Informatic parcellation of the network involved in the computation of subjective value

Trait reward sensitivity modulates connectivity with the temporoparietal junction and Anterior Insula during strategic decision making

Many decisions happen in social contexts such as negotiations, yet little is understood about how people balance fairness versus selfishness. Past investigations found that activation in brain areas involved in executive function and reward processing was associated with people offering less with no threat of rejection from their partner, compared to offering more when there was a threat of rejection. However, it remains unclear how trait reward sensitivity may modulate activation and connectivity patterns in these situations. To address this gap, we used task-based fMRI to examine the relation between reward sensitivity and the neural correlates of bargaining choices. Participants (N = 54) completed the Sensitivity to Punishment (SP)/Sensitivity to Reward (SR) Questionnaire and the Behavioral Inhibition System/Behavioral Activation System scales. Participants performed the Ultimatum and Dictator Games as proposers and exhibited strategic decisions by being fair when there was a threat of rejection, but being selfish when there was not a threat of rejection. We found that strategic decisions evoked activation in the Inferior Frontal Gyrus (IFG) and the Anterior Insula (AI). Next, we found elevated IFG connectivity with the Temporoparietal junction (TPJ) during strategic decisions. Finally, we explored whether trait reward sensitivity modulated brain responses while making strategic decisions. We found that people who scored lower in reward sensitivity made less strategic choices when they exhibited higher AI-Angular Gyrus connectivity. Taken together, our results demonstrate how trait reward sensitivity modulates neural responses to strategic decisions, potentially underscoring the importance of this factor within social and decision neuroscience.

Rational inattention in neural coding for economic choice

Mental operations like computing the value of an option are computationally expensive. Even before we evaluate options, we must decide how much attentional effort to invest in the evaluation process. More precise evaluation will improve choice accuracy, and thus reward yield, but the gain may not justify the cost. Rational Inattention theories provide an accounting of the internal economics of attentionally effortful economic decisions. To understand this process, we examined choices and neural activity in several brain regions in six macaques making risky choices. We extended the rational inattention framework to incorporate the foraging theoretic understanding of local environmental richness or reward rate, which we predict will promote attentional effort. Consistent with this idea, we found local reward rate positively predicted choice accuracy. Supporting the hypothesis that this effect reflects variations in attentional effort, richer contexts were associated with increased baseline and evoked pupil size. Neural populations likewise showed systematic baseline coding of reward rate context. During increased reward rate contexts, ventral striatum and orbitofrontal cortex showed both an increase in value decodability and a rotation in the population geometries for value. This confluence of these results suggests a mechanism of attentional effort that operates by controlling gain through using partially distinct population codes for value. Additionally, increased reward rate accelerated value code dynamics, which have been linked to improved signal-to-noise. These results extend the theory of rational inattention to static and stationary contexts and align theories of rational inattention with specific costly, neural processes.

Decision-Making with Predictions of Others' Likely and Unlikely Choices in the Human Brain

For better decisions in social interactions, humans often must understand the thinking of others and predict their actions. Since such predictions are uncertain, multiple predictions may be necessary for better decision-making. However, the neural processes and computations underlying such social decision-making remain unclear. We investigated this issue by developing a behavioral paradigm and performing functional magnetic resonance imaging and computational modeling. In our task, female and male participants were required to predict others' choices in order to make their own value-based decisions, as the outcome depended on others' choices. Results showed, to make choices, the participants mostly relied on a value difference (primary) generated from the case where others would make a likely choice, but sometimes they additionally used another value difference (secondary) from the opposite case where others make an unlikely choice. We found that the activations in the posterior cingulate cortex (PCC) correlated with the primary difference while the activations in the right dorsolateral prefrontal cortex (rdlPFC) correlated with the secondary difference. Analysis of neural coupling and temporal dynamics suggested a three-step processing network, beginning with the left amygdala signals for predictions of others' choices. Modulated by these signals, the PCC and rdlPFC reflect the respective value differences for self-decisions. Finally, the medial prefrontal cortex integrated these decision signals for a final decision. Our findings elucidate the neural process of constructing value-based decisions by predicting others and illuminate their key variables with social modulations, providing insight into the differential functional roles of these brain regions in this process.

Trait Reward Sensitivity Modulates Connectivity with the Temporoparietal Junction and Anterior Insula during Strategic Decision Making

Many decisions happen in social contexts such as negotiations, yet little is understood about how people balance fairness versus selfishness. Past investigations found that activation in brain areas involved in executive function and reward processing was associated with people offering less with no threat of rejection from their partner, compared to offering more when there was a threat of rejection. However, it remains unclear how trait reward sensitivity may modulate activation and connectivity patterns in these situations. To address this gap, we used task-based fMRI to examine the relation between reward sensitivity and the neural correlates of bargaining choices. Participants (N = 54) completed the Sensitivity to Punishment (SP)/Sensitivity to Reward (SR) Questionnaire and the Behavioral Inhibition System/Behavioral Activation System scales. Participants performed the Ultimatum and Dictator Games as proposers and exhibited strategic decisions by being fair when there was a threat of rejection, but being selfish when there was not a threat of rejection. We found that strategic decisions evoked activation in the Inferior Frontal Gyrus (IFG) and the Anterior Insula (AI). Next, we found elevated IFG connectivity with the Temporoparietal junction (TPJ) during strategic decisions. Finally, we explored whether trait reward sensitivity modulated brain responses while making strategic decisions. We found that people who scored lower in reward sensitivity made less strategic choices when they exhibited higher AI-Angular Gyrus connectivity. Taken together, our results demonstrate how trait reward sensitivity modulates neural responses to strategic decisions, potentially underscoring the importance of this factor within social and decision neuroscience.

Neural Representations of Sensory Uncertainty and Confidence Are Associated with Perceptual Curiosity

Humans are immensely curious and motivated to reduce uncertainty, but little is known about the neural mechanisms that generate curiosity. Curiosity is inversely associated with confidence, suggesting that it is triggered by states of low confidence (subjective uncertainty), but the neural mechanisms of this link, have been little investigated. Inspired by studies of sensory uncertainty, we hypothesized that visual areas provide multivariate representations of uncertainty, which are read out by higher-order structures to generate signals of confidence and, ultimately, curiosity. We scanned participants (17 female, 15 male) using fMRI while they performed a new task in which they rated their confidence in identifying distorted images of animals and objects and their curiosity to see the clear image. We measured the activity evoked by each image in the occipitotemporal cortex (OTC) and devised a new metric of "OTC Certainty" indicating the strength of evidence this activity conveys about the animal versus object categories. We show that, perceptual curiosity peaked at low confidence and OTC Certainty negatively correlated with curiosity, establishing a link between curiosity and a multivariate representation of sensory uncertainty. Moreover, univariate (average) activity in two frontal areas-vmPFC and ACC-correlated positively with confidence and negatively with curiosity, and the vmPFC mediated the relationship between OTC Certainty and curiosity. The results reveal novel mechanisms through which uncertainty about an event generates curiosity about that event.

