Posterior parietal cortex is causally involved in reward valuation but not in probability weighting during risky choice.

This study provides evidence that the posterior parietal cortex is causally involved in risky decision making via the processing of reward values but not reward probabilities. In the within-group experimental design, participants performed a binary lottery choice task following transcranial magnetic stimulation of the right posterior parietal cortex, left posterior parietal cortex, and a right posterior parietal cortex sham (placebo) stimulation. The continuous theta-burst stimulation protocol supposedly downregulating the cortical excitability was used. Both, mean-variance and the prospect theory approach to risky choice showed that the posterior parietal cortex stimulation shifted participants toward greater risk aversion compared with sham. On the behavioral level, after the posterior parietal cortex stimulation, the likelihood of choosing a safer option became more sensitive to the difference in standard deviations between lotteries, compared with sham, indicating greater risk avoidance within the mean-variance framework. We also estimated the shift in prospect theory parameters of risk preferences after posterior parietal cortex stimulation. The hierarchical Bayesian approach showed moderate evidence for a credible change in risk aversion parameter toward lower marginal reward value (and, hence, lower risk tolerance), while no credible change in probability weighting was observed. In addition, we observed anecdotal evidence for a credible increase in the consistency of responses after the left posterior parietal cortex stimulation compared with sham.

Do sparse brain activity patterns underlie human cognition?

Accumulating multivariate pattern analysis (MVPA) results from fMRI studies suggest that information is represented in fingerprint patterns of activations and deactivations during perception, emotions, and cognition. We postulate that these fingerprint patterns might reflect neuronal-population level sparse code documented in two-photon calcium imaging studies in animal models, i.e., information represented in specific and reproducible ensembles of a few percent of active neurons amidst widespread inhibition in neural populations. We suggest that such representations constitute a fundamental organizational principle via interacting across multiple levels of brain hierarchy, thus giving rise to perception, emotions, and cognition.

Action in auctions: neural and computational mechanisms of bidding behaviour.

Competition for resources is a fundamental characteristic of evolution. Auctions have been widely used to model competition of individuals for resources, and bidding behaviour plays a major role in social competition. Yet, how humans learn to bid efficiently remains an open question. We used model-based neuroimaging to investigate the neural mechanisms of bidding behaviour under different types of competition. Twenty-seven subjects (nine male) played a prototypical bidding game: a double action, with three "market" types, which differed in the number of competitors. We compared different computational learning models of bidding: directional learning models (DL), where the model bid is "nudged" depending on whether it was accepted or rejected, along with standard reinforcement learning models (RL). We found that DL fit the behaviour best and resulted in higher payoffs. We found the binary learning signal associated with DL to be represented by neural activity in the striatum distinctly posterior to a weaker reward prediction error signal. We posited that DL is an efficient heuristic for valuation when the action (bid) space is continuous. Indeed, we found that the posterior parietal cortex represents the continuous action space of the task, and the frontopolar prefrontal cortex distinguishes among conditions of social competition. Based on our findings, we proposed a conceptual model that accounts for a sequence of processes that are required to perform successful and flexible bidding under different types of competition.

Neural Mechanisms of Cognitive Dissonance (Revised): An EEG Study.

Cognitive dissonance theory suggests that our preferences are modulated by the mere act of choosing. A choice between two similarly valued alternatives creates psychological tension (cognitive dissonance) that is reduced by a postdecisional reevaluation of the alternatives. We measured EEG of human subjects during rest and free-choice paradigm. Our study demonstrates that choices associated with stronger cognitive dissonance trigger a larger negative frontocentral evoked response similar to error-related negativity, which has in turn been implicated in general performance monitoring. Furthermore, the amplitude of the evoked response is correlated with the reevaluation of the alternatives. We also found a link between individual neural dynamics (long-range temporal correlations) of the frontocentral cortices during rest and follow-up neural and behavioral effects of cognitive dissonance. Individuals with stronger resting-state long-range temporal correlations demonstrated a greater postdecisional reevaluation of the alternatives and larger evoked brain responses associated with stronger cognitive dissonance. Thus, our results suggest that cognitive dissonance is reflected in both resting-state and choice-related activity of the prefrontal cortex as part of the general performance-monitoring circuitry.SIGNIFICANCE STATEMENT Contrary to traditional decision theory, behavioral studies repeatedly demonstrate that our preferences are modulated by the mere act of choosing. Difficult choices generate psychological (cognitive) dissonance, which is reduced by the postdecisional devaluation of unchosen options. We found that decisions associated with a higher level of cognitive dissonance elicited a stronger negative frontocentral deflection that peaked ∼60 ms after the response. This activity shares similar spatial and temporal features as error-related negativity, the electrophysiological correlate of performance monitoring. Furthermore, the frontocentral resting-state activity predicted the individual magnitude of preference change and the strength of cognitive dissonance-related neural activity.

