Alterations in ventral attention network connectivity in individuals with prediabetes.

Objective: Type 2 diabetes (T2D) is associated with aberrant neural functioning; however, the point at which brain function alterations occur in the progression of T2D is unknown. Here, we tested for differences in functional connectivity in adults with prediabetes and healthy individuals. We hypothesized that prediabetes, defined by glycated hemoglobin (HbA1c) 5.7-6.4% would be associated with disruptions in default mode network (DMN) connectivity. Methods: Fourteen brain networks were tested in 88 adults (prediabetes: n = 44; HbA1c = 5.8±0.2%; healthy: n = 44; HbA1c = 4.7±0.2%) matched for sex, age, and BMI. Results: We did not find differences in DMN connectivity between groups. Individuals with prediabetes showed stronger connectivity between the ventral attention network and (1) a visual network (p FWE = 0.0001); (2) a somatosensory network (p FWE = 0.0027). Individuals with healthy HbA1c showed stronger connectivity of the ventral attention network and (1) cingulo-opercular network (p FWE = 0.002); (2) a thalamic-striatal-visual network (p FWE = 0.001). Conclusions: Relative to individuals with prediabetes, those with a healthy HbA1c showed stronger connectivity between brain networks underlying self-control and attention to stimuli. In contrast, those with prediabetes demonstrated stronger connectivity between brain networks associated with sensory and attention to stimuli. While T2D reported contribute to decreased DMN connectivity, prediabetes is characterized by a shift in functional connectivity from a self-control network towards increasing connectivity in sensory network.

The influence of COVID-19-related stress on food motivation.

The COVID-19 pandemic and public health measures to reduce its transmission have increased stress. Stress is associated with alterations in eating behavior which may be partly driven by effects on food-related motivation. To investigate effects of COVID-related stress on food motivation, we recruited adults (N = 429; 272 F, 157 M) to complete an online survey via Amazon MTurk in May 2020. Current COVID-related stress, retrospective pre-COVID stress, and motivation in relation to individualized preferred foods from five categories (sweet snacks, fruit, savory snacks, vegetables, and fast food) were assessed. Food motivation measures included willingness to wait, willingness to expend low effort [finger taps], willingness to expend high effort [jumping jacks], and willingness to pay for hypothetical delivery of the food item. Food motivation for each food type was assessed using a novel instrument designed for brief assessment of multiple aspects of food motivation across multiple food types. Participants were willing to pay the most for fast food followed by sweet snacks, and willing to wait longer for sweet snacks relative to other food types. While fast food and sweets also generated the most willingness to expend high and low effort, willingness to expend low effort for fruit was similar to that for fast food and sweets, and willingness to expend high effort for fruit was comparable to that for fast food. Participants were least willing to pay or expend low effort for vegetables. Higher COVID-related stress levels were associated with willingness to expend more effort and pay more for food items. These data collected during the pandemic demonstrate that highly processed and sweet foods have high motivating value across multiple measures of motivation, and COVID-related stress increases food motivation across food categories. Interventions to mitigate stress and target the link between stress and overeating may help to limit the effects of the COVID-19 pandemic on obesity.

Individual differences in appeal of energy dense foods predicts lower body mass change during adolescence.

Highly energy dense foods are often synonymous with high palatability, excess intake and weight gain. However, food preferences show individual differences. Food preferences are closely related to food intake, which can impact weight change over time. We examined whether the energy density of food images rated as appetizing and unappetizing foods related to baseline BMI and change in BMI over 3-year follow-up (n = 117; 45% Male, Baseline BMI: 21.1 ± 1.9. Participants completed hedonic visual analog scales (-100 to 100) ratings of 103 food images, and reported dietary intake at baseline, and had their height and weight directly measured over 3-year follow-up. Energy density (ED) of the food depicted in each image was calculated. For each participant, food images (kcal/g) were categorized into appetizing (32 images) and unappetizing foods (32 images) based on each individual's hedonic ratings. We observed significant interaction between energy density and hedonic value driven by an inverse relation between unappetizing food energy density and BMI change (p = 0.008). Specifically, participants who rated higher energy dense foods as unappetizing showed less weight gain (ß= -0.83; p = 0.00052). There was no significant relation between the energy density of appetizing foods and weight change (p = 0.67), suggesting that dislike of highly energy dense foods more strongly associates with lower weight gain than preference for low energy dense foods. Post-hoc analyses revealed that individuals with a higher preference for low energy density foods showed less weight gain over 3-years (ß = - 0.007, p = 0.02). Results support the idea that individual hedonic ratings for foods varying in energy density is a determinant of weight change in adolescents and may represent an important intervention target for obesity prevention programs.

