The Cerebellar Response to Visual Portion Size Cues Is Associated with the Portion Size Effect in Children.

The neural mechanisms underlying susceptibility to eating more in response to large portions (i.e., the portion size effect) remain unclear. Thus, the present study examined how neural responses to portion size relate to changes in weight and energy consumed as portions increase. Associations were examined across brain regions traditionally implicated in appetite control (i.e., an appetitive network) as well as the cerebellum, which has recently been implicated in appetite-related processes. Children without obesity (i.e., BMI-for-age-and-sex percentile < 90; N = 63; 55% female) viewed images of larger and smaller portions of food during fMRI and, in separate sessions, ate four meals that varied in portion size. Individual-level linear and quadratic associations between intake (kcal, grams) and portion size (i.e., portion size slopes) were estimated. The response to portion size in cerebellar lobules IV-VI was associated with the quadratic portion size slope estimated from gram intake; a greater response to images depicting smaller compared to larger portions was associated with steeper increases in intake with increasing portion sizes. Within the appetitive network, neural responses were not associated with portion size slopes. A decreased cerebellar response to larger amounts of food may increase children's susceptibility to overeating when excessively large portions are served.

Does 'portion size' matter? Brain responses to food and non-food cues presented in varying amounts.

Larger portions of food elicit greater intake than smaller portions of food, particularly when foods are high in energy density (kcal/g; ED). The neural mechanisms underlying this effect remain unclear. The present study used fMRI to assess brain activation to food (higher-ED, lower-ED) and non-food (office supplies) images presented in larger and smaller (i.e., age-appropriate) amounts in 61, 7-8-year-olds (29 male, 32 female) without obesity. Larger amounts of food increased activation in bilateral visual and right parahippocampal areas compared to smaller amounts; greater activation to food amount (larger > smaller) in this cluster was associated with smaller increases in food intake as portions increased. Activation to amount (larger > smaller) was stronger for food than office supplies in primary and secondary visual areas, but, for office supplies only, extended into bilateral parahippocampus, inferior parietal cortex, and additional visual areas (e.g., V7). Activation was greater for higher-vs. lower-ED food images in ventromedial prefrontal cortex for both larger and smaller amounts of food; however, this activation extended into left lateral orbital frontal cortex for smaller amounts only. Activation to food cues did not differ by familial risk for obesity. These results highlight potentially distinct neural pathways for encoding food energy content and quantity.

Poorer inhibitory control was related to greater food intake across meals varying in portion size: A randomized crossover trial.

Individuals eat more food when larger portions are served, and this portion size effect could be influenced by inhibitory control (the ability to suppress an automatic response). Inhibitory control may also relate to obesogenic meal behaviors such as eating faster, taking larger bites, and frequent switching between meal components (such as bites of food and sips of water). In a randomized crossover design, 44 adults ate lunch four times in the laboratory. Lunch consisted of a pasta dish that was varied in portion size (400, 500, 600, or 700 g) along with 700 g of water. Meals were video-recorded to assess meal duration and bite and sip counts, which were used to determine mean eating rate (g/min), mean bite size (g/bite), and number of switches between bites and sips. Participants completed a food-specific stop-signal task, which was used to calculate Stop-Signal Reaction Time (SSRT). Across participants, SSRT values ranged from 143 to 306 msec, where greater SSRT indicates poorer inhibitory control. As expected, serving larger portions increased meal intake (p < 0.0001); compared to the smallest portion, intake of the largest increased by 121 ± 17 g (mean ± SEM). SSRT did not moderate the portion size effect (p = 0.34), but individuals with poorer inhibitory control ate more across all meals: 24 ± 11 g for each one SD unit increase in SSRT (p = 0.035). SSRT was not related to eating rate or bite size (both p > 0.13), but poorer inhibitory control predicted greater switching between bites and sips, such that 1.5 ± 0.7 more switches were made during meals for each one SD unit increase in SSRT (p = 0.03). These findings indicate that inhibitory control can contribute to overconsumption across meals varying in portion size, potentially in part by promoting switching behavior.

Children at high familial risk for obesity show executive functioning deficits prior to development of excess weight status.

