Behavioral and neural valuation of foods is driven by implicit knowledge of caloric content

Altered food liking in depression is driven by macronutrient composition

Major depressive disorder (MDD) is characterized by changes in appetite and body weight as well as blunted reward sensitivity (‘anhedonia’). However, it is not well understood which mechanisms are driving changes in reward sensitivity, specifically regarding food. Here, we used a sample of 117 participants (54 patients with MDD and 63 healthy control participants [HCPs]) who completed a food cue reactivity task with ratings of wanting and liking for 60 food and 20 non-food items. To evaluate which components of the food may contribute to altered ratings in depression, we tested for associations with macronutrients of the depicted items. In line with previous studies, we found reduced ratings of food wanting (p = .003) but not liking (p = .23) in patients with MDD compared to matched HCPs. Adding macronutrient composition to the models of wanting and liking substantially improved their fit (ps < .001). Compared to carbohydrate-rich foods, patients with MDD reported lower liking and wanting ratings for high-fat and high-protein foods. Moreover, patients with MDD showed weaker correlations in their preferences for carbohydrate- versus fat- or protein-rich foods (ps < .001), pointing to potential disturbances in metabolic signaling. To conclude, our results suggest that depression-related alterations in food reward ratings are more specific to the macronutrient composition of the food than previously anticipated, hinting at disturbances in gut–brain signaling. These findings raise the intriguing question of whether interventions targeting the gut could help normalize aberrant reward signals for foods rich in fat or protein.

Creation and validation of a NOVA scored picture set to evaluate ultra-processed foods

There has been a rapid shift in the modern food environment towards increased processing in foods consumed in the United States (US) and globally. The NOVA system (not an acronym) for classifying food on degree of processing currently has the most empirical support. Consumption of foods in the NOVA 4 category, ultra-processed foods (UPF), is a risk factor for a host of poor health outcomes including heart disease, stroke, and cancer. Despite these poor health outcomes, UPF make up 58% of calories consumed in the US. Methodologies for assessing the reinforcing and rewarding properties of these foods are necessary tools. The Becker-DeGroot-Marschak auction paradigm (BDM) is a well validated tool for measuring value and is amenable to neuromonitoring environments. To allow for the testing of hypotheses based on level of food processing, we present a picture set of 14 UPF and 14 minimally-processed foods (MPF) matched on visual properties, food characteristics (fat, carbohydrate, cost, etc.), and rated perceptual properties. Further, we report our scoring of these foods using the NOVA classification system and provide additional data from credentialed nutrition professionals and on inter-rater reliability using NOVA, a critique of the system. Finally, we provide all pictures, data, and code used to create this picture set as a tool for researchers.

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

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

Prebiotic diet changes neural correlates of food decision-making in overweight adults: a randomised controlled within-subject cross-over trial

OBJECTIVE

Animal studies suggest that prebiotic, plant-derived nutrients could improve homoeostatic and hedonic brain functions through improvements in microbiome-gut-brain communication. However, little is known if these results are applicable to humans. Therefore, we tested the effects of high-dosed prebiotic fibre on reward-related food decision-making in a randomised controlled within-subject cross-over study and assayed potential microbial and metabolic markers.

DESIGN

59 overweight young adults (19 females, 18-42 years, body mass index 25-30 kg/m2) underwent functional task MRI before and after 14 days of supplementary intake of 30 g/day of inulin (prebiotics) and equicaloric placebo, respectively. Short chain fatty acids (SCFA), gastrointestinal hormones, glucose/lipid and inflammatory markers were assayed in fasting blood. Gut microbiota and SCFA were measured in stool.

RESULTS

Compared with placebo, participants showed decreased brain activation towards high-caloric wanted food stimuli in the ventral tegmental area and right orbitofrontal cortex after prebiotics (preregistered, family wise error-corrected p <0.05). While fasting blood levels remained largely unchanged, 16S-rRNA sequencing showed significant shifts in the microbiome towards increased occurrence of, among others, SCFA-producing Bifidobacteriaceae, and changes in >60 predicted functional signalling pathways after prebiotic intake. Changes in brain activation correlated with changes in Actinobacteria microbial abundance and associated activity previously linked with SCFA production, such as ABC transporter metabolism.

CONCLUSIONS

In this proof-of-concept study, a prebiotic intervention attenuated reward-related brain activation during food decision-making, paralleled by shifts in gut microbiota.

TRIAL REGISTRATION NUMBER

NCT03829189.

Does food recognition depend on color?

Color is considered important in food perception, but its role in food-specific visual mechanisms is unclear. We explore this question in North American adults. We build on work revealing contributions from domain-general and domain-specific abilities in food recognition and a negative correlation between the domain-specific component and food neophobia (FN, aversion to novel food). In Study 1, participants performed two food-recognition tests, one in color and one in grayscale. Removing color reduced performance, but food recognition was predicted by domain-general and -specific abilities, and FN negatively correlated with food recognition. In Study 2, we removed color from both food tests. Food recognition was still predicted by domain-general and food-specific abilities, but with a relation between food-specific ability and FN. In Study 3, color-blind men reported lower FN than men with normal color perception. These results suggest two separate food-specific recognition mechanisms, only one of which is dependent on color.

