Person-centred Approaches to Psychopathology in the ABCD Study: Phenotypes and Neurocognitive Correlates.

Issues with classifying psychopathology using narrow diagnostic categories have prompted calls for the use of dimensional approaches. Yet questions remain about how closely dimensional approaches reflect the way symptoms cluster in individuals, whether known risk factors (e.g. preterm birth) produce distinct symptom phenotypes, and whether profiles reflecting symptom clusters are associated with neurocognitive factors. To identify distinct profiles of psychopathology, latent class analysis was applied to the syndrome scales of the parent-reported Child Behaviour Checklist for 11,381 9- and 10- year-olds from the Adolescent Brain Cognitive Development study. Four classes were identified, reflecting different profiles, to which children were assigned probabilistically; Class 1 (88.6%) reflected optimal functioning; Class 2 (7.1%), predominantly internalising; Class 3 (2.4%), predominantly externalising; and Class 4 (1.9%), universal difficulties. To investigate the presence of a possible preterm behavioural phenotype, the proportion of participants allocated to each class was cross-tabulated with gestational age category. No profile was specific to preterm birth. Finally, to assess the neurocognitive factors associated with class membership, elastic net regressions were conducted revealing a relatively distinct set of neurocognitive factors associated with each class. Findings support the use of large datasets to identify psychopathological profiles, explore phenotypes, and identify associated neurocognitive factors.

Brief Report: Local-Global Processing and Co-occurrence of Anxiety, Autistic and Obsessive-Compulsive Traits in a Non-clinical Sample.

PURPOSE: Increased local-to-global interference has been found in those with ASD, AD and OCD, and as such, may represent a transdiagnostic marker. As a first step to investigating this, we aimed to assess the overlap in traits of these disorders in a non-clinical sample, and whether local-global processing relates to the traits of the three conditions. METHODS: Participants (n = 149) completed questionnaires including the Autism Quotient (AQ), the Obsessive-Compulsive Inventory (OCI-R) and the Zung Self-rating Anxiety Scale (SAS) and an online version of the Navon task. Behavioural metrics of interference and precedence were extracted from the task and correlated with trait scores. RESULTS: We found moderate to strong correlations between the total scores for ASD, anxiety and OCD. Most local-global processing indices did not relate to traits. CONCLUSION: The study found evidence for an overlap in autism, anxiety and obsessive-compulsive traits in a non-clinical sample. However, local-global processing, as measured by the Navon task, did not appear to underpin symptomatology in the sample and could not be considered a transdiagnostic marker. Future research should investigate the value of alternate metrics.

At-risk alcohol users have disrupted valence discrimination during reward anticipation.

Alcohol use disorder is characterised by disrupted reward learning, underpinned by dysfunctional cortico-striatal reward pathways, although relatively little is known about the biology of reward processing in populations who engage in risky alcohol use. Cues that trigger reward anticipation can be categorized according to their learnt valence (i.e., positive vs. negative outcomes) and motivational salience (i.e., incentive vs. neutral cues). Separating EEG signals associated with these dimensions is challenging because of their inherent collinearity, but the recent application of machine learning methods to single EEG trials affords a solution. Here, the Alcohol Use Disorders Identification Test (AUDIT) was used to quantify risky alcohol use, with participants split into high alcohol (HA) (n = 22, mean AUDIT score: 13.82) and low alcohol (LA) (n = 22, mean AUDIT score: 5.77) groups. We applied machine learning multivariate single-trial classification to the electroencephalography (EEG) data collected during reward anticipation. The LA group demonstrated significant valence discrimination in the early stages of reward anticipation within the cue-P3 time window (400-550 ms), whereas the HA group was insensitive to valence within this time window. Notably, the LA, but not the HA group demonstrated a relationship between single-trial variability in the early valence component and reaction times for gain and loss trials. This study evidences disrupted hypoactive valence sensitivity in the HA group, revealing potential neurophysiological markers for risky drinking behaviours which place individuals at-risk of adverse health events.