Sex differences in change-of-mind neuroeconomic decision-making is modulated by LINC00473 in medial prefrontal cortex

Changing one's mind is a complex cognitive phenomenon involving a continuous re-appraisal of the trade-off between past costs and future value. Recent work modeling this behavior across species has established associations between aspects of this choice process and their contributions to altered decision-making in psychopathology. Here, we investigated the actions in medial prefrontal cortex (mPFC) neurons of long intergenic non-coding RNA, LINC00473, known to induce stress resilience in a striking sex-dependent manner, but whose role in cognitive function is unknown. We characterized complex decision-making behavior in male and female mice longitudinally in our neuroeconomic foraging paradigm, Restaurant Row, following virus-mediated LINC00473 expression in mPFC neurons. On this task, mice foraged for their primary source of food among varying costs (delays) and subjective value (flavors) while on a limited time-budget during which decisions to accept and wait for rewards were separated into discrete stages of primary commitments and secondary re-evaluations. We discovered important differences in decision-making behavior between female and male mice. LINC00473 expression selectively influenced multiple features of re-evaluative choices, without affecting primary decisions, in female mice only. These behavioral effects included changing how mice (i) cached the value of the passage of time and (ii) weighed their history of economically disadvantageous choices. Both processes were uniquely linked to change-of-mind decisions and underlie the computational bases of distinct aspects of counterfactual thinking. These findings reveal a key bridge between a molecular driver of stress resilience and psychological mechanisms underlying sex-specific decision-making proclivities.

Disentangling effort from probability of success: Temporal dynamics of frontal midline theta in effort-based reward processing

The ability to weigh a reward against the effort required to acquire it is critical for decision-making. However, extant experimental paradigms oftentimes confound increased effort demand with decreased reward probability, thereby obscuring neural correlates underlying these cognitive processes. To resolve this issue, we designed novel tasks that disentangled probability of success - and therefore reward probability - from effort demand. In Experiment 1, reward magnitude and effort demand were varied while reward probability was kept constant. In Experiment 2, effort demand and reward probability were varied while reward magnitude remained fixed. Electroencephalogram (EEG) data was recorded to explore how frontal midline theta (FMT; an electrophysiological index of mPFC function) and component P3 (an index of incentive salience) respond to effort demand, and reward magnitude and probability. We found no evidence that FMT tracked effort demands or net value during cue evaluation. At feedback, however, FMT power was enhanced for high compared to low effort trials, but not modulated by reward magnitude or probability. Conversely, P3 was sensitive to reward magnitude and probability at both cue and feedback phases and only integrated expended effort costs at feedback, such that P3 amplitudes continued to scale with reward magnitude and probability but were also increased for high compared to low effort reward feedback. These findings suggest that, when likelihood of success is equal, FMT power does not track net value of prospective effort-based rewards. Instead, expended cognitive effort potentiates FMT power and enhances the saliency of rewards at feedback. SIGNIFICANCE STATEMENT: The way the brain weighs rewards against the effort required to achieve them is critical for understanding motivational disorders. Current paradigms confound increased effort demand with decreased reward probability, making it difficult to disentangle neural activity associated with effort costs from those associated with reward likelihood. Here, we explored the temporal dynamics of effort-based reward (via frontal midline theta (FMT) and component P3) while participants underwent a novel paradigm that kept probability of reward constant between mental effort demand conditions. Our findings suggest that the FMT does not track net value and that expended effort enhances, instead of attenuates, the saliency of rewards.

Distinct basal ganglia contributions to learning from implicit and explicit value signals in perceptual decision-making

Metacognitive evaluations of confidence provide an estimate of decision accuracy that could guide learning in the absence of explicit feedback. We examine how humans might learn from this implicit feedback in direct comparison with that of explicit feedback, using simultaneous EEG-fMRI. Participants performed a motion direction discrimination task where stimulus difficulty was increased to maintain performance, with intermixed explicit- and no-feedback trials. We isolate single-trial estimates of post-decision confidence using EEG decoding, and find these neural signatures re-emerge at the time of feedback together with separable signatures of explicit feedback. We identified these signatures of implicit versus explicit feedback along a dorsal-ventral gradient in the striatum, a finding uniquely enabled by an EEG-fMRI fusion. These two signals appear to integrate into an aggregate representation in the external globus pallidus, which could broadcast updates to improve cortical decision processing via the thalamus and insular cortex, irrespective of the source of feedback.

Neurobiological foundations and clinical relevance of effort-based decision-making

Applying effort-based decision-making tasks provides insights into specific variables influencing choice behaviors. The current review summarizes the structural and functional neuroanatomy of effort-based decision-making. Across 39 examined studies, the review highlights the ventromedial prefrontal cortex in forming reward-based predictions, the ventral striatum encoding expected subjective values driven by reward size, the dorsal anterior cingulate cortex for monitoring choices to maximize rewards, and specific motor areas preparing for effort expenditure. Neuromodulation techniques, along with shifting environmental and internal states, are promising novel treatment interventions for altering neural alterations underlying decision-making. Our review further articulates the translational promise of this construct into the development, maintenance and treatment of psychiatric conditions, particularly those characterized by reward-, effort- and valuation-related deficits.

Neural Reward Representations Enable Utilitarian Welfare Maximization

From deciding which meal to prepare for our guests to trading off the proenvironmental effects of climate protection measures against their economic costs, we often must consider the consequences of our actions for the well-being of others (welfare). Vexingly, the tastes and views of others can vary widely. To maximize welfare according to the utilitarian philosophical tradition, decision-makers facing conflicting preferences of others should choose the option that maximizes the sum of the subjective value (utility) of the entire group. This notion requires comparing the intensities of preferences across individuals. However, it remains unclear whether such comparisons are possible at all and (if they are possible) how they might be implemented in the brain. Here, we show that female and male participants can both learn the preferences of others by observing their choices and represent these preferences on a common scale to make utilitarian welfare decisions. On the neural level, multivariate support vector regressions revealed that a distributed activity pattern in the ventromedial prefrontal cortex (VMPFC), a brain region previously associated with reward processing, represented the preference strength of others. Strikingly, also the utilitarian welfare of others was represented in the VMPFC and relied on the same neural code as the estimated preferences of others. Together, our findings reveal that humans can behave as if they maximized utilitarian welfare using a specific utility representation and that the brain enables such choices by repurposing neural machinery processing the reward others receive.