Correlation of cue-locked FRN and feedback-locked FRN in the auditory monetary incentive delay task.

Reflecting the discrepancy between received and predicted outcomes, the reward prediction error (RPE) plays an important role in learning in a dynamic environment. A number of studies suggested that the feedback-related negativity (FRN) component of an event-related potential, known to be associated with unexpected outcomes, encodes RPEs. While FRN was clearly shown to be sensitive to the probability of outcomes, the effect of outcome magnitude on FRN remains to be further clarified. In studies on the neural underpinnings of reward anticipation and outcome evaluation, a monetary incentive delay (MID) task proved to be particularly useful. We investigated whether feedback-locked FRN and cue-locked dN200 responses recorded during an auditory MID task were sensitive to the probability and magnitude of outcomes. The cue-locked dN200 is associated with the update of information about the magnitude of prospective outcomes. Overall, we showed that feedback-locked FRN was modulated by both the magnitude and the probability of outcomes during an auditory version of MID task, whereas no such effect was found for cue-locked dN200. Furthermore, the cue-locked dN200, which is associated with the update of information about the magnitude of prospective outcomes, correlated with the standard feedback-locked FRN, which is associated with a negative RPE. These results further expand our knowledge on the interplay between the processing of predictive cues that forecast future outcomes and the subsequent revision of these predictions during outcome delivery.

(Non)-experiencing the intention to move: On the comparisons between the Readiness Potential onset and Libet's W-time.

A seminal study by Libet et al. (1983) provided a popular approach to compare the introspective timing of movement execution (the M-time) and the intention to move (the W-time) with respect to the onset of the readiness potential (RP). The difference between the W-time and the RP onsets contributed significantly to the current free-will discussion, insofar as it has been repeatedly shown that the RP onset unequivocally precedes the W-time. However, the interpretations of Libet's paradigm continuously attract criticism, questioning the use of both the W-time and the RP onset as indicators of motor intention. In the current study, we further probe whether the W-time is rather an intention-unrelated product of the participant's inference than an unambiguous temporal marker of the intention to move. Using behavioral reports and concurrent multichannel EEG, we investigated the relationship between the W-time and M-time introspective reports in two groups of participants who started an experiment with a series of different reports. Congruently with previous studies, we have shown that the W-time is affected by the experimental procedures: participants who had prior experience reporting the M-time provided significantly earlier W-time. However, contrary to previous papers, we revealed that even naive participants do introspectively differentiate the W-time and the M-time, which suggests that the W-time might actually reflect the intention to move, at least to some extent. We, therefore, suggest that training-based modulation of the W-time values may explain this finding. Moreover, we further confirm the absence of a direct link between the RP onset and the W-time by showing no covariation between them in both experimental groups. In turn, our findings question the overall interpretation of the comparison between these two time points. Overall, our study further emphasizes the ambiguity of Libet's paradigm, and suggests that the relatedness of both the RP and the W-time to the movement initiation processes should not be assumed a priori.

Electrophysiological correlates of third-party punishment: ERP study.

Human societies benefit from social norms that increase cooperation and support social order. Hence, the understanding of effective mechanisms enforcing norms is crucial. One of such mechanisms is "third-party punishment" (TPP) - a form of social punishment that could be delivered by a third-party, not directly affected by the actions of the norm violator. Previous electrophysiological studies (ERP) reported that perceived violations of norms evoked the medial frontal negativity in third-parties. The current study further probed the link between the medial frontal negativity (MFN) and actual TPP of norm violation, as it was not shown directly before. Participants played a dictator game as third-parties, being able to select different levels of punishment of an unfair violator's decisions. We replicated previous findings and showed the amplitude of the MFN correlated with the intensity of TPP (Fz, r = -0.516, p = 0.034, FCz, r = -0.509; p = 0.037). Overall, our findings further support the direct link between the MFN and the intensity of TPP.

