < 0.05, n = 19, see Table 4 and Fig. 4). Direct comparisons between cued and uncued versions for high-risk versus low-risk decisions, both across all trials and restricted to rational decisions, revealed no significant differences in neural activation at the predefined threshold (flexible factorial model, contrast: high-risk > low-risk and high-risk < low-risk for cued uncued trial p < .001, cluster-extent corrected pFWE < 0.05). When comparing rational versus irrational decisions with the uncued version as a reference, the cued trial showed more activation in the precuneus on both sides, right supramarginal cortex, lingula, left and right medial frontal lobe, right putamen (flexible factorial model, contrast: high-risk > low-risk for cued > uncued trial for rational decisions, p < .001, cluster-extent corrected pFWE < 0.05, n = 19, see Table 4 and Fig. 4). In contrast, significantly higher neuronal activation was found in the uncued trial in the right lingula, bilateral frontal lobe, the left superior temporal, right gyrus pre- and postcentralis (flexible factorial model, contrast: high-risk > low-risk for cued < uncued trial for rational decisions, p < .001, cluster-extent corrected pFWE low-risk in the uncued paradigm version Cluster size t max MNI coordinates [x, y, z] Brain structure 745 6.27 52 -68 22 Right angular gyrus, middle temporal gyrus, middle occipital gyrus 262 5.24 26 26 -26 Right olfactory cortex, superior frontal gyrus, orbital part, middle frontal gyrus, orbital part, insula 490 4.92 12 -86 8 Right cuneus, superior occipital gyrus, lingual gyrus 291 4.59 -24 -4 54 Left middle frontal gyrus, supplementary motor area, superior frontal gyrus, precentral gyrus 303 4.54 -20 -54 66 Left inferior parietal lobule, superior parietal lobule 248 4.39 -24 34 52 Left middle frontal gyrus, superior frontal gyrus Neural activation patterns high-risk > low-risk in the cued > uncued paradigm version for rational decisions 266 6.59 20 42 -4 Right superior frontal gyrus, orbital part and medial part Neural activation patterns high-risk > low-risk in the cued < uncued paradigm version for rational decisions 418 8.44 74 -28 12 Right superior temporal gyrus, inferior temporal gyrus, middle temporal gyrus 1524 5.44 0 -8 60 Right superior parietal lobule, superior frontal gyrus, postcentral gyrus, supplementary motor area, precentral gyrus, left precentral gyrus 844 5.39 46 -18 32 Right supramarginal gyrus, precentral gyrus, insula 396 5.32 6 62 -26 Left superior and medial frontal gyrus, orbital part, right superior and medial frontal gyrus, orbital part 282 5.22 -42 56 -14 Left middle frontal gyrus, orbital part, superior temporal pole 290 5.06 -42 -6 56 Left postcentral gyrus, inferior parietal lobule, precentral gyrus 451 4.62 -64 -20 14 Left rolandic operculum, supramarginal gyrus, insula, superior temporal gyrus Significant neural activation patterns, Flexible factorial model, contrast: high-risk > low-risk in the uncued paradigm version, high-risk > low-risk in the cued > uncued paradigm version for rational decisions, high-risk > low-risk in the cued < uncued paradigm version for rational decisions, p < .001, cluster-extent corrected pFWE < .05, n = 19 Neural activation patterns in the decision phase Depiction of the neural activation patterns, the scale represents the gradation of the t-values. Flexible factorial model, contrast: a. high-risk > low-risk in the uncued paradigm version, b. high-risk > low-risk in the cued > uncued paradigm version for rational decisions, c. high-risk > low-risk in the cued < uncued paradigm version for rational decisions, p < .001, cluster-extent corrected pFWE < .05, n = 19 Discussion In this pilot study, win-contingent audiovisual cues did not significantly alter the proportion of high-risk choices or rational versus irrational decisions in healthy volunteers. Behavioral performance was comparable between cued and uncued versions across trials with advantageous, disadvantageous and ambiguous expected values. Participants frequently selected options that did not maximize expected value, irrespective of cue condition, which aligns with previous work showing that healthy individuals often deviate from strict EV‑maximizing strategies in gambling‑like tasks. In line with previous studies, such as those by [17] and [4], there were also no significant effects of audiovisual stimuli on risk assessment and decision-making in healthy individuals. Similarly in another study investigating our paradigm using eye tracking, while no differences in risky decision-making were found [2], the cued paradigm version showed significant deviations of visual attention. A comparable study by [26] found significant effects of audiovisual stimuli on high-risk decisions in a large sample. As the statistically significant effect could be determined with the larger sample size, it is possible that we were unable to see a significant effect due to the small number of test subjects. Further studies with a larger number of participants and realistic gambling simulations are needed to be able to depict even small effect sizes. While the parallelization of the paradigm versions ensures a similarity in the versions for a more accurate data analysis, it may also make it more difficult to find differences. So not enough visual differences between the cued and uncued paradigm version could lessen the effect of audiovisual stimuli on decision-making. Overall, it can therefore be said that the current study situation does not yet provide sufficient evidence to support the hypothesis that win contingency audiovisual stimuli cause more frequent risk-taking decisions in healthy test subjects. This task may be better suited to differentiate between the groups of healthy individuals and individuals with GD, as shown by [2]. Feedback Phase: Difference in neuronal activation patterns with and without audiovisual stimuli At the neural level, wins in the uncued condition elicited robust activation in hippocampal, parietal, frontal, occipital and insular regions, reflecting the engagement of memory, attentional and salience networks during outcome processing.​ This is supported by prior research that showed that the presentation of gambling-associated stimuli, as well as near wins in people with GD, induced robust insula activation (Clark et al., 2014; Naqvi & Bechara, 2009)[7, 14]. While these studies found stronger insular activation in people with GD, not healthy individuals, Tsurumi et al found that in a high-risk gambling task, the subgroup of risk seeking healthy individuals showed less activation in the insula compared to the risk avoiding subgroup [28]. The relative attenuation of activation in hippocampi, insula, superior parietal and occipital cortices, as well as anterior cingulate and amygdala, during cued compared with uncued win feedback suggests that win-contingent audiovisual cues may partially replace internal evaluative and monitoring processes by providing externally generated sensory feedback.​ While insular activation was shown to reflect risk anticipation [21], less activation may indicate less risk anticipation during cued trials, therefore showing the effectiveness of win-contingent cues. The fact that a similar pattern was observed specifically for rational decisions indicates that cue-related modulation of outcome processing occurs even when participants choose the option with higher expected value, pointing to a dissociation between neural encoding of outcomes and overt decision quality. During the feedback phase of the paradigm version with win-contingent cues, we observed lower activation in the insula and the superior parietal lobe. In cued versus uncued trials, there was less activation in the insula and the superior parietal lobe, during both during all decisions and rational choices. With decreased activation of the insula in rational choices in cued trials, it can be concluded that audiovisual stimuli influence neuronal activation in rational decision-making, and potentially reduce loss avoidance. Further research on whether audiovisual cues may reduce loss aversion in healthy subjects is needed. Decision phase: effect of audiovisual stimuli on neural activation The absence of robust cue‑related differences in decision‑phase activation mirrors the behavioral findings, suggesting that, under the present conditions, win‑contingent cues modulate outcome processing more strongly than the neural implementation of choice itself. The engagement of frontoparietal and occipital regions during high‑ versus low‑risk decisions in the uncued version is consistent with prior work implicating these networks in risk evaluation, attention and action selection [6, 8, 16, 23, 30]. The absence of robust cue‑related differences in decision‑phase activation mirrors the behavioral findings, suggesting that, under the present conditions, win‑contingent cues modulate outcome processing more strongly than the neural implementation of choice itself. The reduced insular and superior parietal activation in cued versus uncued trials may indicate a shift from internally driven risk and loss monitoring towards externally driven, cue‑based feedback processing. In healthy individuals, this attenuation may be compensated by intact cognitive control, preventing overt increases in risk‑taking despite altered neural responses. In individuals with or at risk for gambling disorder, such a shift might contribute to diminished sensitivity to losses and near losses, and thereby to the persistence of gambling behavior in the presence of adverse outcomes. Longitudinal and case–control studies using similar paradigms are needed to test whether the neural patterns observed here in healthy volunteers represent early vulnerability markers for GD. Limitations Although the present study provides further insight into the neural processing of gain-contingent audiovisual stimuli, some limitations need to be addressed. The present study examined a young, inexperienced sample of participants, comparable to those in similar studies, but not representative of the general population. Due to the limited sample size and the absence of subjects with GD, the results are only transferable to this group to a limited extent. The study used a cross-over design, which increased the power, but further studies with a larger sample are required for smaller effects, especially for risky decision-making. The virtual gambling paradigm was perceived as realistic, but the results are limited due to the limitations of immersion in an MRI scanner. The pseudo-randomization of the gambling process enabled us to depict the “oversampling” of winnings at