Mapping the Neural Basis of Neuroeconomics with Functional Magnetic Resonance Imaging: A Narrative Literature Review

Neuroeconomics merges neuroscience, economics, and psychology to investigate the neural basis of decision making. Decision making involves assessing outcomes with subjective value, shaped by emotions and experiences, which are crucial in economic decisions. Functional MRI (fMRI) reveals key areas of the brain, including the ventro-medial prefrontal cortex, that are involved in subjective value representation. Collaborative interdisciplinary efforts are essential for advancing the field of neuroeconomics, with implications for clinical interventions and policy design. This review explores subjective value in neuroeconomics, highlighting brain regions identified through fMRI studies.

Continuous decision to wait for a future reward is guided by fronto-hippocampal anticipatory dynamics

Deciding whether to wait for a future reward is crucial for surviving in an uncertain world. While seeking rewards, agents anticipate a reward in the present environment and constantly face a trade-off between staying in their environment or leaving it. It remains unclear, however, how humans make continuous decisions in such situations. Here, we show that anticipatory activity in the anterior prefrontal cortex, ventrolateral prefrontal cortex, and hippocampus underpins continuous stay-leave decision-making. Participants awaited real liquid rewards available after tens of seconds, and their continuous decision was tracked by dynamic brain activity associated with the anticipation of a reward. Participants stopped waiting more frequently and sooner after they experienced longer delays and received smaller rewards. When the dynamic anticipatory brain activity was enhanced in the anterior prefrontal cortex, participants remained in their current environment, but when this activity diminished, they left the environment. Moreover, while experiencing a delayed reward in a novel environment, the ventrolateral prefrontal cortex and hippocampus showed anticipatory activity. Finally, the activity in the anterior prefrontal cortex and ventrolateral prefrontal cortex was enhanced in participants adopting a leave strategy, whereas those remaining stationary showed enhanced hippocampal activity. Our results suggest that fronto-hippocampal anticipatory dynamics underlie continuous decision-making while anticipating a future reward.

Dissociable Contributions of the Medial Parietal Cortex to Recognition Memory

Human neuroimaging studies of episodic memory retrieval routinely observe the engagement of specific cortical regions beyond the medial temporal lobe. Of these, medial parietal cortex (MPC) is of particular interest given its distinct functional characteristics during different retrieval tasks. Specifically, while recognition and autobiographical recall tasks are both used to probe episodic retrieval, these paradigms consistently drive distinct spatial patterns of response within MPC. However, other studies have emphasized alternate MPC functional dissociations in terms of brain network connectivity profiles or stimulus category selectivity. As the unique contributions of MPC to episodic memory remain unclear, adjudicating between these different accounts can provide better consensus regarding MPC function. Therefore, we used a precision-neuroimaging dataset (7T functional magnetic resonance imaging) to examine how MPC regions are differentially engaged during recognition memory and how these task-related dissociations may also reflect distinct connectivity and stimulus category functional profiles. We observed interleaved, though spatially distinct, subregions of MPC where responses were sensitive to either recognition decisions or the semantic representation of stimuli. In addition, this dissociation was further accentuated by functional subregions displaying distinct profiles of connectivity with the hippocampus during task and rest. Finally, we show that recent observations of dissociable person and place selectivity within the MPC reflect category-specific responses from within identified semantic regions that are sensitive to mnemonic demands. Together, by examining precision functional mapping within individuals, these data suggest that previously distinct observations of functional dissociation within MPC conform to a common principle of organization throughout hippocampal-neocortical memory systems.

Ventromedial prefrontal cortex activation and neurofeedback modulation during episodic future thinking for individuals with suicidal thoughts and behaviors

Individuals experiencing suicidal thoughts and behaviors (STBs) show less specificity and positivity during episodic future thinking (EFT). Here, we present findings from two studies aiming to (1) further our understanding of how STBs may relate to neural responsivity during EFT and (2) examine the feasibility of modulating EFT-related activation using real-time fMRI neurofeedback (rtfMRI-nf). Study 1 involved 30 individuals with major depressive disorder (MDD; half with STBs) who performed an EFT task during fMRI, for which they imagined personally-relevant future positive, negative, or neutral events. Positive EFT elicited greater ventromedial prefrontal cortex (vmPFC) activation compared to negative EFT. Importantly, the MDD + STB group exhibited reduced vmPFC activation across all EFT conditions compared to MDD-STB; although EFT fluency and subjective experience remained consistent across groups. Study 2 included rtfMRI-nf focused on vmPFC modulation during positive EFT for six participants with MDD + STBs. Results support the feasibility and acceptability of the rtfMRI-nf protocol and quantitative and qualitative observations are provided to help inform future, larger studies aiming to examine similar neurofeedback protocols. Results implicate vmPFC blunting as a promising treatment target for MDD + STBs and suggest rtfMRI-nf as one potential technique to explore for enhancing vmPFC engagement.

Pre-acquired Functional Connectivity Predicts Choice Inconsistency

Economic choice theories usually assume that humans maximize utility in their choices. However, studies have shown that humans make inconsistent choices, leading to suboptimal behavior, even without context-dependent manipulations. Previous studies showed that activation in value and motor networks are associated with inconsistent choices at the moment of choice. Here, we investigated if the neural predispositions, measured before a choice task, can predict choice inconsistency in a later risky choice task. Using functional connectivity (FC) measures from resting-state functional magnetic resonance imaging (rsfMRI), derived before any choice was made, we aimed to predict subjects' inconsistency levels in a later-performed choice task. We hypothesized that rsfMRI FC measures extracted from value and motor brain areas would predict inconsistency. Forty subjects (21 females) completed a rsfMRI scan before performing a risky choice task. We compared models that were trained on FC that included only hypothesized value and motor regions with models trained on whole-brain FC. We found that both model types significantly predicted inconsistency levels. Moreover, even the whole-brain models relied mostly on FC between value and motor areas. For external validation, we used a neural network pretrained on FC matrices of 37,000 subjects and fine-tuned it on our data and again showed significant predictions. Together, this shows that the tendency for choice inconsistency is predicted by predispositions of the nervous system and that synchrony between the motor and value networks plays a crucial role in this tendency.

