The effect of hunger state on hypothalamic functional connectivity in response to food cues.

The neural underpinnings of the integration of internal and external cues that reflect nutritional status are poorly understood in humans. The hypothalamus is a key integrative area involved in short- and long-term energy intake regulation. Hence, we examined the effect of hunger state on the hypothalamus network using functional magnetic resonance imaging. In a multicenter study, participants performed a food cue viewing task either fasted or sated on two separate days. We evaluated hypothalamic functional connectivity (FC) using psychophysiological interactions during high versus low caloric food cue viewing in 107 adults (divided into four groups based on age and body mass index [BMI]; age range 24-76 years; BMI range 19.5-41.5 kg/m2 ). In the sated compared to the fasted condition, the hypothalamus showed significantly higher FC with the bilateral caudate, the left insula and parts of the left inferior frontal cortex. Interestingly, we observed a significant interaction between hunger state and BMI group in the dorsolateral prefrontal cortex (DLPFC). Participants with normal weight compared to overweight and obesity showed higher FC between the hypothalamus and DLPFC in the fasted condition. The current study showed that task-based FC of the hypothalamus can be modulated by internal (hunger state) and external cues (i.e., food cues with varying caloric content) with a general enhanced communication in the sated state and obesity-associated differences in hypothalamus to DLPFC communication. This could potentially promote overeating in persons with obesity.

Brain insulin responsiveness is linked to age and peripheral insulin sensitivity.

AIMS: Insulin action in the brain influences cognitive processes, peripheral metabolism and eating behaviour. However, the influence of age and peripheral insulin sensitivity on brain insulin action remains unclear. MATERIALS AND METHODS: We used intranasal administration of insulin and functional magnetic resonance imaging in a randomized, placebo-controlled within-subject design in 110 participants (54 women, body mass index 18-49 kg/m2 , age 21-74 years). Cerebral blood flow was measured before and after nasal spray application to assess brain insulin action. Peripheral insulin sensitivity was assessed by a five-point oral glucose tolerance test. Linear regressions were used to investigate associations between age and peripheral insulin sensitivity with brain insulin action in predefined region of interests (i.e. insulin-sensitive brain regions). RESULTS: We found significant negative associations between age and insulin action in the hippocampus (ß = -0.215; p = .017) and caudate nucleus (ß = -0.184; p = .047); and between peripheral insulin sensitivity and insulin action in the amygdala (ß = -0.190, p = .023). Insulin action in the insular cortex showed an interaction effect between age and peripheral insulin sensitivity (ß = -0.219 p = .005). Furthermore, women showed the strongest negative association between age and hippocampal insulin action, while men showed the strongest associations with peripheral insulin sensitivity and age in reward-related brain regions. CONCLUSION: We could show a region-specific relationship between brain insulin responsiveness, age and peripheral insulin sensitivity. Our findings underline the need to study brain insulin action in both men and women and further substantiate that brain insulin sensitivity is a possible link between systemic metabolism and neurocognitive functions.

Sex differences in central insulin action: Effect of intranasal insulin on neural food cue reactivity in adults with normal weight and overweight.

BACKGROUND/OBJECTIVES: Central insulin action influences cognitive processes, peripheral metabolism, and eating behavior. However, the contribution of obesity and sex on central insulin-mediated neural food cue processing still remains unclear. SUBJECTS/METHODS: In a randomized within-participant design, including two visits, 60 participants (30 women, BMI 18-32 kg/m2, age 21-69 years) underwent a functional MRI task measuring blood oxygen level-dependent (BOLD) signal in response to visual food cues after intranasal insulin or placebo spray administration. Central insulin action was defined as the neural BOLD response to food cues after insulin compared to placebo administration. Afterwards, participants were asked to rate the food cues for desire to eat (i.e., wanting rating). For statistical analyses, participants were grouped according to BMI and sex. RESULTS: Food cue reactivity in the amygdala showed higher BOLD activation in response to central insulin compared to placebo. Furthermore, women with overweight and obesity and men of normal weight showed higher BOLD neural food cue responsivity to central insulin compared to placebo. Higher central insulin action in the insular cortex was associated with better peripheral insulin sensitivity and higher cognitive control. Moreover, central insulin action in the dorsolateral prefrontal cortex (DLPFC) revealed significant sex differences. In response to central insulin compared to placebo, men showed lower DLPFC BOLD activity, whereas women showed higher DLPFC activity in response to highly desired food cues. On behavioral level, central insulin action significantly reduced hunger, whereas the desire to eat, especially for low caloric food cues was significantly higher with central insulin than with placebo. CONCLUSIONS: Obesity and sex influenced the central insulin-mediated neural BOLD activity to visual food cues in brain regions implicated in reward and cognitive control. These findings show that central insulin action regulates food response differentially in men and women, which may have consequences for metabolism and eating behavior.