the beginning of a game but limits the significance of the results, especially for the second trial run. Conclusion While this study shows effects of win-contingent audiovisual stimuli on neuronal activities during gambling in healthy individuals, no behavioral change could be observed, likely due to the intact behavioral control and conscious reflection of the choices made during the gambling paradigm. Declarations The authors did not receive support from any organization for the submitted work. The authors have no competing interests to declare that are relevant to the content of this article. The authors declare that they have no conflict of interest. Author contributions All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Lisa Jil Krause, Patrick Bach and Ronald Fischer. The first draft of the manuscript was written by Lisa Jil Krause, revised by Patrick Bach and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. References American Psychiatric Association (2013) Diagnostic and statistical manual of mental disorders : Dsm-5. American Psychiatric Association, Arlington, VA Baumann G, Fischer R, Reinhard I, Hoffmann S, Kiefer F, Leménager T, Bach P (2025) Investigating decision-making under risk in pathological gambling using a virtual slot machine: A pilot eye-tracking study. Eur Addict Res 31:308-324 Beesdo-Baum K, First MB (2019) Scid-5-pd: Strukturiertes klinisches interview für dsm-5 persönlichkeitsstörungen : Deutsche bearbeitung des structured clinical interview for dsm-5® - personality disorders von michael b. First, janet b.W. Wiliams, lorna smith benjamin, robert l. Spitzer : Manual. Hogrefe Cherkasova MV, Clark L, Barton JJS, Schulzer M, Shafiee M, Kingstone A, Stoessl AJ, Winstanley CA (2018) Win-concurrent sensory cues can promote riskier choice. The Journal of Neuroscience 38:10362-10370 Clark L, Boileau I, Zack M (2019) Neuroimaging of reward mechanisms in gambling disorder: An integrative review. Mol Psychiatry 24:674-693 Crockford DN, Goodyear B, Edwards J, Quickfall J, el-Guebaly N (2005) Cue-induced brain activity in pathological gamblers. Biol Psychiatry 58:787-795 Fauth-Bühler M, Zois E, Vollstädt-Klein S, Lemenager T, Beutel M, Mann K (2014) Insula and striatum activity in effort-related monetary reward processing in gambling disorder: The role of depressive symptomatology. Neuroimage Clin 6:243-251 Gelskov SV, Madsen KH, Ramsøy TZ, Siebner HR (2016) Aberrant neural signatures of decision-making: Pathological gamblers display cortico-striatal hypersensitivity to extreme gambles. NeuroImage 128:342-352 Gläscher J, Gitelman D (2008) Contrast weights in flexible factorial design with multiple groups of subjects. Goodie AS, MacKillop J, Miller JD, Fortune EE, Maples J, Lance CE, Campbell WK (2013) Evaluating the south oaks gambling screen with dsm-iv and dsm-5 criteria:Results from a diverse community sample of gamblers. Assessment 20:523-531 Griffiths M (1993) Fruit machine gambling: The importance of structural characteristics. Journal of Gambling Studies 9:101-120 Kiefer F, Fauth-Buhler M, Heinz A, Mann K (2013) [neurobiology of behavioral addictions]. Nervenarzt 84:557-562 Klar J, Slotboom J, Lerch S, Koenig J, Wiest R, Kaess M, Kindler J (2024) Higher striatal glutamate in male youth with internet gaming disorder. Eur Arch Psychiatry Clin Neurosci 274:301-309 Limbrick-Oldfield EH, Mick I, Cocks RE, McGonigle J, Sharman SP, Goldstone AP, Stokes PR, Waldman A, Erritzoe D, Bowden-Jones H, Nutt D, Lingford-Hughes A, Clark L (2017) Neural substrates of cue reactivity and craving in gambling disorder. Transl Psychiatry 7:e992 Linnet J (2020) The anticipatory dopamine response in addiction: A common neurobiological underpinning of gambling disorder and substance use disorder? Prog Neuropsychopharmacol Biol Psychiatry 98:109802 Liu G-C, Yen J-Y, Chen C-Y, Yen C-F, Chen C-S, Lin W-C, Ko C-H (2014) Brain activation for response inhibition under gaming cue distraction in internet gaming disorder. The Kaohsiung Journal of Medical Sciences 30:43-51 Miedl SF, Fehr T, Meyer G, Herrmann M (2010) Neurobiological correlates of problem gambling in a quasi-realistic blackjack scenario as revealed by fmri. Psychiatry Res 181:165-173 Moeller S, Yacoub E, Olman CA, Auerbach E, Strupp J, Harel N, Ugurbil K (2010) Multiband multislice ge-epi at 7 tesla, with 16-fold acceleration using partial parallel imaging with application to high spatial and temporal whole-brain fmri. Magn Reson Med 63:1144-1153 Moritz S, Gehlenborg J, Bierbrodt J, Wittekind C, Bücker L (2020) A ghost in the machine? The predictive role of metacognitive beliefs, cognitive biases, and machine-related features in the severity of problematic slot machine gambling. Personality and Individual Differences 171:110539 Potenza MN, Balodis IM, Derevensky J, Grant JE, Petry NM, Verdejo-Garcia A, Yip SW (2019) Gambling disorder. Nat Rev Dis Primers 5:51 Preuschoff K, Quartz SR, Bossaerts P (2008) Human insula activation reflects risk prediction errors as well as risk. The Journal of Neuroscience 28:2745-2752 Romanczuk-Seiferth N, Mörsen C, Heinz A (2016) Impulskontrollstörungen/verhaltenssüchte. Übersichten. Pathologisches glücksspiel und delinquenz. Pathological gambling and delinquency. Forensische Psychiatrie, Psychologie, Kriminologie 10 Seitz R (2011) Medialer frontalkortex und subjektive verhaltenskontrolle. e-Neuroforum 17 Setsompop K, Gagoski BA, Polimeni JR, Witzel T, Wedeen VJ, Wald LL (2012) Blipped-controlled aliasing in parallel imaging for simultaneous multislice echo planar imaging with reduced g-factor penalty. Magn Reson Med 67:1210-1224 Sharp ME, Viswanathan J, Lanyon LJ, Barton JJ (2012) Sensitivity and bias in decision-making under risk: Evaluating the perception of reward, its probability and value. PLoS One 7:e33460 Spetch ML, Madan CR, Liu YS, Ludvig EA (2020) Effects of winning cues and relative payout on choice between simulated slot machines. Addiction 115:1719-1727 Steenbergh TA, Meyers AW, May RK, Whelan JP (2002) Development and validation of the gamblers' beliefs questionnaire. Psychol Addict Behav 16:143-149 Tsurumi K, Kawada R, Yokoyama N, Sugihara G, Sawamoto N, Aso T, Fukuyama H, Murai T, Takahashi H (2014) Insular activation during reward anticipation reflects duration of illness in abstinent pathological gamblers. Frontiers in Psychology 5 van Holst RJ, van den Brink W, Veltman DJ, Goudriaan AE (2010) Brain imaging studies in pathological gambling. Curr Psychiatry Rep 12:418-425 Wang P, Chen S, Deng K, Zhang B, Im H, Feng J, Liu L, Yang Q, Zhao G, He Q, Chen C, Wang H, Wang Q (2023) Distributed attribute representation in the superior parietal lobe during probabilistic decision‐making. Human Brain Mapping 44:5693-5711 Winstanley CA, Hynes TJ (2021) Clueless about cues: The impact of reward-paired cues on decision making under uncertainty. Current Opinion in Behavioral Sciences 41:167-174 World Health Organization (2018) International classification of diseases for mortality and morbidity statistics (11th revision). Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterialNeuralProcessingGamblingKrause.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9001151","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":628730606,"identity":"4aa1a3f6-44b2-40dd-9115-8bd6f0019b92","order_by":0,"name":"Lisa Jil Krause","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFklEQVRIie2PP0vDQBiH3yOQLEddLwj6Fd5SCC7SD+JyRYhLAwEnt0ydYrtGBP0K5+IcKDRLMetBRFP6BdpFMgT0cnXMqaPDPcPdj+Oe9w+AxfIPQUcdZKYzqQF1cEGH/Ccl1dnBvym6fHb4yb4f3cNlUjxvsyPi7RTL5eqmieHi6P52Ve/iZxgUiWEwOmKkvh4KGYaSIUTZ68vVMMMK/HV/G6WAUjgRkgYS8TNK5DQ4pkpByQ2Kt22I4GNRlh8xV10eO6XtlPfaoEDASMYnIp+6kCtFdAroLob1HRqcTVJ+eSfDkZ8o5UkpfooV9df9g40XxVbuZ/x8Xi43+6aF6EEprGmrk0HRv76mtxo1/7dYLBbLb3wBcCBhTodqVWMAAAAASUVORK5CYII=","orcid":"","institution":"Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University","correspondingAuthor":true,"prefix":"","firstName":"Lisa","middleName":"Jil","lastName":"Krause","suffix":""},{"id":628730607,"identity":"87d34af1-c0ff-4986-93eb-6abfdd1e5f37","order_by":1,"name":"Ronald Fischer","email":"","orcid":"","institution":"Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University","correspondingAuthor":false,"prefix":"","firstName":"Ronald","middleName":"","lastName":"Fischer","suffix":""},{"id":628730608,"identity":"c96134bc-0567-4d77-9974-bb26ac3efa5e","order_by":2,"name":"Falk Kiefer","email":"","orcid":"","institution":"Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University","correspondingAuthor":false,"prefix":"","firstName":"Falk","middleName":"","lastName":"Kiefer","suffix":""},{"id":628730615,"identity":"6cf17e70-24ef-4c15-8a58-3e358595df73","order_by":3,"name":"Tagrid Leménager","email":"","orcid":"","institution":"Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University","correspondingAuthor":false,"prefix":"","firstName":"Tagrid","middleName":"","lastName":"Leménager","suffix":""},{"id":628730617,"identity":"1ebd73a9-6f4f-47b8-8229-53d34166f4d5","order_by":4,"name":"Patrick Bach","email":"","orcid":"","institution":"Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University","correspondingAuthor":false,"prefix":"","firstName":"Patrick","middleName":"","lastName":"Bach","suffix":""}],"badges":[],"createdAt":"2026-03-01 11:38:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9001151/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9001151/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108029927,"identity":"14e62b15-7b29-4fd8-85a6-fa9a01abb1aa","added_by":"auto","created_at":"2026-04-28 15:50:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1268725,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eDesign of the virtual gambling paradigm: uncued and cued version\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe two different gambling paradigm versions during the win output, on the left the uncued version, on the right the cued version with the strongest stimuli and the highest reward magnitude. (Einsatz: German for stake, Gewinn: reward magnitude, Spielstand: score)\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-9001151/v1/0470f231424c01b14b78966d.png"},{"id":108181878,"identity":"98fe8907-8753-45a8-911b-39c5d33212ff","added_by":"auto","created_at":"2026-04-30 08:58:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":388651,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eDesign of the virtual gambling paradigm: phases of the gambling paradigm\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe 3 phases of each trial run in an uncued trial: decision phase with the stakes, the win probability and the reward magnitude for the high-risk and low-risk game option, anticipation phase with the wheels turning and feedback phase with the display of a win with the new score (Einsatz: German for stake, Gewinn: reward magnitude, Chance: win probability, Spielstand: score, Leider verloren: loss)\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-9001151/v1/b3cc42f83576f49e2f740385.png"},{"id":108029928,"identity":"e1b06b82-535c-4a0f-8f28-198f40e9d35f","added_by":"auto","created_at":"2026-04-28 15:50:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":6794662,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eNeural activation patterns in the feedback phase\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eDepiction of the neural activation patterns, the scale represents the gradation of the t-values.