Neuromodulation of choice-induced preference changes: the tDCS study of cognitive dissonance.

Introduction: Difficult choices between two equally attractive options result in a cognitive discrepancy between dissonant cognitions such as preferences and actions often followed by a sense of psychological discomfort known as cognitive dissonance. It can lead to changes in the desirability of options: the chosen option becomes more desirable, whereas the rejected option is devalued. Despite the ample experimental evidence to show this effect, the neural mechanisms and timing of such choice-induced preference changes are not fully understood. Methods: In this study, we used transcranial direct current stimulation (tDCS) to modulate the activity of the posterior medial frontal cortex (pMFC), which has been associated with conflict monitoring and choice-induced preference changes in neuroimaging studies. Prior to a revised version of Brehm's free-choice paradigm, participants in two experiments underwent cathodal (inhibitory) or anodal (excitatory) tDCS of the pMFC compared to sham (placebo) stimulation prior to the choice phase. Results: Our results showed that cathodal tDCS significantly decreased the choice-induced preference change relative to a sham, but only in direct comparisons of rejected options. No significant effect of anodal tDCS in comparison with sham was observed. Discussion: This study replicates the general behavioral effect of cognitive dissonance and provide partial support for the theory of the pMFC contribution to choice-related cognitive dissonance and subsequent preference changes, with possible limitations of an under-sampling for the obtained effect size and an asymmetry in the inhibitory-excitatory effects of non-invasive tDCS.

Neurochronometry of choice-induced preference changes: when do preferences actually change?

According to cognitive dissonance theory, a discrepancy between preferences and actions may lead to the revaluation of preferences, increasing preference for the chosen options and decreasing for the rejected options. This phenomenon is known as the spreading of alternatives (SoA), which results in a choice-induced preference change (CIPC). Previous neuroimaging studies have identified several brain regions that play a role in cognitive dissonance. However, the neurochronometry of the cognitive mechanisms underlying CIPC is a topic of debate. In other words, does it occur during the difficult choice, immediately after the choice, or when people encounter the options again? Furthermore, it remains unclear what is the exact time point, relative to the onset of facing options, either within the choice or after it, when the attitudes start to be revised. We argue that applying online protocols of transcranial magnetic stimulation (TMS), during or immediately after the choice process, could be the most efficient way to better understand the temporal dynamics of the SoA effect. TMS allows for achieving high temporal and spatial resolution, modulating the activity of areas of interest, and examining the causal relationships. Besides, unlike the offline TMS, the online instrument allows tracking of the neurochronometry of attitude change, by varying stimulation onsets and durations with respect to the option stimuli. Based on scrupulous analysis of previous findings, employing online TMS studies of conflict monitoring, cognitive control, and CIPC neuroimaging results, we conclude that the use of online TMS is critical to examine the neurochronometry of CIPC.

Neural mechanisms of expert persuasion on willingness to pay for sugar.

Introduction: Sugar consumption is associated with many negative health consequences. It is, therefore, important to understand what can effectively influence individuals to consume less sugar. We recently showed that a healthy eating call by a health expert can significantly decrease the willingness to pay (WTP) for sugar-containing food. Here, we investigate which aspects of neural responses to the same healthy eating call can predict the efficacy of expert persuasion. Methods: Forty-five healthy participants performed two blocks of a bidding task, in which they had to bid on sugar-containing, sugar-free and non-edible products, while their electroencephalography (EEG) was recorded. In between the two blocks, they listened to a healthy eating call by a nutritionist emphasizing the risks of sugar consumption. Results: We found that after listening to the healthy eating call, participants significantly decreased their WTP for sugar-containing products. Moreover, a higher intersubject correlation of EEG (a measure of engagement) during listening to the healthy eating call resulted in a larger decrease in WTP for sugar-containing food. Whether or not a participant's valuation of a product was highly influenced by the healthy eating call could also be predicted by spatiotemporal patterns of EEG responses to the healthy eating call, using a machine learning classification model. Finally, the healthy eating call increased the amplitude of the P300 component of the visual event-related potential in response to sugar-containing food. Disussion: Overall, our results shed light on the neural basis of expert persuasion and demonstrate that EEG is a powerful tool to design and assess health-related advertisements before they are released to the public.

The prediction of market-level food choices by the neural valuation signal.