Body mass variability is represented by distinct functional connectivity patterns.

Understanding weight-related differences in functional connectivity provides key insight into neurocognitive factors implicated in obesity. Here, we sampled three groups from human connectome project data: 1) 47 pairs of BMI-discordant twins (n = 94; average BMI-discordancy 6.7 ±â€¯3.1 kg/m2), 2) 47 pairs of gender and BMI matched BMI-discordant, unrelated individuals, and 3) 47 pairs of BMI-similar twins, to test for body mass dependent differences in between network functional connectivity. Across BMI discordant samples, three networks appeared to be highly sensitive to weight status; specifically, a network comprised of gustatory processing regions, a visual processing network, and the default mode network (DMN). Further, in the BMI-discordant twin sample, twins with lower BMI had stronger connectivity between striatal/thalamic and prefrontal networks (pFWE = 0.04). We also observed that individuals with a higher BMI than their twin had stronger connectivity between cerebellar and insular networks (pFWE = 0.04). Connectivity patterns observed in the BMI-discordant twin sample were not seen in a BMI-similar sample, providing evidence that the results are specific to BMI discordance. Beyond the involvement of gustatory and visual networks and the DMN, little overlap in results were seen between the two BMI-discordant samples. In concordance with previous findings, we hypothesize that stronger cortical-striatal-thalamic connectivity associated with lower body mass in twins may facilitate increased regulation of hedonically motivated behaviors. In twins with higher body mass, increased cerebellar-insula connectivity may be associated with compromised satiation signaling, an interpretation dovetailing prior research. The lack of overlapping results between the two BMI discordant samples may be a function of higher study design sensitivity in the BMI-discordant twin sample, relative to the more generalizable results in the unrelated sample. These findings demonstrate that distinct connectivity patterns can represent weight variability, adding to mounting evidence that implicates atypical brain functioning with the accumulation and/or maintenance of elevated weight.

Multi-year clinical outcomes of cancers diagnosed following detection by a blood-based multi-cancer early detection (MCED) test.

In the U.S., <20% of cancers are diagnosed by standard-of-care (SoC) screening. Multi-cancer early detection (MCED) tests offer the opportunity to expand cancer screening. Understanding the characteristics and clinical outcomes of MCED-detected cancers is critical to clarifying MCED tests' potential impact. DETECT-A is the first prospective interventional trial of an MCED blood test (CancerSEEK). CancerSEEK, coupled with diagnostic PET-CT, identified cancers including those not detected by SoC screening, the majority of which were localized or regional. We report multi-year outcomes in patients with cancers diagnosed following a positive CancerSEEK test. Nine cancer types were diagnosed in 26 participants whose cancers were first detected by CancerSEEK. Information on cancer diagnoses, treatments, and clinical outcomes was extracted from medical records through November 2022. Data collection occurred a median of 4.4 years (IQR: 4.1-4.6) following study enrollment. Thirteen of 26 (50%) participants were alive and cancer-free [ovarian (4), thyroid (1), uterine (2), breast (1), colorectal (2), and lung (3)]; 7/13 (54%) had cancers without recommended SoC screening modalities. All 8 treated stage I or II participants (8/8, 100%) and 12/14 (86%) surgically-treated participants were alive and cancer-free. Eligibility for surgical treatment was associated with favorable multi-year outcomes (p = 0.0002). Half of participants with MCED-detected cancers were alive and cancer-free after 4.4 years median follow-up. Most were diagnosed with early-stage cancers and were treated surgically. These results suggest that early cancer detection by CancerSEEK may have facilitated curative-intent treatments and associated positive clinical outcomes in some DETECT-A participants.

