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Background/Objectives Intranasal (IN) administration of insulin decreases appetite in humans, but the underlying mechanisms are unclear, and it is unknown whether IN insulin affects the food intake of women with obesity. Subjects/Methods In a double-blind, placebo-controlled, crossover design, participants (35 lean women and 17 women with obesity) were randomized to receive 160 IU/1.6 mL of IN insulin or placebo in a counterbalanced order in the post prandial state. The effects of IN insulin on cookie intake, appetite, mood, food reward, cognition and neural activity were assessed. Results IN insulin in the post prandial state reduced cookie intake, appetite and food reward relative to placebo and these effects were more pronounced for women with obesity compared with lean women. IN insulin also improved mood in women with obesity. In both BMI groups, IN insulin increased neural activity in the insula when viewing food pictures. IN insulin did not affect cognitive function. Conclusions These results suggest that IN insulin decreases palatable food intake when satiated by reducing food reward and that women with obesity may be more sensitive to this effect than lean women. Further investigation of the therapeutic potential of IN insulin for weight management in women with obesity is warranted.

Deficits in interoception have been associated with disordered eating but there has been no systematic review of whether the interoceptive deficits are observed across all types of disordered eating and across interoceptive modalities. There has also been no evaluation of whether deficits in interoception play a causal role in the development of disordered eating. Nor has there been a review of the moderating/mediating factors of the relationship between interoception and disordered eating. To address these gaps we conducted a systematic review using PRISMA guidelines. 104 studies with 32883 participants were included. Deficits in interoception were observed across disordered eating types and interoceptive modalities suggesting that interoception may constitute a transdiagnostic feature of disordered eating. There is currently limited evidence on the causal role of interoception in the development of disordered eating and no studies have formally analysed the moderators/mediators. Future mechanistic research examining particular dimensions of interoception will provide insights into the specific interoceptive deficits associated with disordered eating and could lead to the development of improved therapies.

Lisdexamfetamine dimesylate (LDX) is the only drug currently approved by the FDA for the treatment of Binge-Eating Disorder (BED), but little is known about the behavioural mechanisms that underpin the efficacy of LDX in treating BED. We examined the behavioural and neural effects of an acute dose of LDX (50 mg) in 22 women with binge-eating symptomatology using a randomised, crossover, double-blind, placebo-controlled experimental medicine design. LDX reduced self-reported appetite ratings and intake of both a pasta meal and a palatable cookie snack. LDX also decreased the eating rate of pasta but not of cookies and reduced self-reported liking ratings for pasta at the end of the meal. When viewing food pictures during an fMRI scan, LDX reduced activity bilaterally in the thalamus. LDX enhanced sustained attention and reduced impulsive responding in a continuous performance task but had no effect on emotional bias or working memory. These results suggest the observed effects of LDX on food intake (and by implication the efficacy of LDX in treating BED) may be related to the actions of the drug to enhance satiety, reduce food-related reward responding when full and/or increase cognitive control. Novel pharmacotherapies for BED might be most effective if they have a broad spectrum of effects on appetite, reward and cognition.

Real-time fMRI neurofeedback is an increasingly popular neuroimaging technique that allows an individual to gain control over his/her own brain signals, which can lead to improvements in behavior in healthy participants as well as to improvements of clinical symptoms in patient populations. However, a considerably large ratio of participants undergoing neurofeedback training do not learn to control their own brain signals and, consequently, do not benefit from neurofeedback interventions, which limits clinical efficacy of neurofeedback interventions. As neurofeedback success varies between studies and participants, it is important to identify factors that might influence neurofeedback success. Here, for the first time, we employed a big data machine learning approach to investigate the influence of 20 different design-specific (e.g. activity vs. connectivity feedback), region of interest-specific (e.g. cortical vs. subcortical) and subject-specific factors (e.g. age) on neurofeedback performance and improvement in 608 participants from 28 independent experiments. With a classification accuracy of 60% (considerably different from chance level), we identified two factors that significantly influenced neurofeedback performance: Both the inclusion of a pre-training no-feedback run before neurofeedback training and neurofeedback training of patients as compared to healthy participants were associated with better neurofeedback performance. The positive effect of pre-training no-feedback runs on neurofeedback performance might be due to the familiarization of participants with the neurofeedback setup and the mental imagery task before neurofeedback training runs. Better performance of patients as compared to healthy participants might be driven by higher motivation of patients, higher ranges for the regulation of dysfunctional brain signals, or a more extensive piloting of clinical experimental paradigms. Due to the large heterogeneity of our dataset, these findings likely generalize across neurofeedback studies, thus providing guidance for designing more efficient neurofeedback studies specifically for improving clinical neurofeedback-based interventions. To facilitate the development of data-driven recommendations for specific design details and subpopulations the field would benefit from stronger engagement in open science research practices and data sharing. publishedVersion