\u003c/p\u003e\n\u003cp\u003eFlexible factorial model, contrasts: a. win \u0026gt; loss + near win in the uncued paradigm version, b. win \u0026gt; loss + near win in the cued \u0026lt; uncued paradigm version, c. win \u0026gt; loss + near win in the cued \u0026lt; uncued paradigm version for rational decisions, p \u0026lt; .001, cluster-extent corrected pFWE \u0026lt; .05, n = 19\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-9001151/v1/01e833248c8ffc67f04999cc.png"},{"id":108029930,"identity":"31fa851d-bfbc-4f34-9ad5-e2ba6700dccb","added_by":"auto","created_at":"2026-04-28 15:50:02","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":7457793,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eNeural activation patterns in the decision phase\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eDepiction of the neural activation patterns, the scale represents the gradation of the t-values.\u003c/p\u003e\n\u003cp\u003eFlexible factorial model, contrast: a. high-risk \u0026gt; low-risk in the uncued paradigm version, b. high-risk \u0026gt; low-risk in the cued \u0026gt; uncued paradigm version for rational decisions, c. high-risk \u0026gt; low-risk in the cued \u0026lt; uncued paradigm version for rational decisions, p \u0026lt; .001, cluster-extent corrected pFWE \u0026lt; .05, n = 19\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-9001151/v1/2a5a6bc7d109c1c9abf67eec.png"},{"id":108184051,"identity":"fff024bc-8249-4212-ab81-31e110c4a032","added_by":"auto","created_at":"2026-04-30 09:03:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":28364354,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9001151/v1/cfcb57a8-7eb2-418e-afa5-ffb172ca64f7.pdf"},{"id":108029926,"identity":"cab4f83f-639c-4315-afc5-96299040fd68","added_by":"auto","created_at":"2026-04-28 15:50:02","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1251799,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterialNeuralProcessingGamblingKrause.docx","url":"https://assets-eu.researchsquare.com/files/rs-9001151/v1/7d2c1587b126e74049f6d9f9.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Neural processing of win-contingent audiovisual cues during virtual gambling: An fMRI cross-over study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOver the last 30 years, the global incidence and prevalence of gambling disorders (GD) has increased. The risk for GD is particularly high, when using gambling and slot machines [19, 22]. Characteristics such as high availability, high event and payout frequency, increasable stakes and winnings create the illusion of control over the game outcome and increase the possibility of excessive gambling and risky decisions. The occurrence of near wins, where one reel is one position away from a jackpot, similarly promotes GD behavior via activation of similar frontostriatal circuits like actual monetary gains do [11, 22, 29].\u003c/p\u003e \u003cp\u003eAnother mechanism to increase the addictive potential of slot machines is the delivery of choices and wins with audiovisual cues such as sounds and colorful lights and symbols. These cues have shown to affect the decision-making of healthy individuals towards more risky decisions [4, 26, 31].\u003c/p\u003e \u003cp\u003eIn people with GD the cerebral reward system shows an increase in responsiveness (\u0026ldquo;cue reactivity\u0026rdquo;) to gambling-related stimuli, especially in the ventral striatum, as an important part of the limbic system [12, 22].\u003c/p\u003e \u003cp\u003eIn the frontostriatal regions, such as the striatum and prefrontal cortex, reduced activation during cue exposure, gambling simulations, impulse control and anticipation of winning was found [13, 20]. Reduced connectivity between the two areas is thought to play a role in cue-induced craving [20].\u003c/p\u003e \u003cp\u003eHowever, few studies used real-world gambling paradigms. Recent reviews (Linnet 2020 and Clark 2019) stressed the relevance of such tasks due to their external validity and their capacity to demonstrate hyperreactivity in the striatum, midbrain, and medial and prefrontal cortex in people with GD. In addition, the review advocated for further research using realistic gambling tasks to investigate outcome anticipation and its role in the learning process in GD [5, 15].\u003c/p\u003e \u003cp\u003eThus, to further elucidate the processing of win‑contingent audiovisual stimuli, we investigated the neurobiological basis of these cues in a realistic virtual slot-machine paradigm in healthy volunteers. Specifically, we tested whether win‑contingent cues (i) increase risky decision-making and (ii) alter neural responses during decision-making and outcome processing, with a particular focus on regions implicated in GD such as the insula, striatum and prefrontal cortex.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eThis randomized cross-over study compared the effects of a virtual slot machine paradigm with win-contingent cues (henceforth \u0026ldquo;cued version\u0026rdquo;) to a parallel version without win-contingent cues (henceforth \u0026ldquo;uncued version\u0026rdquo;) on neural brain activation during feedback (win, loss near win) and on decisions during the gambling task (choice of the high- versus low-risk gambling bet).\u003c/p\u003e \u003cp\u003eTwo test blocks (cued and uncued test block) were conducted per person, each with and without win-contingent audiovisual stimuli, 30 trials of 41 seconds each per block, totaling 23.5 minutes per block with a randomized sequence of the two paradigm versions. The study was a pilot trial that enrolled a total of 20 healthy individuals.\u003c/p\u003e \u003cp\u003e The study was approved by the local ethics committee (Heidelberg University), conducted in accordance to the Declaration of Helsinki and pre-registered (German clinical trials database: DRKS00021178). Participants provided written informed consent. All study procedures were conducted at the Central Institute of Mental Health in Mannheim, Germany.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eA total of N\u0026thinsp;=\u0026thinsp;20 right-handed healthy volunteers were recruited though public advertisements, on the Central Institute of Mental Health Website and on social media.\u003c/p\u003e \u003cp\u003eParticipants were required to be between the ages of 18 and 65 with sufficient eyesight to participate either with contact lenses or MRI-compatible glasses. Only participants with a negative COVID-19 test, a breath alcohol of 0.0%, and a negative drug urine test and negative pregnancy test were enrolled.\u003c/p\u003e \u003cp\u003eBefore enrollment, a medical history was recorded and participants were screened for psychiatric disorders via Structured Clinical Interview for DSM-5 (SCID) [3]. Severe somatic, neurological, and psychiatric illnesses, including current manic or severe depressive episodes and schizoaffective disorders, led to exclusion from the study. Exceptions were nicotine dependence and affective disorders associated with the use of antidepressants if their dose was unchanged for at least 30 days. The use of other psychotropic drugs also led to exclusion from the study. All participants were screened for GD via the ICD-10 and DSM-5 diagnostic criteria and the Gamblers\u0026lsquo; Believe Questionnaire (GBQ) and South Oaks Gambling Screen (SOGS) [1, 10, 27, 32].\u003c/p\u003e \u003cp\u003eOne participant was removed from the study, due to indications for multiple psychiatric comorbidities during the screening process.\u003c/p\u003e\n\u003ch3\u003ePrimary outcome measures\u003c/h3\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSlot machine paradigm\u003c/h2\u003e \u003cp\u003eAs our slot machine paradigm, we used a modified version of the Vancouver Gambling Task (VGT) [25], a virtual slot machine, with the two paradigm versions, one with and one win-contingent audiovisual stimuli (\u0026ldquo;cued\u0026rdquo;) and one without (from here on \u0026ldquo;uncued\u0026rdquo;), the order of presentation (i.e. first cued or uncued version) of the versions was randomized (see Fig.\u0026nbsp;1 and Fig.\u0026nbsp;9 in the supplementary information for a more detailed depiction).\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure\u0026nbsp;1\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDesign of the virtual gambling paradigm: uncued and cued version\u003c/h3\u003e\n\u003cp\u003e \u003c/p\u003e \u003cp\u003eThe two different gambling paradigm versions during the win output, on the left the uncued version, on the right the cued version with the strongest stimuli and the highest reward magnitude. (Einsatz: German for stake, Gewinn: reward magnitude, Spielstand: score)\u003c/p\u003e \u003cp\u003eThis paradigm has been successfully used and validated in prior independent studies [2].\u003c/p\u003e \u003cp\u003eInstead of real money, each participant started with a virtual account of 30 points and was told that they could earn or lose points during the game. The aim was to earn as many points as possible to receive the highest possible voucher as compensation for participation. Each paradigm version consisted of 30 trial runs (10 wins, 10 near wins, 10 losses). The sequence of the wins and losses was predetermined and the same in both paradigms, this pseudo-randomization ensuring parallelism, and with an oversampling of wins in the beginning to facilitate cue-outcome learning.\u003c/p\u003e \u003cp\u003eThe paradigm consisted of three phases per trial run: decision, anticipation, and feedback phase.