Introduction One in two cardiac patients fear having another heart event or their heart condition getting worse. Research in other chronic illnesses demonstrates that screening for fear of progression and recurrence is vital for adequately addressing such concerns in clinical care. The current project aims to develop and validate a measure for fear of progression and recurrence in cardiac patients. Methods The Fear of Cardiac Recurrence and Progression Scale (FCRP) will be developed through a multistep process. An initial item pool will be generated through a review of the literature and existing measures and consultation with and feedback from key informants. The item pool will be tested in a sample of over 250 adults who have ever had an acute coronary event, undergone cardiac surgery, or a chronic cardiac condition. Exploratory factor analysis will be used to identify the underlying factors, and Rasch analysis will be used to reduce the number of items. A short form version of the FCRP will be developed for use as a brief screening tool, informed by clinical relevance and Rasch psychometric indices. Discussion While many cardiac patients experience fears related to the progression or recurrence of their illness, there remains the need for a validated tool with which these concerns can be identified and measured. It is expected that the design and validation of the FCRP will aid identification of cardiac patients suffering from clinically significant levels of fear of progression and recurrence and facilitate the design of tailored psychological interventions to target these fears.

Substance use disorders (SUD) are chronic conditions with devastating effects on brain health, functioning, and survival. In this study, we compared brain morphometry of 2,782 individuals with SUD to 1,951 controls and assessed the topographic overlap of these differences with brain connectivity and receptor architecture. Across SUD, we identified a morphometric signature involving frontal, parietal, temporal and limbic systems that overlapped with cortical hub regions and harbored cortical and subcortical disease epicenters. Findings were highly consistent across six substances and numerous robustness and generalizability analyses. Transdiagnostic comparisons showed high spatial overlap of SUD epicenters with those of schizophrenia and bipolar disorder, suggesting shared network-constrained cortical differences. Finally, multivariate mapping revealed that SUD brain differences aligned with two neurotransmitter axes contrasting cannabinoid-opioid and dopaminergic systems. These findings indicate that addiction-related brain differences are shaped by connectome and neurotransmitter architecture, positioning brain network and neurochemical organization as key principles of SUD-related brain alterations.

Background:An emerging area of psycho-cardiology explores fear of disease progression in cardiac patients, following extensive research of this topic in psycho-oncology. Novel interventions that target cardiac fear of progression(FoP) may be valuable in bridging the gap between the high psychological support needs in cardiac care and limitations surrounding the efficacy of standard psychosocial treatments. However, there appears to be limited research characterizing FoP in cardiac patients with which to inform potential interventions.Aims:Using a mixed methods approach in two inter-related studies, we aimed to develop a preliminary conceptualization of cardiac-FoP.Methods:Study 1 involved a scoping review of existing qualitative research to identify the range of fears relating to disease progression reported by cardiac patients. Study 2 investigated the prevalence and distress levels associated with a selection of fears identified in Study 1 through a quantitative study of 194 cardiac patient admissions at two Australian hospitals.Results:Study 1 conceptualized cardiac-FoP in two ways, by the content of the fears and by the behavioral responses to the fears. Fears were categorized into seven broad domains: fears associated with death, health, interpersonal relationships, treatment, accessing help, role responsibilities, and physical activity. Five categories of behavioral responses were identified: avoidance, hyperawareness, symptom misattribution, seeking help, and lifestyle changes. Study 2 indicated a high prevalence of fear, with an average endorsement of 40.9%. When fear was endorsed, an average of 45.2% of cardiac patients experienced moderate-to-severe distress.Discussion:This paper provides an initial conceptualization of FoP in cardiac patients, providing preliminary evidence of the rates of fear and associated distress in this population. Drawing on this conceptualization, unique measurement tools and interventions should be developed to identify and address FoP in cardiac patients.

