Disentangling neural representations of value and salience in the human brain

A neural code supporting prospective probabilistic reasoning for instrumental information demand in humans

When making adaptive decisions, we actively demand information, but relatively little is known about the mechanisms of active information gathering. An open question is how the brain prospectively estimates the information gains that are expected to accrue from various sources by integrating simpler quantities of prior certainty and the reliability (diagnosticity) of a source. We examine this question using fMRI in a task in which people placed bids to obtain information in conditions that varied independently in the rewards, decision uncertainty, and information diagnosticity. We show that, consistent with value of information theory, the participants' bids are sensitive to prior certainty (the certainty about the correct choice before gathering information) and expected posterior certainty (the certainty expected after gathering information). Expected posterior certainty is decoded from multivoxel activation patterns in the posterior parietal and extrastriate cortices. This representation is independent of instrumental rewards and spatially overlaps with distinct representations of prior certainty and expected information gains. The findings suggest that the posterior parietal and extrastriate cortices are candidates for mediating the prospection of posterior probabilities as a key step to anticipating information gains during active gathering of instrumental information.

Neural Hyperresponsivity During the Anticipation of Tangible Social and Nonsocial Rewards in Autism Spectrum Disorder: A Concurrent Neuroimaging and Facial Electromyography Study

BACKGROUND

Atypical anticipation of social reward has been shown to lie at the core of the social challenges faced by individuals with autism spectrum disorder (ASD). However, previous research has yielded inconsistent results and has often overlooked crucial characteristics of stimuli. Here, we investigated ASD reward processing using social and nonsocial tangible stimuli, carefully matched on several key dimensions.

METHODS

We examined the anticipation and consumption of social (interpersonal touch) and nonsocial (flavored milk) rewards in 25 high-functioning individuals with ASD and 25 neurotypical adult individuals. In addition to subjective ratings of wanting and liking, we measured physical energetic expenditure to obtain the rewards, brain activity with neuroimaging, and facial reactions through electromyography on a trial-by-trial basis.

RESULTS

Participants with ASD did not exhibit reduced motivation for social or nonsocial rewards; their subjective ratings, motivated efforts, and facial reactions were comparable to those of neurotypical participants. However, anticipation of higher-value rewards increased neural activation in lateral parietal cortices, sensorimotor regions, and the orbitofrontal cortex. Moreover, participants with ASD exhibited hyperconnectivity between frontal medial regions and occipital regions and the thalamus.

CONCLUSIONS

Individuals with ASD who experienced rewards with tangible characteristics, whether social or nonsocial, displayed typical subjective and objective motivational and hedonic responses. Notably, the observed hyperactivations in sensory and attentional nodes during anticipation suggest atypical sensory overprocessing of forthcoming rewards rather than decreased reward value. While these atypicalities may not have manifested in observable behavior here, they could impact real-life social interactions that require nuanced predictions, potentially leading to the misperception of reduced interest in rewarding social stimuli in ASD.

Neural Representation of Valenced and Generic Probability and Uncertainty

Representing the probability and uncertainty of outcomes facilitates adaptive behavior by allowing organisms to prepare in advance and devote attention to relevant events. Probability and uncertainty are often studied only for valenced (appetitive or aversive) outcomes, raising the question of whether the identified neural machinery also processes the probability and uncertainty of motivationally neutral outcomes. Here, we aimed to dissociate valenced from valence-independent (i.e., generic) probability (p; maximum at p = 1) and uncertainty (maximum at p = 0.5) signals using human neuroimaging. In a Pavlovian task (n = 41; 19 females), different cues predicted appetitive, aversive, or neutral liquids with different probabilities (p = 0, p = 0.5, p = 1). Cue-elicited motor responses accelerated, and pupil sizes increased primarily for cues that predicted valenced liquids with higher probability. For neutral liquids, uncertainty rather than probability tended to accelerate cue-induced responding and decrease pupil size. At the neural level, generic uncertainty signals were limited to the occipital cortex, while generic probability also activated the anterior ventromedial prefrontal cortex. These generic probability and uncertainty signals contrasted with cue-induced responses that only encoded the probability and uncertainty of valenced liquids in medial prefrontal, insular, and occipital cortices. Our findings show a behavioral and neural dissociation of generic and valenced signals. Thus, some parts of the brain keep track of motivational charge while others do not, highlighting the need and usefulness of characterizing the exact nature of learned representations.

Brain representations of affective valence and intensity in sustained pleasure and pain

Pleasure and pain are two fundamental, intertwined aspects of human emotions. Pleasurable sensations can reduce subjective feelings of pain and vice versa, and we often perceive the termination of pain as pleasant and the absence of pleasure as unpleasant. This implies the existence of brain systems that integrate them into modality-general representations of affective experiences. Here, we examined representations of affective valence and intensity in an functional MRI (fMRI) study (n = 58) of sustained pleasure and pain. We found that the distinct subpopulations of voxels within the ventromedial and lateral prefrontal cortices, the orbitofrontal cortex, the anterior insula, and the amygdala were involved in decoding affective valence versus intensity. Affective valence and intensity predictive models showed significant decoding performance in an independent test dataset (n = 62). These models were differentially connected to distinct large-scale brain networks-the intensity model to the ventral attention network and the valence model to the limbic and default mode networks. Overall, this study identified the brain representations of affective valence and intensity across pleasure and pain, promoting a systems-level understanding of human affective experiences.

The neural mechanism of communication between graduate students and advisers in different adviser-advisee relationships

Communication is crucial in constructing the relationship between students and advisers, ultimately bridging interpersonal interactions. Only a few studies however explore the communication between postgraduate students and advisers. To fill the gaps in the empirical researches, this study uses functional near-infrared spectroscopy (FNIRS) techniques to explore the neurophysiology differences in brain activation of postgraduates with different adviser-advise relationships during simulated communication with their advisers. Results showed significant differences in the activation of the prefrontal cortex between high-quality and the low-quality students during simulating and when communicating with advisers, specifically in the Broca's areas, the frontal pole, and the orbitofrontal and dorsolateral prefrontal cortices. This further elucidated the complex cognitive process of communication between graduate students and advisers.

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.

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

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

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.

Fractionation of neural reward processing into independent components by novel decoding principle

How to retrieve latent neurobehavioural processes from complex neurobiological signals is an important yet unresolved challenge. Here, we develop a novel approach, orthogonal-Decoding multi-Cognitive Processes (DeCoP), to reveal underlying latent neurobehavioural processing and show that its performance is superior to traditional non-orthogonal decoding in terms of both false inference and robustness. Processing value and salience information are two fundamental but mutually confounded pathways of reward reinforcement essential for decision making. During reward/punishment anticipation, we applied DeCoP to decode brain-wide responses into spatially overlapping, yet functionally independent, evaluation and readiness processes, which are modulated differentially by meso‑limbic vs nigro-striatal dopamine systems. Using DeCoP, we further demonstrated that most brain regions only encoded abstract information but not the exact input, except for dorsal anterior cingulate cortex and insula. Furthermore, we anticipate our novel analytical principle to be applied generally in decoding multiple latent neurobehavioral processes and thus advance both the design and hypothesis testing for cognitive tasks.

