Common genetic factors for uncontrolled eating mechanisms.

OBJECTIVE: Reward-based eating drives are putative mechanisms of uncontrolled eating implicated in obesity and disordered eating (e.g., binge eating). Uncovering the genetic and environmental contributions to reward-related eating, and their genetic correlation with BMI, could shed light on key mechanisms underlying eating and weight-related disorders. METHOD: We conducted a classical twin study to examine how much variance in uncontrolled eating phenotypes and body mass index (BMI) was explained by genetic factors, and the extent that these phenotypes shared common genetic factors. 353 monozygotic twins and 128 dizygotic twins completed the Reward-based Eating Drive 13 scale, which measures three distinct uncontrolled eating phenotypes (loss of control over eating, preoccupation with thoughts about food, and lack of satiety), and a demographic questionnaire which included height and weight for BMI calculation. We estimated additive genetic (A), common environmental (C), and unique environmental (E) factors for each phenotype, as well as their genetic correlations, with a multivariate ACE model. A common pathway model also estimated whether genetic variance in the uncontrolled eating phenotypes was better explained by a common latent uncontrolled eating factor. RESULTS: There were moderate genetic correlations between uncontrolled eating phenotypes and BMI (.26-.41). Variance from the uncontrolled eating phenotypes was also best explained by a common latent uncontrolled eating factor that was explained by additive genetic factors (52%). DISCUSSION: These results suggest that uncontrolled eating phenotypes are heritable traits that also share genetic variance with BMI. This has implications for understanding the cognitive mechanisms that underpin obesity and disordered eating. PUBLIC SIGNIFICANCE: Our study clarifies the degree to which uncontrolled eating phenotypes and BMI are influenced by shared genetics and shows that vulnerability to uncontrolled eating traits is impacted by common genetic factors.

Model-based and model-free mechanisms in methamphetamine use disorder.

People with methamphetamine use disorder (MUD) struggle to shift their behaviour from methamphetamine-orientated habits to goal-oriented choices. The model-based/model-free framework is well suited to understand this difficulty by unpacking the computational mechanisms that support experienced-based (model-free) and goal-directed (model-based) choices. We aimed to examine whether 1) participants with MUD differed from controls on behavioural proxies and/or computational mechanisms of model-based/model-free choices; 2) model-based/model-free decision-making correlated with MUD symptoms; and 3) model-based/model-free deficits improved over six weeks in the group with MUD. Participants with MUD and controls with similar age, IQ and socioeconomic status completed the Two-Step Task at treatment commencement (MUD n = 30, Controls n = 31) and six weeks later (MUD n = 23, Controls n = 26). We examined behavioural proxies of model-based/model-free decisions using mixed logistic regression, and their underlying mechanisms using computational modelling. At a behavioural level, participants with MUD were more likely to switch their choices following rewarded actions, although this pattern improved at follow up. At a computational level, groups were similar in their use of model-based mechanisms, but participants with MUD were less likely to apply model-free mechanisms and less likely to repeat rewarded actions. We did not find evidence that individual differences in model-based or model-free parameters were associated with greater severity of methamphetamine dependence, nor did we find that group differences in computational parameters changed between baseline and follow-up assessment. Decision-making challenges in people with MUD are likely related to difficulties in pursuing choices previously associated with positive outcomes.

Mechanisms underlying performance in a cued go/no-go Pavlovian-to-instrumental transfer paradigm.

Environmental cues that remind us of rewarding outcomes (drugs, food) play a significant role in addiction relapse. In the lab the Pavlovian-to-instrumental transfer (PIT) task has been used to formally examine how cues associated with reward or punishment can bias ongoing instrumental responding. Using a version of this paradigm that integrates PIT with a go/no-go task many studies have related stronger PIT effects (with non-drug rewards) to problematic alcohol use including risky alcohol users relative to non-risky drinkers, individuals with alcohol dependence versus healthy controls and individuals in recovery from alcohol use disorder who are more likely to relapse. However the theoretical importance of these findings and the implications for models of addiction was previously not clear. Understanding if this task indexes the general motivating effects of reward cues on instrumental responding (and whether this is sensitive to shifts in motivation for those outcomes) is critical for understanding these previous results within the context of addiction. Thus, in the current study we aimed to delineate the associative mechanisms that drive the stimulus effects observed in this PIT task. Specifically, we wished to examine whether the cueing effects observed in the cued-go/no-go task were selective in their effect on action, insofar as Pavlovian cues specifically invigorated (or suppressed) responding only if they were associated with congruent outcomes. We conclude that the PIT measured with this task is general in nature. Surprisingly however, the biasing effects of Pavlovian cues on instrumental responding did not appear to be sensitive to outcome devaluation.

