The valuation system: a coordinate-based meta-analysis of BOLD fMRI experiments examining neural correlates of subjective value

Why it is good to communicate the bad: understanding the influence of message framing in persuasive communication on consumer decision-making processes

Introduction

One approach to bridging the gap between consumer intentions and behavior is persuasive communication to reinforce their intentions and thereby support their behavior change. Message framing has proven to be a useful, persuasive communication tool. However, message framing is considered more complicated than other types of framing because, in addition to concept-specific elements, it is also strongly influenced by and, in turn, influences emotions. Therefore, it is almost impossible for consumers to verbally express their attitudes, so the challenge is to explain and measure its impact. This research aims to help in this regard by suggesting a theoretical model to understand how message framing is processed from a consumer neuroscience perspective. More precisely, the factors that constitute message framing are systematized and built on a reflective-impulsive model and a neural emotion-cognition framework interpreted to explain the persuasive effects of message framing.

Method

A functional magnetic resonance imaging (fMRI) experiment is used to examine the effects of message framing for four different frame types that are hypothesized to affect consumer information processing differently.

Result

The results suggest that communication strategies should take into account the valence of the objects and the frame used. The behavioral results partially confirm the assumption that two types of information processing could take place, as suggested by the reflective-impulsive model. At the neural level, using the network perspective, the results show that certain brain regions primarily associated with emotional and cognitive interaction processes are active during processing, depending on the framing of the message.

Discussion

In cases of indirect avoidance value-consistent framing, it may be good to communicate the bad in the appropriate frame to influence information processing.

Dopamine regulates decision thresholds in human reinforcement learning in males

Dopamine fundamentally contributes to reinforcement learning, but recent accounts also suggest a contribution to specific action selection mechanisms and the regulation of response vigour. Here, we examine dopaminergic mechanisms underlying human reinforcement learning and action selection via a combined pharmacological neuroimaging approach in male human volunteers (n = 31, within-subjects; Placebo, 150 mg of the dopamine precursor L-dopa, 2 mg of the D2 receptor antagonist Haloperidol). We found little credible evidence for previously reported beneficial effects of L-dopa vs. Haloperidol on learning from gains and altered neural prediction error signals, which may be partly due to differences experimental design and/or drug dosages. Reinforcement learning drift diffusion models account for learning-related changes in accuracy and response times, and reveal consistent decision threshold reductions under both drugs, in line with the idea that lower dosages of D2 receptor antagonists increase striatal DA release via an autoreceptor-mediated feedback mechanism. These results are in line with the idea that dopamine regulates decision thresholds during reinforcement learning, and may help to bridge action selection and response vigor accounts of dopamine.

Mood Variability, Craving, and Substance Use Disorders: From Intrinsic Brain Network Connectivity to Daily Life Experience

BACKGROUND

Substance use disorders (SUDs) are major contributors to morbidity and mortality rates worldwide, and this global burden is attributable in large part to the chronic nature of these conditions. Increased mood variability might represent a form of emotional dysregulation that may have particular significance for the risk of relapse in SUD, independent of mood severity or diagnostic status. However, the neural biomarkers that underlie mood variability remain poorly understood.

METHODS

Ecological momentary assessment was used to assess mood variability, craving, and substance use in real time in 54 patients treated for addiction to alcohol, cannabis, or nicotine and 30 healthy control subjects. Such data were jointly examined relative to spectral dynamic causal modeling of effective brain connectivity within 4 networks involved in emotion generation and regulation.

RESULTS

Differences in effective connectivity were related to daily life variability of emotional states experienced by persons with SUD, and mood variability was associated with craving intensity. Relative to the control participants, effective connectivity was decreased for patients in the prefrontal control networks and increased in the emotion generation networks. Findings revealed that effective connectivity within the patient group was modulated by mood variability.

CONCLUSIONS

The intrinsic causal dynamics in large-scale neural networks underlying emotion regulation play a predictive role in a patient's susceptibility to experiencing mood variability (and, subsequently, craving) in daily life. The findings represent an important step toward informing interventional research through biomarkers of factors that increase the risk of relapse in persons with SUD.

Machine learning-based classifying of risk-takers and risk-aversive individuals using resting-state EEG data: A pilot feasibility study

BACKGROUND

Decision-making is vital in interpersonal interactions and a country's economic and political conditions. People, especially managers, have to make decisions in different risky situations. There has been a growing interest in identifying managers' personality traits (i.e., risk-taking or risk-averse) in recent years. Although there are findings of signal decision-making and brain activity, the implementation of an intelligent brain-based technique to predict risk-averse and risk-taking managers is still in doubt.

METHODS

This study proposes an electroencephalogram (EEG)-based intelligent system to distinguish risk-taking managers from risk-averse ones by recording the EEG signals from 30 managers. In particular, wavelet transform, a time-frequency domain analysis method, was used on resting-state EEG data to extract statistical features. Then, a two-step statistical wrapper algorithm was used to select the appropriate features. The support vector machine classifier, a supervised learning method, was used to classify two groups of managers using chosen features.

RESULTS

Intersubject predictive performance could classify two groups of managers with 74.42% accuracy, 76.16% sensitivity, 72.32% specificity, and 75% F1-measure, indicating that machine learning (ML) models can distinguish between risk-taking and risk-averse managers using the features extracted from the alpha frequency band in 10 s analysis window size.

CONCLUSIONS

The findings of this study demonstrate the potential of using intelligent (ML-based) systems in distinguish between risk-taking and risk-averse managers using biological signals.

Odour-imagery ability is linked to food craving, intake, and adiposity change in humans

It is well-known that food-cue reactivity (FCR) is positively associated with body mass index (BMI)1 and weight change2, but the mechanisms underlying these relationships are incompletely understood. One prominent theory of craving posits that the elaboration of a desired substance through sensory imagery intensifies cravings, thereby promoting consumption3. Olfaction is integral to food perception, yet the ability to imagine odours varies widely4. Here we test in a basic observational study whether this large variation in olfactory imagery drives FCR strength to promote adiposity in 45 adults (23 male). We define odour-imagery ability as the extent to which imagining an odour interferes with the detection of a weak incongruent odour (the 'interference effect'5). As predicted in our preregistration, the interference effect correlates with the neural decoding of imagined, but not real, odours. These perceptual and neural measures of odour imagery are in turn associated with FCR, defined by the rated craving intensity of liked foods and cue-potentiated intake. Finally, odour imagery exerts positive indirect effects on changes in BMI and body-fat percentage over one year via its influences on FCR. These findings establish odour imagery as a driver of FCR that in turn confers risk for weight gain.

Single-trial visually evoked potentials predict both individual choice and market outcomes

A central assumption in the behavioral sciences is that choice behavior generalizes enough across individuals that measurements from a sampled group can predict the behavior of the population. Following from this assumption, the unit of behavioral sampling or measurement for most neuroimaging studies is the individual; however, cognitive neuroscience is increasingly acknowledging a dissociation between neural activity that predicts individual behavior and that which predicts the average or aggregate behavior of the population suggesting a greater importance of individual differences than is typically acknowledged. For instance, past work has demonstrated that some, but not all, of the neural activity observed during value-based decision-making is able to predict not just individual subjects' choices but also the success of products on large, online marketplaces-even when those two behavioral outcomes deviate from one another-suggesting that some neural component processes of decision-making generalize to aggregate market responses more readily across individuals than others do. While the bulk of such research has highlighted affect-related neural responses (i.e. in the nucleus accumbens) as a better predictor of group-level behavior than frontal cortical activity associated with the integration of more idiosyncratic choice components, more recent evidence has implicated responses in visual cortical regions as strong predictors of group preference. Taken together, these findings suggest a role of neural responses during early perception in reinforcing choice consistency across individuals and raise fundamental scientific questions about the role sensory systems in value-based decision-making processes. We use a multivariate pattern analysis approach to show that single-trial visually evoked electroencephalographic (EEG) activity can predict individual choice throughout the post-stimulus epoch; however, a nominally sparser set of activity predicts the aggregate behavior of the population. These findings support an account in which a subset of the neural activity underlying individual choice processes can scale to predict behavioral consistency across people, even when the choice behavior of the sample does not match the aggregate behavior of the population.

