Salience network functional integration with the central executive network and the default mode network at rest has been shown to predict real-life self-control. It has been proposed that a network interaction index reflecting stronger functional integration of the salience network with the central executive network and reduced functional connectivity of the salience network with the default mode network represents a trait neural correlate of successful self-control exertion. Here, we attempted to replicate this result using data from our own study where 121 participants completed an fMRI self-control task comprising real-life scenarios and data from a second study (N = 79) retrieved from OpenNeuro (dataset ID: ds002643) where participants completed an fMRI food choice task. We could not replicate the proposed role of salience network resting-state functional connectivity in self-controlled decision-making in either of those data sets. Instead, we found evidence for the exact opposite effect, specifically a negative association between self-control performance and the network interaction index. The role of analysis pipelines, appropriate network ROIs, and the measurement of self-control are discussed in the context of our findings.

Rapid serial visual presentation (RSVP) tasks have been frequently used to assess attentional control in psychiatric samples; however, it is unclear whether RSVP tasks exhibits the psychometric properties necessary to assess these individual differences. In the current study, we examined the reliability and validity of single-target computerized RSVP task outcomes in a sample of 63 participants with moderate to severe psychiatric illness. At the group level, we observed the classical attentional blink phenomenon. At the individual level, conventional indices of attentional blink magnitude exhibited poor internal consistency. We empirically evaluated a novel index for assessing attentional blink magnitude using a single-target RSVP task that involves collapsing across experimental trials in which the attentional blink phenomenon occurs and disregarding performance on control trials, which suffer from ceiling effects. We found that this new index resulted in much improved reliability estimates. Both novel and conventional indices provided evidence of convergent validity. Consequently, this novel index may be worth examining and adopting for researchers interested in assessing individual differences in attentional blink magnitude.

Background/Objectives: Eating disorders (EDs) are associated with cognitive inefficiencies related to cognitive flexibility, central coherence, and inhibition. Transdiagnostic cognitive remediation therapy (TCRT) is a new adaption of cognitive remediation therapy aimed at addressing these difficulties across ED diagnoses. This study investigates the effects of TCRT as an adjunctive treatment for patients with EDs on cognitive and clinical outcomes. Methods: A randomized controlled trial compared the effect of 9 individual sessions of TCRT in conjunction with treatment as usual (TAU) compared to TAU only for patients with EDs and concurrent cognitive difficulties. Participants were assessed at baseline, post-treatment (12 weeks after baseline), and follow-up (6 months after post-treatment assessment). The outcome measures included neuropsychological tests and self-report questionnaires measuring cognitive difficulties and ED psychopathology. The analysis was in accordance with intention to treat principles. Results: Sixty patients with various ED diagnosis and concurrent cognitive difficulties were recruited. The TCRT group (n = 30) displayed significantly greater improvement in self-reported executive functioning, measured by the Behavior Rating Inventory of Executive Function-Adult version compared to the control group (n = 30). However, no superiority of TCRT was observed on performance-based measures of set shifting, central coherence, or inhibition. Moreover, there was no significant difference in improvement in self-reported ED psychopathology. Conclusions: TCRT may enhance compensatory mechanisms for cognitive inefficiencies rather than improve cognitive effectiveness or ED symptoms directly for patients with EDs and concurrent cognitive difficulties. Further investigation of how these impact everyday functioning may provide valuable insights into TCRT's role in ED treatment.

The flanker task is a widely used measure of cognitive control abilities. Drift-diffusion modeling of flanker task behavior can yield separable parameters of cognitive control-related subprocesses, but the parameters' psychometrics are not well-established. We examined the reliability and validity of four behavioral measures: (1) raw accuracy, (2) reaction time (RT) interference, (3) NIH Toolbox flanker score, and (4) two drift-diffusion model (DDM) parameters-drift rate and boundary separation-capturing evidence accumulation efficiency and speed-accuracy trade-off, respectively. Participants from two independent studies - one cross-sectional (N = 381) and one with three timepoints (N = 83) - completed the flanker task while electroencephalography data were collected. Across both studies, drift rate and boundary separation demonstrated comparable split-half and test-retest reliability to accuracy, RT interference, and NIH Toolbox flanker score, but better incremental convergent validity with psychophysiological measures (i.e., the error-related negativity; ERN) and neuropsychological measures of cognitive control than the other behavioral indices. Greater drift rate (i.e., faster and more accurate responses) to congruent and incongruent stimuli, and smaller boundary separation to incongruent stimuli were related to 1) larger ERN amplitudes (in both studies) and 2) faster and more accurate inhibition and set-shifting over and above raw accuracy, reaction time, and NIH Toolbox flanker scores (in Study 1). Computational models, such as DDM, can parse behavioral performance into subprocesses that exhibit comparable reliability to other scoring approaches, but more meaningful relationships with other measures of cognitive control. The application of these computational models may be applied to existing data and enhance the identification of cognitive control deficits in psychiatric disorders.

Background/Objectives: The following systematic review integrates neuroimaging techniques with deep learning approaches concerning emotion detection. It, therefore, aims to merge cognitive neuroscience insights with advanced algorithmic methods in pursuit of an enhanced understanding and applications of emotion recognition. Methods: The study was conducted following PRISMA guidelines, involving a rigorous selection process that resulted in the inclusion of 64 empirical studies that explore neuroimaging modalities such as fMRI, EEG, and MEG, discussing their capabilities and limitations in emotion recognition. It further evaluates deep learning architectures, including neural networks, CNNs, and GANs, in terms of their roles in classifying emotions from various domains: human-computer interaction, mental health, marketing, and more. Ethical and practical challenges in implementing these systems are also analyzed. Results: The review identifies fMRI as a powerful but resource-intensive modality, while EEG and MEG are more accessible with high temporal resolution but limited by spatial accuracy. Deep learning models, especially CNNs and GANs, have performed well in classifying emotions, though they do not always require large and diverse datasets. Combining neuroimaging data with behavioral and cognitive features improves classification performance. However, ethical challenges, such as data privacy and bias, remain significant concerns. Conclusions: The study has emphasized the efficiencies of neuroimaging and deep learning in emotion detection, while various ethical and technical challenges were also highlighted. Future research should integrate behavioral and cognitive neuroscience advances, establish ethical guidelines, and explore innovative methods to enhance system reliability and applicability.