Prior information use and response caution in perceptual decision-making: No evidence for a relationship with autistic-like traits.

Interpreting the world around us requires integrating incoming sensory signals with prior information. Autistic individuals have been proposed to rely less on prior information and make more cautious responses than non-autistic individuals. Here, we investigated whether these purported features of autistic perception vary as a function of autistic-like traits in the general population. We used a diffusion model framework, whereby decisions are modelled as noisy evidence accumulation processes towards one of two bounds. Within this framework, prior information can bias the starting point of the evidence accumulation process. Our pre-registered hypotheses were that higher autistic-like traits would relate to reduced starting point bias caused by prior information and increased response caution (wider boundary separation). 222 participants discriminated the direction of coherent motion stimuli as quickly and accurately as possible. Stimuli were preceded with a neutral cue (square) or a directional cue (arrow). 80% of the directional cues validly predicted the upcoming motion direction. We modelled accuracy and response time data using a hierarchical Bayesian model in which starting point varied with cue condition. We found no evidence for our hypotheses, with starting point bias and response caution seemingly unrelated to Adult Autism Spectrum Quotient (AQ) scores. Alongside future research applying this paradigm to autistic individuals, our findings will help refine theories regarding the role of prior information and altered decision-making strategies in autistic perception. Our study also has implications for models of bias in perceptual decision-making, as the most plausible model was one that incorporated bias in both decision-making and sensory processing.

A comparison of open-label and deceptive placebo analgesia in a healthy sample.

OBJECTIVES: A small number of studies have supported the efficacy of open-label placebos (OLPs) in reducing pain. However, research comparing the effectiveness of OLPs with deceptive placebos (DPs) is limited, and the relative impact on pain tolerance versus intensity are not yet understood. This study therefore, examined the effectiveness of a nasal placebo administered openly and deceptively on pain intensity and tolerance during a cold pressor test (CPT). METHOD: 75 healthy participants were allocated to one of three groups; OLP (n = 25), DP (n = 26) and no-treatment (NT; n = 24). A pre-test post-test design was used, with all participants completing a baseline and post-treatment CPT, following placebo administration in the treatment groups. RESULTS: A one-way ANCOVA revealed significant differences between groups for pain intensity, with planned contrasts revealing that this effect was driven by an increase in pain intensity scores for the NT group within the post treatment CPT, which was not evident in the OLP and DP groups. There were no significant differences between groups for changes in pain tolerance. CONCLUSION: The increase in pain intensity reported within the post-treatment CPT in the NT group was not apparent in either the OLP or DP groups, with no significant differences between OLP and DP effectiveness. These findings suggest that deception may not be necessary for effective placebo treatment and have implications for the management of pain.

Using drift diffusion modeling to understand inattentive behavior in preterm and term-born children.

OBJECTIVE: Children born very preterm are at increased risk of inattention, but it remains unclear whether the underlying processes are the same as in their term-born peers. Drift diffusion modeling (DDM) may better characterize the cognitive processes underlying inattention than standard reaction time (RT) measures. This study used DDM to compare the processes related to inattentive behavior in preterm and term-born children. METHOD: Performance on a cued continuous performance task was compared between 33 children born very preterm (VP; ≤ 32 weeks' gestation) and 32 term-born peers (≥ 37 weeks' gestation), aged 8-11 years. Both groups included children with a wide spectrum of parent-rated inattention (above average attention to severe inattention). Performance was defined using standard measures (RT, RT variability and accuracy) and modeled using a DDM. A hierarchical regression assessed the extent to which standard or DDM measures explained variance in parent-rated inattention and whether these relationships differed between VP and term-born children. RESULTS: There were no group differences in performance on standard or DDM measures of task performance. Parent-rated inattention correlated significantly with hit rate, RT variability, and drift rate (a DDM estimate of processing efficiency) in one or both groups. Regression analysis revealed that drift rate was the best predictor of parent-rated inattention. This relationship did not differ significantly between groups. CONCLUSIONS: Findings suggest that less efficient information processing is a common mechanism underlying inattention in both VP and term-born children. This study demonstrates the benefits of using DDM to better characterize atypical cognitive processing in clinical samples. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Eye movement data reveal increased attention to combined health warnings on cigarette packs.