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 Distinct Neural Code Supports Prospection of Future Probabilities During Instrumental Information-Seeking

To make adaptive decisions, we must actively demand information, but relatively little is known about the mechanisms of active information gathering. An open question is how the brain estimates expected information gains (EIG) when comparing the current decision uncertainty with the uncertainty that is expected after gathering information. We examined this question using fMRI in a task in which people placed bids to obtain information in conditions that varied independently by prior decision uncertainty, information diagnosticity, and the penalty for an erroneous choice. Consistent with value of information theory, bids were sensitive to EIG and its components of prior certainty and expected posterior certainty. Expected posterior certainty was decoded above chance from multivoxel activation patterns in the posterior parietal and extrastriate cortices. This representation was independent of instrumental rewards and overlapped with distinct representations of EIG and prior certainty. Thus, posterior parietal and extrastriate cortices are candidates for mediating the prospection of posterior probabilities as a key step to estimate EIG during active information gathering.

Higher subjective socioeconomic status is linked to increased charitable giving and mentalizing-related neural value coding

Socioeconomic status (SES), a concept related to an individual's economic and social position relative to others, can shape social interactions like altruistic behaviors. However, little is known about the exact neurocognitive mechanisms that link SES with altruism. Our study aimed to provide a comprehensive account of the sociocognitive and neural mechanisms through which SES affects charitable giving - an important variant of human altruism. To this end, participants completed a charitable donation task while their brain activity was measured using functional magnetic resonance imaging (fMRI). We also assessed participants' socio-cognitive ability to infer other people's mental states (i.e., mentalizing) - a driver of prosocial behavior - in an independent social task. Behaviorally, we found that both charitable giving and social cognition were status-dependent, as subjective SES positively predicted donations and mentalizing capacity. Moreover, the link between SES and charitable giving was mediated by individuals' mentalizing capacity. At the neural level, a multivariate pattern analysis of fMRI data revealed that higher subjective SES was associated with stronger value coding in the right temporoparietal junction (rTPJ). The strength of this value representation predicted charitable giving and was linked to mentalizing. Furthermore, we observed an increased negative functional coupling between rTPJ and left putamen with higher SES. Together, increased charitable giving in higher-status individuals could be explained by status-dependent recruitment of mentalizing-related value coding and altered functional connectivity in the brain. Our findings provide insights into the socio- and neurocognitive mechanisms explaining why and when higher SES leads to prosociality, which might ultimately inform targeted interventions to promote prosocial behavior in human societies.

The dorsomedial prefrontal cortex represents subjective value across effort-based and risky decision-making

Decisions that require taking effort costs into account are ubiquitous in real life. The neural common currency theory hypothesizes that a particular neural network integrates different costs (e.g., risk) and rewards into a common scale to facilitate value comparison. Although there has been a surge of interest in the computational and neural basis of effort-related value integration, it is still under debate if effort-based decision-making relies on a domain-general valuation network as implicated in the neural common currency theory. Therefore, we comprehensively compared effort-based and risky decision-making using a combination of computational modeling, univariate and multivariate fMRI analyses, and data from two independent studies. We found that effort-based decision-making can be best described by a power discounting model that accounts for both the discounting rate and effort sensitivity. At the neural level, multivariate decoding analyses indicated that the neural patterns of the dorsomedial prefrontal cortex (dmPFC) represented subjective value across different decision-making tasks including either effort or risk costs, although univariate signals were more diverse. These findings suggest that multivariate dmPFC patterns play a critical role in computing subjective value in a task-independent manner and thus extend the scope of the neural common currency theory.

Neural signatures of social inferences predict the number of real-life social contacts and autism severity

We regularly infer other people's thoughts and feelings from observing their actions, but how this ability contributes to successful social behavior and interactions remains unknown. We show that neural activation patterns during social inferences obtained in the laboratory predict the number of social contacts in the real world, as measured by the social network index, in three neurotypical samples (total n = 126) and one sample of autistic adults (n = 23). We also show that brain patterns during social inference generalize across individuals in these groups. Cross-validated associations between brain activations and social inference localize selectively to the right posterior superior temporal sulcus and were specific for social, but not nonsocial, inference. Activation within this same brain region also predicts autism-like trait scores from questionnaires and autism symptom severity. Thus, neural activations produced while thinking about other people's mental states predict variance in multiple indices of social functioning in the real world.

Critical tests of fuzzy trace theory in brain and behavior: uncertainty across time, probability, and development

Uncertainty permeates decisions from the trivial to the profound. Integrating brain and behavioral evidence, we discuss how probabilistic (varied outcomes) and temporal (delayed outcomes) uncertainty differ across age and individuals; how critical tests adjudicate between theories of uncertainty (prospect theory and fuzzy-trace theory); and how these mechanisms might be represented in the brain. The same categorical gist representations of gains and losses account for choices and eye-tracking data in both value-allocation (add money to gambles) and risky-choice tasks, disconfirming prospect theory and confirming predictions of fuzzy-trace theory. The analysis is extended to delay discounting and disambiguated choices, explaining hidden-zero effects that similarly turn on categorical distinctions between some gain and no gain, certain gain and uncertain gain, gain and loss, and now and later. Bold activation implicates dorsolateral prefrontal and posterior parietal cortices in gist strategies that are not just one tool in a grab-bag of cognitive options but rather are general strategies that systematically predict behaviors across many different tasks involving probabilistic and temporal uncertainty. High valuation (e.g., ventral striatum; ventromedial prefrontal cortex) and low executive control (e.g., lateral prefrontal cortex) contribute to risky and impatient choices, especially in youth. However, valuation in ventral striatum supports reward-maximizing and gist strategies in adulthood. Indeed, processing becomes less "rational" in the sense of maximizing gains and more noncompensatory (eye movements indicate fewer tradeoffs) as development progresses from adolescence to adulthood, as predicted. Implications for theoretically predicted "public-health paradoxes" are discussed, including gist versus verbatim thinking in drug experimentation and addiction.