Obesity is associated with altered responses to food stimuli in prefrontal brain networks that mediate inhibitory control of ingestive behavior. In particular, activity of the dorsolateral prefrontal cortex (dlPFC) is reduced in obese compared to normal-weight subjects and has been linked to the success of weight-loss dietary interventions. In a randomized controlled trial in overweight/obese subjects, we investigated the effect on eating behavior of volitional up-regulation of dlPFC activity via real-time functional magnetic resonance imaging (fMRI) neurofeedback training. Thirty-eight overweight or obese subjects (BMI 25–40 kg/m2) took part in fMRI neurofeedback training with the aim of increasing activity of the left dlPFC (dlPFC group; n = 17) or of the visual cortex (VC/control group; n = 21). Participants were blinded to group assignment. The training session took place on a single day and included three training runs of six trials of up-regulation and passive viewing. Food appraisal and snack intake were assessed at screening, after training, and in a follow-up session four weeks later. Participants of both groups succeeded in up-regulating activity of the targeted brain area. However, participants of the control group also showed increased left dlPFC activity during up-regulation. Functional connectivity between dlPFC and ventromedial PFC, an area that processes food value, was generally increased during up-regulation compared to passive viewing. At follow-up compared to baseline, both groups rated pictures of high-, but not low-calorie foods as less palatable and chose them less frequently. Actual snack intake remained unchanged but palatability and choice ratings for chocolate cookies decreased after training. We demonstrate that one session of fMRI neurofeedback training enables individuals with increased body weight to up-regulate activity of the left dlPFC. Behavioral effects were observed in both groups, which might have been due to dlPFC co-activation in the control group and, in addition, unspecific training effects. Improved dlPFC-vmPFC functional connectivity furthermore suggested enhanced food intake-related control mechanisms. Neurofeedback training might support therapeutic strategies aiming at improved self-control in obesity, although the respective contributions of area-specific mechanisms and general regulation effects are in need of further investigation.

Real-time fMRI neurofeedback is an increasingly popular neuroimaging technique that allows an individual to gain control over his/her own brain signals, which can lead to improvements in behavior in healthy participants as well as to improvements of clinical symptoms in patient populations. However, a considerably large ratio of participants undergoing neurofeedback training do not learn to control their own brain signals and, consequently, do not benefit from neurofeedback interventions, which limits clinical efficacy of neurofeedback interventions. As neurofeedback success varies between studies and participants, it is important to identify factors that might influence neurofeedback success. Here, for the first time, we employed a big data machine learning approach to investigate the influence of 20 different design-specific (e.g. activity vs. connectivity feedback), region of interest-specific (e.g. cortical vs. subcortical) and subject-specific factors (e.g. age) on neurofeedback performance and improvement in 608 participants from 28 independent experiments.With a classification accuracy of 60% (considerably different from chance level), we identified two factors that significantly influenced neurofeedback performance: Both the inclusion of a pre-training no-feedback run before neurofeedback training and neurofeedback training of patients as compared to healthy participants were associated with better neurofeedback performance. The positive effect of pre-training no-feedback runs on neurofeedback performance might be due to the familiarization of participants with the neurofeedback setup and the mental imagery task before neurofeedback training runs. Better performance of patients as compared to healthy participants might be driven by higher motivation of patients, higher ranges for the regulation of dysfunctional brain signals, or a more extensive piloting of clinical experimental paradigms. Due to the large heterogeneity of our dataset, these findings likely generalize across neurofeedback studies, thus providing guidance for designing more efficient neurofeedback studies specifically for improving clinical neurofeedback-based interventions. To facilitate the development of data-driven recommendations for specific design details and subpopulations the field would benefit from stronger engagement in Open Science and data sharing.

