The self in context: brain systems linking mental and physical health.

Increasing evidence suggests that mental health and physical health are linked by neural systems that jointly regulate somatic physiology and high-level cognition. Key systems include the ventromedial prefrontal cortex and the related default-mode network. These systems help to construct models of the 'self-in-context', compressing information across time and sensory modalities into conceptions of the underlying causes of experience. Self-in-context models endow events with personal meaning and allow predictive control over behaviour and peripheral physiology, including autonomic, neuroendocrine and immune function. They guide learning from experience and the formation of narratives about the self and one's world. Disorders of mental and physical health, especially those with high co-occurrence and convergent alterations in the functionality of the ventromedial prefrontal cortex and the default-mode network, could benefit from interventions focused on understanding and shaping mindsets and beliefs about the self, illness and treatment.

The Cognitive Neuroscience of Placebo Effects: Concepts, Predictions, and Physiology.

Placebos have been used ubiquitously throughout the history of medicine. Expectations and associative learning processes are important psychological determinants of placebo effects, but their underlying brain mechanisms are only beginning to be understood. We examine the brain systems underlying placebo effects on pain, autonomic, and immune responses. The ventromedial prefrontal cortex (vmPFC), insula, amygdala, hypothalamus, and periaqueductal gray emerge as central brain structures underlying placebo effects. We argue that the vmPFC is a core element of a network that represents structured relationships among concepts, providing a substrate for expectations and a conception of the situation-the self in context-that is crucial for placebo effects. Such situational representations enable multidimensional predictions, or priors, that are combined with incoming sensory information to construct percepts and shape motivated behavior. They influence experience and physiology via descending pathways to physiological effector systems, including the spinal cord and other peripheral organs.

A multistudy analysis reveals that evoked pain intensity representation is distributed across brain systems.

Information is coded in the brain at multiple anatomical scales: locally, distributed across regions and networks, and globally. For pain, the scale of representation has not been formally tested, and quantitative comparisons of pain representations across regions and networks are lacking. In this multistudy analysis of 376 participants across 11 studies, we compared multivariate predictive models to investigate the spatial scale and location of evoked heat pain intensity representation. We compared models based on (a) a single most pain-predictive region or resting-state network; (b) pain-associated cortical-subcortical systems developed from prior literature ("multisystem models"); and (c) a model spanning the full brain. We estimated model accuracy using leave-one-study-out cross-validation (CV; 7 studies) and subsequently validated in 4 independent holdout studies. All spatial scales conveyed information about pain intensity, but distributed, multisystem models predicted pain 20% more accurately than any individual region or network and were more generalizable to multimodal pain (thermal, visceral, and mechanical) and specific to pain. Full brain models showed no predictive advantage over multisystem models. These findings show that multiple cortical and subcortical systems are needed to decode pain intensity, especially heat pain, and that representation of pain experience may not be circumscribed by any elementary region or canonical network. Finally, the learner generalization methods we employ provide a blueprint for evaluating the spatial scale of information in other domains.

An fMRI-Based Brain Marker of Individual Differences in Delay Discounting.

Individual differences in delay discounting-how much we discount future compared to immediate rewards-are associated with general life outcomes, psychopathology, and obesity. Here, we use machine learning on fMRI activity during an intertemporal choice task to develop a functional brain marker of these individual differences in human adults. Training and cross-validating the marker in one dataset (Study 1, N = 110 male adults) resulted in a significant prediction-outcome correlation (r = 0.49), generalized to predict individual differences in a completely independent dataset (Study 2: N = 145 male and female adults, r = 0.45), and predicted discounting several weeks later. Out-of-sample responses of the functional brain marker, but not discounting behavior itself, differed significantly between overweight and lean individuals in both studies, and predicted fasting-state blood levels of insulin, c-peptide, and leptin in Study 1. Significant predictive weights of the marker were found in cingulate, insula, and frontoparietal areas, among others, suggesting an interplay among regions associated with valuation, conflict processing, and cognitive control. This new functional brain marker is a step toward a generalizable brain model of individual differences in delay discounting. Future studies can evaluate it as a potential transdiagnostic marker of altered decision-making in different clinical and developmental populations.SIGNIFICANCE STATEMENT People differ substantially in how much they prefer smaller sooner rewards or larger later rewards such as spending money now versus saving it for retirement. These individual differences are generally stable over time and have been related to differences in mental and bodily health. What is their neurobiological basis? We applied machine learning to brain-imaging data to identify a novel brain activity pattern that accurately predicts how much people prefer sooner versus later rewards, and which can be used as a new brain-based measure of intertemporal decision-making in future studies. The resulting functional brain marker also predicts overweight and metabolism-related blood markers, providing new insight into the possible links between metabolism and the cognitive and brain processes involved in intertemporal decision-making.