Predictors of real-time fMRI neurofeedback performance and improvement - A machine learning mega-analysis.

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.

Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity?

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.

Health, pleasure, and fullness: changing mindset affects brain responses and portion size selection in adults with overweight and obesity.

BACKGROUND: Increased portion size is an essential contributor to the current obesity epidemic. The decision of how much to eat before a meal begins (i.e. pre-meal planning), and the attention assigned to this task, plays a vital role in our portion control. OBJECTIVE: We investigated whether pre-meal planning can be influenced by a shift in mindset in individuals with overweight and obesity in order to influence portion size selection and brain activity. DESIGN: We investigated the neural underpinnings of pre-meal planning in 36 adults of different weight groups (BMI < 25 kg/m2 and BMI ≥ 25 kg/m2) by means of functional magnetic resonance imaging. To examine the important role of attentional focus, participants were instructed to focus their mindset on the health effects of food, expected pleasure, or their intention to stay full until dinnertime, while choosing their portion size for lunch. RESULTS: We observed that participants of all weight groups reduced their portion size when adopting a health mindset, which was accompanied by enhanced activation of the self-control network (i.e. left prefrontal cortex). Fullness and pleasure mindsets resulted in contrasting reward responses in individuals with overweight and obesity compared to normal-weight individuals. Under the pleasure mindset, persons with overweight and obesity showed heightened activity in parts of the taste cortex (i.e. right frontal operculum), while the fullness mindset caused reduced activation in the ventral striatum, an important component of the reward system. Moreover, participants with overweight and obesity did not modify their behaviour under the pleasure mindset and selected larger portions than the normal-weight group. CONCLUSIONS: We were able to identify specific brain response patterns as participants made a final choice of a portion size. The results demonstrate that different brain responses and behaviours during pre-meal planning can inform the development of effective strategies for healthy weight management.

Real-time fMRI neurofeedback training to improve eating behavior by self-regulation of the dorsolateral prefrontal cortex: A randomized controlled trial in overweight and obese subjects.

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.

Intermittent theta burst stimulation over right somatosensory larynx cortex enhances vocal pitch-regulation in nonsingers.

While the significance of auditory cortical regions for the development and maintenance of speech motor coordination is well established, the contribution of somatosensory brain areas to learned vocalizations such as singing is less well understood. To address these mechanisms, we applied intermittent theta burst stimulation (iTBS), a facilitatory repetitive transcranial magnetic stimulation (rTMS) protocol, over right somatosensory larynx cortex (S1) and a nonvocal dorsal S1 control area in participants without singing experience. A pitch-matching singing task was performed before and after iTBS to assess corresponding effects on vocal pitch regulation. When participants could monitor auditory feedback from their own voice during singing (Experiment I), no difference in pitch-matching performance was found between iTBS sessions. However, when auditory feedback was masked with noise (Experiment II), only larynx-S1 iTBS enhanced pitch accuracy (50-250 ms after sound onset) and pitch stability (>250 ms after sound onset until the end). Results indicate that somatosensory feedback plays a dominant role in vocal pitch regulation when acoustic feedback is masked. The acoustic changes moreover suggest that right larynx-S1 stimulation affected the preparation and involuntary regulation of vocal pitch accuracy, and that kinesthetic-proprioceptive processes play a role in the voluntary control of pitch stability in nonsingers. Together, these data provide evidence for a causal involvement of right larynx-S1 in vocal pitch regulation during singing.