When we make a decision, we also estimate the probability that our choice is correct or accurate. This probability estimate is termed our degree of decision confidence. Recent work has reported event-related potential (ERP) correlates of confidence both during decision formation (the centro-parietal positivity component; CPP) and after a decision has been made (the error positivity component; Pe). However, there are several measurement confounds that complicate the interpretation of these findings. More recent studies that overcome these issues have so far produced conflicting results. To better characterise the ERP correlates of confidence we presented participants with a comparative brightness judgment task while recording electroencephalography. Participants judged which of two flickering squares (varying in luminance over time) was brighter on average. Participants then gave confidence ratings ranging from “surely incorrect” to “surely correct”. To elicit a range of confidence ratings we manipulated both the mean luminance difference between the brighter and darker squares (relative evidence) and the overall luminance of both squares (absolute evidence). We found larger CPP amplitudes in trials with higher confidence ratings. This association was not simply a by-product of differences in relative evidence (which covaries with confidence) across trials. We did not identify postdecisional ERP correlates of confidence, except when they were artificially produced by pre-response ERP baselines. These results provide further evidence for neural correlates of processes that inform confidence judgments during decision formation.

Adaptive behaviours depend on dynamically updating internal representations of the world based on the ever-changing environmental contingencies. People with a substance use disorder (pSUD) show maladaptive behaviours with high persistence in drug-taking, despite severe negative consequences. We recently proposed a salience misattribution model for addiction (SMMA; Kalhan et al. 2021), arguing that pSUD have aberrations in their updating processes where drug cues are misattributed as strong predictors of positive outcomes, but weaker predictors of negative outcomes. We also argued that conversely, non-drug cues are misattributed as weak predictors of positive outcomes, but stronger predictors of negative outcomes. We tested these hypotheses using a multi-cue reversal learning task, with reversals in whether drug or non-drug cues are relevant in predicting the outcome (monetary win or loss). We show that people with a tobacco use disorder (pTUD), do form misaligned internal representations. We found that pTUD updated less towards learning the drug cue’s relevance in predicting a loss. Further, when neither drug nor non-drug cue predicted a win, pTUD updated more towards the drug cue being relevant predictors of that win. Our Bayesian belief updating model revealed that pTUD had a low estimated likelihood of non-drug cues being predictors of wins, compared to drug cues, which drove the misaligned updating. Overall, several hypotheses of the SMMA were supported, but not all. Our results implicate that strengthening the non-drug cue association with positive outcomes may help restore the misaligned internal representation in pTUD, and offers a quantifiable, computational account of these updating processes.

IntroductionAmbulatory assessment of executive function - particularly in the form working memory (WM) - is increasingly common. Few studies to date, however, have also incorporated ambulatory measures of inhibitory control. Critically, the extended within-person reliability of ambulatory tasks tapping each of these constructs has been largely overlooked.MethodParticipants (N = 283, Mage = 23.74 years, SD = 9.04) received notifications every 3 days (for 4 weeks) to undertake ambulatory assessment versions of the n-Back and Stop-Signal Tasks (SST) via the smartphone application CheckCog. Within-person reliability of these measures was explored.ResultsCompliance ranged from 66% (for eight sessions) to 89% (for four sessions). Our results reveal significant changes in performance within the first two sessions for both the n-Back and SST, with performance remaining largely consistent across the remaining (two to eight) sessions. In terms of test-retest reliability, the ICC (C, 1) values ranged from .29 to .68 on the n-Back (with overall accuracy being .51) and .31-.73 on the SST (with stop-signal reaction time being .53).ConclusionThe results of the current study contribute to the literature by demonstrating the reliability of brief measures of executive function - in the form of inhibitory control and WM - delivered using smartphones in participants' natural environments. Based on our findings, the CheckCog app reliability tracks baseline systematic changes in WM and response inhibition across multiple time points and for an extended period in healthy individuals.