INTRODUCTION: In 2016 the UK introduced standardised pack design regulations, limiting branding and aiming to increase the salience of health warnings. Existing evidence suggests that the effectiveness of pack design in focusing a smoker's attention toward warnings may depend on how much they smoke. Our study aimed to directly compare attention to branding and warnings between the pre-regulation and post-regulation packs in smokers, and to determine whether this was affected by the amount smoked, to assess the effectiveness of the new policies. METHOD: 47 adult smokers were recruited, including daily and non-daily smokers to ensure a wide range in cigarettes smoked per week. Eye movement data were recorded while images of cigarette packs were displayed sequentially on screen. Each trial presented one of two types of cigarette pack; pre-regulation packs with a text health warning, or post-regulation packs compliant with governmental guidance introduced in 2016, with plain branding and a combined pictorial and text health warning. Eye movement data were compared between packs, covarying the number of cigarettes smoked per week. RESULTS: Eye movement analysis revealed that smokers attended more to health warnings and less to branding when looking at post-regulation packs compared with pre-regulation packs. These effects did not relate to number of cigarettes smoked per week. CONCLUSION: Standardised regulations for cigarette packs successfully direct smokers' attention away from branding, and towards health warnings, with no association with cigarettes smoked per week. This study adds to the growing body of evidence advocating broader uptake of similar packaging regulations.

Separate neural representations of prediction error valence and surprise: Evidence from an fMRI meta-analysis.

Learning occurs when an outcome differs from expectations, generating a reward prediction error signal (RPE). The RPE signal has been hypothesized to simultaneously embody the valence of an outcome (better or worse than expected) and its surprise (how far from expectations). Nonetheless, growing evidence suggests that separate representations of the two RPE components exist in the human brain. Meta-analyses provide an opportunity to test this hypothesis and directly probe the extent to which the valence and surprise of the error signal are encoded in separate or overlapping networks. We carried out several meta-analyses on a large set of fMRI studies investigating the neural basis of RPE, locked at decision outcome. We identified two valence learning systems by pooling studies searching for differential neural activity in response to categorical positive-versus-negative outcomes. The first valence network (negative > positive) involved areas regulating alertness and switching behaviours such as the midcingulate cortex, the thalamus and the dorsolateral prefrontal cortex whereas the second valence network (positive > negative) encompassed regions of the human reward circuitry such as the ventral striatum and the ventromedial prefrontal cortex. We also found evidence of a largely distinct surprise-encoding network including the anterior cingulate cortex, anterior insula and dorsal striatum. Together with recent animal and electrophysiological evidence this meta-analysis points to a sequential and distributed encoding of different components of the RPE signal, with potentially distinct functional roles.

Spatiotemporal neural characterization of prediction error valence and surprise during reward learning in humans.

Reward learning depends on accurate reward associations with potential choices. These associations can be attained with reinforcement learning mechanisms using a reward prediction error (RPE) signal (the difference between actual and expected rewards) for updating future reward expectations. Despite an extensive body of literature on the influence of RPE on learning, little has been done to investigate the potentially separate contributions of RPE valence (positive or negative) and surprise (absolute degree of deviation from expectations). Here, we coupled single-trial electroencephalography with simultaneously acquired fMRI, during a probabilistic reversal-learning task, to offer evidence of temporally overlapping but largely distinct spatial representations of RPE valence and surprise. Electrophysiological variability in RPE valence correlated with activity in regions of the human reward network promoting approach or avoidance learning. Electrophysiological variability in RPE surprise correlated primarily with activity in regions of the human attentional network controlling the speed of learning. Crucially, despite the largely separate spatial extend of these representations our EEG-informed fMRI approach uniquely revealed a linear superposition of the two RPE components in a smaller network encompassing visuo-mnemonic and reward areas. Activity in this network was further predictive of stimulus value updating indicating a comparable contribution of both signals to reward learning.