We investigated the neural correlates of working memory guided attentional selection of food versus non-food stimuli in young women. Participants were thirty-two women, aged 20.6y (± 0.5) who were presented with a cue (food or non-food item) to hold in working memory. Subsequently, they had to search for a target in a 2-item display where target and distractor stimuli were each flanked by a picture of a food or a non-food item. The behavioural data showed that attention is particularly efficiently drawn to food stimuli when thinking about food. Using fMRI, we found that holding a non-food versus food stimulus in working memory was associated with increased activity in occipital gyrus, fusiform, inferior and superior frontal gyrus. In the posterior cingulum, retrosplenial cortex, a food item that re-appeared in the search array when it was held in memory led to a reduced response, compared to when it did not re-appear. The reverse effect was found for non-food stimuli. The extent of the reappearance effect correlated with the attentional capture of food as measured behaviourally. In conclusion, these results suggest that holding food in mind may bias attention because thinking of food facilitated neuronal responses to sensory input related to food stimuli and because holding food-related information in mind is less taxing on memory.

International audience; This review details the proceedings of a Pennington Biomedical scientific symposium titled, "What Should I Eat and Why? The Environmental, Genetic, and Behavioral Determinants of Food Choice." The symposium was designed to review the literature about energy homeostasis, particularly related to food choice and feeding behaviors, from psychology to physiology. This review discusses the intrinsic determinants of food choice, including biological mechanisms (genetics), peripheral and central signals, brain correlates, and the potential role of the microbiome. This review also address the extrinsic determinants (environment) of food choice within our physical and social environments. Finally, this review reports the current treatment practices for the clinical management of eating-induced overweight and obesity. An improved understanding of these determinants will inform best practices for the clinical treatment and prevention of obesity. Strategies paired with systemic shifts in our public health policies and changes in our "obesogenic" environment will be most effective at attenuating the obesity epidemic.

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large interindividual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pre-training functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pre-training activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning.

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real‐time fMRI neurofeedback studies report large inter‐individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta‐analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no‐feedback runs (i.e., self‐regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain‐based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning., Many real‐time fMRI neurofeedback studies report large inter‐individual differences in learning success, but the factors that cause this vast variability between participants remain unknown. Here, we used a meta‐analytic approach including data from 24 different neurofeedback studies with a total of 401 participants to determine whether levels of activity in target brain regions during pretraining functional localizer or no‐feedback runs could predict neurofeedback learning success. We were not able to identify common brain‐based success predictors across our diverse cohort of studies.

The hypothalamic neurohormone oxytocin decreases food intake via largely unexplored mechanisms. We investigated the central nervous mediation of oxytocin’s hypophagic effect in comparison to its impact on the processing of generalized rewards. Fifteen fasted normal-weight, young men received intranasal oxytocin (24 IU) or placebo before functional magnetic resonance imaging (fMRI) measurements of brain activity during exposure to food stimuli and a monetary incentive delay task (MID). Subsequently, ad-libitum breakfast intake was assessed. Oxytocin compared to placebo increased activity in the ventromedial prefrontal cortex, supplementary motor area, anterior cingulate, and ventrolateral prefrontal cortices in response to high- vs. low-calorie food images in the fasted state, and reduced calorie intake by 12%. During anticipation of monetary rewards, oxytocin compared to placebo augmented striatal, orbitofrontal and insular activity without altering MID performance. We conclude that during the anticipation of generalized rewards, oxytocin stimulates dopaminergic reward-processing circuits. In contrast, oxytocin restrains food intake by enhancing the activity of brain regions that exert cognitive control, while concomitantly increasing the activity of structures that process food reward value. This pattern points towards a specific role of oxytocin in the regulation of eating behaviour in humans that might be of relevance for potential clinical applications.

In the face of the alarming prevalence of obesity and its associated metabolic impairments, it is of high basic and clinical interest to reach a complete understanding of the central nervous pathways that establish metabolic control. In recent years, the hypothalamic neuropeptide oxytocin, which is primarily known for its involvement in psychosocial processes and reproductive behavior, has received increasing attention as a modulator of metabolic function. Oxytocin administration to the brain of normal-weight animals, but also animals with diet-induced or genetically engineered obesity reduces food intake and body weight, and can also increase energy expenditure. Up to now, only a handful of studies in humans have investigated oxytocin's contribution to the regulation of eating behavior. Relying on the intranasal pathway of oxytocin administration, which is a non-invasive strategy to target central nervous oxytocin receptors, these experiments have yielded some promising first results. In normal-weight and obese individuals, intranasal oxytocin acutely limits meal intake and the consumption of palatable snacks. It is still unclear to which extent - or if at all - such metabolic effects of oxytocin in humans are conveyed or modulated by oxytocin's impact on cognitive processes, in particular on psychosocial function. We shortly summarize the current literature on oxytocin's involvement in food intake and metabolic control, ponder potential links to social and cognitive processes, and address future perspectives as well as limitations of oxytocin administration in experimental and clinical contexts.