Just add water: Effects of added gastric distention by water on gastric emptying and satiety related brain activity.

BACKGROUND: Gastric distention contributes to meal termination. There is little research on the neural correlates of gastric distention by food. To date, neural measures have not been obtained concurrently with measurements of gastric distention. OBJECTIVES: 1) To study how offering a small versus a large water load following a standardized nutrient load affects gastric distention over time. 2) To assess associations between satiety experiences and brain activity and the degree of gastric distention. METHOD: 19 healthy males (age 22.2 ±â€¯2.5 y, BMI 21.8 ±â€¯1.5 kg/m2) participated in a randomized crossover study with two treatments: ingestion of a 500-kcal 150-mL liquid meal shake followed by a low (LV, 50 mL) or a high volume (HV, 350 mL) water load. At baseline and three times after ingestion satiety was scored, MRI scans were made to determine total gastric content volume (TGV) and functional MRI scans were made to measure cerebral blood flow (CBF). RESULTS: TGV was significantly higher for HV compared to LV at all time points (p < 0.001) with relative differences between HV and LV of 292 ±â€¯37 mL after ingestion, 182 ±â€¯83 mL at t = 15 min and 62 ±â€¯57 mL at t = 35 min. Hunger decreased (p = 0.023) and fullness increased (p = 0.030) significantly more for HV compared to LV. Ingestion increased CBF in the inferior frontal gyrus and the anterior insula, but there were no differences between treatments. There were no significant correlations between appetite ratings and CBF values. CONCLUSION: Performing concurrent gastric MRI and CBF measurements can be used to investigate neural correlates of gastric distention. Increased distention did not induce significantly greater brain activation. Future research should further examine the role of the inferior frontal gyrus in satiety.

Eating less or more - Mindset induced changes in neural correlates of pre-meal planning.

Obesity develops due to an imbalance between energy intake and expenditure. Besides the decision about what to eat, daily energy intake might be even more dependent on the decision about the portion size to be consumed. For decisions between different foods, attentional focus is considered to play a key role in the choice selection. In the current study, we investigated the attentional modulation of portion size selection during pre-meal planning. We designed a functional magnetic resonance task in which healthy participants were directed to adopt different mindsets while selecting their portion size for lunch. Compared with a free choice condition, participants reduced their portion sizes when considering eating for health or pleasure, which was accompanied by increased activity in left prefrontal cortex and left orbitofrontal cortex, respectively. When planning to be full until dinner, participants selected larger portion sizes and showed a trend for increased activity in left insula. These results provide first evidence that also the cognitive process of pre-meal planning is influenced by the attentional focus at the time of choice, which could provide an opportunity for influencing the control of meal size selection by mindset manipulation.

Volitional regulation of brain responses to food stimuli in overweight and obese subjects: A real-time fMRI feedback study.

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 ± 1.4 kg/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.

Voxel-based morphometry in opera singers: Increased gray-matter volume in right somatosensory and auditory cortices.

In contrast to instrumental musicians, professional singers do not train on a specific instrument but perfect a motor system that has already been extensively trained during speech motor development. Previous functional imaging studies suggest that experience with singing is associated with enhanced somatosensory-based vocal motor control. However, experience-dependent structural plasticity in vocal musicians has rarely been studied. We investigated voxel-based morphometry (VBM) in 27 professional classical singers and compared gray matter volume in regions of the "singing-network" to an age-matched group of 28 healthy volunteers with no special singing experience. We found right hemispheric volume increases in professional singers in ventral primary somatosensory cortex (larynx S1) and adjacent rostral supramarginal gyrus (BA40), as well as in secondary somatosensory (S2) and primary auditory cortices (A1). Moreover, we found that earlier commencement with vocal training correlated with increased gray-matter volume in S1. However, in contrast to studies with instrumental musicians, this correlation only emerged in singers who began their formal training after the age of 14years, when speech motor development has reached its first plateau. Structural data thus confirm and extend previous functional reports suggesting a pivotal role of somatosensation in vocal motor control with increased experience in singing. Results furthermore indicate a sensitive period for developing additional vocal skills after speech motor coordination has matured.