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure\u0026nbsp;2\u003c/b\u003e \u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eDesign of the virtual gambling paradigm: phases of the gambling paradigm\u003c/h2\u003e \u003cp\u003e \u003cdiv description=\"\" class=\"Drawing\" id=\"153215224\" name=\"Grafik 1\"\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe 3 phases of each trial run in an uncued trial: decision phase with the stakes, the win probability and the reward magnitude for the high-risk and low-risk game option, anticipation phase with the wheels turning and feedback phase with the display of a win with the new score (Einsatz: German for stake, Gewinn: reward magnitude, Chance: win probability, Spielstand: score, Leider verloren: loss)\u003c/p\u003e \u003cp\u003eIn the decision phase, the participants were given the task of choosing one of two game options with different risk profiles, one of them being a low-risk option, the other a high-risk option. The risk profiles differed in winning probability, stake, and total win, with the riskier option having higher stakes, higher wins, and lower probabilities of winning.\u003c/p\u003e \u003cp\u003eBased on the different expected value (EV) ratios, we classified the choices as rational, when they aligned with risk profile favored by the EV ratio [25].\u003c/p\u003e \u003cp\u003eThe EV Ratio was calculated as shown by Sharp et al. (2012)\u003c/p\u003e \u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\u003cp\u003eIn three trial runs per version, both risk profiles were rational choices, in order to investigate risky decision-making under these circumstances.\u003c/p\u003e \u003cp\u003eThe anticipation phase consisted of the three wheels of the virtual slot machine turning.\u003c/p\u003e \u003cp\u003eFor the feedback phase, the wheel stopped turning, displaying the outcome of the trial run and the new score after the potential win was added and the stake subtracted. There were then three scenarios: win (all three reels showing the same symbol), \u0026ldquo;pure\u0026rdquo; loss (all three reels showed different symbols), and near win. This is a monetary loss in which the first two reels show the same symbol, but the last reel is one position away from the winning position [11].\u003c/p\u003e \u003cp\u003eFor the cued paradigm version the outcome was accompanied by audiovisual stimuli of varying intensity depending on the reward magnitude, as used by [4]. The uncued version did not display any of these additional stimuli, as shown in Fig.\u0026nbsp;1.\u003c/p\u003e \u003cp\u003eTo ensure that the different phases were of the same length for all measurements, a maximum duration of 16 s was set for the anticipation phase. If the test subjects decided earlier, a fixation cross was displayed for the remaining time. If no decision was made during this period, the last decision was replicated by the program.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eBehavioral data\u003c/h3\u003e\n\u003cp\u003eIn addition to the fMRI data, the participants' decisions regarding the choice of game options were also analyzed in SPSS (Statistical Package for the Social Sciences, SPSS Inc., Chicago, IL, USA; Release 29.0.0). Descriptive statistics were generated for high- and low-risk decisions, as well as rational and irrational decisions. The main effect of the game versions (with versus without win contingent audiovisual stimuli) was analyzed using a general linear model with the game version as a fixed factor, the order of presentation of the game versions as a covariate, as well as their interaction, and the proportion of high-risk decisions, rational decisions and high-risk decisions in trials with an EV ratio of 0 as the dependent variable.\u003c/p\u003e\n\u003ch3\u003eData acquisition\u003c/h3\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003efMRI\u003c/h2\u003e \u003cp\u003eAll fMRI measurements were performed on the same Siemens MAGNETOM 3 Tesla whole-body-tomograph (MAGNETOM PRIMSA\u003csup\u003efit\u003c/sup\u003e, Siemens, Erlangen, Germany). A total of 60 T2*-weighted echo-planar images (EPI) were acquired during the slot machine task using the CMRR multi-band EPI sequence [18, 24] (TR\u0026thinsp;=\u0026thinsp;0.869 s, TE\u0026thinsp;=\u0026thinsp;38 ms, flip angle\u0026thinsp;=\u0026thinsp;58\u0026deg;, 60 interleaved slices, slice thickness\u0026thinsp;=\u0026thinsp;2.4 mm, voxel dimensions\u0026thinsp;=\u0026thinsp;2.4 x 2.4 x 2.4 mm\u003csup\u003e3\u003c/sup\u003e, FOV\u0026thinsp;=\u0026thinsp;210 x 210mm\u003csup\u003e2\u003c/sup\u003e, 88 x 88 matrix, AP phase-encoding, multi-band factor 6, bandwidth 1832 Hz/Px, MB LeakBlock Kernel, weak raw filter, prescan normalization, excite pulse duration 7ms). Field map images were acquired with a standard Siemens dual gradient echo sequence (TR\u0026thinsp;=\u0026thinsp;0.698 s, TE1\u0026thinsp;=\u0026thinsp;5.19 ms, TE2\u0026thinsp;=\u0026thinsp;7.65 ms, flip angle\u0026thinsp;=\u0026thinsp;54\u0026deg;, 64 interleaved slices, slice thickness\u0026thinsp;=\u0026thinsp;2.4 mm, voxel dimensions 2.4 x 2.4 x 2.4 mm\u003csup\u003e3\u003c/sup\u003e, FOV\u0026thinsp;=\u0026thinsp;210 x 210mm\u003csup\u003e2\u003c/sup\u003e, 88 x 88 matrix, AP phase-encoding, bandwidth 279 Hz/Px).\u003c/p\u003e \u003cp\u003eThe paradigm was run using the Presentation\u0026reg; software (version 9.9, Neurobehavioral Systems, Inc., Albany, CA, USA). Auditory stimuli were delivered via the MRI-compatible Opto Acoustics OptoActiveTM II ANC headphones.\u003c/p\u003e \u003cp\u003eBefore the start of the paradigm, a T1-weighted MPRAGE data set was also acquired on the 3 T MRI with a 12-channel head coil to visualize brain morphology (TR\u0026thinsp;=\u0026thinsp;2.00 s, TE\u0026thinsp;=\u0026thinsp;2.03 ms, flip angle\u0026thinsp;=\u0026thinsp;8\u0026deg;, 208 slices, slice thickness\u0026thinsp;=\u0026thinsp;1 mm, voxel dimensions 1 x 1 x 1 mm\u003csup\u003e3\u003c/sup\u003e, FOV\u0026thinsp;=\u0026thinsp;256 x 256 mm\u003csup\u003e2\u003c/sup\u003e, AP phase-encoding, bandwidth 240 Hz/Px). The slices were oriented sagittal, and the acquisition was performed in ascending order.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003efMRI pre-processing\u003c/h2\u003e \u003cp\u003eThe pre-processing and statistical analysis of the fMRI data was performed using the statistical parametric mapping software (SPM12, Wellcome Department of Imaging Neuroscience, University College London, London, UK) for Matlab. The initial six scans of each trial were discarded, to account for possible effects of magnetic saturation. Spatial correction of all images was performed on the first remaining data set to compensate for subject movement during the trial. The structural T2* EPI-MPRage image was normalized to a standard EPI template (MNI brain) using a 12-parameter affine transformation with additional nonlinear components.\u003c/p\u003e \u003cp\u003eFor quality control, the movement parameters of the test subjects were checked for movement artifacts. A single run was excluded in the case of an abrupt translational movement of more than 2 mm and \u0026gt;\u0026thinsp;2\u0026deg; in rotational movements. Here, strong movements were excluded, which have a negative influence on the accuracy of the localization of neuronal activations.\u003c/p\u003e \u003cp\u003eIn addition, the normalization was checked for plausibility and the occurrence of artefacts such as ghost artefacts.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003efMRI first level processing\u003c/h2\u003e \u003cp\u003eFirst level analyses of mean activation during cued and uncued blocks were computed for each participant in SPM12. For modelling the experimental conditions (cued and uncued) a general linear model (GLM) was used. The resulting contrast images of all participants were included in a second-level analysis to identify differences between the paradigm versions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003efMRI second level processing\u003c/h2\u003e \u003cp\u003eAs recommended for crossover studies flexible factorial models were used for both within-subject analyses (period and paradigm version) and between-subject analyses, as well as for the interaction of version*period in order to asses sequence effects[9].\u003c/p\u003e \u003cp\u003eA cluster-extent corrected threshold of familywise error (FWE) of pFWE \u0026lt; .05 was set as the statistical threshold for all analyses.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eSample characteristics\u003c/h2\u003e \u003cp\u003eThe sample characteristics and sociodemographic data of the \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;20 healthy participants are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, as well as the results of the psychometric questionnaires.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eSample characteristics\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuestionnaire\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMinimum [possible min]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMaximum [possible max]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCut-off\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.05 (10.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW:M 12:8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOGS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.25 (0.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 [0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 [20]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5 pathological\u003c/p\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2 problematic\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGUQ mean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.17 (0.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 [1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 [6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGBQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.15 (0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 [7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 [1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean cognitive distortion\u0026thinsp;\u0026lt;\u0026thinsp;4.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDesire scale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.20 (0.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 [1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 [11]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntention scale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.30 (0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 [1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 [11]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative Feelings scale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.20 (0.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 [1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 [11]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive expectation scale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.70 (1.