Different topological patterns in structural covariance networks between high and low delay discounters

Introduction

People prefer immediate over future rewards because they discount the latter's value (a phenomenon termed "delay discounting," used as an index of impulsivity). However, little is known about how the preferences are implemented in brain in terms of the coordinated pattern of large-scale structural brain networks.

Methods

To examine this question, we classified high discounting group (HDG) and low discounting group (LDG) in young adults by assessing their propensity for intertemporal choice. We compared global and regional topological properties in gray matter volume-based structural covariance networks between two groups using graph theoretical analysis.

Results

HDG had less clustering coefficient and characteristic path length over the wide sparsity range than LDG, indicating low network segregation and high integration. In addition, the degree of small-worldness was more significant in HDG. Locally, HDG showed less betweenness centrality (BC) in the parahippocampal gyrus and amygdala than LDG.

Discussion

These findings suggest the involvement of structural covariance network topology on impulsive choice, measured by delay discounting, and extend our understanding of how impulsive choice is associated with brain morphological features.

Measuring utility with diffusion models

The drift diffusion model (DDM) is a prominent account of how people make decisions. Many of these decisions involve comparing two alternatives based on differences of perceived stimulus magnitudes, such as economic values. Here, we propose a consistent estimator for the parameters of a DDM in such cases. This estimator allows us to derive decision thresholds, drift rates, and subjective percepts (i.e., utilities in economic choice) directly from the experimental data. This eliminates the need to measure these values separately or to assume specific functional forms for them. Our method also allows one to predict drift rates for comparisons that did not occur in the dataset. We apply the method to two datasets, one comparing probabilities of earning a fixed reward and one comparing objects of variable reward value. Our analysis indicates that both datasets conform well to the DDM. We find that utilities are linear in probability and slightly convex in reward.

Development and validation of an fMRI-informed EEG model of reward-related ventral striatum activation

Reward processing is essential for our mental-health and well-being. In the current study, we developed and validated a scalable, fMRI-informed EEG model for monitoring reward processing related to activation in the ventral-striatum (VS), a significant node in the brain's reward system. To develop this EEG-based model of VS-related activation, we collected simultaneous EEG/fMRI data from 17 healthy individuals while listening to individually-tailored pleasurable music - a highly rewarding stimulus known to engage the VS. Using these cross-modal data, we constructed a generic regression model for predicting the concurrently acquired Blood-Oxygen-Level-Dependent (BOLD) signal from the VS using spectro-temporal features from the EEG signal (termed hereby VS-related-Electrical Finger Print; VS-EFP). The performance of the extracted model was examined using a series of tests that were applied on the original dataset and, importantly, an external validation dataset collected from a different group of 14 healthy individuals who underwent the same EEG/FMRI procedure. Our results showed that the VS-EFP model, as measured by simultaneous EEG, predicted BOLD activation in the VS and additional functionally relevant regions to a greater extent than an EFP model derived from a different anatomical region. The developed VS-EFP was also modulated by musical pleasure and predictive of the VS-BOLD during a monetary reward task, further indicating its functional relevance. These findings provide compelling evidence for the feasibility of using EEG alone to model neural activation related to the VS, paving the way for future use of this scalable neural probing approach in neural monitoring and self-guided neuromodulation.

Elevated reward, emotion, and memory region response to thin models predicts eating disorder symptom persistence: A prospective functional magnetic resonance imaging study

Because few studies have identified biological factors that predict the persistence of eating pathology, we tested the hypotheses that elevated responsivity of brain regions implicated in reward valuation to thin models and high-calorie binge foods would predict the persistence of eating pathology. We analyzed data from 146 women (Mage = 21.87 ± 3.81) with threshold or subthreshold anorexia nervosa, bulimia nervosa, binge eating disorder, or purging disorder who completed functional magnetic resonance imaging scans assessing neural response to thin models and binge foods at baseline, were randomized to two eating disorder treatments or a waitlist control condition and completed diagnostic interviews that assessed change in symptoms over 2.5-month follow-up. Elevated activation in regions associated with memory (parahippocampal gyrus r = .38; hippocampus r = .25) and with reward valuation and emotional salience (amygdala r = .35) in response to thin versus average-weight models predicted future persistence of an eating disorder symptom composite (all analyses controlled for treatment condition). Neural response to high-calorie binge foods did not predict the persistence of eating disorder symptoms. There was no evidence that either treatment moderated the relation of baseline neural responsivity to thin models to future persistence of eating disorder symptoms, though power for these post hoc analyses was limited. Results suggest that overvaluation of the thin ideal increases the risk for the persistence of eating disorder symptoms but provided no support for the hypothesis that overvaluation of high-calorie foods would predict symptom persistence. Results imply that treatments should seek to reduce the overvaluation of the thin ideal. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Connectome-based predictive modeling of smoking severity using individualized structural covariance network in smokers

Introduction

Abnormal interactions among distributed brain systems are implicated in the mechanisms of nicotine addiction. However, the relationship between the structural covariance network, a measure of brain connectivity, and smoking severity remains unclear. To fill this gap, this study aimed to investigate the relationship between structural covariance network and smoking severity in smokers.

Methods

A total of 101 male smokers and 51 male non-smokers were recruited, and they underwent a T1-weighted anatomical image scan. First, an individualized structural covariance network was derived via a jackknife-bias estimation procedure for each participant. Then, a data-driven machine learning method called connectome-based predictive modeling (CPM) was conducted to infer smoking severity measured with Fagerström Test for Nicotine Dependence (FTND) scores using an individualized structural covariance network. The performance of CPM was evaluated using the leave-one-out cross-validation and a permutation testing.

Results

As a result, CPM identified the smoking severity-related structural covariance network, as indicated by a significant correlation between predicted and actual FTND scores (r = 0.23, permutation p = 0.020). Identified networks comprised of edges mainly located between the subcortical-cerebellum network and networks including the frontoparietal default model and motor and visual networks.

Discussion

These results identified smoking severity-related structural covariance networks and provided a new insight into the neural underpinnings of smoking severity.

"Switching" between fast and slow processes is just reward-based branching

Shortcuts to goals are rewarded by faster attainment and punished by more frequent failure, so selection of the various kinds - heuristics, cached sequences (habits or macros), gut instincts - depends on reward history just like other kinds of choice. The speeds of shortcuts lie on continua along with speeds of deliberation, and these continua have no obvious separation points.