Exploration of height dissatisfaction, muscle dissatisfaction, body ideals, and eating disorder symptoms in men.

Objective: Height is a significant, yet under-studied dimension of body dissatisfaction in men. The present study examined the relationship between height dissatisfaction, height, muscle and fat dissatisfaction, body ideals, and eating disorder symptoms in men. Participants and methods: Participants were a sample of male undergraduate Australian students (N = 224) who were administered self-report measures of height, muscle, and fat dissatisfaction, eating disorder symptoms, and muscle and body fat body-ideals, and reported their height. Results: Results showed that height, muscle dissatisfaction, and desired muscularity were important for explaining height dissatisfaction. Additionally, although eating disorder symptoms did not uniquely predict height dissatisfaction, there were small positive correlations between height dissatisfaction and eating disorder symptoms. Conclusions: This study highlights the importance of height in male body dissatisfaction and its association with muscular dissatisfaction and desired muscularity, as well as the potential significance of height in male eating disorders.

The Somatomorphic Matrix-Female: More evidence for the validity of bidimensional figural rating scales for women.

Our study aimed to develop and provide a preliminary psychometric validation of the Somatomorphic Matrix-Female (SM-F), a new bidimensional female figural rating scale which can be used to gauge actual and desired levels of both body fat and muscularity in a consolidated measure, as well as providing an index of actual-desired body discrepancy based on these measures. Across two studies undergraduate women (n Study 1 = 481; n Study 2 = 391) completed the Eating Disorder Examination-Questionnaire, the Body Shape Questionnaire-34, and the Depression Anxiety Stress Scales-21 (Study 1) and the Drive for Thinness Scale and the Drive for Muscularity Scale (Study 2), as well as the SM-F. Overall, the SM-F demonstrated sound content, concurrent, and convergent validity for actual and desired body fat, actual and desired muscularity, and their respective discrepancy scores.

Pavement Quality Evaluation Using Connected Vehicle Data.

Modern vehicles have extensive instrumentation that can be used to actively assess the condition of infrastructure such as pavement markings, signs, and pavement smoothness. Currently, pavement condition evaluations are performed by state and federal officials typically using the industry standard of the International Roughness Index (IRI) or visual inspections. This paper looks at the use of on-board sensors integrated in Original Equipment Manufacturer (OEM) connected vehicles to obtain crowdsource estimates of ride quality using the International Rough Index (IRI). This paper presents a case study where over 112 km (70 mi) of Interstate-65 in Indiana were assessed, utilizing both an inertial profiler and connected production vehicle data. By comparing the inertial profiler to crowdsourced connected vehicle data, there was a linear correlation with an R2 of 0.79 and a p-value of <0.001. Although there are no published standards for using connected vehicle roughness data to evaluate pavement quality, these results suggest that connected vehicle roughness data is a viable tool for network level monitoring of pavement quality.

Measuring Roadway Lane Widths Using Connected Vehicle Sensor Data.

The United States has over three trillion vehicle miles of travel annually on over four million miles of public roadways, which require regular maintenance. To maintain and improve these facilities, agencies often temporarily close lanes, reconfigure lane geometry, or completely close the road depending on the scope of the construction project. Lane widths of less than 11 feet in construction zones can impact highway capacity and crash rates. Crash data can be used to identify locations where the road geometry could be improved. However, this is a manual process that does not scale well. This paper describes findings for using data from onboard sensors in production vehicles for measuring lane widths. Over 200 miles of roadway on US-52, US-41, and I-65 in Indiana were measured using vehicle sensor data and compared with mobile LiDAR point clouds as ground truth and had a root mean square error of approximately 0.24 feet. The novelty of these results is that vehicle sensors can identify when work zones use lane widths substantially narrower than the 11 foot standard at a network level and can be used to aid in the inspection and verification of construction specification conformity. This information would contribute to the construction inspection performed by agencies in a safer, more efficient way.

Prioritizing Roadway Pavement Marking Maintenance Using Lane Keep Assist Sensor Data.

There are over four million miles of roads in the United States, and the prioritization of locations to perform maintenance activities typically relies on human inspection or semi-automated dedicated vehicles. Pavement markings are used to delineate the boundaries of the lane the vehicle is driving within. These markings are also used by original equipment manufacturers (OEM) for implementing advanced safety features such as lane keep assist (LKA) and eventually autonomous operation. However, pavement markings deteriorate over time due to the fact of weather and wear from tires and snowplow operations. Furthermore, their performance varies depending upon lighting (day/night) as well as surface conditions (wet/dry). This paper presents a case study in Indiana where over 5000 miles of interstate were driven and LKA was used to classify pavement markings. Longitudinal comparisons between 2020 and 2021 showed that the percentage of lanes with both lines detected increased from 80.2% to 92.3%. This information can be used for various applications such as developing or updating standards for pavement marking materials (infrastructure), quantifying performance measures that can be used by automotive OEMs to warn drivers of potential problems with identifying pavement markings, and prioritizing agency pavement marking maintenance activities.

