Neural basis of decision making guided by emotional outcomes

A calculus of probability or belief? Neural underpinnings of social decision-making in a card game

For decades, the prefrontal cortex (PFC) has been the focus of social neuroscience research, specifically regarding its role in competitive social decision-making. However, the distinct contributions of PFC subregions when making strategic decisions involving multiple types of information (social, non-social, and mixed information) remain unclear. This study investigates decision-making strategies (pure probability calculation vs. mentalizing) and their neural representations using functional near-infrared spectroscopy (fNIRS) data collected during a two-person card game. We observed individual differences in information processing strategy, indicating that some participants relied more on probability than others. Overall, the use of pure probability decreased over time in favor of other types of information (e.g., mixed information), with this effect being more pronounced within-round trials than across rounds. In the brain, (1) the lateral PFC activates when decisions are driven by probability calculations; (2) the right lateral PFC responds to trial difficulty; and (3) the anterior medial PFC is engaged when decision-making involves mentalizing. Furthermore, neural synchrony, which reflects the real-time interplay between individuals' cognitive processes, did not consistently contribute to correct decisions and fluctuated throughout the experiment, suggesting a hierarchical mentalizing mechanism at work.

The human cerebellum in reward anticipation and reward outcome processing: An activation likelihood estimation meta-analysis

The cerebellum generates internal prediction models and actively compares anticipated and actual outcomes in order to reach a desired end state. In this process, reward can serve as a reinforcer that shapes internal prediction models, enabling context-appropriate behavior. While the involvement of the cerebellum in reward processing has been established in animals, there is no detailed account of which cerebellar regions are involved in reward anticipation and reward outcome processing in humans. To this end, an activation likelihood estimation meta-analysis of functional neuroimaging studies was performed to investigate cerebellar functional activity patterns associated with reward anticipation and reward outcome processing in healthy adults. Results showed that reward anticipation (k=31) was associated with regional activity in the bilateral anterior lobe, bilateral lobule VI, left Crus I and the posterior vermis, while reward outcome (k=16) was associated with regional activity in the declive and left lobule VI. The findings of this meta-analysis show distinct involvement of the cerebellum in reward anticipation and reward outcome processing as part of a predictive coding routine.

Impulsivity and Emotional Dysregulation Predict Choice Behavior During a Mixed-Strategy Game in Adolescents With Borderline Personality Disorder

Impulsivity and emotional dysregulation are two core features of borderline personality disorder (BPD), and the neural mechanisms recruited during mixed-strategy interactions overlap with frontolimbic networks that have been implicated in BPD. We investigated strategic choice patterns during the classic two-player game, Matching Pennies, where the most efficient strategy is to choose each option randomly from trial-to-trial to avoid exploitation by one’s opponent. Twenty-seven female adolescents with BPD (mean age: 16 years) and twenty-seven age-matched female controls (mean age: 16 years) participated in an experiment that explored the relationship between strategic choice behavior and impulsivity in both groups and emotional dysregulation in BPD. Relative to controls, BPD participants showed marginally fewer reinforcement learning biases, particularly decreased lose-shift biases, increased variability in reaction times (coefficient of variation; CV), and a greater percentage of anticipatory decisions. A subset of BPD participants with high levels of impulsivity showed higher overall reward rates, and greater modulation of reaction times by outcome, particularly following loss trials, relative to control and BPD participants with lower levels of impulsivity. Additionally, BPD participants with higher levels of emotional dysregulation showed marginally increased reward rate and increased entropy in choice patterns. Together, our preliminary results suggest that impulsivity and emotional dysregulation may contribute to variability in mixed-strategy decision-making in female adolescents with BPD.

Basal ganglia lateralization in different types of reward

Reward processing is a fundamental human activity. The basal ganglia are recognized for their role in reward processes; however, specific roles of the different nuclei (e.g., nucleus accumbens, caudate, putamen and globus pallidus) remain unclear. Using quantitative meta-analyses we assessed whole-brain and basal ganglia specific contributions to money, erotic, and food reward processing. We analyzed data from 190 fMRI studies which reported stereotaxic coordinates of whole-brain, within-group results from healthy adult participants. Results showed concordance in overlapping and distinct cortical and sub-cortical brain regions as a function of reward type. Common to all reward types was concordance in basal ganglia nuclei, with distinct differences in hemispheric dominance and spatial extent in response to the different reward types. Food reward processing favored the right hemisphere; erotic rewards favored the right lateral globus pallidus and left caudate body. Money rewards engaged the basal ganglia bilaterally including its most anterior part, nucleus accumbens. We conclude by proposing a model of common reward processing in the basal ganglia and separate models for money, erotic, and food rewards.