Processes formalized in classic Reinforcement Learning (RL) theory, such as model-based (MB) control, habit formation, and exploration have proven fertile in cognitive and computational neuroscience, as well as computational psychiatry. Dysregulations in MB control and exploration and their neurocomputational underpinnings play a key role across several psychiatric disorders. Yet, computational accounts mostly study these processes in isolation. The current study extended standard hybrid models of a widely-used sequential RL-task (two-step task; TST) employed to measure MB control. We implemented and compared different computational model extensions for this task to quantify potential exploration and perseveration mechanisms. In two independent data sets spanning two different variants of the task, an extended hybrid RL model with a higher-order perseveration and heuristic-based exploration mechanism provided the best fit. While a simpler model with complex perseveration only, was equally well equipped to describe the data, we found a robust positive effect of directed exploration on choice probabilities in stage one of the task. Posterior predictive checks further showed that the extended model reproduced choice patterns present in both data sets. Results are discussed with respect to implications for computational psychiatry and the search for neurocognitive endophenotypes.

Background/Objectives: This systematic review of neuropsychological rehabilitation strategies for primary progressive aphasia will consider recent developments in cognitive neuroscience, especially neuroimaging techniques such as EEG and fMRI, to outline how these tools might be integrated into clinical practice to maximize treatment outcomes. Methods: A systematic search of peer-reviewed literature from the last decade was performed following the PRISMA guidelines across multiple databases. A total of 63 studies were included, guided by predefined inclusion and exclusion criteria, with a focus on cognitive and language rehabilitation in PPA, interventions guided by neuroimaging, and mechanisms of neuroplasticity. Results: Integration of neuroimaging techniques contributes to the increase in the efficacy of interventions with critical information about the neural mechanisms underlying language deficits in the aphasias. Traditional rehabilitation strategies, technology-assisted interventions, and non-invasive brain stimulation techniques hold considerable promise for language improvement. Neuroimaging was also found to be necessary in subtype-specific differentiation toward tailoring therapeutic intervention. Evidence also shows that directed and sustained interventions using neuroplasticity can have long-term effects in managing the symptoms of PPA. Conclusions: The present review underlines the necessity of including cognitive neuroscience techniques within neuropsychological rehabilitation to enhance therapeutic outcomes in PPA. In addition, neuroimaging modalities such as EEG and fMRI are also of great importance in understanding the underlying neurobiology of language disturbances and guiding tailored interventions. Long-term benefits of these approaches should be evaluated, including their applicability in routine clinical practice.

Irritability, or an increased proneness to frustration and anger, is common in youth; however, few studies have examined neurostructural correlates of irritability in children. The purpose of the current study was to examine concurrent and longitudinal associations between brain structure and irritability in a large sample of 9-10-year-old children. Participants included 10,647 children from the Adolescent Brain Cognitive Developmentsm Study (ABCD Study®). We related a latent irritability factor to gray matter volume, cortical thickness, and surface area in 68 cortical regions and to gray matter volume in 19 subcortical regions using structural equation modeling. Multiple comparisons were adjusted for using the false discovery rate (FDR). After controlling for age, sex, race/ethnicity, scanner model, parent's highest level of education, medication use, and total intracranial volume, irritability was associated with smaller volumes in primarily temporal and parietal regions at baseline. Longitudinal analyses showed that baseline gray matter volume did not predict irritability symptoms at the 3rd-year follow-up. No significant associations were found for cortical thickness or surface area. The current study demonstrates inverse associations between irritability and volume in regions implicated in emotional processing/social cognition, attention allocation, and movement/perception. We advance prior research by demonstrating that neurostructural differences associated with irritability are already apparent by age 9-10 years, extending this work to children and supporting theories positing socioemotional deficits as a key feature of irritability.

Substance use disorder (SUD) is common in psychiatric patients and has a negative impact on health and well-being. However, SUD often goes untreated, and there is a need for psychiatrists, of all specialties, to address this pervasive clinical problem. In this review, the authors' goal is to provide a resource that describes treatments for SUD, using neuroscience as a framework. They discuss the effect of pharmacotherapy on craving, intoxication, and withdrawal and its ability to interrupt the cycle of substance use in SUD. The neuroscience of stress is reviewed, including medications targeting neurotransmitter systems activated by alarm and fear. Neuroplasticity and promising treatments that use this mechanism, including ketamine, psilocybin, and transcranial magnetic stimulation (TMS), are discussed. The authors conclude by listing resources and practice guidelines for physicians interested in learning more about treatments for SUD.

Many autistic people struggle with mental health problems like anxiety, depression, inattention, and aggression, which can be challenging to treat. Executive function challenges, which impact many autistic individuals, may serve as a risk factor for mental health problems or make treating mental health conditions more difficult. While some people respond well to medication or therapy, others do not. This study tried to understand if there are different subgroups of autistic young people who may have similar patterns of executive function strengths and challenges-like flexibility, planning, self-monitoring, and emotion regulation. Then, we investigated whether executive function subgroups were related to mental health problems in autistic youth. We found three different types of executive function subgroups in autistic youth, each with different patterns of mental health problems. This helps us identify specific profiles of executive function strengths and challenges that may be helpful with identifying personalized supports, services, and treatment strategies for mental health conditions.

Cognitive control and reward-related abnormalities are centrally implicated in addiction. However, findings from longitudinal studies addressing neurocognitive predictors of addictive behaviors are mixed. Further, little work has been conducted predicting non-substance-related addictive behaviors. Our study aimed to assess predictors of substance and non-substance addictive behaviors in a community sample, systematically evaluating each neurocognitive function's independent influence on addictive behavior.

Australians (N = 294; 51.7% female; M[SD] age = 24.8[4.7] years) completed online neurocognitive tasks and surveys at baseline and 3-month follow-up. Self-report scales assessed problematic alcohol use, addictive eating (AE), problematic pornography use (PPU), and problematic internet use (PUI) at 3- and 6-month follow-ups. Linear regressions with bootstrapping assessed neurocognitive predictors for each addictive behavior across a 6-month period.