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

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

Further evidence for sensitivity to energy density and a two-component model of meal size: Analysis of meal calorie intakes in Argentina and Malaysia

Previously, we demonstrated a non-linear association between meal caloric intake and meal energy density (ED, kcal/g) in data from a controlled trial in the US and from free-living participants in the UK [1]. In both datasets, meal caloric intake increased with ED in lower energy-dense meals (below ∼1.75 kcal/g) and decreased in higher energy-dense meals (above ∼1.75 kcal/g). In the current study, we sought to explore whether this pattern extends to data from free-living participants in Argentina (N = 2738 meals) and Malaysia (N = 4658 meals). Again, a significant breakpoint was found in both the Argentinean (2.04 kcal/g (SE = 0.06)) and Malaysian (2.17 kcal/g (SE = 0.06)) datasets with mean centered meal caloric intake increasing with ED below the breakpoint and decreasing above the breakpoint. These results lend further support for our two-component theoretical model of meal size (g) in which a volume signal is dominant in lower energy-dense meals and a calorie-content signal is dominant in higher energy-dense meals. Together, our research adds to evidence supporting human sensitivity to calories and exposes a complexity in the correspondence between meal energy content and meal size in everyday (non-manipulated) meals. Further research is needed to provide causal evidence for this sensitivity and whether individual variation impacts meal size and energy balance.

The effect of cognitive load on preference and intensity processing of sweet taste in the brain

Distracted eating can cause overconsumption. Whereas previous work has shown that cognitive load suppresses perceived taste intensity and increases subsequent consumption, the mechanism behind distraction-induced overconsumption remains unclear. To elucidate this, we performed two event-related fMRI experiments that examined how cognitive load affects neural responses and perceived intensity and preferred intensity, respectively, to solutions varying in sweetness. In Experiment 1 (N = 24), participants tasted weak sweet and strong sweet glucose solutions and rated their intensity while we concurrently varied cognitive load using a digit-span task. In Experiment 2 (N = 22), participants tasted five different glucose concentrations under varying cognitive load and then indicated whether they wanted to keep, decrease or increase its sweetness. Participants in Experiment 1 rated strong sweet solutions as less sweet under high compared to low cognitive load, which was accompanied by attenuated activation the right middle insula and bilateral DLPFC. Psychophysiological interaction analyses showed that cognitive load moreover altered connectivity between the middle insula and nucleus accumbens and DLPFC and middle insula while tasting strong sweet solutions. In Experiment 2, cognitive load did not affect participants' preferred sweetness intensity. fMRI results revealed that cognitive load attenuated DLPFC activation for the strongest sweet solutions in the study. In conclusion, our behavioral and neuroimaging results suggest that cognitive load dampens the sensory processing of strong sweet solutions in particular, which may indicate higher competition for attentional resources for strong sweet than weak sweet solutions under high cognitive load. Implications for future research are discussed.

Economic value in the Brain: A meta-analysis of willingness-to-pay using the Becker-DeGroot-Marschak auction

Forming and comparing subjective values (SVs) of choice options is a critical stage of decision-making. Previous studies have highlighted a complex network of brain regions involved in this process by utilising a diverse range of tasks and stimuli, varying in economic, hedonic and sensory qualities. However, the heterogeneity of tasks and sensory modalities may systematically confound the set of regions mediating the SVs of goods. To identify and delineate the core brain valuation system involved in processing SV, we utilised the Becker-DeGroot-Marschak (BDM) auction, an incentivised demand-revealing mechanism which quantifies SV through the economic metric of willingness-to-pay (WTP). A coordinate-based activation likelihood estimation meta-analysis analysed twenty-four fMRI studies employing a BDM task (731 participants; 190 foci). Using an additional contrast analysis, we also investigated whether this encoding of SV would be invariant to the concurrency of auction task and fMRI recordings. A fail-safe number analysis was conducted to explore potential publication bias. WTP positively correlated with fMRI-BOLD activations in the left ventromedial prefrontal cortex with a sub-cluster extending into anterior cingulate cortex, bilateral ventral striatum, right dorsolateral prefrontal cortex, right inferior frontal gyrus, and right anterior insula. Contrast analysis identified preferential engagement of the mentalizing-related structures in response to concurrent scanning. Together, our findings offer succinct empirical support for the core structures participating in the formation of SV, separate from the hedonic aspects of reward and evaluated in terms of WTP using BDM, and show the selective involvement of inhibition-related brain structures during active valuation.

Central Regulation of Eating Behaviors in Humans: Evidence from Functional Neuroimaging Studies

Neuroimaging has great potential to provide insight into the neural response to food stimuli. Remarkable advances have been made in understanding the neural activity underlying food perception, not only in normal eating but also in obesity, eating disorders, and disorders of gut-brain interaction in recent decades. In addition to the abnormal brain function in patients with eating disorders compared to healthy controls, new therapies, such as neurofeedback and neurostimulation techniques, have been developed that target the malfunctioning brain regions in patients with eating disorders based on the results of neuroimaging studies. In this review, we present an overview of early and more recent research on the central processing and regulation of eating behavior in healthy and patient populations. In order to better understand the relationship between the gut and the brain as well as the neural mechanisms underlying abnormal ingestive behaviors, we also provide suggestions for future directions to enhance our current methods used in food-related neuroimaging studies.

Human nutritional intelligence underestimated? Exposing sensitivities to food composition in everyday dietary decisions

The social and cultural significance of food is woven into every aspect of our dietary behaviour, and it contributes to our complex interaction with food. To find order within this complexity scientists often look for dietary 'universals' - phenomena or basic principles that guide our food choice and meal size, irrespective of wider context. One such idea is that taste characteristics provide a signal for dietary composition (e.g., sweet taste signals carbohydrate). Others have suggested that behaviour is guided by learning and is based on associations that form between the flavour of a food and its post-ingestive effects. Despite a large body of research, evidence supporting both processes is equivocal, leading some to conclude that humans are largely indifferent to food composition. Here, we argue that human abilities to gauge the nutritional composition or value of food have been underestimated, and that they can be exposed by embracing alternative methods, including cross-cultural comparisons, large nutrition surveys, and the use of virtual portion-selection tools. Our group has focused on assessments of food choice and expected satiety, and how comparisons across everyday foods can reveal non-linear relationships with food energy density, and even the potential for sensitivity to micronutrient composition. We suggest that these abilities might reflect a complex form of social learning, in which flavour-nutrient associations are not only formed but communicated and amplified across individuals in the form of a cuisine. Thus, rather than disregarding sociocultural influences as extraneous, we might reimagine their role as central to a process that creates and imbues a 'collective dietary wisdom.' In turn, this raises questions about whether rapid dietary, technological, and cultural change disrupts a fundamental process, such that it no longer guarantees a 'nutritional intelligence' that confers benefits for health.