Human appetitive Pavlovian-to-instrumental transfer: a goal-directed account.

Pavlovian-to-instrumental transfer (PIT) tasks assess the impact of environmental stimuli on instrumental actions. Since their initial translation from animal to human experiments, PIT tasks have provided insight into the mechanisms that underlie reward-based behaviour. This review first examines the main types of PIT tasks used in humans. We then seek to contribute to the current debate as to whether human PIT effects reflect a controlled, goal-directed process, or a more automatic, non-goal-directed mechanism. We argue that the data favour a goal-directed process. The extent to which the major theories of PIT can account for these data is then explored. We discuss a number of associative accounts of PIT as well as dual-process versions of these theories. Ultimately, however, we favour a propositional account, in which human PIT effects are suggested to be driven by both perceived outcome availability and outcome value. In the final section of the review, we present the potential objections to the propositional approach that we anticipate from advocates of associative link theories and our response to them. We also identify areas for future research.

Negative Mood Induction Increases Choice of Heroin Versus Food Pictures in Opiate-Dependent Individuals: Correlation With Self-Medication Coping Motives and Subjective Reactivity.

Acute growth in negative affect is thought to play a major role in triggering relapse in opiate-dependent individuals. Consistent with this view, three lab studies have demonstrated that negative mood induction increases opiate craving in opiate-dependent individuals. The current study sought to confirm these effects with a behavioral measure of heroin seeking, and test whether the effect is associated with self-reported opiate use to cope with negative affect and subjective reactivity to mood induction. Participants were heroin-dependent individuals engaged with treatment services (n = 47) and control participants (n = 25). Heroin users completed a questionnaire assessing reasons for using heroin: negative affect, social pressure, and cued craving. Baseline heroin choice was measured by preference to enlarge heroin versus food thumbnail pictures in two-alternative forced-choice trials. Negative mood was then induced by depressive statements and music before heroin choice was tested again. Subjective reactivity was indexed by negative and positive mood reported at the pre-induction to post-test timepoints. Heroin users chose heroin images more frequently than controls overall ( p = .001) and showed a negative mood-induced increase in heroin choice compared to control participants (interaction p < .05). Mood-induced heroin choice was associated with self-reported heroin use to cope with negative affect ( p < .05), but not social pressure ( p = .39) or cued craving ( p = .52), and with subjective mood reactivity ( p = .007). These data suggest that acute negative mood is a trigger for heroin seeking in heroin-dependent individuals, and this effect is pronounced in those who report using heroin to cope with negative affect, and those who show greater subjective reactivity to negative triggers. Interventions should seek to target negative coping motives to build resilience to affective triggers for relapse.

Intact goal-directed control in treatment-seeking drug users indexed by outcome-devaluation and Pavlovian to instrumental transfer: critique of habit theory.

Animal studies have demonstrated that chronic exposure to drugs of abuse impairs goal-directed control over action selection indexed by the outcome-devaluation and specific Pavlovian to instrumental transfer procedures, suggesting this impairment might underpin addiction. However, there is currently only weak evidence for impaired goal-directed control in human drug users. Two experiments were undertaken in which treatment-seeking drug users and non-matched normative reference samples (controls) completed outcome-devaluation and specific Pavlovian to instrumental transfer procedures notionally translatable to animal procedures (Experiment 2 used a more challenging biconditional schedule). The two experiments found significant outcome-devaluation and specific Pavlovian to instrumental transfer effects overall and there was no significant difference between groups in the magnitude of these effects. Moreover, Bayes factor supported the null hypothesis for these group comparisons. Although limited by non-matched group comparisons and small sample sizes, the two studies suggest that treatment-seeking drug users have intact goal-directed control over action selection, adding uncertainty to already mixed evidence concerning the role of habit learning in human drug dependence. Neuro-interventions might seek to tackle goal-directed drug-seeking rather than habit formation in drug users.

Examining Perceived Stress, Childhood Trauma and Interpersonal Trauma in Individuals With Drug Addiction.