Cognitive and neural bases of visual-context-guided decision-making

Humans adjust their behavioral strategies based on feedback, a process that may depend on intrinsic preferences and contextual factors such as visual salience. In this study, we hypothesized that decision-making based on visual salience is influenced by habitual and goal-directed processes, which can be evidenced by changes in attention and subjective valuation systems. To test this hypothesis, we conducted a series of studies to investigate the behavioral and neural mechanisms underlying visual salience-driven decision-making. We first established the baseline behavioral strategy without salience in Experiment 1 (n = 21). We then highlighted the utility or performance dimension of the chosen outcome using colors in Experiment 2 (n = 30). We demonstrated that the difference in staying frequency increased along the salient dimension, confirming a salience effect. Furthermore, the salience effect was abolished when directional information was removed in Experiment 3 (n = 28), suggesting that the salience effect is feedback-specific. To generalize our findings, we replicated the feedback-specific salience effects using eye-tracking and text emphasis. The fixation differences between the chosen and unchosen values were enhanced along the feedback-specific salient dimension in Experiment 4 (n = 48) but unchanged after removing feedback-specific information in Experiment 5 (n = 32). Moreover, the staying frequency was correlated with fixation properties, confirming that salience guides attention deployment. Lastly, our neuroimaging study (Experiment 6, n = 25) showed that the striatum subregions encoded salience-based outcome evaluation, while the vmPFC encoded salience-based behavioral adjustments. The connectivity of the vmPFC-ventral striatum accounted for individual differences in utility-driven, whereas the vmPFC-dmPFC for performance-driven behavioral adjustments. Together, our results provide a neurocognitive account of how task-irrelevant visual salience drives decision-making by involving attention and the frontal-striatal valuation systems. PUBLIC SIGNIFICANCE STATEMENT: Humans may use the current outcome to make behavior adjustments. How this occurs may depend on stable individual preferences and contextual factors, such as visual salience. Under the hypothesis that visual salience determines attention and subsequently modulates subjective valuation, we investigated the underlying behavioral and neural bases of visual-context-guided outcome evaluation and behavioral adjustments. Our findings suggest that the reward system is orchestrated by visual context and highlight the critical role of attention and the frontal-striatal neural circuit in visual-context-guided decision-making that may involve habitual and goal-directed processes.

Neural responses to reward valence and magnitude from pre- to early adolescence

BACKGROUND

Neural activation during reward processing is thought to underlie critical behavioral changes that take place during the transition to adolescence (e.g., learning, risk-taking). Though literature on the neural basis of reward processing in adolescence is booming, important gaps remain. First, more information is needed regarding changes in functional neuroanatomy in early adolescence. Another gap is understanding whether sensitivity to different aspects of the incentive (e.g., magnitude and valence) changes during the transition into adolescence. We used fMRI from a large sample of preadolescent children to characterize neural responses to incentive valence vs. magnitude during anticipation and feedback, and their change over a period of two years.

METHODS

Data were taken from the Adolescent Cognitive and Brain DevelopmentSM (ABCD®) study release 3.0. Children completed the Monetary Incentive Delay task at baseline (ages 9-10) and year 2 follow-up (ages 11-12). Based on data from two sites (N = 491), we identified activation-based Regions of Interest (ROIs; e.g., striatum, prefrontal regions, etc.) that were sensitive to trial type (win $5, win $0.20, neutral, lose $0.20, lose $5) during anticipation and feedback phases. Then, in an independent subsample (N = 1470), we examined whether these ROIs were sensitive to valence and magnitude and whether that sensitivity changed over two years.

RESULTS

Our results show that most ROIs involved in reward processing (including the striatum, prefrontal cortex, and insula) are specialized, i.e., mainly sensitive to either incentive valence or magnitude, and this sensitivity was consistent over a 2-year period. The effect sizes of time and its interactions were significantly smaller (0.002≤η2≤0.02) than the effect size of trial type (0.06≤η2≤0.30). Interestingly, specialization was moderated by reward processing phase but was stable across development. Biological sex and pubertal status differences were few and inconsistent. Developmental changes were mostly evident during success feedback, where neural reactivity increased over time.

CONCLUSIONS

Our results suggest sub-specialization to valence vs. magnitude within many ROIs of the reward circuitry. Additionally, in line with theoretical models of adolescent development, our results suggest that the ability to benefit from success increases from pre- to early adolescence. These findings can inform educators and clinicians and facilitate empirical research of typical and atypical motivational behaviors during a critical time of development.

Economic value in the Brain: A meta-analysis of willingness-to-pay using the Becker-DeGroot-Marschak auction

Forming and comparing subjective values (SVs) of choice options is a critical stage of decision-making. Previous studies have highlighted a complex network of brain regions involved in this process by utilising a diverse range of tasks and stimuli, varying in economic, hedonic and sensory qualities. However, the heterogeneity of tasks and sensory modalities may systematically confound the set of regions mediating the SVs of goods. To identify and delineate the core brain valuation system involved in processing SV, we utilised the Becker-DeGroot-Marschak (BDM) auction, an incentivised demand-revealing mechanism which quantifies SV through the economic metric of willingness-to-pay (WTP). A coordinate-based activation likelihood estimation meta-analysis analysed twenty-four fMRI studies employing a BDM task (731 participants; 190 foci). Using an additional contrast analysis, we also investigated whether this encoding of SV would be invariant to the concurrency of auction task and fMRI recordings. A fail-safe number analysis was conducted to explore potential publication bias. WTP positively correlated with fMRI-BOLD activations in the left ventromedial prefrontal cortex with a sub-cluster extending into anterior cingulate cortex, bilateral ventral striatum, right dorsolateral prefrontal cortex, right inferior frontal gyrus, and right anterior insula. Contrast analysis identified preferential engagement of the mentalizing-related structures in response to concurrent scanning. Together, our findings offer succinct empirical support for the core structures participating in the formation of SV, separate from the hedonic aspects of reward and evaluated in terms of WTP using BDM, and show the selective involvement of inhibition-related brain structures during active valuation.

Self-evaluation of social-rank in socially anxious individuals associates with enhanced striatal reward function

BACKGROUND

Negative self-views, especially in the domain of power (i.e. social-rank), characterize social anxiety (SA). Neuroimaging studies on self-evaluations in SA have mainly focused on subcortical threat processing systems. Yet, self-evaluation may concurrently invoke diverse affective processing, as motivational systems related to desired self-views may also be activated. To investigate the conflictual nature that may accompany self-evaluation of certain social domains in SA, we examined brain activity related to both threat and reward processing.

METHODS

Participants (N = 74) differing in self-reported SA-severity underwent fMRI while completing a self-evaluation task, wherein they judged the self-descriptiveness of high- v. low-intensity traits in the domains of power and affiliation (i.e. social connectedness). Participants also completed two auxiliary fMRI tasks designated to evoke reward- and threat-related activations in the ventral striatum (VS) and amygdala, respectively. We hypothesized that self-evaluations in SA, particularly in the domain of power, involve aberrant brain activity related to both threat and reward processing.

RESULTS

SA-severity was more negatively associated with power than with affiliation self-evaluations. During self-evaluative judgment of high-power (e.g. dominant), SA-severity associated with increased activity in the VS and ventromedial prefrontal cortex. Moreover, SA-severity correlated with higher similarity between brain activity patterns activated by high-power traits and patterns activated by incentive salience (i.e. reward anticipation) in the VS during the reward task.

CONCLUSIONS

Our findings indicate that self-evaluation of high-power in SA involves excessive striatal reward-related activation, and pinpoint the downregulation of VS-VMPFC activity within such self-evaluative context as a potential neural outcome for therapeutic interventions.

Strengths of social ties modulate brain computations for third-party punishment

Costly punishment of social norm transgressors by third-parties has been considered as a decisive stage in the evolution of human cooperation. An important facet of social relationship knowledge concerns the strength of the social ties between individuals, as measured by social distance. Yet, it is unclear how the enforcement of social norms is influenced by the social distance between a third-party and a norm violator at the behavioral and the brain system levels. Here, we investigated how social distance between punishers and norm-violators influences third-party punishment. Participants as third-party punished norm violators more severely as social distance between them increased. Using model-based fMRI, we disentangled key computations contributing to third-party punishment: inequity aversion, social distance between participant and norm violator and integration of the cost to punish with these signals. Inequity aversion increased activity in the anterior cingulate cortex and bilateral insula, and processing social distance engaged a bilateral fronto-parietal cortex brain network. These two brain signals and the cost to punish were integrated in a subjective value signal of sanctions that modulated activity in the ventromedial prefrontal cortex. Together, our results reveal the neurocomputational underpinnings of third-party punishment and how social distance modulates enforcement of social norms in humans.