Neurocognition at baseline did not predict AE or PUI severity at 6-month follow-up. Less delay discounting at baseline predicted higher PPU at 6-month follow-up (β = -0.16, p = 0.005). Poorer performance monitoring at baseline predicted higher AE at 3-month follow-up (β = -0.16, p = 0.004), and more reward-related attentional capture at 3-months predicted higher AE at 6-month follow-up (β = 0.14, p = 0.033). Less reward-related attentional capture (β = -0.14, p = 0.003) and less risk-taking under ambiguity (β = -0.11, p = 0.029) at baseline predicted higher PUI at 3-month follow-up. All findings were of small effect size. None of the neurocognitive variables predicted problematic alcohol use.

We were unable to identify a core set of specific neurocognitive functions that reliably predict multiple addictive behavior types. However, our findings indicate both cognitive control and reward-related functions predict non-substance addictive behaviors in different ways. Findings suggest that there may be partially distinct neurocognitive mechanisms contributing to addiction depending on the specific addictive behavior.

The current study examined how individual differences in error-related brain activity might moderate the association between high trait neuroticism and internalizing symptoms. Data were collected from a sample of high-achieving young adults (N = 188) as part of a larger study on risk versus resiliency for psychopathology. Participants completed two behavioral tasks to elicit the error-related negativity (ERN): an arrow Flanker task and a Go/No-Go task. Analyses were constrained to two internalizing symptom dimensions of checking behavior and irritability. Contrary to expectations, ERN amplitude was not related to symptom severity at the bivariate level. However, ERN amplitude moderated the association between trait neuroticism and symptoms of ill temper, such that the neuroticism-irritability association was strongest among individuals with a blunted ERN. In addition, this finding was relatively consistent across tasks and across two complementary methods of scoring the ERN, suggesting an effect of ERN variance that is shared between tasks and that is relatively robust regarding processing differences. In all, the current study represents the first attempt to investigate how the ERN interacts with trait neuroticism to predict transdiagnostic symptom dimensions in adulthood.

Executive function deficits have been reported in both autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD). However, little is known regarding which, if any, of these impairments are unique vs. shared in children with ADHD versus ASD. In this Review, we provide an overview of the current literature with a critical eye toward diagnostic, measurement, and third-variable considerations that should be leveraged to provide more definitive answers. We conclude that the field's understanding of ASD and ADHD executive function profiles is highly limited because most research on one disorder has failed to account for their co-occurrence and the presence of symptoms of the other disorder; a vast majority of studies have relied on traditional neuropsychological tests and/or informant-rated executive function scales that have poor specificity and construct validity; and most studies have been unable to account for the well-documented between-person heterogeneity within and across disorders. Currently, the most parsimonious conclusion is that children with ADHD and/or ASD tend to perform moderately worse than neurotypical children on a broad range of neuropsychological tests. However, the extent to which these difficulties are unique vs. shared, or attributable to impairments in specific executive functions subcomponents, remains largely unknown. We end with focused recommendations for future research that we believe will advance this important line of inquiry.

People are able to voluntarily suppress unwanted thoughts or memories, a phenomenon known as suppression-induced forgetting or memory suppression. Despite harmful alcohol use, such as binge drinking, has been linked to impaired inhibitory control (IC) and augmented alcohol-cue reactivity, no study to date has assessed memory inhibition abilities towards alcohol-related cues in binge drinkers (BDs). Thus, the present preregistered study aimed to evaluate the behavioral and neurofunctional mechanisms associated with memory inhibition, specifically those related to the suppression of alcohol-related memories, in young BDs. For this purpose, electroencephalographic activity was recorded in eighty-two college students aged between 18 and 24 years old from the University of Minho (50% females; 40 non/low-drinkers [N/LDS] and 42 BDs) while they performed the Think/No-Think Alcohol task. Brain functional connectivity (FC) was calculated using the phase locking value and, subsequently, a dynamic seed-based analysis was conducted to explore the FC patterns between IC and memory networks. Comparatively to N/LDs, BDs exhibited decreased alpha-band FC between the anterior cingulate cortex and the left fusiform gyrus during attempts to suppress non-alcohol memories, accompanied by unsuccessful forgetting of those memories. Conversely, BDs displayed augmented gamma-band FC between the IC network and memory regions -i.e., hippocampus, parahippocampus and fusiform gyrus- during suppression of alcohol-related memories. Inhibitory abnormalities in BDs may lead to hypoconnectivity between IC and memory networks and deficient suppression of non-alcohol-related memories. However, while suppressing highly salient and reward-predicting stimuli, such as alcohol-related memories, BDs display a hyperconnectivity pattern between IC and memory networks, likely due to their augmented attention towards intrusive alcoholic memories and the attempts to compensate for potential underlying IC deficits. These findings hold important implications for alcohol research and treatment, as they open up new avenues for reducing alcohol use by shifting the focus to empowering suppression/control over alcohol-related memories. CLINICAL TRIAL REGISTRATION: [http://www.ClinicalTrials.gov], identifier [NCT05237414].

Self-harm (SH) increases significantly in early adolescence with great variability, and childhood maltreatment (CM) contributes to this increase. Understanding the developmental pathway from CM to SH could provide clues for SH prevention. This study used latent class analysis (LCA) to detect the phenotype of SH and explored the role of psychological resilience in the pathway from the CM to SH phenotype among 5724 early adolescents (52.5% male). Three interpretable phenotypes of SH were identified: low SH (57.8%), medium SH (29.0%), and high SH (13.2%). Furthermore, CM was positively associated with the SH phenotype, psychological resilience mediated the association between CM and the SH phenotype (all ps < 0.001), and a larger mediating effect was observed in the medium SH (22.41%). Our findings offer new perspectives that improving psychological resilience can be used as an efficient intervention to reduce the risk of SH among early adolescents who have experienced CM.