Influence of eating together on brain activation and hedonic evaluation in response to foods

Previous research has documented the influence of eating together on people's food expectations and choices. We conducted an fMRI study to investigate the influence of the label "eating together" on behavioral and brain responses to healthy or unhealthy foods. The participants (N = 28, 13 females; mean age = 21.19) viewed food photos presented with a label of "eating together" or "eating alone" and estimated the palatability, pleasantness, and desirability of each food. The label "eating together" elicited more positive ratings for both healthy and unhealthy foods than the label "eating alone," and this effect of social context was larger for unhealthy than healthy foods. The label "eating together" also elicited greater activation in the left insula and the right posterior insula for unhealthy foods (p = 0.001 and p = 0.004, whole-brain corrected, respectively). These findings suggest that a label of "eating together" can enhance the reward values of foods, with a potentially greater enhancement for unhealthy foods.

Reward Value Revealed by Auction in Rhesus Monkeys

Economic choice is thought to involve the elicitation of the subjective values of the choice options. Thus far, value estimation in animals has relied on stochastic choices between multiple options presented in repeated trials and expressed from averages of dozens of trials. However, subjective reward valuations are made moment-to-moment and do not always require alternative options; their consequences are usually felt immediately. Here, we describe a Becker-DeGroot-Marschak (BDM) auction-like mechanism that provides more direct and simple valuations with immediate consequences. The BDM encourages agents to truthfully reveal their true subjective value in individual choices ("incentive compatibility"). Male monkeys reliably placed well-ranked BDM bids for up to five juice volumes while paying from a water budget. The bids closely approximated the average subjective values estimated with conventional binary choices (BCs), thus demonstrating procedural invariance and aligning with the wealth of knowledge acquired with these less direct estimation methods. The feasibility of BDM bidding in monkeys paves the way for an analysis of subjective neuronal value signals in single trials rather than from averages; the feasibility also bridges the gap to the increasingly used BDM method in human neuroeconomics.SIGNIFICANCE STATEMENT The subjective economic value of rewards cannot be measured directly but must be inferred from observable behavior. Until now, the estimation method in animals was rather complex and required comparison between several choice options during repeated choices; thus, such methods did not respect the imminence of the outcome from individual choices. However, human economic research has developed a simple auction-like procedure that can reveal in a direct and immediate manner the true subjective value in individual choices [Becker-DeGroot-Marschak (BDM) mechanism]. The current study implemented this mechanism in rhesus monkeys and demonstrates its usefulness for eliciting meaningful value estimates of liquid rewards. The mechanism allows future neurophysiological assessment of subjective reward value signals in single trials of controlled animal tasks.

Is It Worth It? Obesity Affects Snack Food Valuation Across the Menstrual Cycle

Background

The importance of menstrual cycle physiology in appetite and obesity is poorly understood. We investigated the effects of body mass index (BMI), menstrual cycle phase and sweet and salty taste on monetary valuation of snack foods.

Methods

We recruited 72 women and after the application of in- and exclusion criteria 31 participants with healthy weight and 25 with obesity remained. The participants completed a willingness to pay (WTP) task to measure subjective value of 30 snack food items in the pre-ovulatory and mid-luteal cycle phases.

Results

Generalized linear mixed model (GLMM) analysis revealed that BMI, cycle phase and snack taste interacted to influence WTP (−0.15 [−0.22, −0.03], p = 0.002). Hence, WTP was inversely related to BMI, but the strength of the relation depended on cycle phase and taste. The WTP of participants with healthy weight for salty taste changed across cycle phase but the WTP for sweet taste was not affected by cycle phase. Moreover, the cycle effect for the salty snacks ceased in participants with obesity.

Conclusion

The inverse effect of BMI on WTP valuation of snack foods contrasts with the positive effect of BMI on pleasantness ratings for milkshakes by the same women that we previously reported. This indicates that the two measures reflect different aspects of food-related valuative processing in obesity. Furthermore, the WTP data suggest that the selection of salty snacks may differ from that of sweet snacks in the pre-ovulatory phase of the menstrual cycle for individuals of healthy weight. The cycle phase does not seem to affect food valuation of participants with obesity. These findings are relevant to understanding and treating obesity in women.