Specific white matter tissue microstructure changes associated with obesity.

Obesity-related structural brain alterations point to a consistent reduction in gray matter with increasing body mass index (BMI) but changes in white matter have proven to be more complex and less conclusive. Hence, more recently diffusion tensor imaging (DTI) has been employed to investigate microstructural changes in white matter structure. Altogether, these studies have mostly shown a loss of white matter integrity with obesity-related factors in several brain regions. However, the variety of these obesity-related factors, including inflammation and dyslipidemia, resulted in competing influences on the DTI indices. To increase the specificity of DTI results, we explored specific brain tissue properties by combining DTI with quantitative multi-parameter mapping in lean, overweight and obese young adults. By means of multi-parameter mapping, white matter structures showed differences in MRI parameters consistent with reduced myelin, increased water and altered iron content with increasing BMI in the superior longitudinal fasciculus, anterior thalamic radiation, internal capsule and corpus callosum. BMI-related changes in DTI parameters revealed mainly alterations in mean and axial diffusivity with increasing BMI in the corticospinal tract, anterior thalamic radiation and superior longitudinal fasciculus. These alterations, including mainly fiber tracts linking limbic structures with prefrontal regions, could potentially promote accelerated aging in obese individuals leading to an increased risk for cognitive decline.

Meta-analysis of real-time fMRI neurofeedback studies using individual participant data: How is brain regulation mediated?

An increasing number of studies using real-time fMRI neurofeedback have demonstrated that successful regulation of neural activity is possible in various brain regions. Since these studies focused on the regulated region(s), little is known about the target-independent mechanisms associated with neurofeedback-guided control of brain activation, i.e. the regulating network. While the specificity of the activation during self-regulation is an important factor, no study has effectively determined the network involved in self-regulation in general. In an effort to detect regions that are responsible for the act of brain regulation, we performed a post-hoc analysis of data involving different target regions based on studies from different research groups. We included twelve suitable studies that examined nine different target regions amounting to a total of 175 subjects and 899 neurofeedback runs. Data analysis included a standard first- (single subject, extracting main paradigm) and second-level (single subject, all runs) general linear model (GLM) analysis of all participants taking into account the individual timing. Subsequently, at the third level, a random effects model GLM included all subjects of all studies, resulting in an overall mixed effects model. Since four of the twelve studies had a reduced field of view (FoV), we repeated the same analysis in a subsample of eight studies that had a well-overlapping FoV to obtain a more global picture of self-regulation. The GLM analysis revealed that the anterior insula as well as the basal ganglia, notably the striatum, were consistently active during the regulation of brain activation across the studies. The anterior insula has been implicated in interoceptive awareness of the body and cognitive control. Basal ganglia are involved in procedural learning, visuomotor integration and other higher cognitive processes including motivation. The larger FoV analysis yielded additional activations in the anterior cingulate cortex, the dorsolateral and ventrolateral prefrontal cortex, the temporo-parietal area and the visual association areas including the temporo-occipital junction. In conclusion, we demonstrate that several key regions, such as the anterior insula and the basal ganglia, are consistently activated during self-regulation in real-time fMRI neurofeedback independent of the targeted region-of-interest. Our results imply that if the real-time fMRI neurofeedback studies target regions of this regulation network, such as the anterior insula, care should be given whether activation changes are related to successful regulation, or related to the regulation process per se. Furthermore, future research is needed to determine how activation within this regulation network is related to neurofeedback success.

Self-regulation of the anterior insula: Reinforcement learning using real-time fMRI neurofeedback.