Neural correlates of willingness to pay for items: A meta-analysis of functional magnetic resonance imaging studies

Willingness to pay (WTP) pervades every marketplace transaction, therefore, understanding how the brain makes bidding decisions is essential in consumer neuroscience. Although some neuroimaging studies have investigated the neural networks of WTP, systematic understanding remains limited. This study identified reliable neural networks activated by the WTP across different reward types and assessed common and distinct neural networks for different reward types (food and other) bids. We conducted an activation likelihood estimation (ALE) meta-analysis on WTP across different reward types (25 studies; 254 foci; 705 participants), and to compared neural representations of WTP for food reward (22 studies; 232 foci; 628 participants) and other rewards (7 studies, 61 foci; 177 participants). The ALE results revealed that the brain centers of WTP for different rewards mainly consist of the bilateral inferior frontal gyrus (IFG), bilateral insula, bilateral anterior cingulate cortex (ACC), along with the left caudate. This suggests that neural networks encoding WTP for different rewards consist of brain regions associated with reward processing, cost-benefit calculations, and goal-directed action activities. In addition, consistent activation of the bilateral IFG and bilateral insula for food but no other rewards bids suggest their involvement in the neural network of appetite. WTP for food and other rewards commonly activated ACC, suggesting a common region encoding bids for different rewards. Our findings provide novel insights into neural networks associated with WTP for food and other rewards bids and the mechanisms underlying WTP across different reward types.

Value Estimation versus Effort Mobilization: A General Dissociation between Ventromedial and Dorsomedial Prefrontal Cortex

Deciding on a course of action requires both an accurate estimation of option values and the right amount of effort invested in deliberation to reach sufficient confidence in the final choice. In a previous study, we have provided evidence, across a series of judgment and choice tasks, for a dissociation between the ventromedial prefrontal cortex (vmPFC), which would represent option values, and the dorsomedial prefrontal cortex (dmPFC), which would represent the duration of deliberation. Here, we first replicate this dissociation and extend it to the case of an instrumental learning task, in which 24 human volunteers (13 women) choose between options associated with probabilistic gains and losses. According to fMRI data recorded during decision-making, vmPFC activity reflects the sum of option values generated by a reinforcement learning model and dmPFC activity the deliberation time. To further generalize the role of the dmPFC in mobilizing effort, we then analyze fMRI data recorded in the same participants while they prepare to perform motor and cognitive tasks (squeezing a handgrip or making numerical comparisons) to maximize gains or minimize losses. In both cases, dmPFC activity is associated with the output of an effort regulation model, and not with response time. Taken together, these results strengthen a general theory of behavioral control that implicates the vmPFC in the estimation of option values and the dmPFC in the energization of relevant motor and cognitive processes.

The neurobehavioral correlates of exploration without learning: Trading off value for explicit, prospective, and variable information gains

Exploration is typically motivated by gaining information, with previous research showing that potential information gains drive a "directed" type of exploration. Yet, this research usually studies exploration in the context of learning paradigms and does not directly manipulate multiple levels of information gain. Here, we present a task that isolates learning from decision-making and controls the magnitude of prospective information gains. As predicted, participants explore more with larger future information gains. Both value gains and information gains, at a trial-by-trial level, engage the ventromedial prefrontal cortex (vmPFC), the ventral striatum (VStr), the amygdala, the dorsal anterior cingulate cortex (dACC), and the anterior insula (aINS). Moreover, individual sensitivities to value gains and information gains modulate the vmPFC, dACC, and aINS, but the amygdala and VStr are modulated only by individual sensitivities to information gains. Overall, we identify the neural circuitry of information-based exploration and its relationship with inter-individual exploration biases.

Decomposition of Reinforcement Learning Deficits in Disordered Gambling via Drift Diffusion Modeling and Functional Magnetic Resonance Imaging

Gambling disorder is associated with deficits in reward-based learning, but the underlying computational mechanisms are still poorly understood. Here, we examined this issue using a stationary reinforcement learning task in combination with computational modeling and functional resonance imaging (fMRI) in individuals that regular participate in gambling (n = 23, seven fulfilled one to three DSM 5 criteria for gambling disorder, sixteen fulfilled four or more) and matched controls (n = 23). As predicted, the gambling group exhibited substantially reduced accuracy, whereas overall response times (RTs) were not reliably different between groups. We then used comprehensive modeling using reinforcement learning drift diffusion models (RLDDMs) in combination with hierarchical Bayesian parameter estimation to shed light on the computational underpinnings of this performance deficit. In both groups, an RLDDM in which both non-decision time and decision threshold (boundary separation) changed over the course of the experiment accounted for the data best. The model showed good parameter and model recovery, and posterior predictive checks revealed that, in both groups, the model accurately reproduced the evolution of accuracies and RTs over time. Modeling revealed that, compared to controls, the learning impairment in the gambling group was linked to a more rapid reduction in decision thresholds over time, and a reduced impact of value-differences on the drift rate. The gambling group also showed shorter non-decision times. FMRI analyses replicated effects of prediction error coding in the ventral striatum and value coding in the ventro-medial prefrontal cortex, but there was no credible evidence for group differences in these effects. Taken together, our findings show that reinforcement learning impairments in disordered gambling are linked to both maladaptive decision threshold adjustments and a reduced consideration of option values in the choice process.

Temporally organized representations of reward and risk in the human brain

The value and uncertainty associated with choice alternatives constitute critical features relevant for decisions. However, the manner in which reward and risk representations are temporally organized in the brain remains elusive. Here we leverage the spatiotemporal precision of intracranial electroencephalography, along with a simple card game designed to elicit the unfolding computation of a set of reward and risk variables, to uncover this temporal organization. Reward outcome representations across wide-spread regions follow a sequential 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 further highlight the role of the anterior insula in generalizing between reward prediction error and risk prediction error codes. Together our results emphasize the importance of neural dynamics for understanding value-based decisions under uncertainty.