Neuroimaging studies have demonstrated the ability to use the brain activity of a group of individuals to forecast the behavior of an independent group. In the current study, we attempted to forecast aggregate choices in a popular restaurant chain. During our functional magnetic resonance imaging (fMRI) study, 22 participants were exposed to 78 photos of dishes from a new menu of a popular restaurant chain. In addition to self-reported preferences, fMRI data was extracted from an a priori domain-general and task-specific region of interest-the ventral striatum. We investigated the relationship between the neural activity and real one-year sales provided by the restaurant chain. Activity in the ventral striatum, which was defined using the task-specific region of interest, significantly correlated (r = 0.28, p = 0.01) with one-year sales. A regression analysis, which included ventral striatum activity together with the objective characteristics of the products (price and weight), behavioral, and survey data, showed R2 values of 0.33. Overall, our results confirm prior studies, which have suggested, that brain activity in the reward system of a relatively small number of individuals can forecast the aggregate choice of a larger independent group of people.

Correction: The Prediction of Market-level Food Choices by the Neural Valuation Signal.

[This corrects the article DOI: 10.1371/journal.pone.0286648.].

Downregulation of the posterior medial frontal cortex prevents social conformity.

We often change our behavior to conform to real or imagined group pressure. Social influence on our behavior has been extensively studied in social psychology, but its neural mechanisms have remained largely unknown. Here we demonstrate that the transient downregulation of the posterior medial frontal cortex by theta-burst transcranial magnetic stimulation reduces conformity, as indicated by reduced conformal adjustments in line with group opinion. Both the extent and probability of conformal behavioral adjustments decreased significantly relative to a sham and a control stimulation over another brain area. The posterior part of the medial frontal cortex has previously been implicated in behavioral and attitudinal adjustments. Here, we provide the first interventional evidence of its critical role in social influence on human behavior.

Mine or ours? Neural basis of the exploitation of common-pool resources.

Why do people often exhaust unregulated common (shared) natural resources but manage to preserve similar private resources? To answer this question, in this study we combine a neurobiological, economic and cognitive modeling approach. Using functional magnetic resonance imaging on 50 participants, we show that a sharp decrease of common and private resources is associated with deactivation of the ventral striatum, a brain region involved in the valuation of outcomes. Across individuals, when facing a common resource, ventral striatal activity is anticorrelated with resource preservation (less harvesting), whereas with private resources the opposite pattern is observed. This indicates that neural value signals distinctly modulate behavior in response to the depletion of common vs private resources. Computational modeling suggested that overharvesting of common resources was facilitated by the modulatory effect of social comparison on value signals. These results provide an explanation of people's tendency to over-exploit unregulated common natural resources.

Dorsolateral prefrontal cortex plays causal role in probability weighting during risky choice.

In this study, we provide causal evidence that the dorsolateral prefrontal cortex (DLPFC) supports the computation of subjective value in choices under risk via its involvement in probability weighting. Following offline continuous theta-burst transcranial magnetic stimulation (cTBS) of the DLPFC subjects (N = 30, mean age 23.6, 56% females) completed a computerized task consisting of 96 binary lottery choice questions presented in random order. Using the hierarchical Bayesian modeling approach, we then estimated the structural parameters of risk preferences (the degree of risk aversion and the curvature of the probability weighting function) and analyzed the obtained posterior distributions to determine the effect of stimulation on model parameters. On a behavioral level, temporary downregulation of the left DLPFC excitability through cTBS decreased the likelihood of choosing an option with higher expected reward while the probability of choosing a riskier lottery did not significantly change. Modeling the stimulation effects on risk preference parameters showed anecdotal evidence as assessed by Bayes factors that probability weighting parameter increased after the left DLPFC TMS compared to sham.

Behavioral Experience-Sampling Methods in Neuroimaging Studies With Movie and Narrative Stimuli.

Movies and narratives are increasingly utilized as stimuli in functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG), and electroencephalography (EEG) studies. Emotional reactions of subjects, what they pay attention to, what they memorize, and their cognitive interpretations are all examples of inner experiences that can differ between subjects during watching of movies and listening to narratives inside the scanner. Here, we review literature indicating that behavioral measures of inner experiences play an integral role in this new research paradigm via guiding neuroimaging analysis. We review behavioral methods that have been developed to sample inner experiences during watching of movies and listening to narratives. We also review approaches that allow for joint analyses of the behaviorally sampled inner experiences and neuroimaging data. We suggest that building neurophenomenological frameworks holds potential for solving the interrelationships between inner experiences and their neural underpinnings. Finally, we tentatively suggest that recent developments in machine learning approaches may pave way for inferring different classes of inner experiences directly from the neuroimaging data, thus potentially complementing the behavioral self-reports.