Outcomes Following a False-Positive Multi-Cancer Early Detection Test: Results from DETECT-A, the First Large, Prospective, Interventional MCED Study.

Guideline recommended standard of care screening is available for four cancer types; most cancer-related deaths are caused by cancers without standard of care screening. DETECT-A is the first prospective interventional trial evaluating a multi-cancer early detection (MCED) blood test (CancerSEEK) in women without a history of cancer, providing the first opportunity to assess the long-term outcomes of individuals with false-positive (FP) MCED results. This prospective analysis of DETECT-A participants with FP results evaluates the performance of an imaging-based diagnostic workflow and examines cancer risk following a FP result. This analysis included all DETECT-A participants with a positive CancerSEEK test and subsequent flourine-18 fluorodeoxyglucose positron emission tomography-IV contrast-enhanced computed tomography (18-F-FDG PET-CT) imaging and clinical workup indicating no evidence of cancer within 1 year of enrollment (n = 98). Medical records, study interactions, and study surveys were used to assess cancer incidence, treatments, and clinical outcomes through August 2023. Ninety-five of 98 participants with a FP result remained cancer-free with a median follow-up of 3.6 years (IQR: 2.5-4.1) from determination of FP status. Three incident cancers were observed over the follow-up period. One bilateral stage IIIC ovarian cancer was diagnosed 1.9 years after determination of FP status; two stage I breast cancers were diagnosed 0.1 and 1.6 years from determination of FP status. The annual incidence rate of cancer during follow-up from FP determination was 1.0% (95% confidence interval, 0.2%-2.8%). Participants with a positive CancerSEEK test who underwent 18-F-FDG PET-CT and clinical workup without cancer findings had low risk for cancer over the following several years. Prevention Relevance: This study provides multiyear clinical outcomes data following a false-positive multi-cancer early detection test for individuals participating in a prospective interventional trial. It provides a preliminary performance assessment of an imaging-based diagnostic workflow following a false-positive multi-cancer early detection test.

Outcomes following a false positive multi-cancer early detection (MCED) test: Results from DETECT-A, the first large, prospective, interventional MCED study.

Guideline recommended standard of care (SoC) screening is available for four cancer types; most cancer-related deaths are caused by cancers without SoC screening. DETECT-A is the first prospective interventional trial evaluating an MCED blood test (CancerSEEK) in women without a history of cancer, providing the first opportunity to assess the long-term outcomes of individuals with false positive (FP) MCED results. This prospective analysis of DETECT-A participants with FP results evaluates the performance of an imaging-based diagnostic workflow and examines cancer risk following a FP result. This analysis included all DETECT-A participants with a positive CancerSEEK test and subsequent flourine-18 fluorodeoxyglucose positron emission tomography-IV contrast enhanced computed tomography (18-F-FDG PET-CT) imaging and clinical workup indicating no evidence of cancer within one year of enrollment (n=98). Medical records, study interactions, and study surveys were used to assess cancer incidence, treatments, and clinical outcomes through August 2023. Ninety-five of 98 participants with a FP result remained cancer-free with a median follow-up of 3.6 years (IQR: 2.5-4.1) from determination of FP status. Three incident cancers were observed over the follow-up period. One bilateral stage IIIC ovarian cancer was diagnosed 1.9 years after determination of FP status; two stage I breast cancers were diagnosed 0.1 and 1.6 years from determination of FP status. The annual incidence rate of cancer during follow-up from FP determination was 1.0% (95% CI: 0.2%-2.8%). Participants with a positive CancerSEEK test who underwent 18-F-FDG PET-CT and clinical workup without cancer findings had low risk for cancer over the following several years.

Correlates of neural adaptation to food cues and taste: the role of obesity risk factors.