Functional Connectivity of the Nucleus Accumbens across Variants of Callous-Unemotional Traits: A Resting-State fMRI Study in Children and Adolescents

A large body of literature suggests that the primary (high callousness-unemotional traits [CU] and low anxiety) and secondary (high CU traits and anxiety) variants of psychopathy significantly differ in terms of their clinical profiles. However, little is known about their neurobiological differences. While few studies showed that variants differ in brain activity during fear processing, it remains unknown whether they also show atypical functioning in motivational and reward system. Latent Profile Analysis (LPA) was conducted on a large sample of adolescents (n = 1416) to identify variants based on their levels of callousness and anxiety. Seed-to-voxel connectivity analysis was subsequently performed on resting-state fMRI data to compare connectivity patterns of the nucleus accumbens across subgroups. LPA failed to identify the primary variant when using total score of CU traits. Using a family-wise cluster correction, groups did not differ on functional connectivity. However, at an uncorrected threshold the secondary variant showed distinct functional connectivity between the nucleus accumbens and posterior insula, lateral orbitofrontal cortex, supplementary motor area, and parietal regions. Secondary LPA analysis using only the callousness subscale successfully distinguish both variants. Group differences replicated results of deficits in functional connectivity between the nucleus accumbens and posterior insula and supplementary motor area, but additionally showed effect in the superior temporal gyrus which was specific to the primary variant. The current study supports the importance of examining the neurobiological markers across subgroups of adolescents at risk for conduct problems to precise our understanding of this heterogeneous population.

A multi-sample evaluation of the measurement structure and function of the modified monetary incentive delay task in adolescents

Interpreting the neural response elicited during task functional magnetic resonance imaging (fMRI) remains a challenge in neurodevelopmental research. The monetary incentive delay (MID) task is an fMRI reward processing task that is extensively used in the literature. However, modern psychometric tools have not been used to evaluate measurement properties of the MID task fMRI data. The current study uses data for a similar task design across three adolescent samples (N = 346 [Agemean 12.0; 44 % Female]; N = 97 [19.3; 58 %]; N = 112 [20.2; 38 %]) to evaluate multiple measurement properties of fMRI responses on the MID task. Confirmatory factor analysis (CFA) is used to evaluate an a priori theoretical model for the task and its measurement invariance across three samples. Exploratory factor analysis (EFA) is used to identify the data-driven measurement structure across the samples. CFA results suggest that the a priori model is a poor representation of these MID task fMRI data. Across the samples, the data-driven EFA models consistently identify a six-to-seven factor structure with run and bilateral brain region factors. This factor structure is moderately-to-highly congruent across the samples. Altogether, these findings demonstrate a need to evaluate theoretical frameworks for popular fMRI task designs to improve our understanding and interpretation of brain-behavior associations.

Identifying distinctive brain regions related to consumer choice behaviors on branded foods using activation likelihood estimation and machine learning

Introduction

Brand equity plays a crucial role in a brand's commercial success; however, research on the brain regions associated with brand equity has had mixed results. This study aimed to investigate key brain regions associated with the decision-making of branded and unbranded foods using quantitative neuroimaging meta-analysis and machine learning.

Methods

Quantitative neuroimaging meta-analysis was performed using the activation likelihood method. Activation of the ventral medial prefrontal cortex (VMPFC) overlapped between branded and unbranded foods. The lingual and parahippocampal gyri (PHG) were activated in the case of branded foods, whereas no brain regions were characteristically activated in response to unbranded foods. We proposed a novel predictive method based on the reported foci data, referencing the multi-voxel pattern analysis (MVPA) results. This approach is referred to as the multi-coordinate pattern analysis (MCPA). We conducted the MCPA, adopting the sparse partial least squares discriminant analysis (sPLS-DA) to detect unique brain regions associated with branded and unbranded foods based on coordinate data. The sPLS-DA is an extended PLS method that enables the processing of categorical data as outcome variables.

Results

We found that the lingual gyrus is a distinct brain region in branded foods. Thus, the VMPFC might be a core brain region in food categories in consumer behavior, regardless of whether they are branded foods. Moreover, the connection between the PHG and lingual gyrus might be a unique neural mechanism in branded foods.

Discussion

As this mechanism engages in imaging the feature-self based on emotionally subjective contextual associative memories, brand managers should create future-oriented relevancies between brands and consumers to build valuable brands.

Mapping expectancy-based appetitive placebo effects onto the brain in women

Suggestions about hunger can generate placebo effects on hunger experiences. But, the underlying neurocognitive mechanisms are unknown. Here, we show in 255 women that hunger expectancies, induced by suggestion-based placebo interventions, determine hunger sensations and economic food choices. Functional magnetic resonance imaging in a subgroup (n = 57/255) provides evidence that the strength of expecting the placebo to decrease hunger moderates medial prefrontal cortex activation at the time of food choice and attenuates ventromedial prefrontal cortex (vmPFC) responses to food value. Dorsolateral prefrontal cortex activation linked to interference resolution formally mediates the suggestion-based placebo effects on hunger. A drift-diffusion model characterizes this effect by showing that the hunger suggestions bias participants' food choices and how much they weigh tastiness against the healthiness of food, which further moderates vmPFC-dlPFC psychophysiological interactions when participants expect decreased hunger. Thus, suggestion-induced beliefs about hunger shape hunger addressing economic choices through cognitive regulation of value computation within the prefrontal cortex.

Distinct spatiotemporal brainstem pathways of outcome valence during reward- and punishment-based learning

Learning to seek rewards and avoid punishments, based on positive and negative choice outcomes, is essential for human survival. Yet, the neural underpinnings of outcome valence in the human brainstem and the extent to which they differ in reward and punishment learning contexts remain largely elusive. Here, using simultaneously acquired electroencephalography and functional magnetic resonance imaging data, we show that during reward learning the substantia nigra (SN)/ventral tegmental area (VTA) and locus coeruleus are initially activated following negative outcomes, while the VTA subsequently re-engages exhibiting greater responses for positive than negative outcomes, consistent with an early arousal/avoidance response and a later value-updating process, respectively. During punishment learning, we show that distinct raphe nucleus and SN subregions are activated only by negative outcomes with a sustained post-outcome activity across time, supporting the involvement of these brainstem subregions in avoidance behavior. Finally, we demonstrate that the coupling of these brainstem structures with other subcortical and cortical areas helps to shape participants' serial choice behavior in each context.

The role of emotion in eating behavior and decisions

The present paper aims to provide the latest perspectives and future directions on the association between emotions and eating behavior. We discussed individual differences in the impact of negative emotions on eating, emotional eating as disinhibited eating decisions with heightened reward values of and sensitivity to palatable foods in response to negative emotions and social isolation, in addition to emotional eating as maladaptive coping strategies under negative emotion and stress, hedonic (pleasure-oriented) eating decisions mediated by the brain reward system, and self-controlled (health-oriented) eating decisions mediated by the brain control system. Perspectives on future directions were addressed, including the development of early eating phenotypes in infancy, shared neural mechanisms mediated by the ventromedial prefrontal cortex and the dorsolateral prefrontal cortex in emotion and eating decision regulation, possible roles of interoception incorporating hunger and satiety signals, gut microbiome, the insula and the orbitofrontal cortex, and emotional processing capacities in hedonic eating and weight gain.