Neural correlates of evidence accumulation during value-based decisions revealed via simultaneous EEG-fMRI.

Current computational accounts posit that, in simple binary choices, humans accumulate evidence in favour of the different alternatives before committing to a decision. Neural correlates of this accumulating activity have been found during perceptual decisions in parietal and prefrontal cortex; however the source of such activity in value-based choices remains unknown. Here we use simultaneous EEG-fMRI and computational modelling to identify EEG signals reflecting an accumulation process and demonstrate that the within- and across-trial variability in these signals explains fMRI responses in posterior-medial frontal cortex. Consistent with its role in integrating the evidence prior to reaching a decision, this region also exhibits task-dependent coupling with the ventromedial prefrontal cortex and the striatum, brain areas known to encode the subjective value of the decision alternatives. These results further endorse the proposition of an evidence accumulation process during value-based decisions in humans and implicate the posterior-medial frontal cortex in this process.

Two spatiotemporally distinct value systems shape reward-based learning in the human brain.

Avoiding repeated mistakes and learning to reinforce rewarding decisions is critical for human survival and adaptive actions. Yet, the neural underpinnings of the value systems that encode different decision-outcomes remain elusive. Here coupling single-trial electroencephalography with simultaneously acquired functional magnetic resonance imaging, we uncover the spatiotemporal dynamics of two separate but interacting value systems encoding decision-outcomes. Consistent with a role in regulating alertness and switching behaviours, an early system is activated only by negative outcomes and engages arousal-related and motor-preparatory brain structures. Consistent with a role in reward-based learning, a later system differentially suppresses or activates regions of the human reward network in response to negative and positive outcomes, respectively. Following negative outcomes, the early system interacts and downregulates the late system, through a thalamic interaction with the ventral striatum. Critically, the strength of this coupling predicts participants' switching behaviour and avoidance learning, directly implicating the thalamostriatal pathway in reward-based learning.

Extinction of cue-evoked drug-seeking relies on degrading hierarchical instrumental expectancies.

There has long been need for a behavioural intervention that attenuates cue-evoked drug-seeking, but the optimal method remains obscure. To address this, we report three approaches to extinguish cue-evoked drug-seeking measured in a Pavlovian to instrumental transfer design, in non-treatment seeking adult smokers and alcohol drinkers. The results showed that the ability of a drug stimulus to transfer control over a separately trained drug-seeking response was not affected by the stimulus undergoing Pavlovian extinction training in experiment 1, but was abolished by the stimulus undergoing discriminative extinction training in experiment 2, and was abolished by explicit verbal instructions stating that the stimulus did not signal a more effective response-drug contingency in experiment 3. These data suggest that cue-evoked drug-seeking is mediated by a propositional hierarchical instrumental expectancy that the drug-seeking response is more likely to be rewarded in that stimulus. Methods which degraded this hierarchical expectancy were effective in the laboratory, and so may have therapeutic potential.

Pelamis: experience from concept to connection.

The development of the Pelamis wave energy converter from its conceptual origins to its commercial deployment is reviewed. The early emphasis on designing for survivability and favourable power absorption characteristics focused attention towards a self-referenced articulated line-absorber in an attenuator orientation. A novel joint and control system allow the machine to be actively tuned to provide a resonant response power amplification in small and moderate seas. In severe seas, the machine is left in its default or natural condition, which is benign and non-resonant. Hydraulic rams at the joints provide the primary power take-off with medium-term storage in high-pressure accumulators yielding smooth electricity generation. Land-based modular construction requiring minimal weather windows for rapid offshore installation is an essential engineering feature necessary for viable commercialization. The second-generation Pelamis designs built for E.ON and ScottishPower Renewables are presented, and the scope for further cost reduction and performance enhancements are explained.