Effect sizes and test-retest reliability of the fMRI-based neurologic pain signature.

Identifying biomarkers that predict mental states with large effect sizes and high test-retest reliability is a growing priority for fMRI research. We examined a well-established multivariate brain measure that tracks pain induced by nociceptive input, the Neurologic Pain Signature (NPS). In N = 295 participants across eight studies, NPS responses showed a very large effect size in predicting within-person single-trial pain reports (d = 1.45) and medium effect size in predicting individual differences in pain reports (d = 0.49). The NPS showed excellent short-term (within-day) test-retest reliability (ICC = 0.84, with average 69.5 trials/person). Reliability scaled with the number of trials within-person, with ≥60 trials required for excellent test-retest reliability. Reliability was tested in two additional studies across 5-day (N = 29, ICC = 0.74, 30 trials/person) and 1-month (N = 40, ICC = 0.46, 5 trials/person) test-retest intervals. The combination of strong within-person correlations and only modest between-person correlations between the NPS and pain reports indicate that the two measures have different sources of between-person variance. The NPS is not a surrogate for individual differences in pain reports but can serve as a reliable measure of pain-related physiology and mechanistic target for interventions.

A Generalizable Multivariate Brain Pattern for Interpersonal Guilt.

Feeling guilty when we have wronged another is a crucial aspect of prosociality, but its neurobiological bases are elusive. Although multivariate patterns of brain activity show promise for developing brain measures linked to specific emotions, it is less clear whether brain activity can be trained to detect more complex social emotional states such as guilt. Here, we identified a distributed guilt-related brain signature (GRBS) across two independent neuroimaging datasets that used interpersonal interactions to evoke guilt. This signature discriminated conditions associated with interpersonal guilt from closely matched control conditions in a cross-validated training sample (N = 24; Chinese population) and in an independent test sample (N = 19; Swiss population). However, it did not respond to observed or experienced pain, or recalled guilt. Moreover, the GRBS only exhibited weak spatial similarity with other brain signatures of social-affective processes, further indicating the specificity of the brain state it represents. These findings provide a step toward developing biological markers of social emotions, which could serve as important tools to investigate guilt-related brain processes in both healthy and clinical populations.

Multiple Brain Networks Mediating Stimulus-Pain Relationships in Humans.

The brain transforms nociceptive input into a complex pain experience comprised of sensory, affective, motivational, and cognitive components. However, it is still unclear how pain arises from nociceptive input and which brain networks coordinate to generate pain experiences. We introduce a new high-dimensional mediation analysis technique to estimate distributed, network-level patterns that formally mediate the relationship between stimulus intensity and pain. We applied the model to a large-scale analysis of functional magnetic resonance imaging data (N = 284), focusing on brain mediators of the relationship between noxious stimulus intensity and trial-to-trial variation in pain reports. We identify mediators in both traditional nociceptive pathways and in prefrontal, midbrain, striatal, and default-mode regions unrelated to nociception in standard analyses. The whole-brain mediators are specific for pain versus aversive sounds and are organized into five functional networks. Brain mediators predicted pain ratings better than previous brain measures, including the neurologic pain signature (Wager et al. 2013). Our results provide a broader view of the networks underlying pain experience, as well as novel brain targets for interventions.

Frontal-Brainstem Pathways Mediating Placebo Effects on Social Rejection.