Electrophysiological population dynamics reveal context dependencies during decision making in human frontal cortex

Evidence from monkeys and humans suggests that the orbitofrontal cortex (OFC) encodes the subjective value of options under consideration during choice. Data from non-human primates suggests that these value signals are context-dependent, representing subjective value in a way influenced by the decision makers' recent experience. Using electrodes distributed throughout cortical and subcortical structures, human epilepsy patients performed an auction task where they repeatedly reported the subjective values they placed on snack food items. High-gamma activity in many cortical and subcortical sites including the OFC positively correlated with subjective value. Other OFC sites showed signals contextually modulated by the subjective value of previously offered goods-a context dependency predicted by theory but not previously observed in humans. These results suggest that value and value-context signals are simultaneously present but separately represented in human frontal cortical activity.

A Neural Mechanism in the Human Orbitofrontal Cortex for Preferring High-Fat Foods Based on Oral Texture

Although overconsumption of high-fat foods is a major driver of weight gain, the neural mechanisms that link the oral sensory properties of dietary fat to reward valuation and eating behavior remain unclear. Here we combine novel food-engineering approaches with functional neuroimaging to show that the human orbitofrontal cortex (OFC) translates oral sensations evoked by high-fat foods into subjective economic valuations that guide eating behavior. Male and female volunteers sampled and evaluated nutrient-controlled liquid foods that varied in fat and sugar ("milkshakes"). During oral food processing, OFC activity encoded a specific oral-sensory parameter that mediated the influence of the foods' fat content on reward value: the coefficient of sliding friction. Specifically, OFC responses to foods in the mouth reflected the smooth, oily texture (i.e., mouthfeel) produced by fatty liquids on oral surfaces. Distinct activity patterns in OFC encoded the economic values associated with particular foods, which reflected the subjective integration of sliding friction with other food properties (sugar, fat, viscosity). Critically, neural sensitivity of OFC to oral texture predicted individuals' fat preferences in a naturalistic eating test: individuals whose OFC was more sensitive to fat-related oral texture consumed more fat during ad libitum eating. Our findings suggest that reward systems of the human brain sense dietary fat from oral sliding friction, a mechanical food parameter that likely governs our daily eating experiences by mediating interactions between foods and oral surfaces. These findings identify a specific role for the human OFC in evaluating oral food textures to mediate preference for high-fat foods.SIGNIFICANCE STATEMENT Fat and sugar enhance the reward value of food by imparting a sweet taste and rich mouthfeel but also contribute to overeating and obesity. Here we used a novel food-engineering approach to realistically quantify the physical-mechanical properties of high-fat liquid foods on oral surfaces and used functional neuroimaging while volunteers sampled these foods and placed monetary bids to consume them. We found that a specific area of the brain's reward system, the orbitofrontal cortex, detects the smooth texture of fatty foods in the mouth and links these sensory inputs to economic valuations that guide eating behavior. These findings can inform the design of low-calorie fat-replacement foods that mimic the impact of dietary fat on oral surfaces and neural reward systems.

If you're happy and you know it: neural correlates of self-evaluated psychological health and well-being

Psychological health and well-being have important implications for individual and societal thriving. Research underscores the subjective nature of well-being, but how do individuals intuit this subjective sense of well-being in the moment? This pre-registered study addresses this question by examining the neural correlates of self-evaluated psychological health and their dynamic relationship with trial-level evaluations. Participants (N = 105) completed a self-evaluation task and made judgments about three facets of psychological health and positive functioning-self-oriented well-being, social well-being and ill-being. Consistent with pre-registered hypotheses, self-evaluation elicited activity in the default mode network, and there was strong spatial overlap among constructs. Trial-level analyses assessed whether and how activity in a priori regions of interest-perigenual anterior cingulate cortex (pgACC), ventromedial prefrontal cortex (vmPFC) and ventral striatum-were related to subjective evaluations. These regions explained additional variance in whether participants endorsed or rejected items but were differentially related to evaluations. Stronger activity in pgACC was associated with a higher probability of endorsement across constructs, whereas stronger activity in vmPFC was associated with a higher probability of endorsing ill-being items, but a lower probability of endorsing self-oriented and social well-being items. These results add nuance to neurocognitive accounts of self-evaluation and extend our understanding of the neurobiological basis of subjective psychological health and well-being.

Lesions to different regions of frontal cortex have dissociable effects on voluntary persistence

Deciding how long to keep waiting for uncertain future rewards is a complex problem. Previous research has shown that choosing to stop waiting results from an evaluative process that weighs the subjective value of the awaited reward against the opportunity cost of waiting. In functional neuroimaging data, activity in ventromedial prefrontal cortex (vmPFC) tracks the dynamics of this evaluation, while activation in the dorsomedial prefrontal cortex (dmPFC) and anterior insula (AI) ramps up before a decision to quit is made. Here, we provide causal evidence of the necessity of these brain regions for successful performance in a willingness-to-wait task. 28 participants with frontal lobe lesions were tested on their ability to adaptively calibrate how long they waited for monetary rewards. We grouped the participants based on the location of their lesions, which were primarily in ventromedial, dorsomedial, or lateral parts of their prefrontal cortex (vmPFC, dmPFC, and lPFC, respectively), or in the anterior insula. We compared the performance of each subset of lesion participants to behavior in a control group without lesions (n=18). Finally, we fit a newly developed computational model to the data to glean a more mechanistic understanding of how lesions affect the cognitive processes underlying choice. We found that participants with lesions to the vmPFC waited less overall, while participants with lesions to the dmPFC and anterior insula were specifically impaired at calibrating their level of persistence to the environment. These behavioral effects were accounted for by systematic differences in parameter estimates from a computational model of task performance: while the vmPFC group showed reduced initial willingness to wait, lesions to the dmPFC/anterior insula were associated with slower learning from negative feedback. These findings corroborate the notion that failures of persistence can be driven by sophisticated cost-benefit analyses rather than lapses in self-control. They also support the functional specialization of different parts of the prefrontal cortex in service of voluntary persistence.

Latent profiles of substance use, early life stress, and attention/externalizing problems and their association with neural correlates of reinforcement learning in adolescents

BACKGROUND

Adolescent substance use, externalizing and attention problems, and early life stress (ELS) commonly co-occur. These psychopathologies show overlapping neural dysfunction in the form of reduced recruitment of reward processing neuro-circuitries. However, it is unclear to what extent these psychopathologies show common v. different neural dysfunctions as a function of symptom profiles, as no studies have directly compared neural dysfunctions associated with each of these psychopathologies to each other.