Obese subjects who achieve weight loss show increased functional connectivity between dorsolateral prefrontal cortex (dlPFC) and ventromedial prefrontal cortex (vmPFC), key areas of executive control and reward processing. We investigated the potential of real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback training to achieve healthier food choices by enhancing self-control of the interplay between these brain areas. We trained eight male individuals with overweight or obesity (age: 31.8±4.4 years, BMI: 29.4±1.4kg/m2) to up-regulate functional connectivity between the dlPFC and the vmPFC by means of a four-day rt-fMRI neurofeedback protocol including, on each day, three training runs comprised of six up-regulation and six passive viewing trials. During the up-regulation runs of the four training days, participants successfully learned to increase functional connectivity between dlPFC and vmPFC. In addition, a trend towards less high-calorie food choices emerged from before to after training, which however was associated with a trend towards increased covertly assessed snack intake. Findings of this proof-of-concept study indicate that overweight and obese participants can increase functional connectivity between brain areas that orchestrate the top-down control of appetite for high-calorie foods. Neurofeedback training might therefore be a useful tool in achieving and maintaining weight loss.

PURPOSE OF REVIEW It is in the brain where the decision is made what and how much to eat. In the last decades neuroimaging research has contributed extensively to new knowledge about appetite control by revealing the underlying brain processes. Interestingly, there is the fast growing idea of using these methods to develop new treatments for obesity and eating disorders. In this review, we summarize the findings of the importance of the use of neuropharmacology and neuroimaging techniques in understanding and modifying appetite control. RECENT FINDINGS Appetite control is a complex interplay between homeostatic, hedonic, and cognitive processes. Administration of the neuropeptides insulin and oxytocin curb food intake and alter brain responses in reward and cognitive control areas. Additionally, these areas can be targeted for neuromodulation or neurofeedback to reduce food cravings and increase self-control to alter food intake. SUMMARY The recent findings reveal the potential of intranasal administration of hormones or modifying appetite control brain networks to reduce food consumption in volunteers with overweight and obesity or individuals with an eating disorder. Although long-term clinical studies are still needed.

After food consumption, the motivation to eat (wanting) decreases and associated brain reward responses change. Wanting-related brain responses and how these are affected by consumption of specific foods are ill documented. Moreover, the predictive value of food-induced brain responses for subsequent consumption has not been assessed. We aimed to determine the effects of consumption of sweet and savory foods on taste activation in the brain and to assess how far taste activation can predict subsequent ad libitum intake. Fifteen healthy men (age: 27 +/- 2 y, BMI: 22.0 +/- 1.5 kg/m(2)) participated in a randomized crossover trial. After a >3-h fast, participants were scanned with the use of functional MR( before and after consumption of a sweet or savory preload (0.35 L fruit or tomato juice) on two occasions. After the scans, the preload juice was consumed ad libitum. During scanning, participants tasted the juices and rated their pleasantness. Striatal taste activation decreased after juice consumption, independent of pleasantness. Sweet and savory taste activation were not differentially affected by consumption. Anterior cingulate taste activation predicted subsequent ad libitum intake of sweet (r = -0.78; P

The intensity of the taste of a food is affected mostly by the amount of sugars (mono- and disaccharides) or salt it contains. To season savory-tasting foods mainly table salt (NaCl) is used and to sweeten foods, sugars like sucrose are used. Foods with highly intense tastes are consumed in smaller amounts. The optimal taste intensity of a food is the intensity at which it is perceived as most pleasant. When taste intensity decreases or increases from optimal, the pleasantness of a food decreases. Here, we investigated the brain representation of sweet and salty taste intensity using functional magnetic resonance imaging. Fifteen subjects visited twice and tasted a range of 4 watery solutions (0-1 M) of either sucrose or NaCl in water. Middle insula activation increased with increasing concentration for both NaCl and sucrose. Despite similar subjective intensity ratings, anterior insula activation by NaCl increased more with concentration than that by sucrose. Amygdala activation increased with increasing NaCl concentration but not sucrose concentration. In conclusion, sweet and salty taste intensity are represented in the middle insula. Amygdala activation is only modulated by saltiness. Further research will need to extrapolate these results from simple solutions to real foods.