Placebo treatments can strongly affect clinical outcomes, but research on how they shape other life experiences and emotional well-being is in its infancy. We used fMRI in humans to examine placebo effects on a particularly impactful life experience, social pain elicited by a recent romantic rejection. We compared these effects with placebo effects on physical (heat) pain, which are thought to depend on pathways connecting prefrontal cortex and periaqueductal gray (PAG). Placebo treatment, compared with control, reduced both social and physical pain, and increased activity in the dorsolateral prefrontal cortex (dlPFC) in both modalities. Placebo further altered the relationship between affect and both dlPFC and PAG activity during social pain, and effects on behavior were mediated by a pathway connecting dlPFC to the PAG, building on recent work implicating opioidergic PAG activity in the regulation of social pain. These findings suggest that placebo treatments reduce emotional distress by altering affective representations in frontal-brainstem systems.SIGNIFICANCE STATEMENT Placebo effects are improvements due to expectations and the socio-medical context in which treatment takes place. Whereas they have been extensively studied in the context of somatic conditions such as pain, much less is known of how treatment expectations shape the emotional experience of other important stressors and life events. Here, we use brain imaging to show that placebo treatment reduces the painful feelings associated with a recent romantic rejection by recruiting a prefrontal-brainstem network and by shifting the relationship between brain activity and affect. Our findings suggest that this brain network may be important for nonspecific treatment effects across a wide range of therapeutic approaches and mental health conditions.

Transforming Pain With Prosocial Meaning: A Functional Magnetic Resonance Imaging Study.

OBJECTIVE: Contextual factors can transform how we experience pain, particularly if pain is associated with other positive outcomes. Here, we test a novel meaning-based intervention. Participants were given the opportunity to choose to receive pain on behalf of their romantic partners, situating pain experience in a positive, prosocial meaning context. We predicted that the ventromedial prefrontal cortex (vmPFC), a key structure for pain regulation and generation of affective meaning, would mediate the transformation of pain experience by this prosocial interpersonal context. METHODS: We studied fMRI activity and behavioral responses in 29 heterosexual female participants during (1) a baseline pain challenge and (2) a task in which participants decided to accept a self-selected number of additional pain trials to reduce pain in their male romantic partners ("accept-partner-pain" condition). RESULTS: Enduring extra pain for the benefit of the romantic partner reduced pain-related unpleasantness (t = -2.54, p = .016) but not intensity, and increased positive thoughts (t = 3.60, p = .001) and pleasant feelings (t = 5.39, p < .0005). Greater willingness to accept the pain of one's partner predicted greater unpleasantness reductions (t = 3.94, p = .001) and increases in positive thoughts (r = .457, p = .013). The vmPFC showed significant increases (q < .05 FDR-corrected) in activation during accept-partner-pain, especially for women with greater willingness to relieve their partner's pain (t = 2.63, p = .014). Reductions in brain regions processing pain and aversive emotion significantly mediated reductions in pain unpleasantness (q < .05 FDR-corrected). CONCLUSIONS: The vmPFC has a key role in transforming the meaning of pain, which is associated with a cascade of positive psychological and brain effects, including changes in affective meaning, value, and pain-specific neural circuits.

Group-regularized individual prediction: theory and application to pain.

Multivariate pattern analysis (MVPA) has become an important tool for identifying brain representations of psychological processes and clinical outcomes using fMRI and related methods. Such methods can be used to predict or 'decode' psychological states in individual subjects. Single-subject MVPA approaches, however, are limited by the amount and quality of individual-subject data. In spite of higher spatial resolution, predictive accuracy from single-subject data often does not exceed what can be accomplished using coarser, group-level maps, because single-subject patterns are trained on limited amounts of often-noisy data. Here, we present a method that combines population-level priors, in the form of biomarker patterns developed on prior samples, with single-subject MVPA maps to improve single-subject prediction. Theoretical results and simulations motivate a weighting based on the relative variances of biomarker-based prediction-based on population-level predictive maps from prior groups-and individual-subject, cross-validated prediction. Empirical results predicting pain using brain activity on a trial-by-trial basis (single-trial prediction) across 6 studies (N=180 participants) confirm the theoretical predictions. Regularization based on a population-level biomarker-in this case, the Neurologic Pain Signature (NPS)-improved single-subject prediction accuracy compared with idiographic maps based on the individuals' data alone. The regularization scheme that we propose, which we term group-regularized individual prediction (GRIP), can be applied broadly to within-person MVPA-based prediction. We also show how GRIP can be used to evaluate data quality and provide benchmarks for the appropriateness of population-level maps like the NPS for a given individual or study.