Neural Representations of Food-Related Attributes in the Human Orbitofrontal Cortex during Choice Deliberation in Anorexia Nervosa

Decisions about what to eat recruit the orbitofrontal cortex (OFC) and involve the evaluation of food-related attributes such as taste and health. These attributes are used differently by healthy individuals and patients with disordered eating behavior, but it is unclear whether these attributes are decodable from activity in the OFC in both groups and whether neural representations of these attributes are differentially related to decisions about food. We used fMRI combined with behavioral tasks to investigate the representation of taste and health attributes in the human OFC and the role of these representations in food choices in healthy women and women with anorexia nervosa (AN). We found that subjective ratings of tastiness and healthiness could be decoded from patterns of activity in the OFC in both groups. However, health-related patterns of activity in the OFC were more related to the magnitude of choice preferences among patients with AN than healthy individuals. These findings suggest that maladaptive decision-making in AN is associated with more consideration of health information represented by the OFC during deliberation about what to eat.SIGNIFICANCE STATEMENT An open question about the OFC is whether it supports the evaluation of food-related attributes during deliberation about what to eat. We found that healthiness and tastiness information was decodable from patterns of neural activity in the OFC in both patients with AN and healthy controls. Critically, neural representations of health were more strongly related to choices in patients with AN, suggesting that maladaptive overconsideration of healthiness during deliberation about what to eat is related to activity in the OFC. More broadly, these results show that activity in the human OFC is associated with the evaluation of relevant attributes during value-based decision-making. These findings may also guide future research into the development of treatments for AN.

Prefrontal cortex interactions with the amygdala in primates

This review addresses functional interactions between the primate prefrontal cortex (PFC) and the amygdala, with emphasis on their contributions to behavior and cognition. The interplay between these two telencephalic structures contributes to adaptive behavior and to the evolutionary success of all primate species. In our species, dysfunction in this circuitry creates vulnerabilities to psychopathologies. Here, we describe amygdala-PFC contributions to behaviors that have direct relevance to Darwinian fitness: learned approach and avoidance, foraging, predator defense, and social signaling, which have in common the need for flexibility and sensitivity to specific and rapidly changing contexts. Examples include the prediction of positive outcomes, such as food availability, food desirability, and various social rewards, or of negative outcomes, such as threats of harm from predators or conspecifics. To promote fitness optimally, these stimulus-outcome associations need to be rapidly updated when an associative contingency changes or when the value of a predicted outcome changes. We review evidence from nonhuman primates implicating the PFC, the amygdala, and their functional interactions in these processes, with links to experimental work and clinical findings in humans where possible.

Fat and Carbohydrate Interact to Potentiate Food Reward in Healthy Weight but Not in Overweight or Obesity

Prior work suggests that actual, but not estimated, energy density drives the reinforcing value of food and that energy from fat and carbohydrate can interact to potentiate reward. Here we sought to replicate these findings in an American sample and to determine if the effects are influenced by body mass index (BMI). Thirty participants with healthy weight (HW; BMI 21.92 ± 1.77; M ± SD) and 30 participants with overweight/obesity (OW/OB; BMI 29.42 ± 4.44) rated pictures of common American snacks in 120-kcal portions for liking, familiarity, frequency of consumption, expected satiety, healthiness, energy content, energy density, and price. Participants then completed an auction task where they bid for the opportunity to consume each food. Snacks contained either primarily carbohydrate, primarily fat, or roughly equal portions of fat and carbohydrate (combo). Replicating prior work, we found that participants with HW bid the most for combo foods in linear mixed model analyses. This effect was not observed among individuals with OW/OB. Additionally, in contrast with previous reports, our linear regression analyses revealed a negative relationship between the actual energy density of the snacks and bid amount that was mediated by food price. Our findings support altered macronutrient reinforcement in obesity and highlight potential influences of the food environment on the regulation of food reward.

Evaluation of energy density and macronutrients after extremely brief time exposure

Many food decisions are made rapidly and without reflective processing. The ability to determine nutritional information accurately is a precursor of food decisions and is important for a healthy diet and weight management. However, little is known about the cognitive evaluation of food attributes based on visual information in relation to assessing nutritional content. We investigated the accuracy of visual encoding of nutritional information after brief and extended time exposures to food images. The following questions were addressed: (1) how accurately do people estimate energy and macronutrients after brief exposure to food images, and (2) how does estimation accuracy change with time exposure and the type of nutritional information? Participants were first asked to rate the energy density (calories) and macronutrient content (carbohydrates/fat/protein) of different sets of food images under three time conditions (97, 500 or 1000 ms) and then asked to perform the task with no time constraints. We calculated estimation accuracy by computing the correlations between estimated and actual nutritional information for each time exposure and compared estimation accuracy with respect to the type of nutritional information and the exposure time. The estimated and actual energy densities and individual macronutrient content were significantly correlated, even after a brief exposure time (97 ms). The degree of accuracy of the estimations did not differ with additional time exposure, suggesting that <100 ms was sufficient to predict the energy and macronutrients from food images. Additionally, carbohydrate estimates were less accurate than the estimates of other nutritional variables (proteins, fat and calories), regardless of the exposure time. These results revealed rapid and accurate assessment of food attributes based on visual information and the accuracy of visual encoding of nutritional information after brief and extended time exposure to food imagery.

Neural Substrates of Food Valuation and Its Relationship With BMI and Healthy Eating in Higher BMI Individuals