Decision-making requires continuous adaptation to internal and external contexts. Changes in decision-making are reliable transdiagnostic symptoms of neuropsychiatric disorders. We created a computational model demonstrating how the striosome compartment of the striatum constructs a mathematical space for decision-making computations depending on context, and how the matrix compartment defines action value depending on the space. The model explains multiple experimental results and unifies other theories like reward prediction error, roles of the direct versus indirect pathways, and roles of the striosome versus matrix, under one framework. We also found, through new analyses, that striosome and matrix neurons increase their synchrony during difficult tasks, caused by a necessary increase in dimensionality of the space. The model makes testable predictions about individual differences in disorder susceptibility, decision-making symptoms shared among neuropsychiatric disorders, and differences in neuropsychiatric disorder symptom presentation. The model reframes the role of the striosomal circuit in neuroeconomic and disorder-affected decision-making.

Striosomes prioritize decision-related data used by matrix to set action values. Striosomes and matrix have different roles in the direct and indirect pathways. Abnormal information organization/valuation alters disorder presentation. Variance in data prioritization may explain individual differences in disorders.

Beck et al. developed a computational model of how a striatal circuit functions during decision-making. The model unifies and extends theories about the direct versus indirect pathways. It further suggests how aberrant circuit function underlies decision-making phenomena observed in neuropsychiatric disorders.

Representations in working memory can affect distractor suppression in human visual search, and this process is modulated by a separate top-down cognitive control. An increasing body of research has demonstrated that patients with substance use disorder (SUD) have deficits in cognitive control over filtering interference by perceptual distractors. However, their ability to resist proactive interference from working memory has received comparatively less attention.

Here, we investigate this issue by employing a working memory/visual search dual-task paradigm. An intervening gap-location search task was instructed to be performed while participants memorized a written color word, with congruent auditory information present during the memory encoding phase on half of the trials.

Results showed that there was a reliable response time (RT) advantage when the meaning of the memory sample agreed with the color of one of the distractors under the visual alone condition. However, such a result was only found in the control group. More importantly, both groups exhibited comparable facilitation under the audiovisual condition, with the facilitation effect appearing later in the SUD group. Furthermore, the facilitation effect was superior in magnitude and time course under the audiovisual condition to the visual alone condition.

These findings highlight how patients with SUD resist distractor interference at the memory level and extend our understanding of how working memory, selective attention, and audiovisual enhancement interact to optimize perceptual decisions in patients with SUD.

Adaptive decision-making, which is often impaired in various psychiatric conditions, is essential for well-being. Recent evidence has indicated that decision-making capacity in multiple tasks could be accounted for by latent dimensions, enlightening the question of whether there is a common disruption of brain networks in economic decision-making across psychiatric conditions. Here, we addressed the issue by combining activation/lesion network mapping analyses with a transdiagnostic brain imaging meta-analysis. Our findings indicate that there were transdiagnostic alterations in the thalamus and ventral striatum during the decision or outcome stage of decision-making. The identified regions represent key nodes in a large-scale network, which is composed of multiple heterogeneous brain regions and plays a causal role in motivational functioning. The findings suggest that disturbances in the network associated with emotion- and reward-related processing play a key role in dysfunctions of decision-making observed in various psychiatric conditions. This study provides the first meta-analytic evidence of common neural alterations linked to deficits in economic decision-making.

In cognitive neuroscience and psychology, reaction times are an important behavioral measure. However, in instrumental learning and goal-directed decision making experiments, findings often rely only on choice probabilities from a value-based model, instead of reaction times. Recent advancements have shown that it is possible to connect value-based decision models with reaction time models. However, typically these models do not provide an integrated account of both value-based choices and reaction times, but simply link two types of models. Here, we propose a novel integrative joint model of both choices and reaction times by combining a computational account of Bayesian sequential decision making with a sampling procedure. This allows us to describe how internal uncertainty in the planning process shapes reaction time distributions. Specifically, we use a recent context-specific Bayesian forward planning model which we extend by a Markov chain Monte Carlo (MCMC) sampler to obtain both choices and reaction times. As we will show this makes the sampler an integral part of the decision making process and enables us to reproduce, using simulations, well-known experimental findings in value based-decision making as well as classical inhibition and switching tasks. Specifically, we use the proposed model to explain both choice behavior and reaction times in instrumental learning and automatized behavior, in the Eriksen flanker task and in task switching. These findings show that the proposed joint behavioral model may describe common underlying processes in these different decision making paradigms.

This study attempted to examine the mechanism of the impact of Addiction-Prone Personality (APP) on creative cognitive styles (idea generation, idea selection), especially to explore the mediating role of novelty seeking and the moderating role of depression tendency on the relationship between APP and creative cognitive styles. College students (N = 576, 79% female) participated in and completed measures of APP, idea generation and selection, novelty seeking, and depression tendency. Results showed that (1) APP was positively related with idea generation while negatively related with idea selection; (2) novelty seeking played a partial mediating role in the relationship between APP and idea generation and a suppressing effect between APP and idea selection; (3) depression tendency moderated the indirect relationship between APP and creative cognitive styles through novelty seeking. Therefore, APP has different indirect effects on idea generation and idea selection via novelty seeking. When there was a higher depression tendency, there was a stronger indirect effect. The study highlights the significant importance of the underlying processes between APP and creative cognitive styles and offers implications for rethinking the relationship between addiction and creativity.

Attentional biases towards reward stimuli have been implicated in substance use-related problems. The value-modulated attentional capture (VMAC) task assesses such reward-related biases. The VMAC task widely used in lab studies tends to be monotonous and susceptible to low effort. We therefore tested a gamified online version of the VMAC that aimed to increase participant engagement. Our goal was to examine how VMAC is associated with substance use-related problems and addictive behaviors, and whether this association is moderated by cognitive control.

We recruited 285 participants from an online community, including heavy alcohol users. All participants completed a novel gamified version of the VMAC task, measures of substance use and addictive behaviors (addictive-like eating behavior, problematic smartphone use), the WebExec measure of problems with executive functions, and the Stroop Adaptive Deadline Task (SDL) as a measure of cognitive control.

The gamified VMAC task successfully identified value-modulated attentional capture effects towards high-reward stimuli. We found no significant associations between VMAC scores, problematic alcohol or cannabis use, addictive behaviors, or any moderation by a behavioral measure of cognitive control. Exploratory analyses revealed that self-reported cognitive problems were associated with more alcohol-, and cannabis-related problems, and addictive behaviors. Greater attentional capture (VMAC) was associated with more cannabis use-related problems among individuals with higher levels of self-reported cognitive problems.