The neural network basis of altered decision-making in patients with amyotrophic lateral sclerosis

OBJECTIVE

Amyotrophic lateral sclerosis (ALS) is a multisystem disorder associated with motor impairment and behavioral/cognitive involvement. We examined decision-making features and changes in the neural hub network in patients with ALS using a probabilistic reversal learning task and resting-state network analysis, respectively.

METHODS

Ninety ALS patients and 127 cognitively normal participants performed this task. Data from 62 ALS patients and 63 control participants were fitted to a Q-learning model.

RESULTS

ALS patients had anomalous decision-making features with little shift in choice until they thought the value of the two alternatives had become equal. The quantified parameters (Pαβ) calculated by logistic regression analysis with learning rate and inverse temperature well represented the unique choice pattern of ALS patients. Resting-state network analysis demonstrated a strong correlation between Pαβ and decreased degree centrality in the anterior cingulate gyrus and frontal pole.

INTERPRETATION

Altered decision-making in ALS patients may be related to the decreased hub function of medial prefrontal areas.

The Effect of Reduced Learning Ability on Avoidance in Psychopathy: A Computational Approach

Individuals with psychopathy often show deficits in learning, which often have negative consequences. Several theories have been proposed to explain psychopathic behaviors, but the learning mechanisms in psychopathy are still unclear. To clarify the learning anomalies in psychopathy, we fitted reinforcement learning (RL) models to behavioral data. We conducted two experiments to examine the effect of psychopathy as a group difference (Experiment 1) and as a continuum (Experiment 2). Forty-three undergraduates (in Experiment 1) and fifty-five undergraduate and graduate students (in Experiment 2) performed a go/no-go based learning task with accompanying rewards or punishments. Although we observed no differences in learning performance among the levels of psychopathic traits, the learning rate for the positive prediction error in the loss domain was lower for those with high-psychopathic trait than for those with low-psychopathic trait. This finding indicates that individuals with high-psychopathic traits update an action value less when they avoid a negative outcome. Our model can represent previous theories under a computational framework and provide a new perspective on impaired learning in psychopathy.

A novel fMRI paradigm to dissociate the behavioral and neural components of mixed-strategy decision making from non-strategic decisions in humans

During competitive interactions, such as predator-prey or team sports, the outcome of one's actions is dependent on both their own choices and those of their opponents. Success in these rivalries requires that individuals choose dynamically and unpredictably, often adopting a mixed strategy. Understanding the neural basis of strategic decision making is complicated by the fact that it recruits various cognitive processes that are often shared with non-strategic forms of decision making, such as value estimation, working memory, response inhibition, response selection, and reward processes. Although researchers have explored neural activity within key brain regions during mixed-strategy games, how brain activity differs in the context of strategic interactions versus non-strategic choices is not well understood. We developed a novel behavioral paradigm to dissociate choice behavior during mixed-strategy interactions from non-strategic choices, and we used task-based functional magnetic resonance imaging (fMRI) to contrast brain activation. In a block design, participants competed in the classic mixed-strategy game, "matching pennies," against a dynamic computer opponent designed to exploit predictability in players' response patterns. Results were contrasted with a non-strategic task that had comparable sensory input, motor output, and reward rate; thus, differences in behavior and brain activation reflect strategic processes. The mixed-strategy game was associated with activation of a distributed cortico-striatal network compared to the non-strategic task. We propose that choosing in mixed-strategy contexts requires additional cognitive demands present to a lesser degree during the control task, illustrating the strength of this design in probing function of cognitive systems beyond core sensory, motor, and reward processes.

Sparking interest in restaurant dishes? Cognitive and affective processes underlying dish design and ecological origin. An fMRI study

This papers aims to verify to what extent the presentation of a restaurant dish and the origin of its food provoke reactions in the consumer's brain during the visualization and the decision-making process, from an exploratory approach. The two independent variables singled out for study were whether the presentation was well or poorly presented and if the ingredients were ecological or non-ecological. The results applying the functional magnetic resonance image (fMRI) methodology reveal that well-presented dishes activate areas in the brain linked to the network of emotions indicating that the visualization in restaurant menus is not a purely cognitive and self-reflexive process but retains a strong affective component. Furthermore, the presence of this component is kept at the moment of choosing a dish, as observed by the activation of the cingulate gyrus, region linked to the regulatory processes of emotions. Hence, research ratifies the existence of an emotional factor during the entire process of decision-making carried out in a restaurant. Yet it is true that exposure to an ecological menu provokes activation of the medial frontal cortex, a region connected to higher reasoning and attention, suggesting that stimuli from well-presented dishes of ecological origin trigger neuronal responses related to high-level cognitive processes. The practical implications derived, along with its limitations and the future research opportunities, are interesting for both developing theory and also practice. Therefore, scholars are encouraged to further test some research proposals (e.g. moderating role of salubrity or simultaneously eye tracking method).