METHODS

In study 1, a latent profile analysis (LPA) was conducted in a sample of 266 adolescents (aged 13-18, 41.7% female, 58.3% male) from a residential youth care facility and the surrounding community to investigate substance use, externalizing and attention problems, and ELS psychopathologies and their co-presentation. In study 2, we examined a subsample of 174 participants who completed the Passive Avoidance learning task during functional magnetic resonance imaging to examine differential and/or common reward processing neuro-circuitry dysfunctions associated with symptom profiles based on these co-presentations.

RESULTS

In study 1, LPA identified profiles of substance use plus rule-breaking behaviors, attention-deficit hyperactivity disorder, and ELS. In study 2, the substance use/rule-breaking profile was associated with reduced recruitment of reward processing and attentional neuro-circuitries during the Passive Avoidance task (p < 0.05, corrected for multiple comparisons).

CONCLUSIONS

Findings indicate that there is reduced responsivity of striato-cortical regions when receiving outcomes on an instrumental learning task within a profile of adolescents with substance use and rule-breaking behaviors. Mitigating reward processing dysfunction specifically may represent a potential intervention target for substance-use psychopathologies accompanied by rule-breaking behaviors.

The Willpower Paradox: Possible and Impossible Conceptions of Self-Control

Self-control denotes the ability to override current desires to render behavior consistent with long-term goals. A key assumption is that self-control is required when short-term desires are transiently stronger (more preferred) than long-term goals and people would yield to temptation without exerting self-control. We argue that this widely shared conception of self-control raises a fundamental yet rarely discussed conceptual paradox: How is it possible that a person most strongly desires to perform a behavior (e.g., eat chocolate) and at the same time desires to recruit self-control to prevent themselves from doing it? A detailed analysis reveals that three common assumptions about self-control cannot be true simultaneously. To avoid the paradox, any coherent theory of self-control must abandon either the assumption (a) that recruitment of self-control is an intentional process, or (b) that humans are unitary agents, or (c) that self-control consists in overriding the currently strongest desire. We propose a taxonomy of different kinds of self-control processes that helps organize current theories according to which of these assumptions they abandon. We conclude by outlining unresolved questions and future research perspectives raised by different conceptions of self-control and discuss implications for the question of whether self-control can be considered rational.

Aberrant neural network activation during reliving of autobiographical memories in adolescent depression

BACKGROUND

Adolescents with depression exhibit negative biases in autobiographical memory with detrimental consequences for their self-concept and well-being. Investigating how adolescents relive positive autobiographical memories and activate the underlying neural networks could reveal mechanisms that drive such biases. This study investigated neural networks when reliving positive and neutral memories, and how neural activity is modulated by valence and vividness in adolescents with and without depression.

METHODS

Adolescents (N = 69; n = 17 with depression) retrieved positive and neutral autobiographical memories. On a separate day, they relived these memories during fMRI scanning, and reported on pleasantness and vividness after reliving each memory. We used a multivariate, data-driven approach - event-related independent component analysis (eICA) - to characterize neural networks supporting autobiographical recollection.

RESULTS

Adolescents with depression reported their positive memories as significantly less pleasant compared to healthy controls, while subjective vividness was unaffected. Using eICA, we identified a broad autobiographical memory network, and subnetworks related to reliving positive vs neutral memories. These subnetworks comprised a 'self-referential processing network' including medial prefrontal cortex, posterior cingulate cortex/precuneus, and temporoparietal junction, anti-correlating with parts of the central executive network and salience network. Adolescents with depression exhibited aberrant activation in this self-referential network, but only when reliving relatively 'low' pleasant memories.

CONCLUSIONS

Our findings provide first insights into how the quality of reliving autobiographical memories in adolescents with depression may relate to aberrant self-referential neural network activation, and underscore the potential of targeting memory reliving in therapeutic interventions to foster self-esteem and diminish depressive symptoms.

Chronic Deep Brain Stimulation of the Human Nucleus Accumbens Region Disrupts the Stability of Intertemporal Preferences

When choosing between rewards that differ in temporal proximity (intertemporal choice), human preferences are typically stable, constituting a clinically relevant transdiagnostic trait. Here we show, in female and male human patients undergoing deep brain stimulation (DBS) of the anterior limb of the internal capsule/NAcc region for treatment-resistant obsessive-compulsive disorder, that long-term chronic (but not phasic) DBS disrupts intertemporal preferences. Hierarchical Bayesian modeling accounting for temporal discounting behavior across multiple time points allowed us to assess both short-term and long-term reliability of intertemporal choice. In controls, temporal discounting was highly reliable, both long-term (6 months) and short-term (1 week). In contrast, in patients undergoing DBS, short-term reliability was high, but long-term reliability (6 months) was severely disrupted. Control analyses confirmed that this effect was not because of range restriction, the presence of obsessive-compulsive disorder symptoms or group differences in choice stochasticity. Model-agnostic between- and within-subject analyses confirmed this effect. These findings provide initial evidence for long-term modulation of cognitive function via DBS and highlight a potential contribution of the human NAcc region to intertemporal preference stability over time.SIGNIFICANCE STATEMENT Choosing between rewards that differ in temporal proximity is in part a stable trait with relevance for many mental disorders, and depends on prefrontal regions and regions of the dopamine system. Here we show that chronic deep brain stimulation of the human anterior limb of the internal capsule/NAcc region for treatment-resistant obsessive-compulsive disorder disrupts the stability of intertemporal preferences. These findings show that chronic stimulation of one of the brain's central motivational hubs can disrupt preferences thought to depend on this circuit.

Economic and social values in the brain: evidence from lesions to the human ventromedial prefrontal cortex

Making good economic and social decisions is essential for individual and social welfare. Decades of research have provided compelling evidence that damage to the ventromedial prefrontal cortex (vmPFC) is associated with dramatic personality changes and impairments in economic and social decision-making. However, whether the vmPFC subserves a unified mechanism in the social and non-social domains remains unclear. When choosing between economic options, the vmPFC is thought to guide decision by encoding value signals that reflect the motivational relevance of the options on a common scale. A recent framework, the "extended common neural currency" hypothesis, suggests that the vmPFC may also assign values to social factors and principles, thereby guiding social decision-making. Although neural value signals have been observed in the vmPFC in both social and non-social studies, it is yet to be determined whether they have a causal influence on behavior or merely correlate with decision-making. In this review, we assess whether lesion studies of patients with vmPFC damage offer evidence for such a causal role of the vmPFC in shaping economic and social behavior.