The anterior insula (AI) plays a key role in affective processing, and insular dysfunction has been noted in several clinical conditions. Real-time functional MRI neurofeedback (rtfMRI-NF) provides a means of helping people learn to self-regulate activation in this brain region. Using the Blood Oxygenated Level Dependant (BOLD) signal from the right AI (RAI) as neurofeedback, we trained participants to increase RAI activation. In contrast, another group of participants was shown 'control' feedback from another brain area. Pre- and post-training affective probes were shown, with subjective ratings and skin conductance response (SCR) measured. We also investigated a reward-related reinforcement learning model of rtfMRI-NF. In contrast to the controls, we hypothesised a positive linear increase in RAI activation in participants shown feedback from this region, alongside increases in valence ratings and SCR to affective probes. Hypothesis-driven analyses showed a significant interaction between the RAI/control neurofeedback groups and the effect of self-regulation. Whole-brain analyses revealed a significant linear increase in RAI activation across four training runs in the group who received feedback from RAI. Increased activation was also observed in the caudate body and thalamus, likely representing feedback-related learning. No positive linear trend was observed in the RAI in the group receiving control feedback, suggesting that these data are not a general effect of cognitive strategy or control feedback. The control group did, however, show diffuse activation across the putamen, caudate and posterior insula which may indicate the representation of false feedback. No significant training-related behavioural differences were observed for valence ratings, or SCR. In addition, correlational analyses based on a reinforcement learning model showed that the dorsal anterior cingulate cortex underpinned learning in both groups. In summary, these data demonstrate that it is possible to regulate the RAI using rtfMRI-NF within one scanning session, and that such reward-related learning is mediated by the dorsal anterior cingulate.

Resting-state functional connectivity of the human hypothalamus.

The hypothalamus is of enormous importance for multiple bodily functions such as energy homeostasis. Especially, rodent studies have greatly contributed to our understanding how specific hypothalamic subregions integrate peripheral and central signals into the brain to control food intake. In humans, however, the neural circuitry of the hypothalamus, with its different subregions, has not been delineated. Hence, the aim of this study was to map the hypothalamus network using resting-state functional connectivity (FC) analyses from the medial hypothalamus (MH) and lateral hypothalamus (LH) in healthy normal-weight adults (n = 49). Furthermore, in a separate sample, we examined differences within the LH and MH networks between healthy normal-weight (n = 25) versus overweight/obese adults (n = 23). FC patterns from the LH and MH revealed significant connections to the striatum, thalamus, brainstem, orbitofrontal cortex, middle and posterior cingulum and temporal brain regions. However, our analysis revealed subtler distinctions within hypothalamic subregions. The LH was functionally stronger connected to the dorsal striatum, anterior cingulum, and frontal operculum, while the MH showed stronger functional connections to the nucleus accumbens and medial orbitofrontal cortex. Furthermore, overweight/obese participants revealed heightened FC in the orbitofrontal cortex and nucleus accumbens within the MH network. Our results indicate that the MH and LH network are tapped into different parts of the dopaminergic circuitry of the brain, potentially modulating food reward based on the functional connections to the ventral and dorsal striatum, respectively. In obese adults, FC changes were observed in the MH network.

Differential effect of glucose ingestion on the neural processing of food stimuli in lean and overweight adults.

Eating behavior is crucial in the development of obesity and Type 2 diabetes. To further investigate its regulation, we studied the effects of glucose versus water ingestion on the neural processing of visual high and low caloric food cues in 12 lean and 12 overweight subjects by functional magnetic resonance imaging. We found body weight to substantially impact the brain's response to visual food cues after glucose versus water ingestion. Specifically, there was a significant interaction between body weight, condition (water versus glucose), and caloric content of food cues. Although overweight subjects showed a generalized reduced response to food objects in the fusiform gyrus and precuneus, the lean group showed a differential pattern to high versus low caloric foods depending on glucose versus water ingestion. Furthermore, we observed plasma insulin and glucose associated effects. The hypothalamic response to high caloric food cues negatively correlated with changes in blood glucose 30 min after glucose ingestion, while especially brain regions in the prefrontal cortex showed a significant negative relationship with increases in plasma insulin 120 min after glucose ingestion. We conclude that the postprandial neural processing of food cues is highly influenced by body weight especially in visual areas, potentially altering visual attention to food. Furthermore, our results underline that insulin markedly influences prefrontal activity to high caloric food cues after a meal, indicating that postprandial hormones may be potential players in modulating executive control.

