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To date, social and nonsocial decisions have been studied largely in isolation. Consequently, the extent to which social and nonsocial forms of decision uncertainty are integrated using shared neurocomputational resources remains elusive. Here, we address this question using simultaneous electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) in healthy human participants (young adults of both sexes) and a task in which decision evidence in social and nonsocial contexts varies along comparable scales. First, we identify time-resolved build-up of activity in the EEG, akin to a process of evidence accumulation (EA), across both contexts. We then use the endogenous trial-by-trial variability in the slopes of these accumulating signals to construct parametric fMRI predictors. We show that a region of the posterior-medial frontal cortex (pMFC) uniquely explains trial-wise variability in the process of evidence accumulation in both social and nonsocial contexts. We further demonstrate a task-dependent coupling between the pMFC and regions of the human valuation system in dorso-medial and ventro-medial prefrontal cortex across both contexts. Finally, we report domain-specific representations in regions known to encode the early decision evidence for each context. These results are suggestive of a domain-general decision-making architecture, whereupon domain-specific information is likely converted into a “common currency” in medial prefrontal cortex and accumulated for the decision in the pMFC.SIGNIFICANCE STATEMENTLittle work has directly compared social-versus-nonsocial decisions to investigate whether they share common neurocomputational origins. Here, using combined electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) and computational modeling, we offer a detailed spatiotemporal account of the neural underpinnings of social and nonsocial decisions. Specifically, we identify a comparable mechanism of temporal evidence integration driving both decisions and localize this integration process in posterior-medial frontal cortex (pMFC). We further demonstrate task-dependent coupling between the pMFC and regions of the human valuation system across both contexts. Finally, we report domain-specific representations in regions encoding the early, domain-specific, decision evidence. These results suggest a domain-general decision-making architecture, whereupon domain-specific information is converted into a common representation in the valuation system and integrated for the decision in the pMFC.

Much work has investigated beneficial effects of mindfulness-based meditation methods, but less work has investigated potential risks and differences across meditation methods. We addressed this in a large pre-registered online survey including 613 mediators where we correlated participants’ experience with fifty meditation techniques to psychotic-like experiences - PLEs (e.g. hallucinations) as detrimental outcomes, and mystical experiences as beneficial outcomes. We found a positive correlation for both PLEs and mystical experiences with techniques aiming at reducing phenomenological content (‘null-directed’, NDM) or classified as non-dual or less embodied. In contrast, methods aiming at achieving an enhanced cognitive state also described as ‘attentional’ or strongly embodied, showed negative correlations with PLEs. Interestingly, participants’ subjectively perceived that all types of meditation techniques were preventative of PLEs but less so for NDM. This study provides important information for meditators about the relationship of different techniques with PLEs and the moderating influences of individual traits.

People and other animals learn the values of choices by observing the contingencies between them and their outcomes. However, decisions are not guided by choice-linked reward associations alone; macaques also maintain a memory of the general, average reward rate – the global reward state – in an environment. Remarkably, global reward state affects the way that each choice outcome is valued and influences future decisions so that the impact of both choice success and failure is different in rich and poor environments. Successful choices are more likely to be repeated but this is especially the case in rich environments. Unsuccessful choices are more likely to be abandoned but this is especially likely in poor environments. Functional magnetic resonance imaging (fMRI) revealed two distinct patterns of activity, one in anterior insula and one in the dorsal raphe nucleus, that track global reward state as well as specific outcome events., Wittmann and colleagues show that not only single outcome events but also the global reward state (GRS) impact learning in macaques; low GRS drives explorative choices. Analyses of macaque BOLD signal reveals that GRS impacts activity in the anterior insula as well as the dorsal raphe nucleus.

To date, social and non-social decisions have been studied in isolation. Consequently, the extent to which social and non-social forms of decision uncertainty are integrated using shared neurocomputational resources remains elusive. Here, we address this question using simultaneous EEG-fMRI and a task in which decision evidence in social and non-social contexts varies along comparable scales. First, we identify comparable time-resolved build-up of activity in the EEG, akin to a process of evidence accumulation. We then use the endogenous trial-by-trial variability in the slopes of these accumulating signals to construct parametric fMRI predictors. We show that a region of the posterior-medial frontal cortex (pMFC) uniquely explains trial-wise variability in the process of evidence accumulation in both the social and non-social contexts. We further demonstrate a task-dependent coupling between the pMFC and regions of the human valuation system in dorso- and ventro-medial prefrontal cortex (dmPFC/vmPFC) across both contexts. Finally, we report domain-specific representations in regions known to encode the early decision evidence for each context. These results are suggestive of a domain-general decision-making architecture, whereupon domain-specific information is likely converted into a “common currency” in the dmPFC/vmPFC and accumulated for the decision in the pMFC.