Triple representation of language, working memory, social and emotion processing in the cerebellum: convergent evidence from task and seed-based resting-state fMRI analyses in a single large cohort

Delineation of functional topography is critical to the evolving understanding of the cerebellum's role in a wide range of nervous system functions. We used data from the Human Connectome Project (n = 787) to analyze cerebellar fMRI task activation (motor, working memory, language, social and emotion processing) and resting-state functional connectivity calculated from cerebral cortical seeds corresponding to the peak Cohen's d of each task contrast. The combination of exceptional statistical power, activation from both motor and multiple non-motor tasks in the same participants, and convergent resting-state networks in the same participants revealed novel aspects of the functional topography of the human cerebellum. Consistent with prior studies there were two distinct representations of motor activation. Newly revealed were three distinct representations each for working memory, language, social, and emotional task processing that were largely separate for these four cognitive and affective domains. In most cases, the task-based activations and the corresponding resting-network correlations were congruent in identifying the two motor representations and the three non-motor representations that were unique to working memory, language, social cognition, and emotion. The definitive localization and characterization of distinct triple representations for cognition and emotion task processing in the cerebellum opens up new basic science questions as to why there are triple representations (what different functions are enabled by the different representations?) and new clinical questions (what are the differing consequences of lesions to the different representations?).

Triple representation of language, working memory, social and emotion processing in the cerebellum: convergent evidence from task and seed-based resting-state fMRI analyses in a single large cohort

Delineation of functional topography is critical to the evolving understanding of the cerebellum's role in a wide range of nervous system functions. We used data from the Human Connectome Project (n = 787) to analyze cerebellar fMRI task activation (motor, working memory, language, social and emotion processing) and resting-state functional connectivity calculated from cerebral cortical seeds corresponding to the peak Cohen's d of each task contrast. The combination of exceptional statistical power, activation from both motor and multiple non-motor tasks in the same participants, and convergent resting-state networks in the same participants revealed novel aspects of the functional topography of the human cerebellum. Consistent with prior studies there were two distinct representations of motor activation. Newly revealed were three distinct representations each for working memory, language, social, and emotional task processing that were largely separate for these four cognitive and affective domains. In most cases, the task-based activations and the corresponding resting-network correlations were congruent in identifying the two motor representations and the three non-motor representations that were unique to working memory, language, social cognition, and emotion. The definitive localization and characterization of distinct triple representations for cognition and emotion task processing in the cerebellum opens up new basic science questions as to why there are triple representations (what different functions are enabled by the different representations?) and new clinical questions (what are the differing consequences of lesions to the different representations?).

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

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

Informational Videos About Alcohol Use: Feasibility and Acceptability

BACKGROUND

An estimated 15.1 million adults ages 18 years and older are classified with an alcohol use disorder, which includes 9.8 million men and 5.3 million women. A brief intervention is indicated for those identified to be at risk because of alcohol use.

OBJECTIVE

To determine the feasibility and acceptability of informational videos about alcohol use.

DESIGN

This feasibility study provided participants with the opportunity to choose one of two videos, Alcohol and the Brain or Rethinking Drinking. An online survey was administered to all study participants to identify alcohol-related risk, readiness to decrease use, and knowledge pertaining to alcohol use.

RESULTS

The two videos provided in this study were feasibly delivered in an on-line format to 129 adults, including 115 males and 5 females identified to be at risk. Knowledge scores increased only slightly. There were mixed results for the readiness scores.

CONCLUSIONS

Future research should examine the efficacy of these two alcohol brief interventions on alcohol-related outcomes.

Cognitive emotion regulation enhances aversive prediction error activity while reducing emotional responses

Cognitive emotion regulation is a powerful way of modulating emotional responses. However, despite the vital role of emotions in learning, it is unknown whether the effect of cognitive emotion regulation also extends to the modulation of learning. Computational models indicate prediction error activity, typically observed in the striatum and ventral tegmental area, as a critical neural mechanism involved in associative learning. We used model-based fMRI during aversive conditioning with and without cognitive emotion regulation to test the hypothesis that emotion regulation would affect prediction error-related neural activity in the striatum and ventral tegmental area, reflecting an emotion regulation-related modulation of learning. Our results show that cognitive emotion regulation reduced emotion-related brain activity, but increased prediction error-related activity in a network involving ventral tegmental area, hippocampus, insula and ventral striatum. While the reduction of response activity was related to behavioral measures of emotion regulation success, the enhancement of prediction error-related neural activity was related to learning performance. Furthermore, functional connectivity between the ventral tegmental area and ventrolateral prefrontal cortex, an area involved in regulation, was specifically increased during emotion regulation and likewise related to learning performance. Our data, therefore, provide first-time evidence that beyond reducing emotional responses, cognitive emotion regulation affects learning by enhancing prediction error-related activity, potentially via tegmental dopaminergic pathways.