Associations between age, social reward processing and social anxiety symptoms

Reward processing undergoes marked changes in adolescence, with social interactions representing a powerful source of reward. Reward processing is also an important factor in the development of social anxiety disorder, a condition that most commonly first appears in adolescence. This study investigated the relationship between age, social reward processing and social anxiety in a cross-sectional sample of female participants (N = 80) aged 13-34. Participants performed two versions of a probabilistic reward anticipation task, in which a speeded response could result in different probabilities of receiving either social or monetary rewarding feedback. Participants also completed self-report assessments of social reward value, trait anxiety and social anxiety symptoms. At high reward probabilities, performance on both reward tasks showed a quadratic effect of age, with the fastest responses at around 22-24 years. A similar quadratic effect was found for subjective liking ratings of both reward stimuli, although these were not associated with performance. Social anxiety was not associated with a subjective liking of the rewards but did predict performance on both tasks at all reward probabilities. Age-related variation in reward processing was not accounted for by age-related variation in social anxiety symptoms, suggesting that, while both social anxiety and age were associated with variation in reward processing, their effects were largely independent. Together, these findings provide evidence that social reward processing continues to develop across adolescence and that individual differences in social anxiety should be considered when considering reward sensitivity during this period.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12144-023-04551-y.

Quantifying aberrant approach-avoidance conflict in psychopathology: A review of computational approaches

Making effective decisions during approach-avoidance conflict is critical in daily life. Aberrant decision-making during approach-avoidance conflict is evident in a range of psychological disorders, including anxiety, depression, trauma-related disorders, substance use disorders, and alcohol use disorders. To help clarify etiological pathways and reveal novel intervention targets, clinical research into decision-making is increasingly adopting a computational psychopathology approach. This approach uses mathematical models that can identify specific decision-making related processes that are altered in mental health disorders. In our review, we highlight foundational approach-avoidance conflict research, followed by more in-depth discussion of computational approaches that have been used to model behavior in these tasks. Specifically, we describe the computational models that have been applied to approach-avoidance conflict (e.g., drift-diffusion, active inference, and reinforcement learning models), and provide resources to guide clinical researchers who may be interested in applying computational modeling. Finally, we identify notable gaps in the current literature and potential future directions for computational approaches aimed at identifying mechanisms of approach-avoidance conflict in psychopathology.

Modulation of aversive value coding in the vertebrate and invertebrate brain

Avoiding potentially dangerous situations is key for the survival of any organism. Throughout life, animals learn to avoid environments, stimuli or actions that can lead to bodily harm. While the neural bases for appetitive learning, evaluation and value-based decision-making have received much attention, recent studies have revealed more complex computations for aversive signals during learning and decision-making than previously thought. Furthermore, previous experience, internal state and systems level appetitive-aversive interactions seem crucial for learning specific aversive value signals and making appropriate choices. The emergence of novel methodologies (computation analysis coupled with large-scale neuronal recordings, neuronal manipulations at unprecedented resolution offered by genetics, viral strategies and connectomics) has helped to provide novel circuit-based models for aversive (and appetitive) valuation. In this review, we focus on recent vertebrate and invertebrate studies yielding strong evidence that aversive value information can be computed by a multitude of interacting brain regions, and that past experience can modulate future aversive learning and therefore influence value-based decisions.

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

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

IT IS A MATTER OF PERSPECTIVE: ATTENTIONAL FOCUS RATHER THAN DIETARY RESTRAINT DRIVES BRAIN RESPONSES TO FOOD STIMULI

Brain responses to food are thought to reflect food's rewarding value and to fluctuate with dietary restraint. We propose that brain responses to food are dynamic and depend on attentional focus. Food pictures (high-caloric/low-caloric, palatable/unpalatable) were presented during fMRI-scanning, while attentional focus (hedonic/health/neutral) was induced in 52 female participants varying in dietary restraint. The level of brain activity was hardly different between palatable versus unpalatable foods or high-caloric versus low-caloric foods. Activity in several brain regions was higher in hedonic than in health or neutral attentional focus (p < 0.05, FWE-corrected). Palatability and calorie content could be decoded from multi-voxel activity patterns (p < 0.05, FDR-corrected). Dietary restraint did not significantly influence brain responses to food. So, level of brain activity in response to food stimuli depends on attentional focus, and may reflect salience, not reward value. Palatability and calorie content are reflected in patterns of brain activity.

More complex than you might think: Neural representations of food reward value in obesity

Obesity reached pandemic proportions and weight-loss treatments are mostly ineffective. The level of brain activity in the reward circuitry is proposed to be proportionate to the reward value of food stimuli, and stronger in people with obesity. However, empirical evidence is inconsistent. This may be due to the double-sided nature of high caloric palatable foods: at once highly palatable and high in calories (unhealthy). This study hypothesizes that, viewing high caloric palatable foods, a hedonic attentional focus compared to a health and a neutral attentional focus elicits more activity in reward-related brain regions, mostly in people with obesity. Moreover, caloric content and food palatability can be decoded from multivoxel patterns of activity most accurately in people with obesity and in the corresponding attentional focus. During one fMRI-session, attentional focus (hedonic, health, neutral) was manipulated using a one-back task with individually tailored food stimuli in 32 healthy-weight people and 29 people with obesity. Univariate analyses (p < 0.05, FWE-corrected) showed that brain activity was not different for palatable vs. unpalatable foods, nor for high vs. low caloric foods. Instead, this was higher in the hedonic compared to the health and neutral attentional focus. Multivariate analyses (MVPA) (p < 0.05, FDR-corrected) showed that palatability and caloric content could be decoded above chance level, independently of either BMI or attentional focus. Thus, brain activity to visual food stimuli is neither proportionate to the reward value (palatability and/or caloric content), nor significantly moderated by BMI. Instead, it depends on people's attentional focus, and may reflect motivational salience. Furthermore, food palatability and caloric content are represented as patterns of brain activity, independently of BMI and attentional focus. So, food reward value is reflected in patterns, not levels, of brain activity.

Salience memories formed by value, novelty and aversiveness jointly shape object responses in the prefrontal cortex and basal ganglia

Ecological fitness depends on maintaining object histories to guide future interactions. Recent evidence shows that value memory changes passive visual responses to objects in ventrolateral prefrontal cortex (vlPFC) and substantia nigra reticulata (SNr). However, it is not known whether this effect is limited to reward history and if not how cross-domain representations are organized within the same or different neural populations in this corticobasal circuitry. To address this issue, visual responses of the same neurons across appetitive, aversive and novelty domains were recorded in vlPFC and SNr. Results showed that changes in visual responses across domains happened in the same rather than separate populations and were related to salience rather than valence of objects. Furthermore, while SNr preferentially encoded outcome related salience memory, vlPFC encoded salience memory across all domains in a correlated fashion, consistent with its role as an information hub to guide behavior.