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 [1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 [11]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbstinence intention scale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.00 (4.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 [11]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 [11]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRealism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.58 (2.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 [1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 [1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFTND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 [0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 [10]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.30 (6.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 [0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21 [63]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;13 mild, \u0026gt;\u0026thinsp;19 moderate,\u003c/p\u003e \u003cp\u003e\u0026gt;\u0026thinsp;25 severe\u003c/p\u003e\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSTAI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.05 (9.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 [20]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60 [80]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;39\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBIS AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.85 (2.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 [8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20 [32]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBIS MI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.00 (2.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 [11]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25 [44]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBIS NI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.43 (2.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 [11]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23 [44]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBIS total\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.29 (3.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 [34]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61 [136]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSPSRQ punishment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.00 (3.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 [0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 [24]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSPSRQ reward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.10 (4.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 [0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 [24]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSPSRQ total\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.10 (6.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 [0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32 [48]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eSample characteristics and psychometric data of the participants. \u003cem\u003en\u0026thinsp;=\u0026thinsp;20;\u003c/em\u003e Item Realism: n\u0026thinsp;=\u0026thinsp;19; GBQ: inverse scale. GUQ: Gambling Urge Questionnaire, FTND: Fagerstr\u0026oslash;m Test for Nicotine Dependence, BDI: Beck Depression Inventory, BIS: Baratt Impulsiveness Scale, AI: Attentional Impulsiveness, MI: Motor Impulsiveness, NI: Nonplanning Impulsiveness, SPSRQ: Sensitivity to Punishment and Reward Questionnaire\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eEffect of win-contingent cues on decision-making\u003c/h2\u003e \u003cp\u003eAcross both task versions, participants showed comparable rates of high-risk choices and rational decisions, with no significant main effects of win-contingent audiovisual cues or cue-by-order interactions on behavioral outcomes.​\u003c/p\u003e \u003cp\u003eThe proportion of high-risk choices did not differ between the cued and uncued versions, neither across all trials nor in trials with an ambiguous expected value ratio (EVR\u0026thinsp;=\u0026thinsp;0). Likewise, the frequency of rational versus irrational choices was comparable between versions, and no significant interaction with task order emerged (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e in Supplementary material).​\u003c/p\u003e \u003cp\u003eParticipants frequently chose options that did not maximize expected value in both task versions, which is consistent with previous reports of suboptimal EV-based choices in gambling-like tasks among healthy individuals.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eEffects of task version and task order on decision-making behavior during virtual gambling\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDependent variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSignificance \u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTask version\u003c/p\u003e \u003cp\u003e(cued versus uncued)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh-risk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.929\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh-risk EVR\u0026thinsp;=\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.860\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRational\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.066\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTask period\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh-risk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.039\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh-risk EVR\u0026thinsp;=\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.133\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRational\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eInteraction task version x period\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh-risk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh-risk EVR\u0026thinsp;=\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.646\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRational\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.991\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.055\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eThe task version and task period showed no significant effect on the occurrence of high-risk or rational decisions. GLM univariate, sample size n\u0026thinsp;=\u0026thinsp;19, EVR\u0026thinsp;=\u0026thinsp;0: EV ratio\u0026thinsp;=\u0026thinsp;0, thus favoring neither of the two winning options, rational: choice of the option conforming to the expected value; task order\u0026thinsp;=\u0026thinsp;order in which the game versions were played\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eNeural response during the feedback phase of cued versus uncued trials\u003c/h2\u003e \u003cp\u003eAs a reference for the following differences for the paradigm versions, we investigated the neural activation patterns during the uncued paradigm version. In the uncued version, wins (vs. losses and near wins) elicited increased activation in the hippocampi, superior parietal and frontal regions, insula and thalamus, consistent with robust engagement of memory, attentional and salience networks during rewarding outcomes (Flexible factorial model, contrast: win\u0026thinsp;\u0026gt;\u0026thinsp;loss\u0026thinsp;+\u0026thinsp;near win in the uncued paradigm version, p \u0026lt; .001, cluster-extent corrected pFWE \u0026lt; .05, n\u0026thinsp;=\u0026thinsp;19, see Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;3).\u003c/p\u003e \u003cp\u003eComparing the cued an uncued paradigm versions with the aforementioned uncued paradigm as the baseline, we computed multiple contrasts to investigate the influence of win-contingent audiovisual cues on neural activation patterns.\u003c/p\u003e \u003cp\u003eRegarding win\u0026thinsp;\u0026gt;\u0026thinsp;loss\u0026thinsp;+\u0026thinsp;near win, this contrast showed no significant additional neural activations in the cued version compared to the uncued trial (Flexible factorial model, contrast: win\u0026thinsp;\u0026gt;\u0026thinsp;loss\u0026thinsp;+\u0026thinsp;near win in the cued\u0026thinsp;\u0026gt;\u0026thinsp;uncued paradigm, p \u0026lt; .001, cluster-extent corrected pFWE \u0026lt; .05, n\u0026thinsp;=\u0026thinsp;19).\u003c/p\u003e \u003cp\u003eWhen directly contrasting the brain activation patterns during the cued task version to the uncued task we revealed higher brain activation for the cued version. Compared to the reference (the uncued trial), less brain activation was found in the superior temporal lobe, the right thalamus cuneus and left precuneus and both inferior parietal lobules when comparing the uncued version to the cued version. Regions that were found in both the reference and this contrast were both hippocampi, the insula and superior frontal gyri (flexible factorial model, contrast: win\u0026thinsp;\u0026gt;\u0026thinsp;loss\u0026thinsp;+\u0026thinsp;near-win for cued\u0026thinsp;\u0026lt;\u0026thinsp;uncued trial, p \u0026lt; .001, cluster-extent corrected pFWE\u0026thinsp;\u0026lt;\u0026thinsp;0.05, n\u0026thinsp;=\u0026thinsp;19, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;3).\u003c/p\u003e \u003cp\u003eFor rational choices, a similar pattern emerged, with significantly less activation in thalamic, temporal, occipital and parietal cortices in rational decision for win\u0026thinsp;\u0026gt;\u0026thinsp;loss\u0026thinsp;+\u0026thinsp;near win in uncued compared to cued trials. Regions corresponding with the reference were hippocampal and insular cortices as well as the right lingual gyrus (Flexible factorial model, contrast: win\u0026thinsp;\u0026gt;\u0026thinsp;loss\u0026thinsp;+\u0026thinsp;near win in the cued\u0026thinsp;\u0026lt;\u0026thinsp;uncued paradigm version for rational decisions, p \u0026lt; .001, cluster-extent corrected pFWE \u0026lt; .05, n\u0026thinsp;=\u0026thinsp;19, see Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;3).\u003c/p\u003e \u003cp\u003eFor rational versus irrational decisions, the cued trial showed no higher neuronal activation in the trial with audiovisual cues for win\u0026thinsp;\u0026gt;\u0026thinsp;loss\u0026thinsp;+\u0026thinsp;near win in comparison to the trial without stimuli (flexible factorial model, contrast: win\u0026thinsp;\u0026gt;\u0026thinsp;loss\u0026thinsp;+\u0026thinsp;near win for cued\u0026thinsp;\u0026gt;\u0026thinsp;uncued trial for rational decisions, p \u0026lt; .001, cluster-extent corrected pFWE\u0026thinsp;\u0026lt;\u0026thinsp;0.05, n\u0026thinsp;=\u0026thinsp;19).