The investigation of psychosocial factors in relation to opiate addiction is limited and typically uses binary measures to assess how incidences of childhood trauma correlate with addiction. There has also been a lack of enquiry into how experiences of noninterpersonal versus interpersonal trauma may impact drug use addiction. In this regard, the current study utilized a novel measurement of interpersonal versus noninterpersonal lifetime trauma and a scale assessing severity of childhood trauma to examine how these factors may impact patients with opioid addiction. The interaction between these factors and current perceived stress was also examined. Thirty-six opioid-dependent individuals (recruited from the Drug Health Services and Opioid Treatment Program at the Royal Prince Alfred Hospital in Sydney, Australia) and 33 healthy controls completed the Childhood Maltreatment Questionnaire, Lifetime Trauma Survey, and Perceived Levels of Stress Scale. The patient group reported significantly greater childhood trauma severity, more incidences of lifetime trauma, and higher perceived stress than controls. Logistic regression analyses indicated that the severity of childhood trauma was more strongly associated with addiction status than perceived stress. A greater number of lifetime trauma incidence was the best predictor of addiction. Contrary to expectations, noninterpersonal lifetime trauma was a better predictor of addiction status than was interpersonal lifetime trauma. Results suggest that lifetime trauma and childhood trauma may play an important factor in opioid addiction over what can be accounted for by stress.

Assessment of the frequency criterion for the diagnosis of non-suicidal self-injury disorder in female adolescents with conduct disorder.

Recent studies suggest a higher threshold number of self-injuries during the past year than the one proposed in the DSM-5 criteria for non-suicidal self-injury disorder (NSSID). Therefore, we aimed to test a validity of the frequency criterion in girls with conduct disorder (CD) based on psychopathology and the level of functioning. Mixture modelling analysis revealed that the frequency of at least 8 self-harm behaviours in the previous year differentiated adolescents with CD. Thus, we divided adolescents into three subgroups: group 1: at least 8 self-harm acts; group 2: 1-7 self-harm behaviours and group 3: those who did not injure themselves during the last 12 months. Individuals from group 1 were significantly younger and had earlier age of self-harm onset. There were significant differences between groups 1 and 3 in terms of anxiety and depressive symptoms, self-esteem, aggression and the global functioning level. The group 1 scored significantly higher on depressive symptoms compared to the group 2. The group 2 scored significantly higher than the group 3 on the level of hostility. Our results provide further evidence supporting the need for modification of the NSSID frequency criterion.

Reward and punishment-based compound cue learning and generalization in opiate dependency.

Substance dependence is thought to be mediated by abnormalities in cognitive abilities, but how this impacts decision-making remains unclear. This study aimed to test whether people who are opiate dependent differed from never-dependent controls in learning from reward and punishment or in the generalization of learning to novel conditions. Participants with opiate dependency consisted of 21 people who were outpatients in a methadone maintenance program; the control group consisted of 21 healthy participants with no histories of substance abuse. Subjects completed a computer-based task that involved two phases: the training phase involved participants being presented with compound stimulus (a shape and color) in each trial, with the goal of learning which compounds to 'pick' for rewards or 'skip' to avoid punishment. The test phase involved a transfer test, where stimuli from the first phase were combined together to form novel compounds without feedback. The control group demonstrated fewer errors compared to opiate-dependent individuals during the training phase. In the test phase, controls used prior knowledge of both shapes and colors in responding; however, opiate-dependent individuals used shapes but did not use their knowledge of color to modulate responding. When performance during training was equated in the groups using a learning threshold, this difference between groups on the generalization test remained. A deficit in learning generalization might be indicative of group differences in learning strategies in operation during training; however, future work is necessary to uncover the specific neural substrates in action during transfer tasks, and to determine the effects of acute methadone dosage on decision-making.

Cognitive function in schizophrenia: conflicting findings and future directions.

INTRODUCTION: Schizophrenia is a severe mental disorder with multiple psychopathological domains being affected. Several lines of evidence indicate that cognitive impairment serves as the key component of schizophrenia psychopathology. Although there have been a multitude of cognitive studies in schizophrenia, there are many conflicting results. We reasoned that this could be due to individual differences among the patients (i.e. variation in the severity of positive vs. negative symptoms), different task designs, and/or the administration of different antipsychotics. METHODS: We thus review existing data concentrating on these dimensions, specifically in relation to dopamine function. We focus on most commonly used cognitive domains: learning, working memory, and attention. RESULTS: We found that the type of cognitive domain under investigation, medication state and type, and severity of positive and negative symptoms can explain the conflicting results in the literature. CONCLUSIONS: This review points to future studies investigating individual differences among schizophrenia patients in order to reveal the exact relationship between cognitive function, clinical features, and antipsychotic treatment.