Functional network connectivity underlying food processing: disturbed salience and visual processing in overweight and obese adults.

In order to adequately explore the neurobiological basis of eating behavior of humans and their changes with body weight, interactions between brain areas or networks need to be investigated. In the current functional magnetic resonance imaging study, we examined the modulating effects of stimulus category (food vs. nonfood), caloric content of food, and body weight on the time course and functional connectivity of 5 brain networks by means of independent component analysis in healthy lean and overweight/obese adults. These functional networks included motor sensory, default-mode, extrastriate visual, temporal visual association, and salience networks. We found an extensive modulation elicited by food stimuli in the 2 visual and salience networks, with a dissociable pattern in the time course and functional connectivity between lean and overweight/obese subjects. Specifically, only in lean subjects, the temporal visual association network was modulated by the stimulus category and the salience network by caloric content, whereas overweight and obese subjects showed a generalized augmented response in the salience network. Furthermore, overweight/obese subjects showed changes in functional connectivity in networks important for object recognition, motivational salience, and executive control. These alterations could potentially lead to top-down deficiencies driving the overconsumption of food in the obese population.

Exposure to gestational diabetes mellitus in utero impacts hippocampal functional connectivity in response to food cues in children.

Objectives: Intrauterine exposure to gestational diabetes mellitus (GDM) increases the risk of obesity in the offspring, but little is known about the underlying neural mechanisms. The hippocampus is crucial for food intake regulation and is vulnerable to the effects of obesity. The purpose of the study was to investigate whether GDM exposure affects hippocampal functional connectivity during exposure to food cues using functional magnetic resonance imaging. Methods: Participants were 90 children age 7-11 years (53 females) who underwent an fMRI-based visual food cue task in the fasted state. Hippocampal functional connectivity (FC) was examined using generalized psychophysiological interaction in response to high-calorie food versus non-food cues. Food-cue induced hippocampal FC was compared between children with and without GDM exposure, while controlling for possible confounding effects of age, sex and waist-to-hip ratio. Results: Children with GDM exposure exhibited stronger hippocampal FC to the insula and striatum (i.e., putamen, pallidum and nucleus accumbens) compared to unexposed children, while viewing high caloric food cues. Conclusions: Intrauterine exposure to GDM was associated with higher food-cue induced hippocampal FC to reward processing regions. Future studies with longitudinal measurements are needed to clarify whether increased hippocampal FC to reward processing regions may raise the risk of the development of metabolic diseases later in life.

Influence of insulin sensitivity on food cue evoked functional brain connectivity in children.

Objective: Insulin resistance during childhood is a risk factor for developing type 2 diabetes and other health problems later in life. Studies in adults have shown that insulin resistance affects regional and network activity in the brain which are vital for behavior, e.g. ingestion and metabolic control. To date, no study has investigated whether brain responses to food cues in children are associated with peripheral insulin sensitivity. Methods: We included 53 children (36 girls) between the age of 7-11 years, who underwent an oral Glucose Tolerance Test (oGTT) to estimate peripheral insulin sensitivity (ISI). Brain responses were measured using functional magnetic resonance imaging (fMRI) before and after glucose ingestion. We compared food-cue task-based activity and functional connectivity (FC) between children with low and high ISI, adjusted for age and BMIz. Results: Independent of prandial state (i.e., glucose ingestion), children with lower ISI showed higher FC between the anterior insula and caudate and lower FC between the posterior insula and mid temporal cortex than children with higher ISI. Sex differences were found based on prandial state and peripheral insulin sensitivity in the insular FC. No differences were found on whole-brain food-cue reactivity. Conclusions: Children with low peripheral insulin sensitivity showed differences in food cue evoked response particularly in insula functional connectivity. These differences might influence eating behavior and future risk of developing diabetes.