The involvement of the posterior parietal cortex in promotion and prevention focus

Motivation plays a critical role in human cognitive function, while acting as a driving force for the necessary behavior to achieve a desired goal and success (i.e., achievement motivation). Based on the theoretical background of achievement motivation, this study designed an incentive delay task with four motivational orientations (i.e., promotion, prevention, mastery/self, and performance/other). To investigate whether people would have their behavioral patterns toward achievement motivation orientation, we applied an unsupervised clustering algorithm to classify individuals’ behavioral responses acquired from the task by categorizing certain behavioral similarities. As a result, this hierarchical clustering approach classified subjects into two distinctive subgroups: Group#1 (i.e., the pro/pre group, n = 52) and Group#2 (i.e., the self/other group, n = 48). Based on clustering, Group#1 showed significantly better performance with promotion/prevention orientations, whereas Group#2 exhibited significantly higher performance with self/other orientations. Structural brain analyses discovered increased gray matter volume and sulcal depth in the posterior parietal cortex (PPC) in the pro/pre group compared to the self/other group. With resting-state functional magnetic resonance imaging data, we found higher local brain fluctuations in the medial prefrontal cortex (mPFC) in the self/other group compared to the pro/pre group. Furthermore, mPFC seed-based functional connectivity showed significantly increased functional coupling with the posterior cingulate cortex in the self/other group relative to the pro/pre group. Taken together, these results shed light on structural and functional neural mechanisms related to achievement motivation and, furthermore, provide novel insights regarding PPC’s role in motivational processing toward promotion- and prevention-focused orientation.

Learning from Ingroup Experiences Changes Intergroup Impressions

Humans form impressions toward individuals of their own social groups (ingroup members) and of different social groups (outgroup members). Outgroup-focused theories predict that intergroup impressions are mainly shaped by experiences with outgroup individuals, while ingroup-focused theories predict that ingroup experiences play a dominant role. Here we test predictions from these two psychological theories by estimating how intergroup impressions are dynamically shaped when people learn from both ingroup and outgroup experiences. While undergoing fMRI, male participants had identical experiences with different ingroup or outgroup members and rated their social closeness and impressions toward the ingroup and the outgroup. Behavioral results showed an initial ingroup bias in impression ratings which was significantly reduced over the course of learning, with larger effects in individuals with stronger ingroup identification. Computational learning models revealed that these changes in intergroup impressions were predicted by the weight given to ingroup prediction errors. Neurally, the individual weight for ingroup prediction errors was related to the coupling between the left inferior parietal lobule and the left anterior insula, which, in turn, predicted learning-related changes in intergroup impressions. Our findings provide computational and neural evidence for ingroup-focused theories, highlighting the importance of ingroup experiences in shaping social impressions in intergroup settings.SIGNIFICANCE STATEMENT Living in multicultural societies, humans interact with individuals of their own social groups (ingroup members) and of different social groups (outgroup members). However, little is known about how people learn from the mixture of ingroup and outgroup interactions, the most natural experiences in current societies. Here, participants had identical, intermixed experiences with different ingroup and outgroup individuals and rated their closeness and impressions toward the ingroup and the outgroup. Combining computational models and fMRI, we find that the weight given to ingroup experiences (ingroup prediction errors) is the main source of intergroup impression change, captured by changes in connectivity between the parietal lobe and insula. These findings highlight the importance of ingroup experiences in shaping intergroup impressions in complex social environments.

Asymmetric representation of aversive prediction errors in Pavlovian threat conditioning

Survival in biological environments requires learning associations between predictive sensory cues and threatening outcomes. Such aversive learning may be implemented through reinforcement learning algorithms that are driven by the signed difference between expected and encountered outcomes, termed prediction errors (PEs). While PE-based learning is well established for reward learning, the role of putative PE signals in aversive learning is less clear. Here, we used functional magnetic resonance imaging in humans (21 healthy men and women) to investigate the neural representation of PEs during maintenance of learned aversive associations. Four visual cues, each with a different probability (0, 33, 66, 100%) of being followed by an aversive outcome (electric shock), were repeatedly presented to participants. We found that neural activity at omission (US-) but not occurrence of the aversive outcome (US+) encoded PEs in the medial prefrontal cortex. More expected omission of aversive outcome was associated with lower neural activity. No neural signals fulfilled axiomatic criteria, which specify necessary and sufficient components of PE signals, for signed PE representation in a whole-brain search or in a-priori regions of interest. Our results might suggest that, different from reward learning, aversive learning does not involve signed PE signals that are represented within the same brain region for all conditions.

Perceptual scale for transparency: Common fate overrides geometrical and color cues

Objects that pass light through are considered transparent, and we generally expect that the light coming out will match the color of the object. However, when the object is placed on a colored surface, the light coming back to our eyes becomes a composite of surface, illumination, and transparency properties. Despite that, we can often perceive separate overlaid and overlaying layers differing in colors. How neurons separate the information to extract the transparent layer remains unknown, but the physical characteristics of transparent filters generate geometrical and color features in retinal images, which could provide cues for separating layers. We estimated the relative importance of such cues in a perceptual scale for transparency, using stimuli in which X- or T-junctions, different relative motions, and consistent or inconsistent colors cooperated or competed in forced-preference psychophysics experiments. Maximum-likelihood Thurstone scaling revealed that motion increased transparency for X-junctions, but decreased transparency for T-junctions by creating the percept of an opaque patch. However, if the motion of a filter uncovered a dynamically changing but stationary pattern, sharing a common fate with the surround but forming T-junctions, the probability of seeing transparency was almost as high as for moving X-junctions, despite the stimulus being physically improbable. In addition, geometric cues overrode color inconsistency to a great degree. Finally, a linear model of transparency perception as a function of relative motions between filter, overlay, and surround layers, contour continuation, and color consistency, quantified a hierarchy of latent influences on when the filter is seen as a separate transparent layer.

At-risk alcohol users have disrupted valence discrimination during reward anticipation

Alcohol use disorder is characterised by disrupted reward learning, underpinned by dysfunctional cortico-striatal reward pathways, although relatively little is known about the biology of reward processing in populations who engage in risky alcohol use. Cues that trigger reward anticipation can be categorized according to their learnt valence (i.e., positive vs. negative outcomes) and motivational salience (i.e., incentive vs. neutral cues). Separating EEG signals associated with these dimensions is challenging because of their inherent collinearity, but the recent application of machine learning methods to single EEG trials affords a solution. Here, the Alcohol Use Disorders Identification Test (AUDIT) was used to quantify risky alcohol use, with participants split into high alcohol (HA) (n = 22, mean AUDIT score: 13.82) and low alcohol (LA) (n = 22, mean AUDIT score: 5.77) groups. We applied machine learning multivariate single-trial classification to the electroencephalography (EEG) data collected during reward anticipation. The LA group demonstrated significant valence discrimination in the early stages of reward anticipation within the cue-P3 time window (400-550 ms), whereas the HA group was insensitive to valence within this time window. Notably, the LA, but not the HA group demonstrated a relationship between single-trial variability in the early valence component and reaction times for gain and loss trials. This study evidences disrupted hypoactive valence sensitivity in the HA group, revealing potential neurophysiological markers for risky drinking behaviours which place individuals at-risk of adverse health events.