IntroductionThere are growing concerns about commonly inflated effect sizes in small neuroimaging studies, yet no study has addressed recalibrating effect size estimates for small samples. To tackle this issue, we propose a hierarchical Bayesian model to adjust the magnitude of single-study effect sizes while incorporating a tailored estimation of sampling variance.MethodsWe estimated the effect sizes of case-control differences on brain structural features between individuals who were dependent on alcohol, nicotine, cocaine, methamphetamine, or cannabis and non-dependent participants for 21 individual studies (Total cases: 903; Total controls: 996). Then, the study-specific effect sizes were modeled using a hierarchical Bayesian approach in which the parameters of the study-specific effect size distributions were sampled from a higher-order overarching distribution. The posterior distribution of the overarching and study-specific parameters was approximated using the Gibbs sampling method.ResultsThe results showed shrinkage of the posterior distribution of the study-specific estimates toward the overarching estimates given the original effect sizes observed in individual studies. Differences between the original effect sizes (i.e., Cohen's d) and the point estimate of the posterior distribution ranged from 0 to 0.97. The magnitude of adjustment was negatively correlated with the sample size (r = −0.27, p < 0.001) and positively correlated with empirically estimated sampling variance (r = 0.40, p < 0.001), suggesting studies with smaller samples and larger sampling variance tended to have greater adjustments.DiscussionOur findings demonstrate the utility of the hierarchical Bayesian model in recalibrating single-study effect sizes using information from similar studies. This suggests that Bayesian utilization of existing knowledge can be an effective alternative approach to improve the effect size estimation in individual studies, particularly for those with smaller samples.

Adaptive behaviours depend on dynamically updating internal representations of the world based on the ever-changing environmental contingencies. People with a substance use disorder (pSUD) show maladaptive behaviours with high persistence in drug-taking, despite severe negative consequences. We recently proposed a salience misattribution model for addiction (SMMA; Kalhan et al., (2021)), arguing that pSUD have aberrations in their updating processes where drug cues are misattributed as strong predictors of positive outcomes, but weaker predictors of negative outcomes. We also argue that conversely, non-drug cues are misattributed as weak predictors of positive outcomes, but stronger predictors of negative outcomes. However, these hypotheses need to be empirically tested. Here we used a multi-cue reversal learning task, with reversals in whether drug or non-drug cues are currently relevant in predicting the outcome (monetary win or loss). We show that compared to controls, people with a tobacco use disorder (pTUD), do form misaligned internal representations. We found that pTUD updated less towards learning the drug cue’s relevance in predicting a loss. Further, when neither drug nor non-drug cue predicted a win, pTUD updated more towards the drug cue being relevant predictors of that win. Our Bayesian belief updating model revealed that pTUD had a low estimated likelihood of non-drug cues being predictors of wins, compared to drug cues, which drove the misaligned updating. Overall, several hypotheses of the SMMA were supported, but not all. Our results implicate that strengthening the non-drug cue association with positive outcomes may help restore the misaligned internal representation in pTUD.

Neurocomputational accounts of psychosis propose mechanisms for how information is integrated into a predictive model of the world, in attempts to understand the occurrence of altered perceptual experiences. Conflicting Bayesian theories postulate aberrations in either top-down or bottom-up processing. The top-down theory predicts an overreliance on prior beliefs or expectations resulting in aberrant perceptual experiences, whereas the bottom-up theory predicts an overreliance on current sensory information, as aberrant salience is directed towards objectively uninformative stimuli. This study empirically adjudicates between these models. We use a perceptual decision-making task in a neurotypical population with varying degrees of psychotic-like experiences. Bayesian modelling was used to compute individuals' reliance on prior relative to sensory information. Across two datasets (discovery dataset n = 363; independent replication in validation dataset n = 782) we showed that psychotic-like experiences were associated with an overweighting of sensory information relative to prior expectations, which seem to be driven by decreased precision afforded to prior information. However, when prior information was more uncertain, participants with greater psychotic-like experiences encoded sensory information with greater noise. Greater psychotic-like experiences were associated with aberrant precision in the encoding both prior and likelihood information, which we suggest may be related to generally heightened perceptions of task instability. Our study lends empirical support to notions of both weaker bottom-up and weaker (rather than stronger) top-down perceptual processes, as well as aberrancies in belief updating that extend into the non-clinical continuum of psychosis.