Social interactions evolve continuously. Sometimes we cooperate, sometimeswe compete, while at other times we strategically position ourselves somewherein between to account for the ever-changing social contexts around us.Research on social interactions often focuses on a binary dichotomy betweencompetition and cooperation, ignoring people’s evolving shifts along a continuum.Here, we develop an economic game – the Space Dilemma – wheretwo players change their degree of cooperativeness over time in cooperativeand competitive contexts. Using computationalmodelling we showhowsocialcontexts bias choices and characterise how inferences about others’ intentionsmodulate cooperativeness. Consistent with the modelling predictions, brainregions previously linked to social cognition, including the temporo-parietaljunction, dorso-medial prefrontal cortex and the anterior cingulate gyrus,encode social prediction errors and context-dependent signals, correlatingwith shifts along a cooperation-competition continuum. These results providea comprehensive account of the computational and neural mechanismsunderlying the continuous trade-off between cooperation and competition.

Description, Noninvasive ultrasound stimulation of primate area 47/12o disrupts credit assignment–related behavior and neural activity., Credit assignment is the association of specific instances of reward to the specific events, such as a particular choice, that caused them. Without credit assignment, choice values reflect an approximate estimate of how good the environment was when the choice was made—the global reward state—rather than exactly which outcome the choice caused. Combined transcranial ultrasound stimulation (TUS) and functional magnetic resonance imaging in macaques demonstrate credit assignment–related activity in prefrontal area 47/12o, and when this signal was disrupted with TUS, choice value representations across the brain were impaired. As a consequence, behavior was no longer guided by choice value, and decision-making was poorer. By contrast, global reward state–related activity in the adjacent anterior insula remained intact and determined decision-making after prefrontal disruption.

Environments furnish multiple information sources for making predictions about future events. Here we use behavioural modelling and functional magnetic resonance imaging to describe how humans select predictors that might be most relevant. First, during early encounters with potential predictors, participants’ selections were explorative and directed towards subjectively uncertain predictors (positive uncertainty effect). This was particularly the case when many future opportunities remained to exploit knowledge gained. Then, preferences for accurate predictors increased over time, while uncertain predictors were avoided (negative uncertainty effect). The behavioural transition from positive to negative uncertainty-driven selections was accompanied by changes in the representations of belief uncertainty in ventromedial prefrontal cortex (vmPFC). The polarity of uncertainty representations (positive or negative encoding of uncertainty) changed between exploration and exploitation periods. Moreover, the two periods were separated by a third transitional period in which beliefs about predictors’ accuracy predominated. The vmPFC signals a multiplicity of decision variables, the strength and polarity of which vary with behavioural context. Trudel et al. find that the ventromedial prefrontal cortex carries multiple decision variables, the strength and polarity of which vary according to their relevance to the context of exploration, exploitation and the transition between these states.

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.

fMRI activity encoding acquisition and processing of feedback enables discrimination of response to self-help CBT in depression., While cognitive behavioral therapy (CBT) is an effective treatment for major depressive disorder, only up to 45% of depressed patients will respond to it. At present, there is no clinically viable neuroimaging predictor of CBT response. Notably, the lack of a mechanistic understanding of treatment response has hindered identification of predictive biomarkers. To obtain mechanistically meaningful fMRI predictors of CBT response, we capitalize on pretreatment neural activity encoding a weighted reward prediction error (RPE), which is implicated in the acquisition and processing of feedback information during probabilistic learning. Using a conventional mass-univariate fMRI analysis, we demonstrate that, at the group level, responders exhibit greater pretreatment neural activity encoding a weighted RPE in the right striatum and right amygdala. Crucially, using multivariate methods, we show that this activity offers significant out-of-sample classification of treatment response. Our findings support the feasibility and validity of neurocomputational approaches to treatment prediction in psychiatry.