Social cues influence perception of others' pain.

BACKGROUND: Accurately perceiving other people's pain is important in both daily life and healthcare settings. However, judging other's pain is inherently difficult and can be biased by various social and cultural factors. Here, we examined whether perception of others' pain and pain management recommendations are socially influenced by seeing the opinions of other raters. METHODS: In Experiment 1 (N = 50), participants rated pictures depicting injured hands or feet of pre-selected high, medium and low intensities. Each picture was preceded by cues indicating ratings of 10 previous participants. Cues were randomized to indicate low (SocialLOW) or high (SocialHIGH) pain judgements and were not predictive of actual normative pain intensity. In Experiment 2 (N = 209), participants viewed facial video clips of patients with chronic shoulder pain making painful movements. They estimated patients' pain intensity and provided pain management recommendations. RESULTS: Experiment 1 revealed that perceivers' pain estimates were significantly and substantially higher for stimuli following SocialHIGH than SocialLOW cues (Cohen's d = 1.26, p < 0.001) and paralleled by increased skin conductance responses. Experiment 2 replicated the effect of social cues on pain judgements (d = 0.58, p < 0.001). However, social cues did not influence post-study pain management recommendations, potentially due to memory limitations. CONCLUSIONS: Together, these studies reveal that judgements of others' pain are robustly modulated by information about others' opinions. Future research could test the prevalence and strength of such effects in clinical settings. SIGNIFICANCE: The present study shows that even arbitrary opinions of other raters influence the perception of others' pain. This finding adds new insight into the growing evidence of social and cultural biases in pain estimation.

Impact of the gut microbiome composition on social decision-making.

There is increasing evidence for the role of the gut microbiome in the regulation of socio-affective behavior in animals and clinical conditions. However, whether and how the composition of the gut microbiome may influence social decision-making in health remains unknown. Here, we tested the causal effects of a 7-week synbiotic (vs. placebo) dietary intervention on altruistic social punishment behavior in an ultimatum game. Results showed that the intervention increased participants' willingness to forgo a monetary payoff when treated unfairly. This change in social decision-making was related to changes in fasting-state serum levels of the dopamine-precursor tyrosine proposing a potential mechanistic link along the gut-microbiota-brain-behavior axis. These results improve our understanding of the bidirectional role body-brain interactions play in social decision-making and why humans at times act "irrationally" according to standard economic theory.

Beneficial Effects of Synbiotics on the Gut Microbiome in Individuals with Low Fiber Intake: Secondary Analysis of a Double-Blind, Randomized Controlled Trial.

Insufficient dietary fiber intake can negatively affect the intestinal microbiome and, over time, may result in gut dysbiosis, thus potentially harming overall health. This randomized controlled trial aimed to improve the gut microbiome of individuals with low dietary fiber intake (<25 g/day) during a 7-week synbiotic intervention. The metabolically healthy male participants (n = 117, 32 ± 10 y, BMI 25.66 ± 3.1 kg/m2) were divided into two groups: one receiving a synbiotic supplement (Biotic Junior, MensSana AG, Forchtenberg, Germany) and the other a placebo, without altering their dietary habits or physical activity. These groups were further stratified by their dietary fiber intake into a low fiber group (LFG) and a high fiber group (HFG). Stool samples for microbiome analysis were collected before and after intervention. Statistical analysis was performed using linear mixed effects and partial least squares models. At baseline, the microbiomes of the LFG and HFG were partially separated. After seven weeks of intervention, the abundance of SCFA-producing microbes significantly increased in the LFG, which is known to improve gut health; however, this effect was less pronounced in the HFG. Beneficial effects on the gut microbiome in participants with low fiber intake may be achieved using synbiotics, demonstrating the importance of personalized synbiotics.