Bayesian inference suggests that perception is inferred from a weighted integration of prior contextual beliefs with current sensory evidence (likelihood) about the world around us. The perceived precision or uncertainty associated with prior and likelihood information is used to guide perceptual decision making, such that more weight is placed on the source of information with greater precision. This provides a framework for understanding a spectrum of clinical transdiagnostic symptoms associated with aberrant perception, as well as individual differences in the general population. Whilst behavioural paradigms are commonly used to characterise individual differences in perception as a trait-like characteristic, measurement reliability in these behavioural tasks is rarely assessed. To remedy this gap, we empirically evaluate the reliability of a perceptual decision-making task that quantifies individual differences in Bayesian belief updating in terms of the relative precision weighting afforded to prior and likelihood information (i.e., sensory weight). We analysed data from participants (n = 37) who performed this task twice. We found that the precision afforded to prior and likelihood information showed high internal consistency and good test re-test reliability (ICC = 0.86, 95%CI[0.72, 0.93]) when averaged across participants, as well as at the individual level using hierarchical modelling. Our results provide support for the assumption that Bayesian belief updating operates as a stable, trait-like characteristic in perceptual decision making. We discuss the utility and applicability of reliable perceptual decision-making paradigms as a measure of individual differences in the general population, as well as a diagnostic tool in psychiatric research.

Emerging evidence suggests distinct neurobiological correlates of alcohol use disorder (AUD) between sexes, which however remain largely unexplored. This work from ENIGMA Addiction Working Group aimed to characterize the sex differences in gray matter (GM) and white matter (WM) correlates of AUD using a whole-brain, voxel-based, multi-tissue mega-analytic approach, thereby extending our recent surface-based region of interest findings on a nearly matching sample using a complementary methodological approach. T1-weighted magnetic resonance imaging (MRI) data from 653 people with AUD and 326 controls was analyzed using voxel-based morphometry. The effects of group, sex, group-by-sex, and substance use severity in AUD on brain volumes were assessed using General Linear Models. Individuals with AUD relative to controls had lower GM volume in striatal, thalamic, cerebellar, and widespread cortical clusters. Group-by-sex effects were found in cerebellar GM and WM volumes, which were more affected by AUD in females than males. Smaller group-by-sex effects were also found in frontotemporal WM tracts, which were more affected in AUD females, and in temporo-occipital and midcingulate GM volumes, which were more affected in AUD males. AUD females but not males showed a negative association between monthly drinks and precentral GM volume. Our results suggest that AUD is associated with both shared and distinct widespread effects on GM and WM volumes in females and males. This evidence advances our previous region of interest knowledge, supporting the usefulness of adopting an exploratory perspective and the need to include sex as a relevant moderator variable in AUD.

Background Cannabis is the third most commonly used drug worldwide, with studies suggesting a deleterious effect on some aspects of performance monitoring. It is unknown, however, whether diminished error awareness influences adaptive behaviour in cannabis users. Therefore, this study examined the effect of error awareness on learning from errors in cannabis users. Methods Thirty-six chronic cannabis users (Mage = 23.81 years; female, 36%) and 34 controls (Mage = 21.53 years; female, 76%) completed a Go/No-Go task that allowed participants to learn from errors and adapt their behaviour. Multilevel models were specified to determine whether the effect of error awareness on learning from errors differs between cannabis users and controls, and whether cannabis-use measures predict error correction while accounting for error awareness. Results While error awareness and correction rates did not differ between the groups, there was a significant effect of age of use onset on error correction in cannabis users. Further, the effect of error awareness was dependent on age of onset, and cannabis use-related frequency and harm. That is, cannabis users reporting an earlier age of regular use or scoring higher on the cannabis use index were less likely to perform correctly following an aware error. Conclusion It appears overall cannabis use might not be tightly coupled to behavioural indices of performance monitoring. There is evidence, however, that aspects of cannabis use predict impairments in learning from errors that may be associated with treatment outcomes.