Contains fulltext : 201971.pdf (Publisher’s version ) (Open Access) The causal role of an area within a neural network can be determined by interfering with its activity and measuring the impact. Many current reversible manipulation techniques have limitations preventing their application, particularly in deep areas of the primate brain. Here, we demonstrate that a focused transcranial ultrasound stimulation (TUS) protocol impacts activity even in deep brain areas: a subcortical brain structure, the amygdala (experiment 1), and a deep cortical region, the anterior cingulate cortex (ACC, experiment 2), in macaques. TUS neuromodulatory effects were measured by examining relationships between activity in each area and the rest of the brain using functional magnetic resonance imaging (fMRI). In control conditions without sonication, activity in a given area is related to activity in interconnected regions, but such relationships are reduced after sonication, specifically for the targeted areas. Dissociable and focal effects on neural activity could not be explained by auditory confounds. 14 p.

The neural mechanisms mediating sensory-guided decision-making have received considerable attention, but animals often pursue behaviors for which there is currently no sensory evidence. Such behaviors are guided by internal representations of choice values that have to be maintained even when these choices are unavailable. We investigated how four macaque monkeys maintained representations of the value of counterfactual choices—choices that could not be taken at the current moment but which could be taken in the future. Using functional magnetic resonance imaging, we found two different patterns of activity co-varying with values of counterfactual choices in a circuit spanning the hippocampus, the anterior lateral prefrontal cortex and the anterior cingulate cortex. Anterior cingulate cortex activity also reflected whether the internal value representations would be translated into actual behavioral change. To establish the causal importance of the anterior cingulate cortex for this translation process, we used a novel technique, transcranial focused ultrasound stimulation, to reversibly disrupt anterior cingulate cortex activity. Fouragnan et al. used neuroimaging and ultrasound neuromodution in non-human primates to demonstrate the causal role of the anterior cingulate cortex in translating counterfactual values in future choices.

BACKGROUNDCognitive behavioural therapy (CBT) is an effective evidence based treatment for depression. At present there is no reliable predictor of CBT in depression. Although the key to successful CBT in depression lies in altering maladaptive information processing, no previous imaging study has probed predictors of CBT response using pre-treatment neural encoding of information processing. METHODS: Using functional magnetic resonance imaging we scanned 37 unmedicated depressed subjects before and after completing computerised CBT (cCBT). We model the trial-by-trial appraisal of feedback information during a probabilistic learning task by means of a dynamic learning rate. To discriminate response to cCBT we capitalise on the pre-treatment blood oxygen level dependent (BOLD) activity encoding the dynamic learning rate as a function of feedback congruence and valence. Additionally, we probe between-group differences in the learning style encoded in the model’s parameters.RESULTSWe show BOLD activity in the dorsomedial prefrontal cortex (dmPFC) to be encoding the dynamic learning rate. Crucially, responders exhibit greater BOLD activity in the dmPFC during incongruent negative trials but lower BOLD activity during congruent negative trials than non-responders. Additionally, on between-group comparisons of model’s parameter estimates we show responders take relatively greater account of previous feedback history and make comparatively smaller adjustments to the learning rate as a result of outcome surprisingness.CONCLUSIONSOur findings provide novel and important insights into the cognitive mechanisms underpinning response to cCBT and lend support to the feasibility and validity of neurocomputational approaches to treatment prediction research in psychiatry.

Current computational accounts posit that, in simple binary choices, humans accumulate evidence in favour of the different alternatives before committing to a decision. Neural correlates of this accumulating activity have been found during perceptual decisions in parietal and prefrontal cortex; however the source of such activity in value-based choices remains unknown. Here we use simultaneous EEG–fMRI and computational modelling to identify EEG signals reflecting an accumulation process and demonstrate that the within- and across-trial variability in these signals explains fMRI responses in posterior-medial frontal cortex. Consistent with its role in integrating the evidence prior to reaching a decision, this region also exhibits task-dependent coupling with the ventromedial prefrontal cortex and the striatum, brain areas known to encode the subjective value of the decision alternatives. These results further endorse the proposition of an evidence accumulation process during value-based decisions in humans and implicate the posterior-medial frontal cortex in this process., Parietal and prefrontal cortices gather information to make perceptual decisions, but it is not known if the same is true for value-based choices. Here, authors use simultaneous EEG-fMRI and modelling to show that during value- and reward-based decisions this evidence is accumulated in the posterior medial frontal cortex.