Altruism under Stress: Cortisol Negatively Predicts Charitable Giving and Neural Value Representations Depending on Mentalizing Capacity

Altruism, defined as costly other-regarding behavior, varies considerably across people and contexts. One prominent context in which people frequently must decide on how to socially act is under stress. How does stress affect altruistic decision-making and through which neurocognitive mechanisms? To address these questions, we assessed neural activity associated with charitable giving under stress. Human participants (males and females) completed a charitable donation task before and after they underwent either a psychosocial stressor or a control manipulation, while their brain activity was measured using functional magnetic resonance imaging. As the ability to infer other people's mental states (i.e., mentalizing) predicts prosocial giving and may be susceptible to stress, we examined whether stress effects on altruism depend on participants' general capacity to mentalize, as assessed in an independent task. Although our stress manipulation per se had no influence on charitable giving, increases in the stress hormone cortisol were associated with reductions in donations in participants with high mentalizing capacity, but not in low mentalizers. Multivariate neural response patterns in the right dorsolateral prefrontal cortex (DLPFC) were less predictive of postmanipulation donations in high mentalizers with increased cortisol, indicating decreased value coding, and this effect mediated the (moderated) association between cortisol increases and reduced donations. Our findings provide novel insights into the modulation of altruistic decision-making by suggesting an impact of the stress hormone cortisol on mentalizing-related neurocognitive processes, which in turn results in decreased altruism. The DLPFC appears to play a key role in mediating this cortisol-related shift in altruism.SIGNIFICANCE STATEMENT Altruism is a fundamental building block of our society. Emerging evidence indicates a major role of acute stress and stress-related neuromodulators in social behavior and decision-making. How and through which mechanisms stress may impact altruism remains elusive. We observed that the stress hormone cortisol was linked to diminished altruistic behavior. This effect was mediated by reduced value representations in the right dorsolateral prefrontal cortex and critically depended on the individual capacity to infer mental states of others. Our findings provide novel insights into the modulation of human altruism linked to stress-hormone dynamics and into the involved sociocognitive and neural mechanisms, with important implications for future developments of more targeted interventions for stress-related decrements in social behavior and social cognition.

A Multivariate Functional Connectivity Approach to Mapping Brain Networks and Imputing Neural Activity in Mice

Temporal correlation analysis of spontaneous brain activity (e.g., Pearson "functional connectivity," FC) has provided insights into the functional organization of the human brain. However, bivariate analysis techniques such as this are often susceptible to confounding physiological processes (e.g., sleep, Mayer-waves, breathing, motion), which makes it difficult to accurately map connectivity in health and disease as these physiological processes affect FC. In contrast, a multivariate approach to imputing individual neural networks from spontaneous neuroimaging data could be influential to our conceptual understanding of FC and provide performance advantages. Therefore, we analyzed neural calcium imaging data from Thy1-GCaMP6f mice while either awake, asleep, anesthetized, during low and high bouts of motion, or before and after photothrombotic stroke. A linear support vector regression approach was used to determine the optimal weights for integrating the signals from the remaining pixels to accurately predict neural activity in a region of interest (ROI). The resultant weight maps for each ROI were interpreted as multivariate functional connectivity (MFC), resembled anatomical connectivity, and demonstrated a sparser set of strong focused positive connections than traditional FC. While global variations in data have large effects on standard correlation FC analysis, the MFC mapping methods were mostly impervious. Lastly, MFC analysis provided a more powerful connectivity deficit detection following stroke compared to traditional FC.

Dynamic Computation of Value Signals via a Common Neural Network in Multi-Attribute Decision-Making

Studies in decision neuroscience have identified robust neural representations for the value of choice options. However, overall values often depend on multiple attributes, and it is not well understood how the brain evaluates different attributes and integrates them to combined values. In particular, it is not clear whether attribute values are computed in distinct attribute-specific regions or within the general valuation network known to process overall values. Here, we used an fMRI choice task in which abstract stimuli had to be evaluated based on variations of the attributes color and motion. The behavioral data showed that participants responded faster when overall values were high and attribute value differences were low. On the neural level, we did not find that attribute values were systematically represented in areas V4 and V5, even though these regions are associated with attribute-specific processing of color and motion, respectively. Instead, attribute values were associated with activity in the posterior cingulate cortex, ventral striatum, and posterior inferior temporal gyrus. Further, overall values were represented in dorsolateral and ventromedial prefrontal cortex, and attribute value differences in dorsomedial prefrontal cortex, which suggests that these regions play a key role for the neural integration of attribute values.

A causal role for the right frontal eye fields in value comparison

Recent studies have suggested close functional links between overt visual attention and decision making. This suggests that the corresponding mechanisms may interface in brain regions known to be crucial for guiding visual attention - such as the frontal eye field (FEF). Here, we combined brain stimulation, eye tracking, and computational approaches to explore this possibility. We show that inhibitory transcranial magnetic stimulation (TMS) over the right FEF has a causal impact on decision making, reducing the effect of gaze dwell time on choice while also increasing reaction times. We computationally characterize this putative mechanism by using the attentional drift diffusion model (aDDM), which reveals that FEF inhibition reduces the relative discounting of the non-fixated option in the comparison process. Our findings establish an important causal role of the right FEF in choice, elucidate the underlying mechanism, and provide support for one of the key causal hypotheses associated with the aDDM.

Sex Differences in the Behavioral Inhibition System and Ventromedial Prefrontal Cortex Connectivity

The reinforcement sensitivity theory proposes brain–behavioral systems that underlie individual differences in sensitivity to punishment and reward. Such trait sensitivity is assessed using the behavioral inhibition/activation system (BIS/BAS) scales. Recent studies have reported sex-linked neuroanatomical correlates of the BIS/BAS, especially in the regions belonging to the valuation and salience networks that are associated with the representation of subjective value (SV), whereas less effort has been focused on investigating the neurofunctional aspects associated with sex differences in the BIS/BAS. We tested whether functional connectivity (FC) of the regions associated with the representation of SV mediates the relationship between sex and BIS sensitivity in healthy young adults by using resting-state functional magnetic resonance imaging data and self-reported BIS/BAS measures. Compared with males, females had heightened BIS sensitivity and increased FC between the ventromedial prefrontal cortex (vmPFC) seed and posterior parietal areas; this FC mediated the impact of sex on BIS sensitivity. Given that the observed vmPFC FC maps are considered part of the default-mode network, which is involved in ruminative processes, and that the BIS is associated with rumination and negative affect, our results may have implications for psychiatric disorders such as depression and anxiety, both of which have high incidence in females.