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eNeural activation patterns in the feedback phase\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eReference: Neural activation patterns win\u0026thinsp;\u0026gt;\u0026thinsp;loss\u0026thinsp;+\u0026thinsp;near win in the uncued paradigm version\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCluster size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003et\u003csub\u003emax\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eMNI coordinates [x, y, z]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBrain structure\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeft hippocampus, parahippocampal gyrus, fusiform gyrus\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4386\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeft superior parietal lobule, superior frontal gyrus, precentral gyrus, inferior parietal lobule, supramarginal gyrus, middle frontal gyrus\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRight olfactory cortex, superior frontal orbitofrontal cortex, insula, parahippocampal gyrus, gyrus rectus, inferior frontal orbitofrontal cortex\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e968\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRight hippocampus, thalamus, parahippocampal gyrus\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeft cuneus, calcarine cortex, right superior occipital gyrus, lingual gyrus\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRight middle frontal gyrus, precentral gyrus, superior frontal gyrus\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeft superior occipital gyrus, calcarine cortex, middle occipital gyrus\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eNeural activation patterns win\u0026thinsp;\u0026gt;\u0026thinsp;loss\u0026thinsp;+\u0026thinsp;near win in the cued\u0026thinsp;\u0026lt;\u0026thinsp;uncued paradigm version\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1949\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeft hippocampus, fusiform gyrus, superior temporal gyrus, inferior frontal gyrus, opercular part, right thalamus, vermis\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeft middle occipital gyrus, cuneus, cerebellum, right hippocampus, cerebellum, cuneus\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1755\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRight inferior parietal lobule, cuneus, paracentral lobule, middle cingulate gyrus, middle occipital gyrus, lingual gyrus\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeft precuneus, inferior parietal lobule, postcentral gyrus, superior parietal lobule\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e748\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRight amygdala, precentral gyrus, insula, rolandic operculum, superior temporal pole, inferior frontal gyrus, opercular part\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e335\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeft anterior cingulate gyrus, middle cingulate gyrus, right anterior cingulate gyrus, middle cingulate gyrus, superior frontal gyrus\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eNeural activation patterns win\u0026thinsp;\u0026gt;\u0026thinsp;loss\u0026thinsp;+\u0026thinsp;near win in the cued\u0026thinsp;\u0026lt;\u0026thinsp;uncued paradigm version\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRight hippocampus, cerebellum, left cerebellum, vermis\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e949\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeft hippocampus, fusiform gyrus, cerebellum, thalamus, right thalamus, vermis\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeft middle occipital gyrus, superior occipital gyrus, cuneus, right cuneus\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e478\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRight amygdala, inferior frontal gyrus, opercular part, superior temporal pole, insula\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRight cuneus, lingual gyrus\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e537\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeft superior temporal gyrus, superior temporal pole, inferior frontal gyrus, opercular part, middle temporal gyrus, insula\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRight precuneus\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eSignificant neural activation patterns, Flexible factorial model, contrasts: win\u0026thinsp;\u0026gt;\u0026thinsp;loss\u0026thinsp;+\u0026thinsp;near win in the uncued paradigm version, win\u0026thinsp;\u0026gt;\u0026thinsp;loss\u0026thinsp;+\u0026thinsp;near win in the cued\u0026thinsp;\u0026lt;\u0026thinsp;uncued paradigm version, win\u0026thinsp;\u0026gt;\u0026thinsp;loss\u0026thinsp;+\u0026thinsp;near win in the cued\u0026thinsp;\u0026lt;\u0026thinsp;uncued paradigm version for rational decisions, p \u0026lt; .001, cluster-extent corrected pFWE \u0026lt; .05, n\u0026thinsp;=\u0026thinsp;19\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003eNeural activation patterns in the feedback phase\u003c/h2\u003e \u003cp\u003e \u003cdiv description=\"\" class=\"Drawing\" id=\"216965616\" name=\"Grafik 6\"\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDepiction of the neural activation patterns, the scale represents the gradation of the t-values.\u003c/p\u003e \u003cp\u003eFlexible factorial model, contrasts: a. win\u0026thinsp;\u0026gt;\u0026thinsp;loss\u0026thinsp;+\u0026thinsp;near win in the uncued paradigm version, b. win\u0026thinsp;\u0026gt;\u0026thinsp;loss\u0026thinsp;+\u0026thinsp;near win in the cued\u0026thinsp;\u0026lt;\u0026thinsp;uncued paradigm version, c. win\u0026thinsp;\u0026gt;\u0026thinsp;loss\u0026thinsp;+\u0026thinsp;near win in the cued\u0026thinsp;\u0026lt;\u0026thinsp;uncued paradigm version for rational decisions, p \u0026lt; .001, cluster-extent corrected pFWE \u0026lt; .05, n\u0026thinsp;=\u0026thinsp;19\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eNeural response during the decision phase of cued versus uncued trials\u003c/h2\u003e \u003cp\u003eAs a reference for the comparison between neural activation during high-risk versus low-risk trials, we investigated the neural response during the uncued paradigm version. During the decision phase, high-risk (vs. low-risk) choices in the uncued version engaged frontoparietal and occipital regions, including right angular gyrus, insula, cuneus and bilateral frontal areas (flexible factorial model, contrast: high-risk\u0026thinsp;\u0026gt;\u0026thinsp;low-risk for uncued trial, p \u0026lt;. 001, cluster-extent corrected pFWE\u0026thinsp;\u0026lt;\u0026thinsp;0.05, n\u0026thinsp;=\u0026thinsp;19, see Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Fig.\u0026nbsp;4).\u003c/p\u003e \u003cp\u003eDirect comparisons between cued and uncued versions for high-risk versus low-risk decisions, both across all trials and restricted to rational decisions, revealed no significant differences in neural activation at the predefined threshold (flexible factorial model, contrast: high-risk\u0026thinsp;\u0026gt;\u0026thinsp;low-risk and high-risk\u0026thinsp;\u0026lt;\u0026thinsp;low-risk for cued\u0026thinsp;\u0026lt;\u0026thinsp;uncued and cued\u0026thinsp;\u0026gt;\u0026thinsp;uncued trial p \u0026lt; .001, cluster-extent corrected pFWE\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eWhen comparing rational versus irrational decisions with the uncued version as a reference, the cued trial showed more activation in the precuneus on both sides, right supramarginal cortex, lingula, left and right medial frontal lobe, right putamen (flexible factorial model, contrast: high-risk\u0026thinsp;\u0026gt;\u0026thinsp;low-risk for cued\u0026thinsp;\u0026gt;\u0026thinsp;uncued trial for rational decisions, p \u0026lt; .001, cluster-extent corrected pFWE\u0026thinsp;\u0026lt;\u0026thinsp;0.05, n\u0026thinsp;=\u0026thinsp;19, see Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Fig.\u0026nbsp;4).\u003c/p\u003e \u003cp\u003eIn contrast, significantly higher neuronal activation was found in the uncued trial in the right lingula, bilateral frontal lobe, the left superior temporal, right gyrus pre- and postcentralis (flexible factorial model, contrast: high-risk\u0026thinsp;\u0026gt;\u0026thinsp;low-risk for cued\u0026thinsp;\u0026lt;\u0026thinsp;uncued trial for rational decisions, p \u0026lt; .001, cluster-extent corrected pFWE\u0026thinsp;\u0026lt;\u0026thinsp;0.05, n\u0026thinsp;=\u0026thinsp;19, see Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Fig.\u0026nbsp;4).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eNeural activation patterns in the decision phase\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eReference: Neural activation patterns high-risk\u0026thinsp;\u0026gt;\u0026thinsp;low-risk in the uncued paradigm version\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCluster size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003et\u003csub\u003emax\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eMNI coordinates [x, y, z]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBrain structure\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRight angular gyrus, middle temporal gyrus, middle occipital gyrus\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRight olfactory cortex, superior frontal gyrus, orbital part, middle frontal gyrus, orbital part, insula\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e490\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRight cuneus, superior occipital gyrus, lingual gyrus\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e291\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeft middle frontal gyrus, supplementary motor area, superior frontal gyrus, precentral gyrus\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeft inferior parietal lobule, superior parietal lobule\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeft middle frontal gyrus, superior frontal gyrus\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eNeural activation patterns high-risk\u0026thinsp;\u0026gt;\u0026thinsp;low-risk in the cued\u0026thinsp;\u0026gt;\u0026thinsp;uncued paradigm version for rational decisions\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRight superior frontal gyrus, orbital part and medial part\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eNeural activation patterns high-risk\u0026thinsp;\u0026gt;\u0026thinsp;low-risk in the cued\u0026thinsp;\u0026lt;\u0026thinsp;uncued