Impact of Synbiotic Intake on Liver Metabolism in Metabolically Healthy Participants and Its Potential Preventive Effect on Metabolic-Dysfunction-Associated Fatty Liver Disease (MAFLD): A Randomized, Placebo-Controlled, Double-Blinded Clinical Trial.

Synbiotics modulate the gut microbiome and contribute to the prevention of liver diseases such as metabolic-dysfunction-associated fatty liver disease (MAFLD). This study aimed to evaluate the effect of a randomized, placebo-controlled, double-blinded seven-week intervention trial on the liver metabolism in 117 metabolically healthy male participants. Anthropometric data, blood parameters, and stool samples were analyzed using linear mixed models. After seven weeks of intervention, there was a significant reduction in alanine aminotransferase (ALT) in the synbiotic group compared to the placebo group (-14.92%, CI: -26.60--3.23%, p = 0.013). A stratified analysis according to body fat percentage revealed a significant decrease in ALT (-20.70%, CI: -40.88--0.53%, p = 0.045) in participants with an elevated body fat percentage. Further, a significant change in microbiome composition (1.16, CI: 0.06-2.25, p = 0.039) in this group was found, while the microbial composition remained stable upon intervention in the group with physiological body fat. The 7-week synbiotic intervention reduced ALT levels, especially in participants with an elevated body fat percentage, possibly due to modulation of the gut microbiome. Synbiotic intake may be helpful in delaying the progression of MAFLD and could be used in addition to the recommended lifestyle modification therapy.

Integration of error agency and representation of others' pain in the anterior insula.

A crucial feature of socially adaptive behavior is the ability to recognize when our actions harm other individuals. Previous research demonstrates that dorsal mediofrontal cortex (dMFC) and anterior insula (AI) are involved in both action monitoring and empathy for pain. Here, we tested whether these regions could integrate monitoring of error agency with the representation of others' pain. While undergoing event-related fMRI, participants played a visual task in turns with a friend placed outside the scanner, who would receive painful stimulation in half of the error trials. Brain activity was enhanced in dMFC and AI for painful compared with nonpainful errors. Left AI and dorsolateral pFC also exhibited a significant interaction with agency and increased responses when painful errors were caused by oneself. We conclude that AI is crucial for integrating inferences about others' feeling states with information about action agency and outcome, thus generating an affective signal that may guide subsequent adjustment.

A neuromarker for drug and food craving distinguishes drug users from non-users.

Craving is a core feature of substance use disorders. It is a strong predictor of substance use and relapse and is linked to overeating, gambling, and other maladaptive behaviors. Craving is measured via self-report, which is limited by introspective access and sociocultural contexts. Neurobiological markers of craving are both needed and lacking, and it remains unclear whether craving for drugs and food involve similar mechanisms. Across three functional magnetic resonance imaging studies (n = 99), we used machine learning to identify a cross-validated neuromarker that predicts self-reported intensity of cue-induced drug and food craving (P < 0.0002). This pattern, which we term the Neurobiological Craving Signature (NCS), includes ventromedial prefrontal and cingulate cortices, ventral striatum, temporal/parietal association areas, mediodorsal thalamus and cerebellum. Importantly, NCS responses to drug versus food cues discriminate drug users versus non-users with 82% accuracy. The NCS is also modulated by a self-regulation strategy. Transfer between separate neuromarkers for drug and food craving suggests shared neurobiological mechanisms. Future studies can assess the discriminant and convergent validity of the NCS and test whether it responds to clinical interventions and predicts long-term clinical outcomes.

Brain mediators of biased social learning of self-perception in social anxiety disorder.