The Limits of Motivational Influence in ADHD: No Evidence for an Altered Reaction to Negative Reinforcement

Functional magnetic resonance imaging studies have reported a diminished response in the brain’s reward circuits to contingent cues predicting future monetary gain in adolescents with attention-deficit/hyperactivity disorder (ADHD). The situation with regard to monetary loss is less clear, despite recognition that both positive and negative consequences impact ADHD behaviour. Here, we employ a new Escape Monetary Loss Incentive task in an MRI scanner, which allows the differentiation of contingency and valence effects during loss avoidance, to examine ADHD-related alterations in monetary loss processing. There was no evidence of atypical processing of contingent or non-contingent monetary loss cues in ADHD — either in terms of ratings of emotional and motivational significance or brain responses. This suggests that the ability to process contingencies between performance and negative outcomes is intact in ADHD and that individuals with ADHD are no more (or less) sensitive to negative outcomes than controls. This latter finding stands in stark contrast to recent evidence from a similar task of atypical emotion network recruitment (e.g. amygdala) in ADHD individuals to cues predicting another negative event, the imposition of delay, suggesting marked specificity in the way they respond to negative events.

Decoding Odor Mixtures in the Dog Brain: An Awake fMRI Study

In working and practical contexts, dogs rely upon their ability to discriminate a target odor from distracting odors and other sensory stimuli. Using awake functional magnetic resonance imaging (fMRI) in 18 dogs, we examined the neural mechanisms underlying odor discrimination between 2 odors and a mixture of the odors. Neural activation was measured during the presentation of a target odor (A) associated with a food reward, a distractor odor (B) associated with nothing, and a mixture of the two odors (A+B). Changes in neural activation during the presentations of the odor stimuli in individual dogs were measured over time within three regions known to be involved with odor processing: the caudate nucleus, the amygdala, and the olfactory bulbs. Average activation within the amygdala showed that dogs maximally differentiated between odor stimuli based on the stimulus-reward associations by the first run, while activation to the mixture (A+B) was most similar to the no-reward (B) stimulus. To clarify the neural representation of odor mixtures in the dog brain, we used a random forest classifier to compare multilabel (elemental) versus multiclass (configural) models. The multiclass model performed much better than the multilabel (weighted-F1 0.44 vs. 0.14), suggesting the odor mixture was processed configurally. Analysis of the subset of high-performing dogs' brain classification metrics revealed a network of olfactory information-carrying brain regions that included the amygdala, piriform cortex, and posterior cingulate. These results add further evidence for the configural processing of odor mixtures in dogs and suggest a novel way to identify high-performers based on brain classification metrics.

Enhanced insightfulness and neural activation induced by metaphorical solutions to appropriate mental distress problems

Although the neural correlates of novelty and appropriateness of creative insight during cognitive tasks have been investigated in several studies, they have not been examined during mental distress in a psychotherapeutic setting. This study aimed to reveal the promoting effects of novelty and appropriateness processing on therapeutic insight in a micro-psychotherapeutic setting. We examined the effects of appropriateness (between-subject factor: appropriateness group, 20 participants; inappropriateness group, 21 participants) by manipulating the preceding negative scenarios that either fit or did not fit the subsequent solutions, and those of novelty (within-subject factor) by varying the linguistic expressions for describing solutions (metaphorical, literal, or problem-restatement). Event-related functional magnetic resonance images were collected. We found the following effects: an interactive effect of the two factors on insightfulness and activation in the bilateral hippocampus and amygdala, right superior frontal gyrus, and left superior/middle temporal gyrus; a simple effect of novelty on activation in the bilateral inferior frontal gyrus, fusiform gyrus, and inferior/middle occipital gyrus; and a simple effect of appropriateness on activation in the left inferior parietal lobule. Our findings indicate that solutions with high novelty and appropriateness generate the highest levels of therapeutic insightfulness as well as the strongest activation in the hippocampus and amygdala, which may be involved in episodic memory encoding.

Value network engagement and effects of memory-related processing during encoding and retrieval of value

Decision makers rely on episodic memory to calculate choice values in everyday life, yet it is unclear how neural mechanisms of valuation differ when value-related information is encoded versus retrieved from episodic memory. The current fMRI study compared neural correlates of value while information was encoded versus retrieved from memory. Scanned tasks were followed by a behavioral episodic memory test for item-attribute associations. Our analyses sought to (i) identify neural correlates of value that were distinct and common across encoding and retrieval, and (ii) determine whether neural mechanisms of valuation and episodic memory interact. The study yielded three primary findings. First, value-related activation in the fronto-striatal reward circuit and posterior parietal cortex was comparable across valuation phases. Second, value-related activation in select fronto-parietal and salience regions was significantly greater at value retrieval than encoding. Third, there was no interaction between neural correlates of valuation and episodic memory. Taken with prior research, the present study indicates that fronto-parietal and salience regions play a key role in retrieval-dependent valuation and context-specific effects likely determine whether neural correlates of value interact with episodic memory.

Neural reward circuit dysfunction as a risk factor for bipolar spectrum disorders and substance use disorders: A review and integration

Bipolar spectrum disorders (BSDs) and substance use disorders (SUDs) are associated with neural reward dysfunction. However, it is unclear what pattern of neural reward function underlies pre-existing vulnerability to BSDs and SUDs, or whether neural reward function explains their high co-occurrence. The current paper provides an overview of the separate literatures on neural reward sensitivity in BSDs and SUDs. We provide a systematic review of 35 studies relevant to identifying neural reward function vulnerability to BSDs and SUDs. These studies include those examining neural reward processing on a monetary reward task with prospective designs predicting initial onset of SUDs, familial risk studies that examine unaffected offspring or first-degree relatives of family members with BSDs or SUDs, and studies that examine individuals with BSDs or SUDs who are not currently in an episode of the disorder. Findings from the review highlight that aberrant responding and connectivity across neural regions associated with reward and cognitive control confers risk for the development of BSDs and SUDs. Discussion focuses on limitations of the extant literature. We conclude with an integration and theoretical model for understanding how aberrant neural reward responding may constitute a vulnerability to the development of both BSDs and SUDs.

Time-Varying Functional Connectivity Decreases as a Function of Acute Nicotine Abstinence

BACKGROUND

The nicotine withdrawal syndrome (NWS) includes affective and cognitive disruptions whose incidence and severity vary across time during acute abstinence. However, most network-level neuroimaging uses static measures of resting-state functional connectivity and assumes time-invariance and is thus unable to capture dynamic brain-behavior relationships. Recent advances in resting-state functional connectivity signal processing allow characterization of time-varying functional connectivity (TVFC), which characterizes network communication between networks that reconfigure over the course of data collection. Therefore, TVFC may more fully describe network dysfunction related to the NWS.

METHODS

To isolate alterations in the frequency and diversity of communication across network boundaries during acute nicotine abstinence, we scanned 25 cigarette smokers in the nicotine-sated and abstinent states and applied a previously validated method to characterize TVFC at a network and a nodal level within the brain.

RESULTS

During abstinence, we found brain-wide decreases in the frequency of interactions between network nodes in different modular communities (i.e., temporal flexibility). In addition, within a subset of the networks examined, the variability of these interactions across community boundaries (i.e., spatiotemporal diversity) also decreased. Finally, within 2 of these networks, the decrease in spatiotemporal diversity was significantly related to NWS clinical symptoms.