Identifying correlates of brain response to food cues and taste provides critical information on individual differences that may influence variability in eating behavior. However, a few studies examine how brain response changes over repeated exposures and the individual factors that are associated with these changes. Using functional magnetic resonance imaging, we examined how brain response to a palatable taste and proceeding cues changed over repeated exposures and how individual differences in weight, familial obesity risk, dietary restraint and reward responsiveness correlate with these changes. In healthy-weight adolescents (n = 154), caudate and posterior cingulate cortex (PCC) response increased with repeated cue presentations, and oral somatosensory cortex and insula response increased with repeated milkshake tastes. The magnitude of increase over exposures in the left PCC to cues was positively associated with body mass index percentile (r = 0.18, P = 0.026) and negatively associated with dietary restraint scores (r = -0.24, P = 0.003). Adolescents with familial obesity risk showed higher cue-evoked caudate response across time, compared to the low-risk group (r = 0.12, P = 0.035). Reward responsiveness positively correlated with right oral somatosensory cortex/insula response to milkshake over time (r = 0.19, P = 0.018). The results show that neural responses to food cues and taste change over time and that individual differences related to weight gain are correlated with these changes.

Paediatric obesity and metabolic syndrome associations with cognition and the brain in youth: Current evidence and future directions.

Obesity and components of the metabolic syndrome (MetS) are associated with differences in brain structure and function and in general and food-related cognition in adults. Here, we review evidence for similar phenomena in children and adolescents, with a focus on the implications of extant research for possible underlying mechanisms and potential interventions for obesity and MetS in youth. Current evidence is limited by a relative reliance on small cross-sectional studies. However, we find that youth with obesity and MetS or MetS components show differences in brain structure, including alterations in grey matter volume and cortical thickness across brain regions subserving reward, cognitive control and other functions, as well as in white matter integrity and volume. Children with obesity and MetS components also show some evidence for hyperresponsivity of food reward regions and hyporesponsivity of cognitive control circuits during food-related tasks, altered brain responses to food tastes, and altered resting-state connectivity including between cognitive control and reward processing networks. Potential mechanisms for these findings include neuroinflammation, impaired vascular reactivity, and effects of diet and obesity on myelination and dopamine function. Future observational research using longitudinal measures, improved sampling strategies and study designs, and rigorous statistical methods, promises to further illuminate dynamic relationships and causal mechanisms. Intervention studies targeted at modifiable biological and behavioural factors associated with paediatric obesity and MetS can further inform mechanisms, as well as test whether brain and behaviour can be altered for beneficial outcomes.

Is obesity in the brain? Parent perceptions of brain influences on obesity.

Neuroimaging studies demonstrate associations of brain structure and function with children's eating behaviour and body weight, and the feasibility of integrating brain measures into obesity risk assessment and intervention is growing. However, little is known about lay perceptions of how the brain influences obesity. We investigated parent perceptions of brain contributions to obesity in three separate studies: 1) a study of mothers of adolescents recruited for neuroimaging research (n = 88), 2) a study of ethnically Chinese parents of 5-13 year olds participating in a parent feeding survey (n = 277), and 3) a study of parents of 3-15 year olds completing an online survey (n = 113). In general, parents believed that brain factors influence obesity, but considered them less influential than behaviours such as diet and exercise. Causal attributions for brain factors were correlated with attributions for genetic factors and biological factors (e.g., metabolism). Parents who perceived their child to be overweight or had a high concern about their child becoming overweight in the future rated brain factors as more important in determining their child's weight and more likely to lessen their child's ability to control their weight. Our results suggest that parents attribute obesity to the brain to a moderate degree, and that education or feedback regarding brain influences on obesity could be a promising obesity intervention component.

Binge Watching during COVID-19: Associations with Stress and Body Weight.