Frontopolar cortex represents complex features and decision value during choice between environments

Important decisions often involve choosing between complex environments that define future item encounters. Despite its importance for adaptive behavior and distinct computational challenges, decision-making research primarily focuses on item choice, ignoring environment choice altogether. Here we contrast previously studied item choice in ventromedial prefrontal cortex with lateral frontopolar cortex (FPl) linked to environment choice. Furthermore, we propose a mechanism for how FPl decomposes and represents complex environments during decision making. Specifically, we trained a choice-optimized, brain-naive convolutional neural network (CNN) and compared predicted CNN activation with actual FPl activity. We showed that the high-dimensional FPl activity decomposes environment features to represent the complexity of an environment to make such choice possible. Moreover, FPl functionally connects with posterior cingulate cortex for guiding environment choice. Further probing FPl's computation revealed a parallel processing mechanism in extracting multiple environment features.

Neural substrates on the judgment of sequential benefits and losses

People need to adapt to situations where they experience sequential benefits (or losses) to ensure survival. This study investigated the neural substrates involved in judgments of sequential benefits and losses. A total of 29 healthy volunteers participated in this study, in which they were asked to participate in a game of purchasing stocks while a magnetic resonance imaging scan was performed. This game had two main types of trials: (1) participants received four sequential financial benefits (or losses), and (2) participants received an equal amount of benefits (or losses) immediately. The results showed greater activation of the orbitofrontal cortex (OFC) when four benefits were received sequentially than when an equal amount of benefits was received immediately. This indicates that the OFC plays a crucial role in the process of mental integration of sequential benefits and interpretation of their valuations. It also showed greater activation of the dorsal striatum when four sequental losses were received than when an equal amount of losses was received immediately. However, it cannot be concluded that activation of the dorsal striatum reflects the differences between sequential and immediate losses, because previous studies have not confirmed this perspective. Therefore, it is necessary to clarify the function of the striatum in processing these losses.

Neural correlates of immediate versus delayed extinction when simultaneously varying the time of the test in humans

Anxiety disorders are effectively treated with exposure therapy based on the extinction of Pavlovian fear conditioning. Animal research indicates that both the timing of extinction and test are important factors to reduce the return of fear. However, empirical evidence in humans is incomplete and inconsistent. In this neuroimaging study, we, therefore, tested 103 young, healthy participants in a 2-factorial between-subjects design with the factors extinction group (immediate, delayed) and test group (+1 day and +7 days). Immediate extinction led to greater retention of fear memory at the beginning of extinction training indicated by increased skin conductance responses. A return of fear was observed in both extinction groups, with a trend toward a greater return of fear in immediate extinction. The return of fear was generally higher in groups with an early test. Neuroimaging results show successful cross-group fear acquisition and retention, as well as activation of the left nucleus accumbens during extinction training. Importantly, the delayed extinction group showed a larger bilateral nucleus accumbens activation during test. This nucleus accumbens finding is discussed in terms of salience, contingency, relief, and prediction error processing. It may imply that the delayed extinction group benefits more from the test as a new learning opportunity.

The neuroscience of social comparison and competition

The study of competition from a social comparison perspective offers valuable insights into the neuroscience of social judgment and decision making under uncertainty. When engaging in social comparison, individuals seek and assess information about similarities or differences between others and themselves, in large part to improve their self-evaluation. By providing information about one's relative position, abilities, outcomes, and more, social comparisons can inform competitive judgments and decisions. People reasonably turn to social comparisons to reduce uncertainty before, during, and after competition. However, the extent to which they do so and the behavioral consequences of social comparisons often fail to match the potential benefits of improved self-evaluation. An examination of the developing neuroscience of social comparison and competition in light of the behavioral evidence reveals numerous questions that merit further investigation.

Outcome Evaluation in Social Comparison: When You Deviate from Others

Individuals often measure their performance through social comparison. With the increase in the deviation degree between the self and others, the outcome evaluation of individuals' abilities in the social comparison context is still unknown. In the current study, we used a two self-outcomes × three others' outcomes within-participant design to investigate the effect of the deviation degree of the self versus others in the social comparison context. Event-related potentials (ERPs) were measured while participants performed a three-person dot estimation task with two other people. When participants received positive results, the amplitudes of feedback-related negativity (FRN) and P300 showed a significant gradient change in the degree of deviation between the self and others (even win vs. better win vs. best win conditions). However, we did not find a similar progressive effect when participants received negative results (even loss vs. worse loss vs. worst loss conditions). These findings suggest that the deviation degree affects the primary and later processing stages of social comparison outcomes only when individuals received positive outcomes, which may reflect how people develop an empathic response to others. In contrast, people tended to avoid deeper social comparison that threatened their self-esteem when they received negative outcomes.

DeePay: deep learning decodes EEG to predict consumer's willingness to pay for neuromarketing

There is an increasing demand within consumer-neuroscience (or neuromarketing) for objective neural measures to quantify consumers' subjective valuations and predict responses to marketing campaigns. However, the properties of EEG raise difficulties for these aims: small datasets, high dimensionality, elaborate manual feature extraction, intrinsic noise, and between-subject variations. We aimed to overcome these limitations by combining unique techniques of Deep Learning Networks (DLNs), while providing interpretable results for neuroscientific and decision-making insight. In this study, we developed a DLN to predict subjects' willingness to pay (WTP) based on their EEG data. In each trial, 213 subjects observed a product's image, from 72 possible products, and then reported their WTP for the product. The DLN employed EEG recordings from product observation to predict the corresponding reported WTP values. Our results showed 0.276 test root-mean-square-error and 75.09% test accuracy in predicting high vs. low WTP, surpassing other models and a manual feature extraction approach. Network visualizations provided the predictive frequencies of neural activity, their scalp distributions, and critical timepoints, shedding light on the neural mechanisms involved with evaluation. In conclusion, we show that DLNs may be the superior method to perform EEG-based predictions, to the benefit of decision-making researchers and marketing practitioners alike.

Neurons in human pre-supplementary motor area encode key computations for value-based choice

Adaptive behaviour in real-world environments requires that choices integrate several variables, including the novelty of the options under consideration, their expected value and uncertainty in value estimation. Here, to probe how integration over decision variables occurs during decision-making, we recorded neurons from the human pre-supplementary motor area (preSMA), ventromedial prefrontal cortex and dorsal anterior cingulate. Unlike the other areas, preSMA neurons not only represented separate pre-decision variables for each choice option but also encoded an integrated utility signal for each choice option and, subsequently, the decision itself. Post-decision encoding of variables for the chosen option was more widely distributed and especially prominent in the ventromedial prefrontal cortex. Our findings position the human preSMA as central to the implementation of value-based decisions.

Anxiety as a disorder of uncertainty: implications for understanding maladaptive anxiety, anxious avoidance, and exposure therapy

In cognitive-behavioral conceptualizations of anxiety, exaggerated threat expectancies underlie maladaptive anxiety. This view has led to successful treatments, notably exposure therapy, but is not consistent with the empirical literature on learning and choice alterations in anxiety. Empirically, anxiety is better described as a disorder of uncertainty learning. How disruptions in uncertainty lead to impairing avoidance and are treated with exposure-based methods, however, is unclear. Here, we integrate concepts from neurocomputational learning models with clinical literature on exposure therapy to propose a new framework for understanding maladaptive uncertainty functioning in anxiety. Specifically, we propose that anxiety disorders are fundamentally disorders of uncertainty learning and that successful treatments, particularly exposure therapy, work by remediating maladaptive avoidance from dysfunctional explore/exploit decisions in uncertain, potentially aversive situations. This framework reconciles several inconsistencies in the literature and provides a path forward to better understand and treat anxiety.