Considerable evidence points to a link between body mass index (BMI), eating behavior, and the brain's reward system. However, much of this research focuses on food cue reactivity without examining the subjective valuation process as a potential mechanism driving individual differences in BMI and eating behavior. The current pre-registered study (https://osf.io/n4c95/) examined the relationship between BMI, healthy eating, and subjective valuation of healthy and unhealthy foods in a community sample of individuals with higher BMI who intended to eat more healthily. Particularly, we examined: (1) alterations in neurocognitive measures of subjective valuation related to BMI and healthy eating; (2) differences in the neurocognitive valuation for healthy and unhealthy foods and their relation to BMI and healthy eating; (3) and whether we could conceptually replicate prior findings demonstrating differences in neural reactivity to palatable vs. plain foods. To this end, we scanned 105 participants with BMIs ranging from 23 to 42 using fMRI during a willingness-to-pay task that quantifies trial-by-trial valuation of 30 healthy and 30 unhealthy food items. We measured out of lab eating behavior via the Automated Self-Administered 24 H Dietary Assessment Tool, which allowed us to calculate a Healthy Eating Index (HEI). We found that our sample exhibited robust, positive linear relationships between self-reported value and neural responses in regions previously implicated in studies of subjective value, suggesting an intact valuation system. However, we found no relationship between valuation and BMI nor HEI, with Bayes Factor indicating moderate evidence for a null relationship. Separating the food types revealed that healthy eating, as measured by the HEI, was inversely related to subjective valuation of unhealthy foods. Imaging data further revealed a stronger linkage between valuation of healthy (compared to unhealthy) foods and corresponding response in the ventromedial prefrontal cortex (vmPFC), and that the interaction between healthy and unhealthy food valuation in this region is related to HEI. Finally, our results did not replicate reactivity differences demonstrated in prior work, likely due to differences in the mapping between food healthiness and palatability. Together, our findings point to disruptions in the valuation of unhealthy foods in the vmPFC as a potential mechanism influencing healthy eating.

Development of MacroPics: A novel food picture set to dissociate the effects of carbohydrate and fat on eating behaviors

Emerging evidence suggests that fat and carbohydrate interact to potentiate the reward value of food (DiFeliceantonio et al., 2018). The primary goal of the current study was to develop a novel picture set to facilitate research into the effects of macronutrient composition on food choice and eating behavior. Toward this aim, we developed "MacroPics." In Experiment 1, we photographed 120-kcal portions of 60 snack foods falling into one of the three macronutrient categories: (1) mostly carbohydrate, (2) mostly fat, or (3) a combination of fat and carbohydrate. Sixty-one participants rated the images for liking, familiarity, frequency of consumption, healthiness, estimated energy content (in kcal), and expected satiation. A subset of these images consisting of 36 items was then selected in an iterative process to minimize differences in ratings between the macronutrient categories while simultaneously ensuring similar within-category variability on a number of food characteristics (e.g., energy density, portion size, retail price) and visual properties (e.g., color, complexity, visual area). In Experiment 2, an independent sample of 67 participants rated the pictures of the final 36-item MacroPics. Both experiments reveal similar participant ratings across categories for item liking, familiarity, frequency, healthiness, and estimated energy content. Protein content was higher in the fat compared to the carbohydrate and combination categories, leading to higher ratings of estimated satiety and energy density for fatty foods. Item and macronutrient category characteristics of the final MacroPics set are reported.

Data Triangulation in Consumer Neuroscience: Integrating Functional Neuroimaging With Meta-Analyses, Psychometrics, and Behavioral Data

This article reviews a wide range of functional magnetic resonance imaging (fMRI) studies conducted in the field of consumer neuroscience to (1) highlight common interpretative approaches of neuroimaging data (i.e., forward inference and reverse inference), (2) discuss potential interpretative issues associated with these approaches, and (3) provide a framework that employs a multi-method approach aimed to possibly raise the explanatory power and, thus, the validity of functional neuroimaging research in consumer neuroscience. Based on this framework, we argue that the validity of fMRI studies can be improved by the triangulation of (1) careful design of neuroimaging studies and analyses of data, (2) meta-analyses, and (3) the integration of psychometric and behavioral data with neuroimaging data. Guidelines on when and how to employ triangulation methods on neuroimaging data are included. Moreover, we also included discussions on practices and research directions that validate fMRI studies in consumer neuroscience beyond data triangulation.

Is obesity related to enhanced neural reactivity to visual food cues? A review and meta-analysis

Theoretical work suggests that obesity is related to enhanced incentive salience of food cues. However, evidence from both behavioral and neuroimaging studies on the topic is mixed. In this work we review the literature on cue reactivity in obesity and perform a preregistered meta-analysis of studies investigating effects of obesity on brain responses to passive food pictures viewing. Further, we examine whether age influences brain responses to food cues in obesity. In the meta-analysis we included 13 studies of children and adults that investigated group differences (obese vs. lean) in responses to food vs. non-food pictures viewing. While we found no significant differences in the overall meta-analysis, we show that age significantly influences brain response differences to food cues in the left insula and the left fusiform gyrus. In the left insula, obese vs. lean brain differences in response to food cues decreased with age, while in the left fusiform gyrus the pattern was opposite. Our results suggest that there is little evidence for obesity-related differences in responses to food cues and that such differences might be mediated by additional factors that are often not considered.

Extrinsic Factors Underlying Food Valuation in the Human Brain

Subjective values for food rewards guide our dietary choices. There is growing evidence that value signals are constructed in the brain by integrating multiple types of information about flavor, taste, and nutritional attributes of the foods. However, much less is known about the influence of food-extrinsic factors such as labels, brands, prices, and packaging designs. In this mini-review article, we outline recent findings in decision neuroscience, consumer psychology, and food science about the effect of extrinsic factors on food value computations in the human brain. To date, studies have demonstrated that, while the integrated value signal is encoded in the ventromedial prefrontal cortex, information on the extrinsic factors of the food is encoded in diverse brain regions previously implicated in a wide range of functions: cognitive control, memory, emotion and reward processing. We suggest that a comprehensive understanding of food valuation requires elucidation of the mechanisms behind integrating extrinsic factors in the brain to compute an overall subjective value signal.