paradigm version for rational decisions\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e418\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRight superior temporal gyrus, inferior temporal gyrus, middle temporal gyrus\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRight superior parietal lobule, superior frontal gyrus, postcentral gyrus, supplementary motor area, precentral gyrus, left precentral gyrus\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e844\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRight supramarginal gyrus, precentral gyrus, insula\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeft superior and medial frontal gyrus, orbital part, right superior and medial frontal gyrus, orbital part\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeft middle frontal gyrus, orbital part, superior temporal pole\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeft postcentral gyrus, inferior parietal lobule, precentral gyrus\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeft rolandic operculum, supramarginal gyrus, insula, superior temporal gyrus\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eSignificant neural activation patterns, Flexible factorial model, contrast: high-risk\u0026thinsp;\u0026gt;\u0026thinsp;low-risk in the uncued paradigm version, high-risk\u0026thinsp;\u0026gt;\u0026thinsp;low-risk in the cued\u0026thinsp;\u0026gt;\u0026thinsp;uncued paradigm version for rational decisions, high-risk\u0026thinsp;\u0026gt;\u0026thinsp;low-risk in the cued\u0026thinsp;\u0026lt;\u0026thinsp;uncued paradigm version for rational decisions, p \u0026lt; .001, cluster-extent corrected pFWE \u0026lt; .05, n\u0026thinsp;=\u0026thinsp;19\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eNeural activation patterns in the decision phase\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDepiction of the neural activation patterns, the scale represents the gradation of the t-values.\u003c/p\u003e \u003cp\u003eFlexible factorial model, contrast: a. high-risk\u0026thinsp;\u0026gt;\u0026thinsp;low-risk in the uncued paradigm version, b. high-risk\u0026thinsp;\u0026gt;\u0026thinsp;low-risk in the cued\u0026thinsp;\u0026gt;\u0026thinsp;uncued paradigm version for rational decisions, c. high-risk\u0026thinsp;\u0026gt;\u0026thinsp;low-risk in the cued\u0026thinsp;\u0026lt;\u0026thinsp;uncued paradigm version for rational decisions, p \u0026lt; .001, cluster-extent corrected pFWE \u0026lt; .05, n\u0026thinsp;=\u0026thinsp;19\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this pilot study, win-contingent audiovisual cues did not significantly alter the proportion of high-risk choices or rational versus irrational decisions in healthy volunteers. Behavioral performance was comparable between cued and uncued versions across trials with advantageous, disadvantageous and ambiguous expected values.\u003c/p\u003e \u003cp\u003eParticipants frequently selected options that did not maximize expected value, irrespective of cue condition, which aligns with previous work showing that healthy individuals often deviate from strict EV‑maximizing strategies in gambling‑like tasks.\u003c/p\u003e \u003cp\u003eIn line with previous studies, such as those by [17] and [4], there were also no significant effects of audiovisual stimuli on risk assessment and decision-making in healthy individuals. Similarly in another study investigating our paradigm using eye tracking, while no differences in risky decision-making were found [2], the cued paradigm version showed significant deviations of visual attention. A comparable study by [26] found significant effects of audiovisual stimuli on high-risk decisions in a large sample. As the statistically significant effect could be determined with the larger sample size, it is possible that we were unable to see a significant effect due to the small number of test subjects. Further studies with a larger number of participants and realistic gambling simulations are needed to be able to depict even small effect sizes.\u003c/p\u003e \u003cp\u003eWhile the parallelization of the paradigm versions ensures a similarity in the versions for a more accurate data analysis, it may also make it more difficult to find differences. So not enough visual differences between the cued and uncued paradigm version could lessen the effect of audiovisual stimuli on decision-making.\u003c/p\u003e \u003cp\u003eOverall, it can therefore be said that the current study situation does not yet provide sufficient evidence to support the hypothesis that win contingency audiovisual stimuli cause more frequent risk-taking decisions in healthy test subjects. This task may be better suited to differentiate between the groups of healthy individuals and individuals with GD, as shown by [2].\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003eFeedback Phase: Difference in neuronal activation patterns with and without audiovisual stimuli\u003c/h2\u003e \u003cp\u003eAt the neural level, wins in the uncued condition elicited robust activation in hippocampal, parietal, frontal, occipital and insular regions, reflecting the engagement of memory, attentional and salience networks during outcome processing.​ This is supported by prior research that showed that the presentation of gambling-associated stimuli, as well as near wins in people with GD, induced robust insula activation (Clark et al., 2014; Naqvi \u0026amp; Bechara, 2009)[7, 14]. While these studies found stronger insular activation in people with GD, not healthy individuals, Tsurumi et al found that in a high-risk gambling task, the subgroup of risk seeking healthy individuals showed less activation in the insula compared to the risk avoiding subgroup [28].\u003c/p\u003e \u003cp\u003eThe relative attenuation of activation in hippocampi, insula, superior parietal and occipital cortices, as well as anterior cingulate and amygdala, during cued compared with uncued win feedback suggests that win-contingent audiovisual cues may partially replace internal evaluative and monitoring processes by providing externally generated sensory feedback.​ While insular activation was shown to reflect risk anticipation [21], less activation may indicate less risk anticipation during cued trials, therefore showing the effectiveness of win-contingent cues.\u003c/p\u003e \u003cp\u003eThe fact that a similar pattern was observed specifically for rational decisions indicates that cue-related modulation of outcome processing occurs even when participants choose the option with higher expected value, pointing to a dissociation between neural encoding of outcomes and overt decision quality.\u003c/p\u003e \u003cp\u003eDuring the feedback phase of the paradigm version with win-contingent cues, we observed lower activation in the insula and the superior parietal lobe. In cued versus uncued trials, there was less activation in the insula and the superior parietal lobe, during both during all decisions and rational choices.\u003c/p\u003e \u003cp\u003eWith decreased activation of the insula in rational choices in cued trials, it can be concluded that audiovisual stimuli influence neuronal activation in rational decision-making, and potentially reduce loss avoidance. Further research on whether audiovisual cues may reduce loss aversion in healthy subjects is needed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003eDecision phase: effect of audiovisual stimuli on neural activation\u003c/h2\u003e \u003cp\u003eThe absence of robust cue‑related differences in decision‑phase activation mirrors the behavioral findings, suggesting that, under the present conditions, win‑contingent cues modulate outcome processing more strongly than the neural implementation of choice itself.\u003c/p\u003e \u003cp\u003eThe engagement of frontoparietal and occipital regions during high‑ versus low‑risk decisions in the uncued version is consistent with prior work implicating these networks in risk evaluation, attention and action selection [6, 8, 16, 23, 30].\u003c/p\u003e \u003cp\u003eThe absence of robust cue‑related differences in decision‑phase activation mirrors the behavioral findings, suggesting that, under the present conditions, win‑contingent cues modulate outcome processing more strongly than the neural implementation of choice itself.\u003c/p\u003e \u003cp\u003eThe reduced insular and superior parietal activation in cued versus uncued trials may indicate a shift from internally driven risk and loss monitoring towards externally driven, cue‑based feedback processing. In healthy individuals, this attenuation may be compensated by intact cognitive control, preventing overt increases in risk‑taking despite altered neural responses. In individuals with or at risk for gambling disorder, such a shift might contribute to diminished sensitivity to losses and near losses, and thereby to the persistence of gambling behavior in the presence of adverse outcomes. Longitudinal and case\u0026ndash;control studies using similar paradigms are needed to test whether the neural patterns observed here in healthy volunteers represent early vulnerability markers for GD.\u003c/p\u003e \u003c/div\u003e"},{"header":"Limitations","content":"\u003cp\u003eAlthough the present study provides further insight into the neural processing of gain-contingent audiovisual stimuli, some limitations need to be addressed.\u003c/p\u003e \u003cp\u003eThe present study examined a young, inexperienced sample of participants, comparable to those in similar studies, but not representative of the general population. Due to the limited sample size and the absence of subjects with GD, the results are only transferable to this group to a limited extent. The study used a cross-over design, which increased the power, but further studies with a larger sample are required for smaller effects, especially for risky decision-making. The virtual gambling paradigm was perceived as realistic, but the results are limited due to the limitations of immersion in an MRI scanner. The pseudo-randomization of the gambling process enabled us to depict the \u0026ldquo;oversampling\u0026rdquo; of winnings at the beginning of a game but limits the significance of the results, especially for the second trial run.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eWhile this study shows effects of win-contingent audiovisual stimuli on neuronal activities during gambling in healthy individuals, no behavioral change could be observed, likely due to the intact behavioral control and conscious reflection of the choices made during the gambling paradigm.