A Fluid Self-Concept: How the Brain Maintains Coherence and Positivity across an Interconnected Self-Concept While Incorporating Social Feedback

People experience instances of social feedback as interdependent with potential implications for their entire self-concept. How do people maintain positivity and coherence across the self-concept while updating self-views from feedback? We present a network model describing how the brain represents the semantic dependency relations among traits and uses this information to avoid an overall loss of positivity and coherence. Both male and female human participants received social feedback during a self-evaluation task while undergoing functional magnetic resonance imaging. We modeled self-belief updating by incorporating a reinforcement learning model within the network structure. Participants learned more rapidly from positive than negative feedback and were less likely to change self-views for traits with more dependencies in the network. Further, participants back propagated feedback across network relations while retrieving prior feedback on the basis of network similarity to inform ongoing self-views. Activation in ventromedial prefrontal cortex (vmPFC) reflected the constrained updating process such that positive feedback led to higher activation and negative feedback to less activation for traits with more dependencies. Additionally, vmPFC was associated with the novelty of a trait relative to previously self-evaluated traits in the network, and angular gyrus was associated with greater certainty for self-beliefs given the relevance of prior feedback. We propose that neural computations that selectively enhance or attenuate social feedback and retrieve past relevant experiences to guide ongoing self-evaluations may support an overall positive and coherent self-concept.SIGNIFICANCE STATEMENT We humans experience social feedback throughout our lives, but we do not dispassionately incorporate feedback into our self-concept. The implications of feedback for our entire self-concept plays a role in how we either change or retain our prior self-beliefs. In a neuroimaging study, we find that people are less likely to change their beliefs from feedback when the feedback has broader implications for the self-concept. This resistance to change is reflected in processing in the ventromedial prefrontal cortex, a region that is central to self-referential and social cognition. These results are broadly applicable given the role that maintaining a positive and coherent self-concept plays in promoting mental health and development throughout the lifespan.

Task state representations in vmPFC mediate relevant and irrelevant value signals and their behavioral influence

The ventromedial prefrontal-cortex (vmPFC) is known to contain expected value signals that inform our choices. But expected values even for the same stimulus can differ by task. In this study, we asked how the brain flexibly switches between such value representations in a task-dependent manner. Thirty-five participants alternated between tasks in which either stimulus color or motion predicted rewards. We show that multivariate vmPFC signals contain a rich representation that includes the current task state or context (motion/color), the associated expected value, and crucially, the irrelevant value of the alternative context. We also find that irrelevant value representations in vmPFC compete with relevant value signals, interact with task-state representations and relate to behavioral signs of value competition. Our results shed light on vmPFC's role in decision making, bridging between its role in mapping observations onto the task states of a mental map, and computing expected values for multiple states.

Relation of Overweight/Obesity to Reward Region Response to Food Reward and the Moderating Effects of Parental History of Eating Pathology in Adolescent Females

OBJECTIVE

To test whether overweight/obesity is associated with an elevated reward region response to milkshake cues and a low reward region response to milkshake receipt. To test whether the risk for eating pathology moderates the effects of weight status on the neural response to milkshake cues and milkshake receipt.

METHOD

The current study used functional magnetic resonance imaging (fMRI) to examine the neuronal responses of female adolescents (n = 80; M age = 14.6 ± 0.9; M BMI = 21.9 ± 3.6; 41% with a biological parental history of eating pathology) during a food receipt paradigm.

RESULTS

Females with overweight/obesity showed a greater ventromedial prefrontal cortex (vmPFC), and ventral anterior cingulate (ACC) response to milkshake cues and a greater ventral striatum, subgenual ACC, and dorsomedial prefrontal cortex response to milkshake receipt than those with a healthy weight. Females with overweight/obesity plus a parental history of eating pathology showed a greater vmPFC/medial orbitofrontal cortex response to milkshake cues than those without a parental history of eating pathology and those with a healthy weight. Females with overweight/obesity and without a parental history of eating pathology showed a greater thalamus and striatum response to milkshake receipt.

CONCLUSIONS

Overweight/obesity is associated with an elevated reward region response to palatable food cues and food receipt. A risk for eating pathology enhances the reward region response to food cues in those with excess weight.

Connecting Circuits with Networks in Addiction Neuroscience: A Salience Network Perspective

Human neuroimaging has demonstrated the existence of large-scale functional networks in the cerebral cortex consisting of topographically distant brain regions with functionally correlated activity. The salience network (SN), which is involved in detecting salient stimuli and mediating inter-network communication, is a crucial functional network that is disrupted in addiction. Individuals with addiction display dysfunctional structural and functional connectivity of the SN. Furthermore, while there is a growing body of evidence regarding the SN, addiction, and the relationship between the two, there are still many unknowns, and there are fundamental limitations to human neuroimaging studies. At the same time, advances in molecular and systems neuroscience techniques allow researchers to manipulate neural circuits in nonhuman animals with increasing precision. Here, we describe attempts to translate human functional networks to nonhuman animals to uncover circuit-level mechanisms. To do this, we review the structural and functional connections of the salience network and its homology across species. We then describe the existing literature in which circuit-specific perturbation of the SN sheds light on how functional cortical networks operate, both within and outside the context of addiction. Finally, we highlight key outstanding opportunities for mechanistic studies of the SN.

Down-Regulation of Tinnitus Negative Valence via Concurrent HD-tDCS and PEI Technique: A Pilot Study

Around 30% of the general population experience subjective tinnitus, characterized by conscious attended awareness perception of sound without an external source. Clinical distress tinnitus is more than just experiencing a phantom sound, as it can be highly disruptive and debilitating, leading those affected to seek clinical help. Effective tinnitus treatments are crucial for psychological well-being, but our limited understanding of the underlying neural mechanisms and a lack of a universal cure necessitate further treatment development. In light of the neurofunctional tinnitus model predictions and transcranial electrical stimulation, we conducted an open-label, single-arm, pilot study that utilized high-definition transcranial direct current stimulation (HD-tDCS) concurrent with positive emotion induction (PEI) techniques for ten consecutive sessions to down-regulate tinnitus negative valence in patients with clinical distress tinnitus. We acquired resting-state functional magnetic resonance imaging scans of 12 tinnitus patients (7 females, mean age = 51.25 ± 12.90 years) before and after the intervention to examine resting-state functional connectivity (rsFC) alterations in specific seed regions. The results showed reduced rsFC at post-intervention between the attention and emotion processing regions as follows: (1) bilateral amygdala and left superior parietal lobule (SPL), (2) left amygdala and right SPL, (3) bilateral dorsolateral prefrontal cortex (dlPFC) and bilateral pregenual anterior cingulate cortex (pgACC), and (4) left dlPFC and bilateral pgACC (FWE corrected p < 0.05). Furthermore, the post-intervention tinnitus handicap inventory scores were significantly lower than the pre-intervention scores (p < 0.05). We concluded that concurrent HD-tDCS and PEI might be effective in reducing tinnitus negative valence, thus alleviating tinnitus distress.

Value-based neural representations predict social decision preferences

Social decision-making is omnipresent in everyday life, carrying the potential for both positive and negative consequences for the decision-maker and those closest to them. While evidence suggests that decision-makers use value-based heuristics to guide choice behavior, very little is known about how decision-makers' representations of other agents influence social choice behavior. We used multivariate pattern expression analyses on fMRI data to understand how value-based processes shape neural representations of those affected by one's social decisions and whether value-based encoding is associated with social decision preferences. We found that stronger value-based encoding of a given close other (e.g. parent) relative to a second close other (e.g. friend) was associated with a greater propensity to favor the former during subsequent social decision-making. These results are the first to our knowledge to explicitly show that value-based processes affect decision behavior via representations of close others.