Our study is one of the first to demonstrate the utility of the gamified version of the VMAC task in capturing attentional reward biases. Self-reported problems with cognitive functions represent a key dimension associated with substance use-related problems and addictive behaviors.

The rat cognitive effort task (rCET), a rodent model of cognitive rather than physical effort, requires animals to choose between an easy or hard visuospatial discrimination, with a correct hard choice more highly rewarded. Like in humans, there is stable individual variation in choice behavior. In previous reports, animals were divided into two groups-workers and slackers-based on their mean preference for the harder option. Although these groups differed in their response to pharmacological challenges, the rationale for using this criterion for grouping was not robust.

We collated experimental data from multiple cohorts of male and female rats performing the rCET and used a model-based framework combining drift diffusion modeling with cluster analysis to identify the decision-making processes underlying variation in choice behavior.

We verified that workers and slackers are statistically different groups but also found distinct intra-group profiles. These subgroups exhibited dissociable performance during the attentional phase, linked to distinct decision-making profiles during choice. Reanalysis of previous pharmacology data using this model-based framework showed that serotonergic drug effects were explained by changes in decision boundaries and non-decision times, while scopolamine's effects were driven by changes in decision starting points and rates of evidence accumulation.

Modeling revealed the decision-making processes that are associated with cognitive effort costs, and how these differ across individuals. Reanalysis of drug data provided insight into the mechanisms through which different neurotransmitter systems impact cognitively effortful attention and decision-making processes, with relevance to multiple psychiatric disorders.

We all experience occasional self-control failures (SCFs) in our daily lives, where we enact behaviors that stand in conflict with our superordinate or long-term goals. Based on the assumption that SCFs share common underlying mechanisms with addictive disorders, we tested the hypothesis that a generally higher susceptibility to daily SCFs predicts more addictive behavior, or vice versa.

At baseline, 338 individuals (19-27 years, 59% female) from a community sample participated in multi-component assessments. These included among others (1) a clinical interview on addictive behaviors (quantity of use, frequency of use, DSM-5 criteria; n = 338) and (2) ecological momentary assessment of SCFs (n = 329, 97%). At the 3-year and 6 year follow-up, participation rates for both assessment parts were 71% (n = 240) and 50% (n = 170), respectively.

Controlling for age, gender, IQ, and baseline addiction level, random-intercept cross-lagged panel models revealed that participants who reported more SCFs also showed pronounced addictive behavior at the between-person level, but we found no evidence of a predictive relationship at the within-person level over time.

A higher rate of SCFs is associated with more addictive behavior, while there is no evidence of an intraindividual predictive relationship. Novel hypotheses suggested by additional exploratory results are that (1) only addiction-related SCFs in daily life are early markers of an escalation of use and thus for addictive disorders and that (2) an explicit monitoring of SCFs increases self-reflection and thereby promotes the mobilization of cognitive control in response to goal-desire conflicts.

Excessive avoidance is characteristic for anxiety disorders, even when approach would lead to positive outcomes. The process of how such approach-avoidance conflicts are resolved is not sufficiently understood. We examined the temporal dynamics of approach-avoidance in intense fear of spiders. Highly fearful and non-fearful participants chose repeatedly between a fixed no spider/low reward and a spider/high reward option with varying fear (probability of spider presentation) and reward information (reward magnitude). By sequentially presenting fear and reward information, we distinguished whether decisions are dynamically driven by both information (sequential-sampling) or whether the impact of fear information is inhibited (cognitive control). Mouse movements were recorded to assess temporal decision dynamics (i.e., how strongly which information impacts decision preference at which timepoint). Highly fearful participants showed stronger avoidance despite lower gains (i.e., costly avoidance). Time-continuous multiple regression of their mouse movements yielded a stronger impact of fear compared to reward information. Importantly, presenting either information first (fear or reward) enhanced its impact during the early decision process. These findings support sequential sampling of fear and reward information, but not inhibitory control. Hence, pathological avoidance may be characterized by biased evidence accumulation rather than altered cognitive control.

Impaired executive functions (EF) have been found within various mental disorders (e.g., attention deficit hyperactivity disorder, autism spectrum disorder, schizophrenia spectrum disorders) as described in DSM-5. However, although impaired EF has been observed within several categories of mental disorders, empirical research on direct relations between EF and broader dimension of psychopathology is still scarce. Therefore, in the current investigation we examined relations between three EF performance tasks and self-reported dimensions of psychopathology (i.e., the internalizing, externalizing, and thought disorder spectra) in a combined dataset of patients with a broad range of mental disorders (N = 440). Despite previously reported results that indicate impaired EF in several categories of mental disorders, in this study no direct relations were found between EF performance tasks and self-reported broader dimensions of psychopathology. These results indicate that relations between EF and psychopathology could be more complex and non-linear in nature. We evaluate the need for integration of EF and dimensional models of psychopathology and reflect on EF as a possible transdiagnostic factor of psychopathology.

Recovery from complex conditions such as gambling disorders (GD) often entail considerable change and require a range of adaptable interventions in the health care system. Outcomes from such avenues to change are influenced by multifarious contextual factors, which are less frequently considered in treatment outcome studies. Accordingly, this scoping review aims to map the level of evidence and explore how contextual factors influence the provision and outcomes of GD interventions.

A systematic search in selected health and social science research databases yielded a total of 2.464 unique references. The results were screened in three selection steps-titles (n = 2.464), abstracts (n = 284) and full-text (n = 104). The scoping approach was applied to provide a narrative account of the final included references (n = 34).

Findings suggest that the research on GD treatment is in the early stages of development. Additionally, studies on GD interventions are characterized by cultural biases (Region and ethnicity and Gender perspectives), while three key elements are described as successful avenues to recover from GD (Competence, Perception and Utilization). In line with these findings, proposals for future research and treatment designs are made.