Neural-based valuation of functional foods among lean and obese individuals

Functional foods may contribute to establish healthy eating habits and reduce obesity and related comorbidities. Differences in the brain mechanisms underpinning the valuation of functional foods in individuals with excess weight may inform the development of attractive functional foods. We aimed to compare brain function during the Willingness to Pay task for functional vs standard foods between individuals with healthy weight (HW), overweight (OW), and obesity (OB). We hypothesized that, in participants with OB, willingness to pay for functional foods would evoke greater activation/connectivity in brain regions previously associated with subjective value. Thirty-six HW, 19 OW, and 20 OB adults performed a functional magnetic resonance imaging-Willingness to Pay task that requires them to decide how much they would pay for presented standard and functional food images tasted in a previous buffet. Whole-brain analyses compared task-related activation and connectivity between participants with OB, OW, and HW. Individuals with OB, relative to HW, showed more similar willingness to pay for functional and standard food. At the brain level, they also showed hyperactivation in the ventral posterior cingulate cortex and the right angular gyrus, as well as an increased functional connectivity between the ventral posterior cingulate cortex and the intraparietal cortices to the valuation of the functional vs the standard foods. Increased willingness to pay for functional foods in people with excessive weight may be driven by recruitment of brain regions that direct attention to internal goals.

Food reward and gut-brain signalling

The increasing availability of ultra-processed, energy dense food is contributing to the spread of the obesity pandemic, which is a serious health threat in today’s world. One possible cause for this association arises from the fact that the brain is wired to derive pleasure from eating. Specifically, food intake activates reward pathways involving dopamine receptor signalling. The reinforcing value of specific food items results from the interplay between taste and nutritional properties. Increasing evidence suggests that nutritional value is sensed in the gut by chemoreceptors in the intestinal tract and the hepatic portal vein, and conveyed to the brain through neuronal and endocrine pathways to guide food selection behaviour. Ultra-processed food is designed to potentiate the reward response through a combination of high fat and high sugar, therebye seeming highly appetizing. There is increasing evidence that overconsumption of processed food distorts normal reward signalling, leading to compulsive eating behaviour and obesity. Hence, it is essential to understand food reward and gut-brain signalling to find an effective strategy to combat the obesity pandemic.

Rethinking Food Reward

The conscious perception of the hedonic sensory properties of caloric foods is commonly believed to guide our dietary choices. Current and traditional models implicate the consciously perceived hedonic qualities of food as driving overeating, whereas subliminal signals arising from the gut would curb our uncontrolled desire for calories. Here we review recent animal and human studies that support a markedly different model for food reward. These findings reveal in particular the existence of subcortical body-to-brain neural pathways linking gastrointestinal nutrient sensors to the brain's reward regions. Unexpectedly, consciously perceptible hedonic qualities appear to play a less relevant, and mostly transient, role in food reinforcement. In this model, gut-brain reward pathways bypass cranial taste and aroma sensory receptors and the cortical networks that give rise to flavor perception. They instead reinforce behaviors independently of the cognitive processes that support overt insights into the nature of our dietary decisions.

Methods for Presenting Real-world Objects Under Controlled Laboratory Conditions

Our knowledge of human object vision is based almost exclusively on studies in which the stimuli are presented in the form of computerized two-dimensional (2-D) images. In everyday life, however, humans interact predominantly with real-world solid objects, not images. Currently, we know very little about whether images of objects trigger similar behavioral or neural processes as do real-world exemplars. Here, we present methods for bringing the real-world into the laboratory. We detail methods for presenting rich, ecologically-valid real-world stimuli under tightly-controlled viewing conditions. We describe how to match closely the visual appearance of real objects and their images, as well as novel apparatus and protocols that can be used to present real objects and computerized images on successively interleaved trials. We use a decision-making paradigm as a case example in which we compare willingness-to-pay (WTP) for real snack foods versus 2-D images of the same items. We show that WTP increases by 6.6% for food items displayed as real objects versus high-resolution 2-D colored images of the same foods -suggesting that real foods are perceived as being more valuable than their images. Although presenting real object stimuli under controlled conditions presents several practical challenges for the experimenter, this approach will fundamentally expand our understanding of the cognitive and neural processes that underlie naturalistic vision.

The influence of gaze direction on food preferences

In our information-rich environment, the gaze direction of another indicates their current focus of attention. Following the gaze of another, results in gaze-evoked shifts in joint attention, a phenomenon critical for the functioning of social cognition. Previous research in joint attention has shown that objects that are attended by another are more liked than ignored objects. Here, we investigated this effect of gaze-cueing on participants' preferences for unknown food items. Participants provided their willingness to pay (WTP), taste and health preferences for food items before and after a standard gaze-cueing paradigm. We observed a significant effect of gaze-cueing on participants' WTP bids. Specifically, participants were willing to pay more money for the food items that were looked at by another person. In contrast, there was a decrease in preference for the food items that were ignored by another person. Interestingly, this increase in WTP occurred without participants' awareness of the contingency between the cue and target. These results highlight the influence of social information on human choice behavior and lay the foundation for experiments in neuromarketing and consumer decision making.

It's in the eye of the beholder: selective attention to drink properties during tasting influences brain activation in gustatory and reward regions

Statements regarding pleasantness, taste intensity or caloric content on a food label may influence the attention consumers pay to such characteristics during consumption. There is little research on the effects of selective attention on taste perception and associated brain activation in regular drinks. The aim of this study was to investigate the effect of selective attention on hedonics, intensity and caloric content on brain responses during tasting drinks. Using functional MRI brain responses of 27 women were measured while they paid attention to the intensity, pleasantness or caloric content of fruit juice, tomato juice and water. Brain activation during tasting largely overlapped between the three selective attention conditions and was found in the rolandic operculum, insula and overlying frontal operculum, striatum, amygdala, thalamus, anterior cingulate cortex and middle orbitofrontal cortex (OFC). Brain activation was higher during selective attention to taste intensity compared to calories in the right middle OFC and during selective attention to pleasantness compared to intensity in the right putamen, right ACC and bilateral middle insula. Intensity ratings correlated with brain activation during selective attention to taste intensity in the anterior insula and lateral OFC. Our data suggest that not only the anterior insula but also the middle and lateral OFC are involved in evaluating taste intensity. Furthermore, selective attention to pleasantness engaged regions associated with food reward. Overall, our results indicate that selective attention to food properties can alter the activation of gustatory and reward regions. This may underlie effects of food labels on the consumption experience of consumers.