Temporally organized representations of reward and risk in the human brain

The value and uncertainty associated with choice alternatives constitute critical features along which decisions are made. While the neural substrates supporting reward and risk processing have been investigated, the temporal organization by which these computations are encoded remains elusive. Here we leverage the high spatiotemporal precision of intracranial electroencephalography (iEEG) to uncover how representations of decision-related computations unfold in time. We present evidence of locally distributed representations of reward and risk variables that are temporally organized across multiple regions of interest. Reward outcome representations across wide-spread regions follow a temporally cascading order along the anteroposterior axis of the brain. In contrast, expected value can be decoded from multiple regions at the same time, and error signals in both reward and risk domains reflect a mixture of sequential and parallel encoding. We highlight the role of the anterior insula in generalizing between reward prediction error (RePE) and risk prediction error (RiPE), within which the encoding of RePE in the distributed iEEG signal predicts RiPE. Together our results emphasize the utility of uncovering temporal dynamics in the human brain for understanding how computational processes critical for value-based decisions under uncertainty unfold.

Striatal hypoactivation during monetary loss anticipation in individuals with substance use disorders in a heterogenous urban American Indian sample

Research suggests that disproportionate exposure to risk factors places American Indian (AI) peoples at higher risk for substance use disorders (SUD). Although SUD is linked to striatal prioritization of drug rewards over other appetitive stimuli, there are gaps in the literature related to the investigation of aversive valuation processing, and inclusion of AI samples. To address these gaps, this study compared striatal anticipatory gain and loss processing between AI-identified with SUD (SUD+; n = 52) and without SUD (SUD-; n = 35) groups from the Tulsa 1000 study who completed a monetary incentive delay (MID) task during functional magnetic resonance imaging. Results indicated that striatal activations in the nucleus accumbens (NAcc), caudate, and putamen were greatest for anticipating gains (ps < 0.001) but showed no group differences. In contrast to gains, the SUD+ exhibited lower NAcc (p = .01, d =0.53) and putamen (p = .04, d =0.40) activation to anticipating large losses than the comparison group. Within SUD+ , lower striatal responses during loss anticipations were associated with slower MID reaction times (NAcc: r = -0.43; putamen: r = -0.35) during loss trials. This is among the first imaging studies to examine underlying neural mechanisms associated with SUD within AIs. Attenuated loss processing provides initial evidence of a potential mechanism wherein blunted prediction of aversive consequences may be a defining feature of SUD that can inform future prevention and intervention targets.

Age-related differences in the social associative learning of trust information

Trust is a key component of social interaction. Older adults, however, often exhibit excessive trust relative to younger adults. One explanation is that older adults may learn to trust differently than younger adults. Here, we examine how younger (N = 33) and older adults (N = 30) learn to trust over time. Participants completed a classic iterative trust game with 3 partners. Younger and older adults shared similar amounts but differed in how they shared money. Compared to younger adults, older adults invested more with untrustworthy partners and less with trustworthy partners. As a group, older adults displayed less learning than younger adults. However, computational modeling suggests that this is not because older adults learn differently from positive and negative feedback than younger adults. Model-based fMRI analyses revealed several age- and learning-related differences in neural processing. Specifically, we found that older learners (N = 19), relative to older non-learners (N = 11), had greater reputation-related activity in metalizing/memory areas while making their decisions. Collectively, these findings suggest that older adult learners use social cues differently from non-learners.

Inhibitory control as a potential treatment target for obesity

OBJECTIVES

Strong reward responsiveness to food and insufficient inhibitory control are thought to be implicated in the development and maintenance of obesity. This narrative review addresses the role of inhibitory control in obesity and weight loss, and in how far inhibitory control is a promising target for weight loss interventions.

METHODS

PubMed, Web of Science, and Google Scholar were searched for papers up to May 2021. 41 papers were included.

RESULTS

Individuals with obesity have poorer food-specific inhibitory control, particularly when hungry, and less concurrent activation of inhibitory brain areas. Moreover, this was strongly predictive of future weight gain. More activation of inhibitory brain areas, on the other hand, was predictive of weight loss: individuals with successful weight loss initially show inhibitory brain activity comparable to that of normal weight individuals. When successful weight maintenance is achieved for at least 1 year, this inhibitory activity is further increased. Interventions targeting inhibitory control in obese individuals have divergent effects. Firstly, food-specific inhibitory control training is particularly effective for people with low inhibitory control and high BMI. Secondly, neuromodulation paradigms are rather heterogeneous: although rTMS to the left dorsolateral prefrontal cortex induced some weight-loss, multiple sessions of tDCS reduced food consumption (desire) and induced weight loss in two thirds of the papers. Thirdly, neurofeedback results in successful upregulation of brain activity and connectivity, but occasionally leads to increased food intake. In conclusion, inhibitory control is implicated in obesity. It can be targeted to promote weight loss although major weight losses have not been achieved.

Prenatal androgen influences on the brain: A review, critique, and illustration of research on congenital adrenal hyperplasia

Sex hormones, especially androgens, contribute to sex and gender differences in the brain and behavior. Organizational effects are particularly important because they are thought to be permanent, reflecting hormone exposure during sensitive periods of development. In human beings, they are often studied with natural experiments in which sex hormones are dissociated from other biopsychosocial aspects of development, such as genes and experiences. Indeed, the greatest evidence for organizational effects on sex differences in human behavior comes from studies of females with congenital adrenal hyperplasia (CAH), who have heightened prenatal androgen exposure, female-typical rearing, and masculinized toy play, activity and career interests, spatial skills, and some personal characteristics. Interestingly, however, neuroimaging studies of females with CAH have revealed few neural mechanisms underlying these hormone-behavior links, with the exception of emotion processing; studies have instead shown reduced gray matter volumes and reduced white matter integrity most consistent with other disease-related processes. The goals of this narrative review are to: (a) describe methods for studying prenatal androgen influences, while offering a brief overview of behavioral outcomes; (b) provide a critical methodological review of neuroimaging research on females with CAH; (c) present an illustrative analysis that overcomes methodological limitations of previous work, focusing on person-specific neural reward networks (and their associations with sensation seeking) in women with CAH and their unaffected sisters in order to inform future research questions and approaches that are most likely to reveal organizational hormone effects on brain structure and function.

Neural correlates of changing food choices while bypassing values

Current theories suggest that altering choices requires value modification. To investigate this, normal-weight female participants' food choices and values were tested before and after an approach-avoidance training (AAT), while neural activity was recorded during the choice task using functional magnetic resonance imaging (fMRI). During AAT, participants consistently approached low- while avoiding high-calorie food cues. AAT facilitated low-calorie food choices, leaving food values unchanged. Instead, we observed a shift in indifference points, indicating the decreased contribution of food values in food choices. Training-induced choice shifts were associated with increased activity in the posterior cingulate cortex (PCC). In contrast, the medial PFC activity was not changed. Additionally, PCC grey matter density predicted individual differences in training-induced functional changes, suggesting anatomic predispositions to training impact. Our findings demonstrate neural mechanisms underlying choice modulation independent of valuation-related processes, with substantial theoretical significance for decision-making frameworks and translational implications for health-related decisions resilient to value shifts.