Social anxiety disorder (SAD) is characterized by an excessive fear of social evaluation and a persistently negative view of the self. Here we test the hypothesis that negative biases in brain responses and in social learning of self-related information contribute to the negative self-image and low self-esteem characteristic of SAD. Adult participants diagnosed with social anxiety (N = 21) and matched controls (N = 23) rated their performance and received social feedback following a stressful public speaking task. We investigated how positive versus negative social feedback altered self-evaluation and state self-esteem and used functional Magnetic Resonance Imaging (fMRI) to characterize brain responses to positive versus negative feedback. Compared to controls, participants with SAD updated their self-evaluation and state self-esteem significantly more based on negative compared to positive social feedback. Responses in the frontoparietal network correlated with and mirrored these behavioral effects, with greater responses to positive than negative feedback in non-anxious controls but not in participants with SAD. Responses to social feedback in the anterior insula and other areas mediated the effects of negative versus positive feedback on changes in self-evaluation. In non-anxious participants, frontoparietal brain areas may contribute to a positive social learning bias. In SAD, frontoparietal areas are less recruited overall and less attuned to positive feedback, possibly reflecting differences in attention allocation and cognitive regulation. More negatively biased brain responses and social learning could contribute to maintaining a negative self-image in SAD and other internalizing disorders, thereby offering important new targets for interventions.

Altered delay discounting in neurodegeneration: insight into the underlying mechanisms and perspectives for clinical applications.

Steeper delay discounting (i.e., the extent to which future rewards are perceived as less valuable than immediate ones) has been proposed as a transdiagnostic process across different health conditions, in particular psychiatric disorders. Impulsive decision-making is a hallmark of different neurodegenerative conditions but little is known about delay discounting in the domain of neurodegenerative conditions. We reviewed studies on delay discounting in patients with Parkinson's disease (PD) and in patients with dementia (Alzheimer's disease / AD or frontotemporal dementia / FTD). We proposed that delay discounting could be an early marker of the neurodegenerative process. We developed the idea that altered delay discounting is associated with overlapping but distinct neurocognitive mechanisms across neurodegenerative diseases: dopaminergic-related disorders of reward processing in PD, memory/projection deficits due to medial temporal atrophy in AD, modified reward processing due to orbitofrontal atrophy in FTD. Neurodegeneration could provide a framework to decipher the neuropsychological mechanisms of value-based decision-making. Further, delay discounting could become a marker of interest in clinical practice, in particular for differential diagnosis.

Odour-imagery ability is linked to food craving, intake, and adiposity change in humans.

It is well-known that food-cue reactivity (FCR) is positively associated with body mass index (BMI)1 and weight change2, but the mechanisms underlying these relationships are incompletely understood. One prominent theory of craving posits that the elaboration of a desired substance through sensory imagery intensifies cravings, thereby promoting consumption3. Olfaction is integral to food perception, yet the ability to imagine odours varies widely4. Here we test in a basic observational study whether this large variation in olfactory imagery drives FCR strength to promote adiposity in 45 adults (23 male). We define odour-imagery ability as the extent to which imagining an odour interferes with the detection of a weak incongruent odour (the 'interference effect'5). As predicted in our preregistration, the interference effect correlates with the neural decoding of imagined, but not real, odours. These perceptual and neural measures of odour imagery are in turn associated with FCR, defined by the rated craving intensity of liked foods and cue-potentiated intake. Finally, odour imagery exerts positive indirect effects on changes in BMI and body-fat percentage over one year via its influences on FCR. These findings establish odour imagery as a driver of FCR that in turn confers risk for weight gain.

Odor imagery but not perception drives risk for food cue reactivity and increased adiposity.

Mental imagery has been proposed to play a critical role in the amplification of cravings. Here we tested whether olfactory imagery drives food cue reactivity strength to promote adiposity in 45 healthy individuals. We measured odor perception, odor imagery ability, and food cue reactivity using self-report, perceptual testing, and neuroimaging. Adiposity was assessed at baseline and one year later. Brain responses to real and imagined odors were analyzed with univariate and multivariate decoding methods to identify pattern-based olfactory codes. We found that the accuracy of decoding imagined, but not real, odor quality correlated with a perceptual measure of odor imagery ability and with greater adiposity changes. This latter relationship was mediated by cue-potentiated craving and intake. Collectively, these findings establish odor imagery ability as a risk factor for weight gain and more specifically as a mechanism by which exposure to food cues promotes craving and overeating.