International audience; Binge eating has been usually viewed as a loss of control and an impulsive behavior. But, little is known about the actual behavior of binging patients (prevalently women) in terms of basic decision-making under risk or under uncertainty. In healthy women, stressful cues bias behavior for safer options, raising the question of whether food cues that are perceived as threatening by binging patients may modulate patients' behaviors towards safer options. A cross-sectional study was conducted with binging patients (20 bulimia nervosa (BN) and 23 anorexia nervosa binging (ANB) patients) and two control groups (22 non-binging restrictive (ANR) anorexia nervosa patients and 20 healthy participants), without any concomitant impulsive disorder. We assessed decisions under risk with a gambling task with known probabilities and decisions under uncertainty with the balloon analog risk taking task (BART) with unknown probabilities of winning, in three cued-conditions including neutral, binge food and stressful cues. In the gambling task, binging and ANR patients adopted similar safer attitudes and coherently elicited a higher aversion to losses when primed by food as compared to neutral cues. This held true for BN and ANR patients in the BART. After controlling for anxiety level, these safer attitudes in the food condition were similar to the ones under stress. In the BART, ANB patients exhibited a higher variability in their choices in the food compared to neutral condition. This higher variability was associated with higher difficulties to discard irrelevant information. All these results suggest that decision-making under risk and under uncertainty is not fundamentally altered in all these patients.

Objective:\ud The role of planning in binge eating episodes is unknown. We investigated the characteristics of planning associated with food cues in binging patients. We studied planning based on backward reasoning, reasoning that determines a sequence of actions back to front from the final outcome.\ud Method:\ud A cross-sectional study was conducted with 20 healthy participants, 20 bulimia nervosa (BN), 22 restrictive (ANR) and 23 binging anorexia nervosa (ANB), without any concomitant impulsive disorder. In neutral/relaxing, binge food and stressful conditions, backward reasoning was assessed with the Race game, promotion of delayed large rewards with an intertemporal discounting task, attention with the Simon task, and repeating a dominant behavior with the Go/No-go task.\ud Results:\ud BN and to a lower extent ANB patients succeeded more at the Race game in food than in neutral condition. This difference discriminated binging from non-binging participants. Backward reasoning in the food condition was associated with lower approach behavior toward food in BN patients, and higher food avoidance in ANB patients. Enhanced backward reasoning in the food condition related to preferences for delayed large rewards in BN patients. In BN and ANB patients the enhanced success rate at the Race game in the food condition was associated with higher attention paid to binge food.\ud Conclusion:\ud These findings introduce a novel process underlying binges: planning based on backward reasoning is associated with binges. It likely aims to reduce craving for binge foods and extend binge refractory period in BN patients, and avoid binging in ANB patients. Shifts between these goals might explain shifts between eating disorder subtypes.

CNRS NR; AERES NR; Humans learn to trust each other by evaluating the outcomes of repeated interpersonal interactions. However, available prior information on the reputation of traders may alter the way outcomes affect learning. Our functional magnetic resonance imaging study is the first to allow the direct comparison of interaction-based and prior-based learning. Twenty participants played repeated trust games with anonymous counterparts. We manipulated two experimental conditions: whether or not reputational priors were provided, and whether counterparts were generally trustworthy or untrustworthy. When no prior information is available our results are consistent with previous studies in showing that striatal activation patterns correlate with behaviorally estimated reinforcement learning measures. However, our study additionally shows that this correlation is disrupted when reputational priors on counterparts are provided. Indeed participants continue to rely on priors even when experience sheds doubt on their accuracy. Notably, violations of trust from a cooperative counterpart elicited stronger caudate deactivations when priors were available than when they were not. However, tolerance to such violations appeared to be mediated by prior-enhanced connectivity between the caudate nucleus and ventrolateral prefrontal cortex, which anticorrelated with retaliation rates. Moreover, on top of affecting learning mechanisms, priors also clearly oriented initial decisions to trust, reflected in medial prefrontal cortex activity.