You can touch this! Brain correlates of aesthetic processing of active fingertip exploration of material surfaces

The haptic exploration and aesthetic processing of all kinds of materials' surfaces are part of everyday life. In the present study, functional near-infrared spectroscopy (fNIRS) was used to investigate the brain correlates of active fingertip exploration of material surfaces and subsequent aesthetic judgments of their pleasantness (feels good or bad?). In absence of other sensory modalities, individuals (n = 21) performed lateral movements on a total of 48 textile and wood surfaces varying in terms of their roughness. Behavioral results confirmed the influence of the stimuli's roughness on aesthetic judgments, with smoother textures being rated as feeling better than rough textures. At the neural level, fNIRS activation results revealed an overall increased engagement of the contralateral sensorimotor areas as well as left prefrontal areas. Moreover, the perceived pleasantness modulated specific activations of left prefrontal areas with increasing pleasantness showing greater activations of these regions. Interestingly, this positive relationship between the individual aesthetic judgments and brain activity was most pronounced for smooth woods. These results demonstrate that positively valenced touch by actively exploring material surfaces is linked to left prefrontal activity and extend previous findings of affective touch underlying passive movements on hairy skin. We suggest that fNIRS can be a valuable tool to provide new insights in the field of experimental aesthetics.

The traps of adaptation: Addiction as maladaptive referent-dependent evaluation

Referent-dependent evaluation theories propose that the ongoing context influences how the brain attributes value to stimuli. What are the implications of these theories for understanding addiction? The paper asks this question by casting this disorder as a form of maladaptive referent-dependent evaluation. Specifically, addiction is proposed to arise from the establishment of an excessive reference point following repeated drug consumption. Several key aspects of the disorder emerge from this perspective, including withdrawal, tolerance, enhanced craving, negative mood, and diminished stimulus discriminability. As highlighted in the paper, this formulation has important analogies with classical accounts of addiction, such as set point theories and associative learning theories. Moreover, this picture fits with the pattern of striatal dopaminergic activity observed in addiction, a key neural signature of the disorder. Overall, the referent-dependent evaluation approach emerges as a useful add-on to the theoretical toolkit adopted to interpret addiction. This also supports the idea that referent-dependent evaluation might offer a general framework to understand various disorders characterised by disrupted motivation.

Evidence that a novel transdiagnostic eating disorder treatment reduces reward region response to the thin beauty ideal and high-calorie binge foods

BACKGROUND

Findings from brain imaging studies with small samples can show limited reproducibility. Thus, we tested whether the evidence that a transdiagnostic eating disorder treatment reduces responsivity of brain valuation regions to thin models and high-calorie binge foods, the intervention targets, from a smaller earlier trial emerged when we recruited additional participants.

METHODS

Women with DSM-5 eating disorders (N = 138) were randomized to the dissonance-based body project treatment (BPT) or a waitlist control condition and completed functional magnetic resonance imaging (fMRI) scans assessing neural response to thin models and high-calorie foods at pretest and posttest.

RESULTS

BPT v. control participants showed significantly greater reductions in responsivity of regions implicated in reward valuation (caudate) and attentional motivation (precuneus) to thin v. average-weight models, echoing findings from the smaller sample. Data from this larger sample also provided novel evidence that BPT v. control participants showed greater reductions in responsivity of regions implicated in reward valuation (ventrolateral prefrontal cortex) and food craving (hippocampus) to high-calorie binge foods v. low-calorie foods, as well as significantly greater reductions in eating disorder symptoms, abstinence from binge eating and purging behaviors, palatability ratings for high calorie foods, monetary value for high-calorie binge foods, and significantly greater increases in attractiveness ratings of average weight models.

CONCLUSIONS

Results from this larger sample provide evidence that BPT reduces valuation of the thin ideal and high-calorie binge foods, the intervention targets, per objective brain imaging data, and produces clinically meaningful reductions in eating pathology.

Neural correlates associated with conformity in adolescent and young adult men

Social influence affects us throughout our lives, shaping our attitudes, behaviors, and preferences. Thus, the current study aimed to examine whether key age groups (adolescence versus young adulthood) were associated with differences in neural correlates associated with processing social feedback and conformity (i.e., conflict detection, positive valuation, and mentalizing) among young men. We recruited 153 participants across 5 studies, who completed a social influence task during an fMRI scan. Overall, participants were more likely to conform by changing their ratings when misaligned with others, and adolescents were more likely to conform when misaligned (compared to aligned) with others compared to young adults. Further, we found that adolescents showed increased activity in mentalizing (TPJ, dmPFC) and positive valuation regions (VS, vmPFC), compared to young adults, in response to misalignment with others. In contrast, young adults showed increased activity in conflict detection regions (AI, dACC) when exposed to feedback that they were misaligned with others and when conforming to that feedback. Overall, our results offer initial evidence that adolescent and young adult men engage different neural processes when they find out they are misaligned with others and when conforming to the recommendations of others, and this difference appears to track with brain responses in conflict detection, mentalizing and value regions. DATA STATEMENT: Raw data and analysis codes are available upon request.

An altered reward system characterizes chronic migraine with medication overuse headache

BACKGROUND

Medication overuse headache shares several characteristics with substance use disorders. However, key features of substance use disorders such as increased impulsivity and alterations in reward processing remain little explored in medication overuse headache.

METHODS

Temporal discounting and impulsive decision making behavior and the associated brain mechanisms were assessed in 26 chronic migraine patients with medication overuse headache and in 28 healthy controls. Regions-of-interest analyses were first performed for task-related regions, namely the ventral striatum and the ventromedial and dorsomedial prefrontal cortices. Resting-state functional connectivity between these regions were then explored. An additional 27 chronic migraine patients without medication overuse headache were included for comparison in the latter analysis.

RESULTS

Patients with medication overuse headache showed steeper temporal discounting behavior than healthy controls. They also showed weaker subjective value representations in the dorsomedial prefrontal cortex, when accepting larger delayed rewards, and in ventral striatum and ventromedial prefrontal cortex, when accepting the smaller immediate reward. Resting-state functional connectivity was reduced among the valuation regions when comparing patients with medication overuse headache to the other two control groups.

CONCLUSIONS

Patients with medication overuse headache were characterized by altered processing and dysconnectivity in the reward system during intertemporal choices and in the resting-state.

Glutamate levels in the ventromedial prefrontal cortex and resting‐state functional connectivity within reward circuits in alcohol‐dependent patients

Great progress has been made in understanding the neural mechanisms associated with alcohol-dependent (AD) patients. However, the interactions within the reward circuits of the patients need further exploration. Glutamatergic projections from the prefrontal cortex to some brain regions are present in the reward circuit. However, little is known about the potential implications of glutamate levels in the prefrontal cortex on abnormal interactions within reward circuits in AD patients. To determine the potential roles of reward circuits in drinking, we investigated differences in resting-state functional connectivity (RSFC) and multivariate Granger causality analysis between 20 AD patients and 20 healthy controls (HC). The neuroimaging findings were then correlated with clinical variables (alcohol use disorder identification test). The ventromedial prefrontal cortex (VmPFC) is believed to play a critical role in addiction disorders, and glutamatergic projections from the prefrontal cortex to several regions of the brain are present in reward circuits. Proton magnetic resonance spectroscopy was also performed to assess the difference in glutamate levels in VmPFC between AD patients and HC. The results showed that the strength of functional connectivity in the reward circuit was generally attenuated in AD patients, and the reciprocal enhancement of activity between the right insula, left thalamus and VmPFC was found to be significantly greater in AD patients. It is worth noting that although glutamate levels in the VmPFC did not show significant differences between the two groups, the level of glutamate in the VmPFC was significantly correlated with RSFC. We hope that the current findings will help us to develop new intervention models based on the important role of the VmPFC in AD.