CONCLUSIONS

Using multiple measures of TVFC in a within-subjects design, we characterized a novel set of changes in network communication and linked these changes to specific behavioral symptoms of the NWS. These reductions in TVFC provide a meso-scale network description of the relative inflexibility of specific large-scale brain networks during acute abstinence.

Dissociating brain systems that respond to contingency and valence during monetary loss avoidance in adolescence

Negative reinforcement processes allow individuals to avoid negative and/or harmful outcomes. They depend on the brain's ability to differentiate; (i) contingency from non-contingency, separately from (ii) judgements about positive and negative valence. Thirty-three males (8-18 years) performed a cued reaction-time task during fMRI scanning to differentiate the brain's responses to contingency and valence during loss avoidance. In two conditions, cues indicated no -contingency between participants' responses and monetary loss - (1) CERTAIN LOSS (negative valence) of €0.20, €1 or €5 or (2) CERTAIN LOSS AVOIDANCE (positive valence). In a third condition, cues indicated a contingency between short reaction times and avoidance of monetary loss. As expected participants had shorter reaction times in this latter condition where CONDITIONAL LOSS AVOIDANCE cues activated salience and motor-response-preparation brain networks - independent of the relative valence of the contrast (CERTAIN LOSS or CERTAIN LOSS AVOIDANCE). Effects of valence were seen toward the session's end where CERTAIN LOSS AVOIDANCE cues activated ventral striatum, medial-orbitofrontal cortex and medial-temporal areas more than CERTAIN LOSS. CONDITIONAL LOSS AVOIDANCE trials with feedback indicating "success" activated ventral striatum more than "failure feedback". The findings support the hypothesis that brain networks controlling contingency and valence processes during negative reinforcement are dissociable.

Single-Dimensional Human Brain Signals for Two-Dimensional Economic Choice Options

Rewarding choice options typically contain multiple components, but neural signals in single brain voxels are scalar and primarily vary up or down. In a previous study, we had designed reward bundles that contained the same two milkshakes with independently set amounts; we had used psychophysics and rigorous economic concepts to estimate two-dimensional choice indifference curves (ICs) that represented revealed stochastic preferences for these bundles in a systematic, integrated manner. All bundles on the same ICs were equally revealed preferred (and thus had same utility, as inferred from choice indifference); bundles on higher ICs (higher utility) were preferred to bundles on lower ICs (lower utility). In the current study, we used the established behavior for testing with functional magnetic resonance imaging (fMRI). We now demonstrate neural responses in reward-related brain structures of human female and male participants, including striatum, midbrain, and medial orbitofrontal cortex (mid-OFC) that followed the characteristic pattern of ICs: similar responses along ICs (same utility despite different bundle composition), but monotonic change across ICs (different utility). Thus, these brain structures integrated multiple reward components into a scalar signal, well beyond the known subjective value coding of single-component rewards.SIGNIFICANCE STATEMENT Rewards have several components, like the taste and size of an apple, but it is unclear how each component contributes to the overall value of the reward. While choice indifference curves (ICs) of economic theory provide behavioral approaches to this question, it is unclear whether brain responses capture the preference and utility integrated from multiple components. We report activations in striatum, midbrain, and orbitofrontal cortex (OFC) that follow choice ICs representing behavioral preferences over and above variations of individual reward components. In addition, the concept-driven approach encourages future studies on natural, multicomponent rewards that are prone to irrational choice of normal and brain-damaged individuals.

Basal ganglia lateralization in different types of reward

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

Computational and Neurobiological Substrates of Cost-Benefit Integration in Altruistic Helping Decision

Although altruistic behaviors, e.g., sacrificing one's own interests to alleviate others' suffering, are widely observed in human society, altruism varies greatly across individuals. Such individual differences in altruistic preference have been hypothesized to arise from both individuals' dispositional empathic concern for others' welfare and context-specific cost-benefit integration processes. However, how cost-benefit integration is implemented in the brain and how it is linked to empathy remain unclear. Here, we combine a novel paradigm with the model-based functional magnetic resonance imaging (fMRI) approach to examine the neurocomputational basis of altruistic behaviors. Thirty-seven adults (16 females) were tested. Modeling analyses suggest that individuals are likely to integrate their own monetary costs with nonlinearly transformed recipients' benefits. Neuroimaging results demonstrate the involvement of an extended common currency system during decision-making by showing that selfish and other-regarding motives were processed in dorsal anterior cingulate cortex (ACC) and right inferior parietal lobe in a domain-general manner. Importantly, a functional dissociation of adjacent but different subregions within anterior insular cortex (aINS) was observed for different subprocesses underlying altruistic behaviors. While dorsal aINS (daINS) and inferior frontal gyrus (IFG) were involved in valuation of benefactors' costs, ventral aINS and middle INS (vaINS/mINS), as empathy-related regions, reflected individual variations in valuating recipients' benefits. Multivariate analyses further suggest that both vaINS/mINS and dorsolateral prefrontal cortex (DLPFC) reflect individual variations in general altruistic preferences which account for both dispositional empathy and context-specific other-regarding tendency. Together, these findings provide valuable insights into our understanding of psychological and neurobiological basis of altruistic behaviors.SIGNIFICANCE STATEMENT Altruistic behaviors play a crucial role in facilitating solidarity and development of human society, but the mechanisms of the cost-benefit integration underlying these behaviors are still unclear. Using model-based neuroimaging approaches, we clarify that people integrate personal costs and non-linearly transformed other's benefits during altruistic decision-making and the implementations of the integration processes are supported by an extended common currency neural network. Importantly, multivariate analyses reveal that both empathy-related and cognitive control-related brain regions are involved in modulating individual variations of altruistic preference, which implicate complex psychological and computational processes. Our results provide a neurocomputational account of how people weigh between different attributes to make altruistic decisions and why altruistic preference varies to a great extent across individuals.

Instrumental and Pavlovian Mechanisms in Alcohol Use Disorder

Purpose of Review

Current theories of alcohol use disorders (AUD) highlight the importance of Pavlovian and instrumental learning processes mainly based on preclinical animal studies. Here, we summarize available evidence for alterations of those processes in human participants with AUD with a focus on habitual versus goal-directed instrumental learning, Pavlovian conditioning, and Pavlovian-to-instrumental transfer (PIT) paradigms.

Recent Findings

The balance between habitual and goal-directed control in AUD participants has been studied using outcome devaluation or sequential decision-making procedures, which have found some evidence of reduced goal-directed/model-based control, but little evidence for stronger habitual responding. The employed Pavlovian learning and PIT paradigms have shown considerable differences regarding experimental procedures, e.g., alcohol-related or conventional reinforcers or stimuli.