To What Extent Memory Could Contribute to Impaired Food Valuation and Choices in Obesity?

Obesity is associated with a diverse array of cognitive and affective deficits, among which impairments in food valuation and choices have received increasing attention. The neural underpinnings of such impairments, however, remain poorly understood, partly because a complete understanding of these processes under normal conditions has yet to be achieved. A rapidly growing literature on the interaction between memory and decision-making has begun to highlight the integral role of memory in decision making especially in the real world, as well as the role of the hippocampus in supporting flexible decision making. Perhaps not coincidentally, altered memory performances in obesity have been well documented, and the underlying neurobiological bases of these memory alterations have also started to be better described, involving pathologies at the biochemical, cellular, and circuit levels. Despite such correspondence, the link between memory impairments and food valuation/choice deficits in obesity has received little attention. In this article, we first summarize the growing empirical support for the relevance of memory for decision making, focusing on flexible value-based decisions. We then describe converging evidence on different forms of memory impairments accompanying obesity. Building on these findings, we formulate a general neuropsychological framework and discuss how dysfunctions in the formation and retrieval of memory may interfere with adaptive decision making for food. Finally, we stress the important practical implications of this framework, arguing that memory deficits are likely a significant contributor to suboptimal food purchase and eating behavior exhibited by obese individuals.

Relation of neural response to palatable food tastes and images to future weight gain: Using bootstrap sampling to examine replicability of neuroimaging findings

Because understanding neural vulnerability factors that predict future weight gain may guide the design of more effective obesity prevention programs and treatments, we tested whether neural response to palatable food tastes and images predicted future weight gain. We recruited 135 initially healthy weight adolescents, to reduce the possibility that a history of overeating affected neural responsivity, had them complete fMRI paradigms examining neural response to tastes of milkshakes that varied in fat and sugar content and images of palatable foods, and assessed BMI annually over a 3-year follow-up. We used a novel bootstrapping analytic approach to investigate the replicability of the fMRI findings. Whole-brain analyses indicated that lower response in the pre-supplemental motor area to high-fat/low-sugar milkshake taste predicted future BMI gain in the full sample and in 5 out of the 10 bootstrap samples. Elevated response in the precentral gyrus/Rolandic operculum to images of appetizing foods predicted future BMI gain in the full sample and in 4 out of the 10 bootstrap samples. Other peaks that emerged in the full sample did not replicate in most of the bootstrap samples, suggesting they were not reliable. Region of interest analyses did not replicate the predictive effects of peaks reported in past papers that used similar paradigms, including the evidence that TaqIA polymorphism moderated the relation of striatal response to palatable food tastes to future weight gain. Results suggest that lower responsivity of a region implicated in motor processing in response to palatable taste was associated with greater BMI gain over time, and further that bootstrap sampling may be useful for estimating the replicability of findings that emerge from whole brain analyses or regions of interest analyses with the full sample.

Neural predictors of eating behavior and dietary change

Recently, there has been an increase in the number of human neuroimaging studies seeking to predict behavior above and beyond traditional measurements such as self-report. This trend has been particularly notable in the area of food consumption, as the percentage of people categorized as overweight or obese continues to rise. In this review, we argue that there is considerable utility in this form of health neuroscience, modeling the neural bases of eating behavior and dietary change in healthy community populations. Further, we propose a model and accompanying evidence indicating that several basic processes underlying eating behavior, particularly reactivity, regulation, and valuation, can be predictive of behavior change. We also discuss future directions for this work.

Supra-Additive Effects of Combining Fat and Carbohydrate on Food Reward

Post-ingestive signals conveying information about the nutritive properties of food are critical for regulating ingestive behavior. Here, using an auction task concomitant to fMRI scanning, we demonstrate that participants are willing to pay more for fat + carbohydrate compared with equally familiar, liked, and caloric fat or carbohydrate foods and that this potentiated reward is associated with response in areas critical for reward valuation, including the dorsal striatum and mediodorsal thalamus. We also show that individuals are better able to estimate the energy density of fat compared with carbohydrate and fat + carbohydrate foods, an effect associated with functional connectivity between visual (fusiform gyrus) and valuation (ventromedial prefrontal cortex) areas. These results provide the first demonstration that foods high in fat and carbohydrate are, calorie for calorie, valued more than foods containing only fat or carbohydrate and that this effect is associated with greater recruitment of central reward circuits.

The real deal: Willingness-to-pay and satiety expectations are greater for real foods versus their images

Laboratory studies of human dietary choice have relied on computerized two-dimensional (2D) images as stimuli, whereas in everyday life, consumers make decisions in the context of real foods that have actual caloric content and afford grasping and consumption. Surprisingly, few studies have compared whether real foods are valued more than 2D images of foods, and in the studies that have, differences in the stimuli and testing conditions could have resulted in inflated bids for the real foods. Moreover, although the caloric content of food images has been shown to influence valuation, no studies to date have investigated whether 'real food exposure effects' on valuation reflect greater sensitivity to the caloric content of real foods versus images. Here, we compared willingness-to-pay (WTP) for, and expectations about satiety after consuming, everyday snack foods that were displayed as real foods versus 2D images. Critically, our 2D images were matched closely to the real foods for size, background, illumination, and apparent distance, and trial presentation and stimulus timing were identical across conditions. We used linear mixed effects modeling to determine whether effects of display format were modulated by food preference and the caloric content of the foods. Compared to food images, observers were willing to pay 6.62% more for (Experiment 1) and believed that they would feel more satiated after consuming (Experiment 2), foods displayed as real objects. Moreover, these effects appeared to be consistent across food preference, caloric content, as well as observers' estimates of the caloric content of the foods. Together, our results confirm that consumers' perception and valuation of everyday foods is influenced by the format in which they are displayed. Our findings raise important new insights into the factors that shape dietary choice in real-world contexts and highlight potential avenues for improving public health approaches to diet and obesity.