Binge watching is becoming increasingly common and may impact energy balance and body weight. The COVID-19 pandemic has created conditions conducive to binge watching and increased stress. We investigated relationships between COVID-related stress and binge watching behaviors, and potential variation in this relationship by body weight. Adults (n = 466) completed a cross-sectional online survey assessing binge watching behaviors during and before the pandemic, COVID-related stress, and body weight. Participants reported an increase in binge watching frequency from before to during the pandemic (F1,401 = 99.970, p < 0.001), with rates of high binge watching ("3-4 times per week" to "3 or more times per day") increasing from 14.6% to 33.0%. Binge watching episode duration increased from 3.26 ± 1.89 h to 3.92 ± 2.08 h (p < 0.001). The increase in binge watching frequency was greatest in individuals with obesity and high stress (F 4,401 = 4.098, p = 0.003). Participants reporting high stress reported higher frequency of eating while binge watching, as well as higher levels of negative emotional triggers, consequences to binge watching, and lack of control over binge watching (all p < 0.001). Our results show that binge watching increased during the pandemic, with greater increases among individuals reporting higher COVID-related stress, especially those with obesity, and concomitant effects on eating, and highlight a need for interventions to minimize the obesogenic impact of binge watching during the pandemic.

COVID-19 Stress and Food Intake: Protective and Risk Factors for Stress-Related Palatable Food Intake in U.S. Adults.

(1) Background: The coronavirus (COVID-19) pandemic has caused disruptions to what people eat, but the pandemic's impact on diet varies between individuals. The goal of our study was to test whether pandemic-related stress was associated with food intake, and whether relationships between stress and intake were modified by appetitive and cognitive traits. (2) Methods: We cross-sectionally surveyed 428 adults to examine current intake frequency of various food types (sweets/desserts, savory snacks, fast food, fruits, and vegetables), changes to food intake during the pandemic, emotional overeating (EOE), cognitive flexibility (CF), and COVID-19-related stress. Models tested associations of stress, EOE, and CF with food intake frequency and changes to intake. (3) Results: Models demonstrated that the positive relationship between stress and intake of sweets/desserts was stronger with higher EOE, while the positive relationship between stress and intake of chips/savory snacks was weaker with higher CF. Higher EOE was associated with greater risk of increased intake of palatable foods. (4) Conclusions: Findings suggest that emotional overeating may escalate stress-associated intake of high-sugar foods, and cognitive flexibility may attenuate stress-associated intake of high-fat foods. Differences in appetitive and cognitive traits may explain changes to and variability in food intake during COVID-19, and efforts to decrease emotional overeating and encourage cognitive flexibility could help lessen the effect of COVID-19-related stress on energy dense food intake.

Longitudinal Associations Between Taste Sensitivity, Taste Liking, Dietary Intake and BMI in Adolescents.

Taste sensitivity and liking drive food choices and ingestive behaviors from childhood to adulthood, yet their longitudinal association with dietary intake and BMI is largely understudied. Here, we examined the longitudinal relationship between sugar and fat sensitivity, sugar and fat liking, habitual dietary intake, and BMI percentiles in a sample of 105 healthy-weight adolescents (baseline: BMI %tile 57.0 ± 24.3; age 14-16 years) over a 4-year period. Taste sensitivity was assessed via a triangle fat and sweet taste discrimination test. Taste liking were rated on a visual analog scale for four milkshakes that varied in sugar and fat contents (high-fat/high-sugar (HF/HS), low-fat/high-sugar (LF/HS), high-fat/low-sugar (HF/LS), low-fat/low-sugar (LF/LS) milkshakes). A modified version of the reduced Block Food Frequency Questionnaire (BFFQ) was used to assess dietary intake. All measurements were repeated annually. Repeated measures correlations and linear mixed effects models were used to model the associations between the variables. Sugar sensitivity was negatively associated with liking for the LF/HS milkshake over the 4-year period. Low sugar sensitivity at baseline predicted increases in BMI percentile over time, but this association didn't survive a correction for multiple comparisons. Percent daily intake from fat was positively associated with liking for the HF/HS milkshake and negatively associated with liking for the LF/LS milkshake over 4 years. Together, these results demonstrate that lower sensitivity to sweet taste is linked to increased hedonic response to high-sugar foods and increased energy intake from fat seems to condition adolescents to show increased liking for high-fat/high-sugar foods.