Working memory and attention in choice

We study the role of attention and working memory in choices where options are presented sequentially rather than simultaneously. We build a model where a costly attention effort is chosen, which can vary over time. Evidence is accumulated proportionally to this effort and the utility of the reward. Crucially, the evidence accumulated decays over time. Optimal attention allocation maximizes expected utility from final choice; the optimal solution takes the decay into account, so attention is preferentially devoted to later times; but convexity of the flow attention cost prevents it from being concentrated near the end. We test this model with a choice experiment where participants observe sequentially two options. In our data the option presented first is, everything else being equal, significantly less likely to be chosen. This recency effect has a natural explanation with appropriate parameter values in our model of leaky evidence accumulation, where the decline is stronger for the option observed first. Analysis of choice, response time and brain imaging data provide support for the model. Working memory plays an essential role. The recency bias is stronger for participants with weaker performance in working memory tasks. Also activity in parietal areas, coding the stored value in working, declines over time as predicted.

Dissociable contributions of the medial parietal cortex to recognition memory

Human neuroimaging studies of episodic memory retrieval routinely observe the engagement of specific cortical regions beyond the medial temporal lobe. Of these, medial parietal cortex (MPC) is of particular interest given its ubiquitous, and yet distinct, functional characteristics during different types of retrieval tasks. Specifically, while recognition memory and autobiographical recall tasks are both used to probe episodic retrieval, these paradigms consistently drive distinct patterns of response within MPC. This dissociation adds to growing evidence suggesting a common principle of functional organization across memory related brain structures, specifically regarding the control or content demands of memory-based decisions. To carefully examine this putative organization, we used a high-resolution fMRI dataset collected at ultra-high field (7T) while subjects performed thousands of recognition-memory trials to identify MPC regions responsive to recognition-decisions or semantic content of stimuli within and across individuals. We observed interleaving, though distinct, functional subregions of MPC where responses were sensitive to either recognition decisions or the semantic representation of stimuli, but rarely both. In addition, this functional dissociation within MPC was further accentuated by distinct profiles of connectivity bias with the hippocampus during task and rest. Finally, we show that recent observations of person and place selectivity within MPC reflect category specific responses from within identified semantic regions that are sensitive to mnemonic demands. Together, these data better account for how distinct patterns of MPC responses can occur as a result of task demands during episodic retrieval and may reflect a common principle of organization throughout hippocampal-neocortical memory systems.

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.

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.

A mesocorticolimbic signature of pleasure in the human brain

Pleasure is a fundamental driver of human behaviour, yet its neural basis remains largely unknown. Rodent studies highlight opioidergic neural circuits connecting the nucleus accumbens, ventral pallidum, insula and orbitofrontal cortex as critical for the initiation and regulation of pleasure, and human neuroimaging studies exhibit some translational parity. However, whether activation in these regions conveys a generalizable representation of pleasure regulated by opioidergic mechanisms remains unclear. Here we use pattern recognition techniques to develop a human functional magnetic resonance imaging signature of mesocorticolimbic activity unique to states of pleasure. In independent validation tests, this signature is sensitive to pleasant tastes and affect evoked by humour. The signature is spatially co-extensive with mu-opioid receptor gene expression, and its response is attenuated by the opioid antagonist naloxone. These findings provide evidence for a basis of pleasure in humans that is distributed across brain systems.

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-Prioritization Reconsidered: Scrutinizing Three Claims

Such is the power of self-relevance, it has been argued that even arbitrary stimuli (e.g., shapes, lines, colors) with no prior personal connection are privileged during information processing following their association with the self (i.e., self-prioritization). This prioritization effect, moreover, is deemed to be stimulus driven (i.e., automatic), grounded in perception, and supported by specialized processing operations. Here, however, we scrutinize these claims and challenge this viewpoint. Although self-relevance unquestionably influences information processing, we contend that, at least at present, there is limited evidence to suggest that the prioritization of arbitrary self-related stimuli is compulsory, penetrates perception, and is underpinned by activity in a dedicated neural network. Rather, self-prioritization appears to be a task-dependent product of ordinary cognitive processes.

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.

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.

Anxiety and depression related abnormalities in socio-affective learning

Affective distress (as observed in anxiety and depression) has been observed to be related to insufficient sensitivity to changing reinforcement during operant learning. Whether such findings are specific to anxiety or depression is unclear given a wider literature relating negative affect to abnormal learning and the possibility that relationships are not consistent across incentive types (i.e., punishment and reward) and outcomes (i.e., positive or negative). In two separate samples (n = 100; n = 88), participants completed an operant learning task with positive or negative, and neutral socio-affective feedback, designed to assess adaptive responses to changing environmental volatility. Individual parameter estimates were generated with hierarchical Bayesian modelling. Effects of manipulations were modelled by decomposing parameters into a linear combination of effects on the logit scale. While effects tended to support prior work, neither general affective distress nor anxiety or depression were consistently related to a decrease in the adaptive adjustment of learning-rates in response to changing environmental volatility (Sample 1: β_{α:volatility} = -0.01, 95 % HDI = -0.14, 0.13; Sample 2: β_{α:volatility} = -0.15, 95 % HDI = -0.37, 0.05). Interaction effects in Sample 1 suggested that while distress was associated with decrements in adaptive learning under punishment-maximisation, it was associated with improvements under reward-maximisation. While our results are broadly consistent with prior work, they suggest that the role of anxiety or depression in volatility learning, if present, is subtle and difficult to detect. Inconsistencies between our samples, along with issues of parameter identifiability complicated interpretation.

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.

Glutamatergic and GABAergic neurons in pontine central gray mediate opposing valence-specific behaviors through a global network

Extracting the valence of environmental cues is critical for animals' survival. How valence in sensory signals is encoded and transformed to produce distinct behavioral responses remains not well understood. Here, we report that the mouse pontine central gray (PCG) contributes to encoding both negative and positive valences. PCG glutamatergic neurons were activated selectively by aversive, but not reward, stimuli, whereas its GABAergic neurons were preferentially activated by reward signals. The optogenetic activation of these two populations resulted in avoidance and preference behavior, respectively, and was sufficient to induce conditioned place aversion/preference. Suppression of them reduced sensory-induced aversive and appetitive behaviors, respectively. These two functionally opponent populations, receiving a broad range of inputs from overlapping yet distinct sources, broadcast valence-specific information to a distributed brain network with distinguishable downstream effectors. Thus, PCG serves as a critical hub to process positive and negative valences of incoming sensory signals and drive valence-specific behaviors with distinct circuits.

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.