Dysfunction in learning and motivational systems are thought to contribute to addictive behaviours. Previous models have suggested that dopaminergic roles in learning and motivation could produce addictive behaviours through pharmacological manipulations that provide excess dopaminergic signalling towards these learning and motivational systems. Redish (2004) suggested a role based on dopaminergic signals of value prediction error, while (Zhang et al., 2009) suggested a role based on dopaminergic signals of motivation. However, both models present significant limitations. They do not explain the reduced sensitivity to drug-related costs/negative consequences, the increased impulsivity generally found in people with a substance use disorder, craving behaviours, and non-pharmacological dependence, all of which are key hallmarks of addictive behaviours. Here, we propose a novel mathematical definition of salience, that combines aspects of dopamine's role in both learning and motivation within the reinforcement learning framework. Using a single parameter regime, we simulated addictive behaviours that the (Zhang et al., 2009; Redish, 2004) models also produce but we went further in simulating the downweighting of drug-related negative prediction-errors, steeper delay discounting of drug rewards, craving behaviours and aspects of behavioural/non-pharmacological addictions. The current salience model builds on our recently proposed conceptual theory that salience modulates internal representation updating and may contribute to addictive behaviours by producing misaligned internal representations (Kalhan et al., 2021). Critically, our current mathematical model of salience argues that the seemingly disparate learning and motivational aspects of dopaminergic functioning may interact through a salience mechanism that modulates internal representation updating.

BACKGROUND:Worldwide, alcohol use is a major contributor to the burden of disease and mortality. A sizeable literature suggests that brief web-based interventions that incorporate personalized normative and/or health consequences feedback are effective at reducing alcohol intake. The relative efficacy of an intervention that also includes individualized feedback about brain health has not been examined, nor has the utility of integrating a smartphone app component.METHOD:Participants (N = 436, Mage  = 21.27) completed baseline protocols (n = 178 recorded alcohol use via an app for 14 days) and were then assigned to one of three feedback conditions using randomized block allocation with stratification based on the total number of standard drinks consumed. Control participants received no feedback; Alcohol Intake Feedback (Alc) participants received personalized information about their alcohol use; Alcohol Intake plus Cognitive Feedback (AlcCog) participants received personalized details about alcohol use plus individualized brain-health information related to impulsivity. The impact of feedback on alcohol consumption behavior was examined as a function of feedback condition and hazardous/non-harmful drinking status (as defined by the World Health Organization) at an 8-week follow-up.RESULTS:Hazardous drinkers in both the Alc and AlcCog conditions reduced their alcohol intake by 31% to 50% more than those in the Control condition. Reductions were not related to whether participants completed web- plus app-based components or web-only components of the intervention. There was no change in the alcohol intake of non-harmful drinkers.CONCLUSIONS:This proof-of-concept study showed that hazardous drinkers respond well to brief electronic interventions that incorporate personalized normative and/or health consequences feedback. Further research is required to determine how best to make impulsivity-related brain-health consequences of drinking manifest and how to maximize the potential of smartphones apps.

Background Considered a facet of behavioral impulsivity, response inhibition facilitates adaptive and goal-directed behavior. It is often assessed using the Stop-Signal Task (SST), which is presented on stand-alone computers under controlled laboratory conditions. Sample size may consequently be a function of cost or time and sample diversity constrained to those willing or able to attend the laboratory. Statistical power and generalizability of results might, in turn, be impacted. Such limitations may potentially be overcome via the implementation of web-based testing. Objective The aim of this study was to investigate if there were differences between variables derived from a web-based SST when it was undertaken independently—that is, outside the laboratory, on any computer, and in the absence of researchers—versus when it was performed under laboratory conditions. Methods We programmed a web-based SST in HTML and JavaScript and employed a counterbalanced design. A total of 166 individuals (mean age 19.72, SD 1.85, range 18-36 years; 146/166, 88% female) were recruited. Of them, 79 undertook the independent task prior to visiting the laboratory and 78 completed the independent task following their laboratory visit. The average time between SST testing was 3.72 (SD 2.86) days. Dependent samples and Bayesian paired samples t tests were used to examine differences between laboratory-based and independent SST variables. Correlational analyses were conducted on stop-signal reaction times (SSRT). Results After exclusions, 123 participants (mean age 19.73, SD 1.97 years) completed the SST both in the laboratory and independently. While participants were less accurate on go trials and exhibited reduced inhibitory control when undertaking the independent—compared to the laboratory-based—SST, there was a positive association between the SSRT of each condition (r=.48; P<.001; 95% CI 0.33-0.61). Conclusions Findings suggest a web-based SST, which participants undertake on any computer, at any location, and in the absence of the researcher, is a suitable measure of response inhibition.