Measuring the function of decision-making systems is a central goal of computational psychiatry. Individual measures of decisional function could be used to describe neurocognitive profiles that underpin psychopathology and offer insights into deficits that are shared across traditional diagnostic classes. However, there are few demonstrably reliable and mechanistically relevant metrics of decision making that can accurately capture the complex overlapping domains of cognition whilst also quantifying the heterogeneity of function between individuals. The WebSurf task is a reverse-translational human experiential foraging paradigm which indexes naturalistic and clinically relevant decision-making. To determine its potential clinical utility, we examined the psychometric properties and clinical correlates of behavioural parameters extracted from WebSurf in an initial exploratory experiment and a pre-registered validation experiment. Behaviour was stable over repeated administrations of the task, as were individual differences. The ability to measure decision making consistently supports the potential utility of the task in predicting an individual's propensity for response to psychiatric treatment, in evaluating clinical change during treatment, and in defining neurocognitive profiles that relate to psychopathology. Specific aspects of WebSurf behaviour also correlate with anhedonic and externalising symptoms. Importantly, these behavioural parameters may measure dimensions of psychological variance that are not captured by traditional rating scales. WebSurf and related paradigms might therefore be useful platforms for computational approaches to precision psychiatry.

Self-regulation, the ability to guide behavior according to one's goals, plays an integral role in understanding loss of control over unwanted behaviors, for example in alcohol use disorder (AUD). Yet, experimental tasks that measure processes underlying self-regulation are not easy to deploy in contexts where such behaviors usually occur, namely outside the laboratory, and in clinical populations such as people with AUD. Moreover, lab-based tasks have been criticized for poor test-retest reliability and lack of construct validity. Smartphones can be used to deploy tasks in the field, but often require shorter versions of tasks, which may further decrease reliability. Here, we show that combining smartphone-based tasks with joint hierarchical modeling of longitudinal data can overcome at least some of these shortcomings. We test four short smartphone-based tasks outside the laboratory in a large sample (N = 488) of participants with AUD. Although task measures indeed have low reliability when data are analyzed traditionally by modeling each session separately, joint modeling of longitudinal data increases reliability to good and oftentimes excellent levels. We next test the measures' construct validity and show that extracted latent factors are indeed in line with theoretical accounts of cognitive control and decision-making. Finally, we demonstrate that a resulting cognitive control factor relates to a real-life measure of drinking behavior and yields stronger correlations than single measures based on traditional analyses. Our findings demonstrate how short, smartphone-based task measures, when analyzed with joint hierarchical modeling and latent factor analysis, can overcome frequently reported shortcomings of experimental tasks.

Alcohol consumption is a leading cause of morbidity and mortality worldwide, disproportionately affecting young men. Heavy episodic drinking is particularly prevalent among men, with this behavior peaking between the ages of 20 and 24.

We sought to identify dimensions of decision-making in men that would predict the development of hazardous alcohol use through emerging adulthood.

This prospective observational study profiled value-based decision-making in 198 healthy men at age 18 and assessed their alcohol involvement annually until age 24. Latent growth curve modeling estimated individual variability in trajectories of alcohol involvement and regressed this variability on five choice dimensions.

Low loss aversion predicted sustained heavy episodic drinking from age 18 to 24. Both high delay discounting and risk-seeking for gains independently predicted a considerably higher cumulative alcohol use during these 6 years, with high delay discounting indicating escalating consumption from age 21. Risk-seeking for gains additionally predicted meeting more criteria for Alcohol Use Disorder in these 6 years. Risk-seeking for losses was not significantly related to alcohol outcomes. Choice preferences were largely independent of each other but were correlated with choice consistency, with low consistency predicting heavy episodic drinking from age 18 to 24 beyond these associations.

The predictive effects collectively suggest that overvaluing immediate and probabilistic incentives, rather than underestimating harm, drives hazardous drinking in young men. The differential relations of choice preferences and consistency to alcohol involvement through emerging adulthood provide distinct cognitive-behavioral patterns that warrant consideration in the development of harm reduction interventions.

Inhibitory control develops in early childhood, and atypical development may be a measurable marker of risk for the later development of psychosis. Additionally, inhibitory control may be a target for intervention.

Behavioral performance on a developmentally appropriate Go/No-Go task including a frustration manipulation completed by children ages 3-5 years (early childhood; n = 107) was examined in relation to psychotic-like experiences (PLEs; 'tween'; ages 9-12), internalizing symptoms, and externalizing symptoms self-reported at long-term follow-up (pre-adolescence; ages 8-11). ERP N200 amplitude for a subset of these children (n = 34) with electrophysiological data during the task was examined as an index of inhibitory control.

Children with lower accuracy on No-Go trials compared to Go trials in early childhood (F(1,101) = 3.976, p = 0.049), evidenced higher PLEs at the transition to adolescence 4-9 years later, reflecting a specific deficit in inhibitory control. No association was observed with internalizing or externalizing symptoms. Decreased accuracy during the frustration manipulation predicted higher internalizing, F(2,202) = 5.618, p = 0.004, and externalizing symptoms, F(2,202) = 4.663, p = 0.010. Smaller N200 amplitudes were observed on No-Go trials for those with higher PLEs, F(1,101) = 6.075, p = 0.020; no relationship was observed for internalizing or externalizing symptoms.

Long-term follow-up demonstrates for the first time a specific deficit in inhibitory control behaviorally and electrophysiology, for individuals who later report more PLEs. Decreases in task performance under frustration induction indicated risk for internalizing and externalizing symptoms. These findings suggest that pathophysiological mechanisms for psychosis are relevant and discriminable in early childhood, and further, suggest an identifiable and potentially modifiable target for early intervention.

High-definition transcranial direct current stimulation (HD-tDCS) holds promise for therapeutic use in psychiatric disorders. One obstacle for the implementation into clinical practice is response variability. One way to tackle this obstacle is the use of Individualized head models.

This study investigated the variability of HD-tDCS induced electric fields (EFs) and its impact on resting-state functional connectivity (rsFC) during different time windows.

In this randomized, double-blind, and sham controlled study, seventy healthy males underwent 20 min of 1.5 mA HD-tDCS on the right inferior frontal gyrus (rIFG) while undergoing resting-state functional magnetic resonance imaging (rs-fMRI). Individual head models and EF simulations were created from anatomical images. The effects of HD-tDCS on rsFC were assessed using a seed-to-voxel analysis. A subgroup analysis explored the relationship between EF magnitude and rsFC during different stimulation time windows.