Familial Obesity Risk and Current Excess Weight Influence Brain Structure in Adolescents.

OBJECTIVE: Obesity risk transmits from parents to children. Underlying neural mechanisms were investigated in this study by evaluating influences of familial obesity risk defined by maternal obesity and influences of current overweight on three indices of brain structure in adolescents. METHODS: In total, 22 lean adolescents with lean mothers (lean low-risk), 25 lean adolescents with mothers with obesity/overweight (lean high-risk), and 36 adolescents with obesity/overweight underwent structural MRI scans for estimation of regional gray and white matter volume and cortical thickness. RESULTS: The lean high-risk compared with the lean low-risk group demonstrated lower gray and white matter volume and cortical thickness in the postcentral gyrus (somatosensory cortex), lower gray and white matter volume in the opercular cortex (taste cortex), lower gray matter volume and cortical thickness in the anterior cingulate cortex, and lower cortical thickness in the precuneus. Comparisons of the lean and obesity/overweight groups revealed further structural alterations in the postcentral gyrus, posterior cingulate gyrus, and middle temporal gyrus. CONCLUSIONS: Familial obesity risk and current obesity/overweight were associated with overlapping and distinct patterns of brain structure alterations. Longitudinal studies are warranted to investigate whether structural changes associated with familial obesity risk predict future weight trajectories.

Earlier onset of menstruation is related to increased body mass index in adulthood and altered functional correlations between visual, task control and somatosensory brain networks.

Later onset of puberty has been associated with lower body mass index (BMI) in adulthood independent of childhood BMI. However, how the relationship between time of onset of puberty and BMI in adulthood is associated with neurocognitive outcomes is largely unstudied. In the present study, women were sampled from the Human Connectome Project 1200 parcellation, timeseries and netmats1 release (PTN) release. Inclusion criteria were: four (15 minutes) resting state fMRI scans, current measured BMI, self-reported age at onset of menstruation (a proxy of age at onset of puberty) and no endocrine complications (eg, polycystic ovarian syndrome). The effect of age at onset of menstruation, measured BMI at scan date and the interaction of age at onset of menstruation by BMI on brain functional correlation was modelled using fslnets (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLNets) controlling for race and age at scan. Corrected significance was set at a family-wise error probability (pFWE) < 0.05. A final sample of n = 510 (age 29.5 years ± 3.6, BMI at scan 25.9 ± 5.6 and age at onset of menstruation 12.7 ± 1.6 were included. Age at onset of menstruation was negatively associated with BMI at scan (r = - 0.19, P < 0.001). The interaction between age at onset of menstruation and BMI at scan was associated with stronger correlation between a somatosensory and visual network (t = 3.45, pFWE = 0.026) and a visual network and cingulo-opercular task control network (t = 4.74, pFWE = 0.0002). Post-hoc analyses of behavioural/cognitive measures showed no effect of the interaction between BMI and age at onset of menstruation on behavioural/cognitive measures. However, post-hoc analyses of heritability showed adult BMI and the correlation between the visual and somatosensory networks have high heritability. In sum, we report increased correlation between visual, taste-associated and self-control brain regions in women at high BMI with later age at onset of menstruation.

Behavioral and physiological characteristics associated with learning performance on an appetitive probabilistic selection task.

Individuals show meaningful variability in food choices. Choices are affected by individual differences in sensitivity to food reward and punishment, so understanding correlates of response to food reinforcement can help characterize food choices. Here, we examined behavioral and physiological correlates of individual differences in how individuals learn from food reward and punishment, as measured by performance on an appetitive probabilistic selection task that used sweet and bitter tastes as reinforcement. Sensitivity to food reward, sensitivity to food punishment, and overall learning performance were measured in 89 adults. Multivariate linear regressions were used to test if variables including body mass index (BMI), external eating, emotional eating, behavioral inhibition/behavioral activation scales (BIS/BAS), and perceived sensitivity to reward and punishment (SPQ/SRQ) were associated with measures of learning performance. External eating (ß=-.035, p=.019), BIS (ß=-.066, p=.004), and SPQ (ß=.003, p=.023) were associated with overall learning performance. BMI (ß=-.000, p=.012), emotional eating (ß=.055, p=.006), and external eating (ß=-.062, p=.004) were associated with sensitivity to food reward. No variables were associated with sensitivity to food punishment. In post hoc analyses, the interaction of sex and SPQ was associated with overall performance (ß=-.005, p=.025), such that the relationship was positive in women only (ß=.006, p=0.002). Results support that, controlling for key individual characteristics, BMI and susceptibility to food cues are associated with lower sensitivity to food reward, which may affect future food choices and eating behavior.