Elucidating the underlying components of food valuation in the human orbitofrontal cortex

The valuation of food is a fundamental component of our decision-making. Yet little is known about how value signals for food and other rewards are constructed by the brain. Using a food-based decision task in human participants, we found that subjective values can be predicted from beliefs about constituent nutritive attributes of food: protein, fat, carbohydrates and vitamin content. Multivariate analyses of functional MRI data demonstrated that, while food value is represented in patterns of neural activity in both medial and lateral parts of the orbitofrontal cortex (OFC), only the lateral OFC represents the elemental nutritive attributes. Effective connectivity analyses further indicate that information about the nutritive attributes represented in the lateral OFC is integrated within the medial OFC to compute an overall value. These findings provide a mechanistic account for the construction of food value from its constituent nutrients.

Undervalued and ignored: Are humans poorly adapted to energy-dense foods?

In many species the capacity to accurately differentiate the energy density (kcal/g) of foods is critical because it greatly improves efficiency in foraging. In modern humans this ability remains intact and is expressed in a selective preference for types of fruit and vegetables that contain more calories. However, humans evolved consuming these low energy-dense foods (typically < 1.75 kcal/g) and it remains unclear whether they can also discriminate more energy-dense foods that now feature in modern Western diets. In two experiment participants (both N = 40) completed four tasks that assessed the 'value' of different sets of 22 foods that ranged in energy density (0.1 kcal/g-5.3 kcal/g and range 0.1 kcal/g to 6.2 kcal/g in Experiment 1 and 2, respectively). In Experiment 1 three measures (expected fullness, calorie estimation, and food choice), and in foods less than approximately 1.5 kcal/g (typically fruits and vegetables), the relationship between perceived value and energy density is linear. Above this, we observed clear compressive functions, indicating relative and progressive undervaluation of higher energy-dense foods. The fourth task (rated liking) failed to provide evidence for any relationship with energy density. In Experiment 2 the same pattern was replicated in measures of expected fullness, and in two different assessments of subjective calorie content. Consistent with the concept of 'evolutionary discordance,' this work indicates that modern human physiology is poorly adapted to evaluate foods that have a historically unusual (high) energy density. This has implications both for our understanding of how 'modern' energy-dense foods affect choice and energy intake, and for strategies aimed at removing calories from highly energy-rich foods.

Nutrition labeling reduces valuations of food through multiple health and taste channels

One popularized technique to promote healthy dietary choice involves posting calorie or other nutritional information at the time individuals make a consumption decision. While the evidence on the effectiveness of such interventions is mixed, relatively little work has focused on the underlying mechanisms of how such labels alter behavior. In the research reported here, we asked 87 hungry laboratory subjects to make bids over foods with or without nutrition labels present. We found that the presence of a nutrition label reduced bids by an average of 25 cents. Furthermore, we found this reduction was driven by differences in perceptions and the importance individuals placed on health features of the foods, but also by differences in the importance individuals placed on more visceral taste features. These results help explain the various methods in which nutritional information postings or other policy tools can nudge individuals to consume healthier options.

Effects of the modern food environment on striatal function, cognition and regulation of ingestive behavior

Emerging evidence from human and animal studies suggest that consumption of palatable foods rich in fat and/or carbohydrates may produce deleterious influences on brain function independently of body weight or metabolic disease. Here we consider two mechanisms by which diet can impact striatal circuits to amplify food cue reactivity and impair inhibitory control. First, we review findings demonstrating that the energetic properties of foods regulate nucleus accumbens food cue reactivity, a demonstrated predictor of weight gain susceptibility, which is then sensitized by chronic consumption of an energy dense diet. Second, we consider evidence for diet-induced adaptations in dorsal striatal dopamine signaling that is associated with impaired inhibitory control and negative outcome learning.

The Neuroscience of Human Decision-Making Through the Lens of Learning and Memory

We are called upon to make decisions, large and small, many times a day. Whether in the voting booth, the stock exchange, or the cafeteria line, we identify potential options, estimate and compare their subjective values, and make a choice. Decision-making has only recently become a focus for cognitive neuroscience. The last two decades have seen rapid progress in our understanding of the brain basis of at least some aspects of this rather complex aspect of cognition. This work has provided fresh perspectives on poorly understood brain regions, such as orbitofrontal cortex and ventral striatum. It has led to interesting interdisciplinary exchanges with diverse fields, notably economics, but also ecology and political science, among others. The novel perspectives arising from these exchanges have begun to be related to better understood aspects of cognition. In particular, it is increasingly clear that decision-making is tightly interlinked with learning and memory. Key early insights in decision neuroscience came from what were essentially reinforcement learning tasks. Recent work has made similar links to aspects of declarative memory. Indeed, decision-making can be seen as the link between memory of the past and future actions. This chapter reviews selected topics in decision neuroscience, with a particular focus on the links to learning and memory, and a particular emphasis on regions within prefrontal cortex.