Central nervous system control of metabolic function relies on the input of endocrine messengers from the periphery, including the pancreatic hormone insulin and the adipokine leptin. This concept primarily derives from experiments in animals where substances can be directly applied to the brain. A feasible approach to study the impact of peptidergic messengers on brain function in humans is the intranasal (IN) route of administration, which bypasses the blood-brain barrier and delivers neuropeptides to the brain compartment, but induces considerably less, if any, peripheral uptake than other administration modes. Experimental IN insulin administration has been extensively used to delineate the role of brain insulin signaling in the control of energy homeostasis, but also cognitive function in healthy humans. Clinical pilot studies have found beneficial effects of IN insulin in patients with memory deficits, suggesting that the IN delivery of this and other peptides bears some promise for new, selectively brain-targeted pharmaceutical approaches in the treatment of metabolic and cognitive disorders. More recently, experiments relying on the IN delivery of the hypothalamic hormone oxytocin, which is primarily known for its involvement in psychosocial processes, have provided evidence that oxytocin influences metabolic control in humans. The IN administration of leptin has been successfully tested in animal models but remains to be investigated in the human setting. We briefly summarize the literature on the IN administration of insulin, leptin, and oxytocin, with a particular focus on metabolic effects, and address limitations and perspectives of IN neuropeptide administration.

During food consumption the brain integrates multiple interrelated neural and hormonal signals involved in the regulation of food intake. Factors influencing the decision to stop eating include the foods' sensory properties, macronutrient content, and volume, which in turn affect gastric distention and appetite hormone responses. So far, the contributions of gastric distention and oral stimulation by food on brain activation have not been studied. The primary objective of this study was to assess the effect of gastric distention with an intra-gastric load and the additional effect of oral stimulation on brain activity after food administration. Our secondary objective was to study the correlations between hormone responses and appetite-related ratings and brain activation. Fourteen men completed three functional magnetic resonance imaging sessions during which they either received a naso-gastric infusion of water (stomach distention), naso-gastric infusion of chocolate milk (stomach distention + nutrients), or ingested chocolate-milk (stomach distention + nutrients + oral exposure). Appetite ratings and blood parameters were measured at several time points. During gastric infusion, brain activation was observed in the midbrain, amygdala, hypothalamus, and hippocampus for both chocolate milk and water, i.e., irrespective of nutrient content. The thalamus, amygdala, putamen and precuneus were activated more after ingestion than after gastric infusion of chocolate milk, whereas infusion evoked greater activation in the hippocampus and anterior cingulate. Moreover, areas involved in gustation and reward were activated more after oral stimulation. Only insulin responses following naso-gastric infusion of chocolate milk correlated with brain activation, namely in the putamen and insula. In conclusion, we show that normal (oral) food ingestion evokes greater activation than gastric infusion in stomach distention and food intake-related brain areas. This provides neural evidence for the importance of sensory stimulation in the process of satiation. Trial Registration ClinicalTrials.gov NCT01644539.

The brain governs food intake behaviour by integrating many different internal and external state and trait-related signals. Understanding how the decisions to start and to stop eating are made is crucial to our understanding of (maladaptive patterns of) eating behaviour. Here, we aim to (1) review the current state of the field of ‘nutritional neuroscience’ with a focus on the interplay between food-induced brain responses and eating behaviour and (2) highlight research needs and techniques that could be used to address these. The brain responses associated with sensory stimulation (sight, olfaction and taste), gastric distension, gut hormone administration and food consumption are the subject of increasing investigation. Nevertheless, only few studies have examined relations between brain responses and eating behaviour. However, the neural circuits underlying eating behaviour are to a large extent generic, including reward, self-control, learning and decision-making circuitry. These limbic and prefrontal circuits interact with the hypothalamus, a key homeostatic area. Target areas for further elucidating the regulation of food intake are: (eating) habit and food preference formation and modification, the neural correlates of self-control, nutrient sensing and dietary learning, and the regulation of body adiposity. Moreover, to foster significant progress, data from multiple studies need to be integrated. This requires standardisation of (neuroimaging) measures, data sharing and the application and development of existing advanced analysis and modelling techniques to nutritional neuroscience data. In the next 20 years, nutritional neuroscience will have to prove its potential for providing insights that can be used to tackle detrimental eating behaviour.