Network organization during probabilistic learning via taste outcomes.

Reinforcement learning guides food decisions, yet how the brain learns from taste in humans is not fully understood. Existing research examines reinforcement learning from taste using passive condition paradigms, but response-dependent instrumental conditioning better reflects natural eating behavior. Here, we examined brain response during a taste-motivated reinforcement learning task and how measures of task-based network structure were related to behavioral outcomes. During a functional MRI scan, 85 participants completed a probabilistic selection task with feedback via sweet taste or bitter taste. Whole brain response and functional network topology measures, including identification of communities and community segregation, were examined during choice, sweet taste, and bitter taste conditions. Relative to the bitter taste, sweet taste was associated with increased whole brain response in the hippocampus, oral somatosensory cortex, and orbitofrontal cortex. Sweet taste was also related to differential community assignment of the ventromedial prefrontal cortex and ventrolateral prefrontal cortex compared to bitter taste. During choice, increasing segregation of a community containing the amygdala, hippocampus, and right fusiform gyrus was associated with increased sensitivity to punishment on the task's posttest. Further, normal BMI was associated with differential community structure compared to overweight and obese BMI, where high BMI reflected increased connectivity of visual regions. Together, results demonstrate that network topology of learning and memory regions during choice is related to avoiding a bitter taste, and that BMI is associated with increased connectivity of area involved in processing external stimuli. Network organization and topology provide unique insight into individual differences in brain response to instrumental conditioning via taste reinforcers.

The impact of elevated body mass on brain responses during appetitive prediction error in postpartum women.

Repeated exposure to highly palatable foods and elevated weight promote: 1) insensitivity to punishment in striatal regions and, 2) increased willingness to work for food. We hypothesized that BMI would be positively associated with negative prediction error BOLD response in the occipital cortex. Additionally, we postulated that food reinforcement value would be negatively associated with negative prediction error BOLD response in the orbital frontal cortex and amygdala. Postpartum women (n = 47; BMI = 25.5 ±â€¯5.1) were 'trained' to associate specific cues paired to either a highly palatable milkshake or a sub-palatable milkshake. We then violated these cue-taste pairings in 40% of the trials by showing a palatable cue followed by the sub-palatable taste (negative prediction error). Contrary to our hypotheses, during negative prediction error (mismatched cue-taste) versus matched palatable cue-taste, women showed increased BOLD response in the central operculum (pFWE = 0.002; k = 1680; MNI: -57, -7,14) and postcentral gyrus (pFWE = 0.006, k = 1219; MNI: 62, -8,18). When comparing the matched sub-palatable cue-taste to the negative prediction error trials, BOLD response increased in the postcentral gyrus (r = -0.60, pFWE = 0.008), putamen (r = -0.55, pFWE = 0.02), and insula (r = -0.50, pFWE = 0.01). Similarly, viewing the palatable cue vs sub-palatable cue was related to BOLD response in the putamen (pFWE = 0.025, k = 53; MNI: -20, 6, -8) and the insula (pFWE = 0.04, k = 19, MNI:38, -12, -6). Neither BMI at 6-month postpartum nor food reinforcement value was related to BOLD response. The insula and putamen appear to encode for visual food cue processing, and the gustatory and somatosensory cortices appear to encode negative prediction errors. Differential response in the somatosensory cortex to the matched cue-taste pairs to negative prediction error may indicate that a palatable cue may dull aversive qualities in the stimulus.