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe authors did not receive support from any organization for the submitted work.\u003c/p\u003e\n\u003cp\u003eThe authors have no competing interests to declare that are relevant to the content of this article.\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Lisa Jil Krause, Patrick Bach and Ronald Fischer. The first draft of the manuscript was written by Lisa Jil Krause, revised by Patrick Bach and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAmerican Psychiatric Association (2013) Diagnostic and statistical manual of mental disorders : Dsm-5. American Psychiatric Association, Arlington, VA\u003c/li\u003e\n\u003cli\u003eBaumann G, Fischer R, Reinhard I, Hoffmann S, Kiefer F, Lem\u0026eacute;nager T, Bach P (2025) Investigating decision-making under risk in pathological gambling using a virtual slot machine: A pilot eye-tracking study. Eur Addict Res 31:308-324\u003c/li\u003e\n\u003cli\u003eBeesdo-Baum K, First MB (2019) Scid-5-pd: Strukturiertes klinisches interview f\u0026uuml;r dsm-5 pers\u0026ouml;nlichkeitsst\u0026ouml;rungen : Deutsche bearbeitung des structured clinical interview for dsm-5\u0026reg; - personality disorders von michael b. First, janet b.W. Wiliams, lorna smith benjamin, robert l. Spitzer : Manual. Hogrefe\u003c/li\u003e\n\u003cli\u003eCherkasova MV, Clark L, Barton JJS, Schulzer M, Shafiee M, Kingstone A, Stoessl AJ, Winstanley CA (2018) Win-concurrent sensory cues can promote riskier choice. The Journal of Neuroscience 38:10362-10370\u003c/li\u003e\n\u003cli\u003eClark L, Boileau I, Zack M (2019) Neuroimaging of reward mechanisms in gambling disorder: An integrative review. Mol Psychiatry 24:674-693\u003c/li\u003e\n\u003cli\u003eCrockford DN, Goodyear B, Edwards J, Quickfall J, el-Guebaly N (2005) Cue-induced brain activity in pathological gamblers. Biol Psychiatry 58:787-795\u003c/li\u003e\n\u003cli\u003eFauth-B\u0026uuml;hler M, Zois E, Vollst\u0026auml;dt-Klein S, Lemenager T, Beutel M, Mann K (2014) Insula and striatum activity in effort-related monetary reward processing in gambling disorder: The role of depressive symptomatology. Neuroimage Clin 6:243-251\u003c/li\u003e\n\u003cli\u003eGelskov SV, Madsen KH, Rams\u0026oslash;y TZ, Siebner HR (2016) Aberrant neural signatures of decision-making: Pathological gamblers display cortico-striatal hypersensitivity to extreme gambles. NeuroImage 128:342-352\u003c/li\u003e\n\u003cli\u003eGl\u0026auml;scher J, Gitelman D (2008) Contrast weights in flexible factorial design with multiple groups of subjects. \u003c/li\u003e\n\u003cli\u003eGoodie AS, MacKillop J, Miller JD, Fortune EE, Maples J, Lance CE, Campbell WK (2013) Evaluating the south oaks gambling screen with dsm-iv and dsm-5 criteria:Results from a diverse community sample of gamblers. Assessment 20:523-531\u003c/li\u003e\n\u003cli\u003eGriffiths M (1993) Fruit machine gambling: The importance of structural characteristics. Journal of Gambling Studies 9:101-120\u003c/li\u003e\n\u003cli\u003eKiefer F, Fauth-Buhler M, Heinz A, Mann K (2013) [neurobiology of behavioral addictions]. Nervenarzt 84:557-562\u003c/li\u003e\n\u003cli\u003eKlar J, Slotboom J, Lerch S, Koenig J, Wiest R, Kaess M, Kindler J (2024) Higher striatal glutamate in male youth with internet gaming disorder. Eur Arch Psychiatry Clin Neurosci 274:301-309\u003c/li\u003e\n\u003cli\u003eLimbrick-Oldfield EH, Mick I, Cocks RE, McGonigle J, Sharman SP, Goldstone AP, Stokes PR, Waldman A, Erritzoe D, Bowden-Jones H, Nutt D, Lingford-Hughes A, Clark L (2017) Neural substrates of cue reactivity and craving in gambling disorder. Transl Psychiatry 7:e992\u003c/li\u003e\n\u003cli\u003eLinnet J (2020) The anticipatory dopamine response in addiction: A common neurobiological underpinning of gambling disorder and substance use disorder? Prog Neuropsychopharmacol Biol Psychiatry 98:109802\u003c/li\u003e\n\u003cli\u003eLiu G-C, Yen J-Y, Chen C-Y, Yen C-F, Chen C-S, Lin W-C, Ko C-H (2014) Brain activation for response inhibition under gaming cue distraction in internet gaming disorder. The Kaohsiung Journal of Medical Sciences 30:43-51\u003c/li\u003e\n\u003cli\u003eMiedl SF, Fehr T, Meyer G, Herrmann M (2010) Neurobiological correlates of problem gambling in a quasi-realistic blackjack scenario as revealed by fmri. Psychiatry Res 181:165-173\u003c/li\u003e\n\u003cli\u003eMoeller S, Yacoub E, Olman CA, Auerbach E, Strupp J, Harel N, Ugurbil K (2010) Multiband multislice ge-epi at 7 tesla, with 16-fold acceleration using partial parallel imaging with application to high spatial and temporal whole-brain fmri. Magn Reson Med 63:1144-1153\u003c/li\u003e\n\u003cli\u003eMoritz S, Gehlenborg J, Bierbrodt J, Wittekind C, B\u0026uuml;cker L (2020) A ghost in the machine? The predictive role of metacognitive beliefs, cognitive biases, and machine-related features in the severity of problematic slot machine gambling. Personality and Individual Differences 171:110539\u003c/li\u003e\n\u003cli\u003ePotenza MN, Balodis IM, Derevensky J, Grant JE, Petry NM, Verdejo-Garcia A, Yip SW (2019) Gambling disorder. Nat Rev Dis Primers 5:51\u003c/li\u003e\n\u003cli\u003ePreuschoff K, Quartz SR, Bossaerts P (2008) Human insula activation reflects risk prediction errors as well as risk. The Journal of Neuroscience 28:2745-2752\u003c/li\u003e\n\u003cli\u003eRomanczuk-Seiferth N, M\u0026ouml;rsen C, Heinz A (2016) Impulskontrollst\u0026ouml;rungen/verhaltenss\u0026uuml;chte. \u0026Uuml;bersichten. Pathologisches gl\u0026uuml;cksspiel und delinquenz. Pathological gambling and delinquency. Forensische Psychiatrie, Psychologie, Kriminologie 10\u003c/li\u003e\n\u003cli\u003eSeitz R (2011) Medialer frontalkortex und subjektive verhaltenskontrolle. e-Neuroforum 17\u003c/li\u003e\n\u003cli\u003eSetsompop K, Gagoski BA, Polimeni JR, Witzel T, Wedeen VJ, Wald LL (2012) Blipped-controlled aliasing in parallel imaging for simultaneous multislice echo planar imaging with reduced g-factor penalty. Magn Reson Med 67:1210-1224\u003c/li\u003e\n\u003cli\u003eSharp ME, Viswanathan J, Lanyon LJ, Barton JJ (2012) Sensitivity and bias in decision-making under risk: Evaluating the perception of reward, its probability and value. PLoS One 7:e33460\u003c/li\u003e\n\u003cli\u003eSpetch ML, Madan CR, Liu YS, Ludvig EA (2020) Effects of winning cues and relative payout on choice between simulated slot machines. Addiction 115:1719-1727\u003c/li\u003e\n\u003cli\u003eSteenbergh TA, Meyers AW, May RK, Whelan JP (2002) Development and validation of the gamblers\u0026apos; beliefs questionnaire. Psychol Addict Behav 16:143-149\u003c/li\u003e\n\u003cli\u003eTsurumi K, Kawada R, Yokoyama N, Sugihara G, Sawamoto N, Aso T, Fukuyama H, Murai T, Takahashi H (2014) Insular activation during reward anticipation reflects duration of illness in abstinent pathological gamblers. Frontiers in Psychology 5\u003c/li\u003e\n\u003cli\u003evan Holst RJ, van den Brink W, Veltman DJ, Goudriaan AE (2010) Brain imaging studies in pathological gambling. Curr Psychiatry Rep 12:418-425\u003c/li\u003e\n\u003cli\u003eWang P, Chen S, Deng K, Zhang B, Im H, Feng J, Liu L, Yang Q, Zhao G, He Q, Chen C, Wang H, Wang Q (2023) Distributed attribute representation in the superior parietal lobe during probabilistic decision‐making. Human Brain Mapping 44:5693-5711\u003c/li\u003e\n\u003cli\u003eWinstanley CA, Hynes TJ (2021) Clueless about cues: The impact of reward-paired cues on decision making under uncertainty. Current Opinion in Behavioral Sciences 41:167-174\u003c/li\u003e\n\u003cli\u003eWorld Health Organization (2018) International classification of diseases for mortality and morbidity statistics (11th revision). \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"FMRI, Pathological gambling, decision-making, win-contingent cues","lastPublishedDoi":"10.21203/rs.3.rs-9001151/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9001151/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRationale: Over the last 30 years, the global incidence and prevalence of gambling disorder (GD) have risen, with particularly high risk associated with slot machine gambling. Win‑contingent audiovisual stimuli are considered a key mechanism that may promote risky decision-making during gambling. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eObjectives: This study aimed to investigate whether win‑conting­­ent audiovisual cues modulate risky decision-making and neural responses during a virtual slot-machine task in healthy volunteers. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMethods: In a randomized cross-over design, N = 20 right-handed healthy volunteers completed a virtual slot-machine paradigm with and without win-contingent audiovisual cues. We compared risky versus safe choices and rational versus irrational decisions and examined differential fMRI (functional magnetic resonance imaging) activation during decision and feedback phases using flexible factorial models. This study was pre-registered in the German clinical trials database: DRKS00021178 on 03.04.2020. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResults: Win‑contingent audiovisual cues did not significantly affect the frequency of high-risk versus low-risk choices or rational versus irrational decisions. In the feedback phase, wins (vs. losses and near wins) elicited robust activation in hippocampal, parietal, frontal and insular regions. Compared with the uncued version, the cued version was associated with reduced activation in temporal, thalamic, parietal and insular cortices during win feedback, particularly for rational decisions. \u0026nbsp;Conclusion: Win‑contingent audiovisual cues modulated neural responses to gambling outcomes in healthy individuals, but did not alter observable choice behavior, suggesting preserved cognitive control despite cue-induced changes in reward- and salience-related networks.\u003c/p\u003e","manuscriptTitle":"Neural processing of win-contingent audiovisual cues during virtual gambling: An fMRI cross-over study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-28 15:49:57","doi":"10.21203/rs.3.rs-9001151/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5cc96bed-a0b4-4e2c-8a67-d5455b7bb625","owner":[],"postedDate":"April 28th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-04T09:52:37+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-04T07:01:40+00:00","index":32,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T10:08:15+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-28 15:49:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9001151","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9001151","identity":"rs-9001151","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}