We often need to rapidly change our mind about perceptual decisions in order to account for new information and correct mistakes. One fundamental, unresolved question is whether information processed prior to a decision being made ('pre-decisional information') has any influence on the likelihood and speed with which that decision is reversed. We investigated this using a luminance discrimination task in which participants indicated which of two flickering greyscale squares was brightest. Following an initial decision, the stimuli briefly remained on screen, and participants could change their response. Using psychophysical reverse correlation, we examined how moment-to-moment fluctuations in stimulus luminance affected participants' decisions. This revealed that the strength of even the very earliest (pre-decisional) evidence was associated with the likelihood and speed of later changes of mind. To account for this effect, we propose an extended diffusion model in which an initial 'snapshot' of sensory information biases ongoing evidence accumulation.

Every decision we make is accompanied by an estimate of the probability that our decision is accurate or ap-propriate. This probability estimate is termed our degree of decision confidence. Recent work has uncovered event-related potential (ERP) correlates of confidence both during decision formation and after a decision has been made. However, the interpretation of these findings is complicated by methodological issues related to ERP amplitude measurement that are prevalent across existing studies. To more accurately characterise the neural correlates of confidence, we presented participants with a difficult perceptual decision task that elicited a broad range of confidence ratings. We identified a frontal ERP component within an onset prior to the behavioural response, which exhibited more positive-going amplitudes in trials with higher confidence ratings. This frontal effect also biased measures of the centro-parietal positivity (CPP) component at parietal electrodes via volume conduction. Amplitudes of the error positivity (Pe) component that followed each decision were negatively asso-ciated with confidence for trials with decision errors, but not for trials with correct decisions, with Bayes factors providing moderate evidence for the null in the latter case. We provide evidence for both pre-and post-decisional neural correlates of decision confidence that are observed in trials with correct and erroneous decisions, respec-tively. Our findings suggest that certainty in having made a correct response is associated with frontal activity during decision formation, whereas certainty in having committed an error is instead associated with the post -decisional Pe component. These findings also highlight the possibility that some previously reported associations between decision confidence and CPP/Pe component amplitudes may have been a consequence of ERP ampli-tude measurement-related confounds. Re-analysis of existing datasets may be useful to test this hypothesis more directly.

Introduction Raven's Advanced Progressive Matrices (APM) are frequently utilized in clinical and experimental settings to index intellectual capacity. As the APM is a relatively long assessment, abridged versions of the test have been proposed. The psychometric properties of an untimed 12-item APM have received some consideration in the literature, but validity explorations have been limited. Moreover, both reliability and validity of a timed 12-item APM have not previously been examined. Method We considered the psychometric properties of untimed (Study 1; N = 608; M-age = 27.89, SD = 11.68) and timed (Study 2; N = 479; M-age = 20.93, SD = 3.12) versions of a brief online 12-item form of the APM. Results Confirmatory factor analyses established both versions of the tests are unidimensional. Item response theory analyses revealed that, in each case, the 12 items are characterized by distinct differences in difficulty, discrimination, and guessing. Differential item functioning showed few male/female or native English/non-native English performance differences. Test-retest reliability was .65 (Study 1) to .69 (Study 2). Both tests had medium-to-large correlations with the Wechsler Abbreviated Scale of Intelligence (2nd ed.) Perceptual Reasoning Index (r = .50, Study 1; r = .56, Study 2) and Full-Scale IQ (r = .34, Study 1; r = .41, Study 2). Conclusion In sum, results suggest both untimed and timed online versions of the brief APM are psychometrically sound. As test duration was found to be highly variable for the untimed version, the timed form might be a more suitable choice when it is likely to form part of a longer battery of tests. Nonetheless, classical test and item response theory analyses, plus validity considerations, suggest the untimed version might be the superior abridged form.