Central EEG Beta/Alpha Ratio Predicts the Population-Wide Efficiency of Advertisements.

Recent studies have demonstrated that the brain activity of a group of people can be used to forecast choices at the population level. In this study, we attempted to neuroforecast aggregate consumer behavior of Internet users. During our electroencephalography (EEG) and eye-tracking study, participants were exposed to 10 banners that were also used in the real digital marketing campaign. In the separate online study, we additionally collected self-reported preferences for the same banners. We explored the relationship between the EEG, eye-tracking, and behavioral indexes obtained in our studies and the banners' aggregate efficiency provided by the large food retailer based on the decisions of 291,301 Internet users. An EEG-based engagement index (central beta/alpha ratio) significantly correlated with the aggregate efficiency of banners. Furthermore, our multiple linear regression models showed that a combination of eye-tracking, EEG and behavioral measurements better explained the market-level efficiency of banner advertisements than each measurement alone. Overall, our results confirm that neural signals of a relatively small number of individuals can forecast aggregate behavior at the population level.

"Expert persuasion" can decrease willingness to pay for sugar-containing food.

Recent studies have revealed types of eating nudges that can steer consumers toward choosing healthier options. However, most of the previously studied interventions target individual decisions and are not directed to changing consumers' underlying perception of unhealthy food. Here, we investigate how a healthy eating call-first-person narrative by a health expert-affects individuals' willingness to pay (WTP) for sugar-free and sugar-containing food products. Participants performed two blocks of a bidding task, in which they had to bid on sweets labeled either as "sugar- free" or as "sugar-containing." In-between the two blocks, half of the participants listened to a narrative by a dietary specialist emphasizing the health risks of sugar consumption, whereas the remaining participants listened to a control narrative irrelevant to food choices. We demonstrate that the health expert's narrative decreased individuals' WTP for sugar-containing food, but did not modulate their WTP for sugar- free food. Overall, our findings confirm that consumers may conform to healthy eating calls by rather devaluating unhealthy food products than by increasing the value of healthy ones. This paves the way for an avenue of innovative marketing strategies to support individuals in their food choices.

Additively Combining Utilities and Beliefs: Research Gaps and Algorithmic Developments.

Value-based decision making in complex environments, such as those with uncertain and volatile mapping of reward probabilities onto options, may engender computational strategies that are not necessarily optimal in terms of normative frameworks but may ensure effective learning and behavioral flexibility in conditions of limited neural computational resources. In this article, we review a suboptimal strategy - additively combining reward magnitude and reward probability attributes of options for value-based decision making. In addition, we present computational intricacies of a recently developed model (named MIX model) representing an algorithmic implementation of the additive strategy in sequential decision-making with two options. We also discuss its opportunities; and conceptual, inferential, and generalization issues. Furthermore, we suggest future studies that will reveal the potential and serve the further development of the MIX model as a general model of value-based choice making.

Role of the prefrontal cortex in prosocial and self-maximization motivations: an rTMS study.

More than a decade of neuroimaging and brain stimulation studies point to a crucial role for the right dorsolateral prefrontal cortex (rDLPFC) in prosocial behavior. The intuitive prosociality model postulates that the rDLPFC controls intuitive prosocial behavior, whereas the reflective model assumes that the rDLPFC controls selfish impulses during prosocial behavior. The intuitive prosociality model implies that the transient disruption of the rDLPFC should increase voluntary transfers in both dictator and generosity games. In contrast, the reflective model suggests that the transient disruption of the rDLPFC should decrease transfers in the dictator game, without affecting voluntary transfers in the generosity game, in which selfish motives are minimized. The aim of this paper was to compare predictions of the intuitive and reflective models using the classic dictator game and generosity game and continuous theta burst stimulation (cTBS). In this study, two groups of healthy participants (dictators) received either cTBS over the rDLPFC or right extrastriate visual areas. As shown by the results, the transient disruption of the rDLPFC significantly promoted prosocial motives in the dictator game only, particularly in the trials with the lowest dictator's costs. These findings partially support the notion that the rDLPFC controls intuitive prosocial behavior.