Results highlighted significant variability in HD-tDCS-induced EFs. Compared to the sham group, the active group showed increased rsFC between the rIFG and the left prefrontal cortex, during and after stimulation. During active stimulation, EF magnitude correlated positively with rsFC between the rIFG and the left hippocampus initially, and negatively during the subsequent period.

This study indicated an HD-tDCS induced increase of rsFC between left and right prefrontal areas. Furthermore, an interaction between the magnitude and the duration of HD-tDCS on rsFC was observed. Due to the high EF variability that was apparent, these findings highlight the need for individualized HD-tDCS protocols and the creation of head models to optimize effects and reduce response heterogeneity.

Recent initiatives have focused on integrating transdiagnostic biobehavioral processes or dispositions with dimensional models of psychopathology. Toward this goal, biobehavioral traits of affiliative capacity (AFF) and inhibitory control (INH) hold particular promise as they demonstrate transdiagnostic stability and predictive validity across developmental stages and differing measurement modalities. The current study employed data from different modes of measurement in a sample of 1830 children aged 5-10 years to test for associations of AFF and INH, individually and interactively, with broad dimensions of psychopathology. Low AFF, assessed via parent-report, evidenced predictive relations with distress- and externalizing-related problems. INH as assessed by cognitive-task performance did not relate itself to either psychopathology dimension, but it moderated the effects observed for low AFF, such that high INH protected against distress symptoms in low-AFF participants, whereas low INH amplified distress and externalizing symptoms in low-AFF participants. Results are discussed in the context of the interface of general trait transdiagnostic risk factors with quantitatively derived dimensional models of psychopathology.

Anorexia nervosa (AN) patients exhibit attentional bias (AB) related to the body, which is the tendency to pay greater attention to weight-related body areas compared to non-weight-related ones. This phenomenon has been linked to elevated levels of body dissatisfaction (BD) and may potentially reduce the effectiveness of body exposure therapy. The purpose of this pilot study is to assess the efficacy of a single session of a new body-related AB modification task (ABMT) that combines virtual reality with eye tracking in patients with AN. The goals of the ABMT are to reduce body-related AB by balancing attention between weight and non-weight-related body areas and to reduce BD levels. Twenty-three adolescent patients with AN were embodied in a virtual avatar and immersed in a virtual environment where they completed the ABMT. Body-related AB measures and BD levels were assessed before and after the training. A paired samples t-test showed statistically significant differences between pre-assessment and post-assessment; the complete fixation time on weight-related body parts was reduced and BD levels decreased. The initial evidence of the efficacy of this ABMT has important clinical implications, since AB and BD are considered risk factors for developing and maintaining eating disorder symptomatology among patients with AN.

The cognitive control network (CCN) is an important network responsible for performing and modulating executive functions. In adolescents, alcohol use has been associated with weaker cognitive control, higher reward sensitivity, and later-in-life alcohol problems. Given that the CCN continues to develop into young adulthood, it is important to understand relations between early alcohol use, the CCN, and reward networks. Participants included individuals 18-23 years without alcohol use disorder. Based upon self-reported age of first alcoholic drink, participants were split into two groups: Early (onset) Drinkers (first drink < age 18, N = 52) and Late (onset) Drinkers (first drink > age 18, N = 44). All participants underwent an 8-minute resting-state fMRI scan. Seed regions of interest included the anterior dorsolateral prefrontal cortex (DLPFC), amygdala, and ventral striatum. Early Drinkers demonstrated significant reduced connectivity of CCN regions, including bilateral anterior DLPFC, compared to Late Drinkers. There were no significant differences between Early and Late Drinkers in connectivity between reward and CCN regions. These results suggest that individuals who begin drinking alcohol earlier in life may have alterations in the development of the CCN; however, longitudinal research is necessary to determine whether lower connectivity precedes or follows early alcohol use, and any other relevant factors.

Cognitive control and the attribution of incentive salience are two key neuropsychological processes proposed to explain substance use disorder (SUD). However, little is known about how they interact to influence the severity of drug use in people with SUD.

To determine if cognitive control exerts a moderating effect on the relation between the attribution of salience to drug/reward-related cues and the severity of drug use in SUD cases.

Sixty-nine SUD cases with methamphetamine as the main drug of consumption were selected and evaluated. Participants performed the Stroop, Go/No-Go, and Flanker tasks to identify a latent cognitive control factor, and the Effort-Expenditure for Reward task, as well as answering the Methamphetamine Incentive Salience Questionnaire to measure the attribution of incentive salience. Severity of drug use was determined by the KMSK scale and an exploratory clinical interview.

As expected, higher incentive salience attribution predicted greater severity of methamphetamine use. Unexpectedly, however, we found a moderating effect of impaired cognitive control on the relations between higher incentive salience scores and higher monthly drug use, and between younger age at onset of systematic drug use and higher incentive salience scores.

Results show the moderating role of cognitive control on the relation between incentive salience attribution and severity of drug use in SUD cases, and help explain the chronic, relapsing nature of addiction, knowledge necessary to develop more precise prevention and treatment strategies.

Anorexia nervosa is a frequent eating disorder that affects predominantly young women and may take a severe and chronically worsening course of disease contributing to its high mortality rate. Although a multitude of treatment options exist, this disease still bears a high relapse rate. In light of these facts, an improvement of existing and development of new treatment targets and options is warranted.

The present review article covers recent developments in psychotherapy associated with the respective neuropsychological and brain alterations as well as highlights current and future pharmacotherapeutic options.

Several encouraging developments in the field of psychotherapy such as interventions targeting neurocognitive profiles or addressing reward processing, brain stimulation as well as pharmacological modulation of hormones, namely leptin, oxytocin, ghrelin and nesfatin-1 signaling might be - most likely as part of a multimodal treatment approach - efficacious in order to improve treatment of patients with anorexia nervosa, especially those with a severe course of disease as well as comorbidities. As anorexia nervosa represents a complex and severe mental disorder, it seems most likely that a combination and integration of different evidence-based treatment approaches and settings will contribute to an improved prognosis of this eating disorder. This should be further explored in future studies.