The relationship between self, value-based reward, and emotion prioritisation effects

People show systematic biases in perception, memory, attention, and decision-making to prioritise information related to self, reward, and positive emotion. A long-standing set of experimental findings points towards putative common properties of these effects. However, the relationship between them remains largely unknown. Here, we addressed this question by assessing and linking these prioritisation effects generated by a common associative matching procedure in three experiments. Self, reward, and positive emotion prioritisation effects were assessed using cluster and shift function analyses to explore and test associations between these effects across individuals. Cluster analysis revealed two distinct patterns of the relationship between the biases. Individuals with faster responses showed a smaller reward and linear positive association between reward and emotion biases. Individuals with slower responses demonstrated a large reward and no association between reward and emotion biases. No evidence of the relationship between self and value-based reward or positive emotion prioritisation effects was found among the clusters. A shift function indicated a partial dominance of high-reward over low-reward distributions at later processing stages in participants with slower but not faster responses. Full stochastic dominance of self-relevance over others and positive over neutral emotion was pertinent to each subgroup of participants. Our findings suggest the independent origin of the self-prioritisation effect. In contrast, commonalities in cognitive mechanisms supporting value-based reward and positive emotion processing are subject to individual differences. These findings add important evidence to a steadily growing research base about the relationship between basic behavioural drivers.

Episodic Memory Retrieval Affects the Onset and Dynamics of Evidence Accumulation during Value-based Decisions

In neuroeconomics, there is much interest in understanding simple value-based choices where agents choose between visually presented goods, comparable to a shopping scenario in a supermarket. However, many everyday decisions are made in the physical absence of the considered goods, requiring agents to recall information about the goods from memory. Here, we asked whether and how this reliance on an internal memory representation affects the temporal dynamics of decision making on a cognitive and neural level. Participants performed a remember-and-decide task in which they made simple purchasing decisions between money offers and snack items while undergoing EEG. Snack identity was presented either visually (value trials) or had to be recalled from memory (memory trials). Behavioral data indicated comparable choice consistency across both trial types, but considerably longer RTs in memory trials. Drift-diffusion modeling suggested that this RT difference was because of longer nondecision time of decision processes as well as altered evidence accumulation dynamics (lower accumulation rate and higher decision threshold). The nondecision time effect was supported by a delayed onset of the lateralized readiness potential. These results show that both decision and nondecision processes are prolonged when participants need to resort to internal memory representations during value-based decisions.

Re-evaluating frontopolar and temporoparietal contributions to detection and discrimination confidence

Previously, we identified a subset of regions where the relation between decision confidence and univariate functional magnetic resonance imaging (fMRI) activity was quadratic, with stronger activation for both high and low compared with intermediate levels of confidence. We further showed that, in a subset of these regions, this quadratic modulation appeared only for confidence in detection decisions about the presence or absence of a stimulus, and not for confidence in discrimination decisions about stimulus identity (Mazor et al. 2021). Here, in a pre-registered follow-up experiment, we sought to replicate our original findings and identify the origins of putative detection-specific confidence signals by introducing a novel asymmetric-discrimination condition. The new condition required discriminating two alternatives but was engineered such that the distribution of perceptual evidence was asymmetric, just as in yes/no detection. We successfully replicated the quadratic modulation of subjective confidence in prefrontal, parietal and temporal cortices. However, in contrast with our original report, this quadratic effect was similar in detection and discrimination responses, but stronger in the novel asymmetric-discrimination condition. We interpret our findings as weighing against the detection-specificity of confidence signatures and speculate about possible alternative origins of a quadratic modulation of decision confidence.

Non-invasive sensory neuromodulation in epilepsy: Updates and future perspectives

Epilepsy, one of the most common neurological disorders, often is not well controlled by current pharmacological and surgical treatments. Sensory neuromodulation, including multi-sensory stimulation, auditory stimulation, olfactory stimulation, is a kind of novel noninvasive mind-body intervention and receives continued attention as complementary safe treatment of epilepsy. In this review, we summarize the recent advances of sensory neuromodulation, including enriched environment therapy, music therapy, olfactory therapy, other mind-body interventions, for the treatment of epilepsy based on the evidence from both clinical and preclinical studies. We also discuss their possible anti-epileptic mechanisms on neural circuit level and propose perspectives on possible research directions for future studies.

Neural valuation of rewards and punishments in posttraumatic stress disorder: a computational approach

Posttraumatic stress disorder (PTSD) is associated with changes in fear learning and decision-making, suggesting involvement of the brain's valuation system. Here we investigate the neural mechanisms of subjective valuation of rewards and punishments in combat veterans. In a functional MRI study, male combat veterans with a wide range of posttrauma symptoms (N = 48, Clinician Administered PTSD Scale, CAPS-IV) made a series of choices between sure and uncertain monetary gains and losses. Activity in the ventromedial prefrontal cortex (vmPFC) during valuation of uncertain options was associated with PTSD symptoms, an effect which was consistent for gains and losses, and specifically driven by numbing symptoms. In an exploratory analysis, computational modeling of choice behavior was used to estimate the subjective value of each option. The neural encoding of subjective value varied as a function of symptoms. Most notably, veterans with PTSD exhibited enhanced representations of the saliency of gains and losses in the neural valuation system, especially in ventral striatum. These results suggest a link between the valuation system and the development and maintenance of PTSD, and demonstrate the significance of studying reward and punishment processing within subject.

Neural bases of frustration-aggression theory: A multi-domain meta-analysis of functional neuroimaging studies

BACKGROUND

Early evidence suggests that unexpected non-reward may increase the risk for aggressive behaviors. Despite the growing interest in understanding brain functions that may be implicated in aggressive behaviors, the neural processes underlying such frustrative events remain largely unknown. Furthermore, meta-analytic results have produced discrepant results, potentially due to substantial differences in the definition of anger/aggression constructs.

METHODS

Therefore, we conducted a coordinate-based meta-analysis, using the activation likelihood estimation algorithm, on neuroimaging studies examining reward omission and retaliatory behaviors in healthy subjects. Conjunction analyses were further examined to discover overlapping brain activations across these meta-analytic maps.

RESULTS

Frustrative non-reward deactivated the orbitofrontal cortex, ventral striatum and posterior cingulate cortex, whereas increased activations were observed in midcingulo-insular regions. Retaliatory behaviors recruited the left fronto-insular and anterior midcingulate cortices, the dorsal caudate and the primary somatosensory cortex. Conjunction analyses revealed that both strongly activated midcingulo-insular regions.

LIMITATIONS

Spatial overlap between neural correlates of frustration and retaliatory behaviors was conducted using a conjunction analysis. Therefore, neurobiological markers underlying the temporal sequence of the frustration-aggression theory should be interpreted with caution.

CONCLUSIONS

Nonetheless, our results underscore the role of anterior midcingulate/pre-supplementary motor area and fronto-insular cortex in both frustration and retaliatory behaviors. A neurobiological framework for understanding frustration-based impulsive aggression is provided.

Similar functional networks predict performance in both perceptual and value-based decision tasks

There are numerous commonalities between perceptual and preferential decision processes. For instance, previous studies have shown that both of these decision types are influenced by context. Also, the same computational models can explain both. However, the neural processes and functional connections that underlie these similarities between perceptual and value-based decisions are still unclear. Hence, in the current study, we examine whether perceptual and preferential processes can be explained by similar functional networks utilizing data from the Human Connectome Project. We used resting-state functional magnetic resonance imaging data to predict performance of 2 different decision-making tasks: a value-related task (the delay discounting task) and a perceptual task (the flanker task). We then examined the existence of shared predictive-network features across these 2 decision tasks. Interestingly, we found a significant positive correlation between the functional networks, which predicted the value-based and perceptual tasks. In addition, a larger functional connectivity between visual and frontal decision brain areas was a critical feature in the prediction of both tasks. These results demonstrate that functional connections between perceptual and value-related areas in the brain are inherently related to decision-making processes across domains.