Summary

While studies of basic learning processes in human participants with AUD support a role of Pavlovian and instrumental learning mechanisms in the development and maintenance of drug addiction, current studies are characterized by large variability regarding methodology, sample characteristics, and results, and translation from animal paradigms to human research remains challenging. Longitudinal approaches with reliable and ecologically valid paradigms of Pavlovian and instrumental processes, including alcohol-related cues and outcomes, are warranted and should be combined with state-of-the-art imaging techniques, computational approaches, and ecological momentary assessment methods.

Stimulus-response learning and expected reward value enhance stimulus cognitive processing: An ERP study

Reward affects our attention to stimuli, prioritizing those that lead to high-value outcomes. Recently, it has been suggested that such reward-related cognitive prioritization might be associated with the process of learning new stimulus-response (S-R) associations, because both are acquired through extended reward training, and once established, they are hard to overcome. We used event-related potentials (ERP) to analyze the contribution of S-R links to the formation of reward-related cognitive prioritization during reinforcement learning. Reward-related cognitive prioritization was measured by comparing the ERP signals for stimuli predicting high-value and low-value outcomes. In addition, we compared a strong S-R link (same stimulus, same response), with a weak S-R link condition (same stimulus, two different responses). The participants' performance was more accurate and faster when the procedure allowed for establishing strong S-R links and for high-value outcomes. Furthermore, those stimuli associated with strong S-R links showed a larger P3 amplitude at parietal sites. Value effects (larger ERP activity for those stimuli predicting a high-value outcome) were obtained at parietal and occipital sites in the P3 time window. However, value effects did not benefit from strong S-R links in either the P1 or the P3 components. These results suggest that strong S-R learning is not necessary to develop reward-related modulations of ERP activity.

The sensory representation of causally controlled objects

Intentional control over external objects is informed by our sensory experience of them. To study how causal relationships are learned and effected, we devised a brain machine interface (BMI) task using wide-field calcium signals. Mice learned to entrain activity patterns in arbitrary pairs of cortical regions to guide a visual cursor to a target location for reward. Brain areas that were normally correlated could be rapidly reconfigured to exert control over the cursor in a sensory-feedback-dependent manner. Higher visual cortex was more engaged when expert but not naive animals controlled the cursor. Individual neurons in higher visual cortex responded more strongly to the cursor when mice controlled it than when they passively viewed it, with the greatest response boosting as the cursor approached the target location. Thus, representations of causally controlled objects are sensitive to intention and proximity to the subject's goal, potentially strengthening sensory feedback to allow more fluent control.

Neural Computations of Threat

A host of learning, memory, and decision-making processes form the individual's response to threat and may be disrupted in anxiety and post-trauma psychopathology. Here we review the neural computations of threat, from the first encounter with a dangerous situation, through learning, storing, and updating cues that predict it, to making decisions about the optimal course of action. The overview highlights the interconnected nature of these processes and their reliance on shared neural and computational mechanisms. We propose an integrative approach to the study of threat-related processes, in which specific computations are studied across the various stages of threat experience rather than in isolation. This approach can generate new insights about the evolution, diagnosis, and treatment of threat-related psychopathology.

Trauma Affects Prospective Relationships Between Reward-Related Ventral Striatal and Amygdala Activation and 1-Year Future Hypo/Mania Trajectories

BACKGROUND

Trauma exposure is associated with a more severe, persistent course of affective and anxiety symptoms. Markers of reward neural circuitry function, specifically activation to reward prediction error (RPE), are impacted by trauma and predict the future course of affective symptoms. This study's purpose was to determine how lifetime trauma exposure influences relationships between reward neural circuitry function and the course of future affective and anxiety symptoms in a naturalistic, transdiagnostic observational context.

METHODS

A total of 59 young adults aged 18-25 (48 female and 11 male participants, mean ± SD = 21.5 ± 2.0 years) experiencing psychological distress completed the study. Participants were evaluated at baseline, 6, and 12 months. At baseline, the participants reported lifetime trauma events and completed a monetary reward functional magnetic resonance imaging task. Affective and anxiety symptoms were reported at each visit, and trajectories were calculated using MPlus. Neural activation during RPE and other phases of reward processing were determined using SPM8. Trauma and reward neural activation were entered as predictors of symptom trajectories.

RESULTS

Trauma exposure moderated prospective relationships between left ventral striatum (β = -1.29, p = .02) and right amygdala (β = 0.58, p = .04) activation to RPE and future hypo/mania severity trajectory: the interaction between greater trauma and greater left ventral striatum activation to RPE was associated with a shallower increase in hypo/mania severity, whereas the interaction between greater trauma and greater right amygdala activation to RPE was associated with increasing hypo/mania severity.

CONCLUSIONS

Trauma exposure affects prospective relationships between markers of reward circuitry function and affective symptom trajectories. Evaluating trauma exposure is thus crucial in naturalistic and treatment studies aiming to identify neural predictors of future affective symptom course.

Associations Between Delay Discounting and Connectivity of the Valuation-control System in Healthy Young Adults

The process of valuation assists in determining if an object or course of action is rewarding. Delay discounting is the observed decay of a rewards' subjective value over time. Encoding the subjective value of rewards across a spectrum has been attributed to brain regions belonging to the valuation and executive control systems. The valuation system (VS) encodes reward value over short and long delays, influencing reinforcement learning and reward representation. The executive control system (ECS) becomes more active as choice difficulty increases, integrating contextual and mnemonic information with salience signals in the modulation of decision-making. Here, we aimed to identify resting-state functional connectivity-based patterns of the VS and ECS correlated with value-setting and delay discounting (outside-scanner paradigm) in a large (n = 992) cohort of healthy young adults from the Human Connectome Project (HCP). Results suggest the VS may be involved in value-setting of small, immediate rewards while the ECS may be involved in value-setting and delay discounting for large and small rewards over a range of delays. We observed magnitude sensitive connections involving the posterior cingulate cortex, time-sensitive connections with the ventromedial and lateral prefrontal cortex while connections involving the posterior parietal cortex appeared both magnitude- and time-sensitive. The ventromedial prefrontal cortex and posterior parietal cortex could act as "comparator" regions, weighing the value of small rewards against large rewards across various delay duration to aid in decision-making.

Learned value and predictiveness affect gaze but not figure assignment

Many factors affect figure-ground segregation, but the contributions of attention and reward history to this process is uncertain. We conducted two experiments to investigate whether reward learning influences figure assignment and whether this relationship was mediated by attention. Participants learned to associate certain shapes with a reward contingency: During a learning phase, they chose between two shapes on each trial, with subsets of shapes associated with high-probability win, low-probability win, high-probability loss, and low-probability loss. In a test phase, participants were given a figure-ground task, in which they indicated which of two regions that shared a contour they perceived as the figure (high-probability win and low-probability win shapes were pitted against each other, as were high-probability loss and low-probability loss shapes). The results revealed that participants had learned the reward contingencies and that, following learning, attention was reliably drawn to the optimal stimulus. Despite this, neither reward history nor the resulting attentional allocation influenced figure-ground organization.