The notion that addiction is a "brain disorder" is widespread. However, there is a lack of evidence on the degree of disorder in terms of error processing in addiction. The present meta-analysis aimed at shedding light on this by comparing error-processes with populations with well-recognized brain disorders. We included 17 addiction and 32 neurological disorder studies that compared error-related negativity (ERN) or error positivity (Pe) amplitudes/latencies between experimental and healthy-control groups. Meta-regression analyses were performed for the intergroup comparison and other moderators. Both diagnoses were accompanied by a diminished ERN amplitude, although the degree of impairment was marginally larger in neurological disorders. Neurological disorders presented shorter ERN latencies than addiction when compared with controls. The two groups did not differ in Pe amplitude/latency. Except for a reduced ERN amplitude found along with aging, no other moderator contributed significantly to divergent findings about these four ERP indexes. The results support the brain disease model of addiction, while stressing the importance of quantifying the degrees of brain dysfunctions as a next step.

Cognitive control involves flexibly combining multiple sensory inputs with task-dependent goals during decision making. Several tasks involving conflicting sensory inputs and motor outputs have been proposed to examine cognitive control, including the Stroop, Flanker, and multi-source interference task. Because these tasks have been studied independently, it remains unclear whether the neural signatures of cognitive control reflect abstract control mechanisms or specific combinations of sensory and behavioral aspects of each task. To address these questions, we record invasive neurophysiological signals from 16 patients with pharmacologically intractable epilepsy and compare neural responses within and between tasks. Neural signals differ between incongruent and congruent conditions, showing strong modulation by conflicting task demands. These neural signals are mostly specific to each task, generalizing within a task but not across tasks. These results highlight the complex interplay between sensory inputs, motor outputs, and task demands underlying cognitive control processes.

Objective: To explore the effect of real-world fear on risky decision-making under certainty and uncertainty. Methods: This quasi-experimental study enrolled non-psychology undergraduate volunteers aged between 17 and 20 years old from the Preventive Medical Institute medical school in Xi'an. Participants were randomly divided into two groups, and each group received a two-stage crossover design intervention (of a calm and fearful situation) and completed the tasks of risky decision-making under uncertainty (the balloon analog risk task: BART) and certainty (the Cambridge gambling task: CGT), respectively. The primary outcomes included the behavioral impulsivity measured by the BART value, and the speed of decision-making, the quality of decisions, the adventure index, behavioral impulsivity, and risk adjustment measured by CGT. The secondary outcome was the concentration of cortisol in the saliva. Results: A total of 60 questionnaires and data were obtained from 60 participants (28 males and 32 females, aged 19.55 ± 0.75). Compared with the calm situation, participants were more likely to have a lower BART value (p = 0.013), slower speed of decision-making (p < 0.05), and higher adventure index (p = 0.018) in the fearful situation. The quality of decisions (p = 0.189), behavioral impulsivity index (p = 0.182), and risk adjustment (p = 0.063) between subjects in the fearful and calm situations were comparable. Furthermore, the mean value of the adventure index of CGT in male subjects was significantly higher than that in female subjects (p < 0.05), and the cortisol concentration in saliva during the fearful situation was significantly higher compared to the calm situation (p < 0.05). Conclusion: Fear might reduce behavioral impulsivity under uncertainty, and increase the adventure index under certainty in risky decision-making. Risky behavior might be influenced by gender: under certainty in risky decision-making, men were more adventurous. Additionally, fear increased the secretion of cortisol in saliva.

Although there is evidence that impaired executive functioning plays a role in addictive behavior, the longitudinal relationship between the two remains relatively unknown.

In a prospective-longitudinal community study, we tested the hypothesis that lower executive functioning is associated with more addictive behavior at one point in time and over time.

Three hundred and thirty-eight individuals (19-27 years, 59% female) from a random community sample were recruited into three groups: addictive disorders related to substances (n = 100) or to behaviors (n = 118), or healthy controls (n = 120). At baseline, participants completed nine executive function tasks from which a latent variable of general executive functioning (GEF) was derived. Addictive behavior (i.e., quantity and frequency of use, and number of DSM-5 criteria met) were assessed using standardized clinical interviews at baseline and three annual follow-ups. The trajectories of addictive behaviors were examined using latent growth curve modeling.

At baseline, we found weak to no evidence of an associations between GEF and addictive behavior. We found evidence for an association between a lower GEF at baseline and a higher increase in the quantity of use and a smaller decrease in frequency of use over time, but no evidence for an association with an increase in the number of DSM-5 criteria met.

Lower EFs appear to lead to a continuing loss of control over use, whereas addictive disorders may develop secondarily after a long period of risky use. Previous etiological models assuming lower EF as a direct vulnerability factor for addictive disorders need to be refined.

Cognitive control guides non-habitual, goal directed behaviors allowing us to flexibly adapt to ongoing demands. Previous work has suggested that multiple cognitive control processes exist that can be classed according to their action on present-oriented/external information versus future-oriented/internal information. These processes can be mapped onto the lateral prefrontal cortex (LPFC) such that increasingly rostral areas are involved in increasingly future-oriented/internal control processes. Whether and how such processes are organized to support goal-directed behavior remains unclear. On the one hand, the LPFC may flexibly adapt based upon demands. On the other hand, there may be a consistent control architecture such as a control hierarchy that generalizes across demands. Previous work using fMRI in humans during a comprehensive control task that engaged several control processes at once found that an area in mid-LPFC consistently exerted widespread influence throughout the LPFC. These data suggested that the mid-LPFC forms an apex of a putative control hierarchy. However, whether such an architecture generalizes across tasks remains to be tested. Here, we utilized a modified comprehensive control task designed to alter how control processes influence one another to test the generalizability of the LPFC control architecture. Univariate fMRI activations revealed distinct control-related activations relative to past work. Despite these changes, effective connectivity modeling revealed a directed architecture similar to previous findings with the mid-LPFC exerting the most widespread influences throughout LPFC. These results suggest that the fundamental control architecture of the LPFC is relatively fixed, and that different demands are accommodated through modulations of this fixed architecture.