OBJECTIVE: The objective of this study was to determine whether children with healthy weight who vary by familial risk for obesity differ in executive functioning. METHODS: Children (age 7-8 years) without obesity (n = 93, 52% male) who differed by familial risk for obesity (based on maternal weight status) completed go/no-go and stop-signal tasks to assess inhibitory control and an N-back task to assess working memory. Dual energy x-ray absorptiometry measured adiposity. Linear and mixed-effect models assessed unique effects and relative importance analysis-quantified relative effects of familial risk and percent body fat. RESULTS: Children at high compared with low familial risk showed worse inhibitory control; however, child adiposity was not associated with inhibitory control. Both high familial risk and greater child adiposity were associated with worse N-back performance when cognitive demand was high (2-back), but not low (0- and 1-back). The relative effect of familial risk on executive functioning was 2.7 to 16 times greater than the relative effect of percent body fat. CONCLUSIONS: These findings provide initial evidence that deficits in executive functioning may precede the development of obesity in children at high familial risk for this disease. Additional family risk studies are needed to elucidate the pathways through which maternal obesity influences child executive functioning and risk for obesity.

Inter-individual differences in children's short-term energy compensation: a systematic review and meta-analysis.

BACKGROUND: The ability to regulate energy intake is often assessed using a preloading paradigm to measure short-term energy compensation. In children, large variability exists with this paradigm both within- and across- studies and is poorly understood. OBJECTIVES: This systematic review and meta-analysis aimed to better understand factors contributing to variability in children's energy compensation. We tested 1) whether children demonstrated "good" energy compensation, defined as adjusting meal intake commensurate with preload intake and 2) differences in children's energy compensation by child age, sex, and weight status (assessed both continuously and categorically). METHODS: Standard guidelines for systematic review were followed to search PubMed, PsychInfo, and Web of Science. Data on study design (preload form, preload-to-meal interval, preload energy difference, study setting) and participant characteristics (sex, age, weight status) were extracted from 29 experiments meeting inclusion criteria, and 13 were included in meta-analyses. COMPx (energy compensation index), a linear transformation comparing food intake following a high- vs. low-energy preload, was the outcome. Hedge's g was calculated, and random intercept-only models tested associations between COMPx and sex, age, and weight status. RESULTS: The systematic review revealed mixed results regarding children's energy compensation and the role of inter-individual differences. Meta-analytic models revealed that children undercompensated (overate) for preload energy (ß = -0.38; P = 0.008). Sex (ß = 0.11; P = 0.76), age (ß = 0.03; P = 0.75), and weight (assessed continuously; ß = -0.07, P = 0.37) were not related to compensation. Children with overweight/obesity (assessed categorically) undercompensated more than children with healthy weight (ß = 0.18; P = 0.04). CONCLUSIONS: The systematic review highlighted wide variability across studies, while the meta-analysis demonstrated differences in COMPx by child weight status but not by age or sex. Standardizing protocols across studies is recommended, along with designing adequately powered studies aiming to test inter-individual differences a priori. Alternative approaches to the use of COMPx are recommended to allow better characterization of children's energy compensation ability. This study was registered at PROSPERO as CRD42020197748.

Switching between foods: A potential behavioral phenotype of hedonic hunger and increased obesity risk in children.

CONTEXT: Reward-based eating is a trait that increases risk for eating in the absence of hunger (EAH) and obesity. Eating behaviors such as switching more frequently between different foods may increase intake during EAH by delaying the onset of sensory-specific satiation (SSS); however, this question has not been empirically tested. OBJECTIVES: 1) Test whether switching between foods mediates the relationship between reward-based eating and EAH intake. 2) Test whether switching between foods during EAH moderates the relationship between reward-based eating and weight status. METHODS: Data were analyzed from a study assessing decision-making in children (n = 63 children; 9.4 ± 1.4 years, 77.0 ± 22.4 BMI%tile). Reward-based eating was quantified using the Children's Eating Behaviour Questionnaire. EAH was assessed as the amount of palatable food consumed following ad libitum consumption of a standard meal. Videos of eating behavior were coded for eating time, number of different foods consumed, and food switches. Ordinary least squares regressions were conducted to test hypotheses. RESULTS: Switching was positively associated with EAH intake for both kcal (p < 0.01) and grams (p < 0.01) such that each additional switch was associated with an increased intake of 17.0 kcal or 3.5 gs. Switching mediated the relationship between reward-based eating and EAH (p < 0.01) such that more frequent switching fully accounted for the positive association between reward-based eating and EAH (ps < 0.01). While reward-based eating was also positively associated with weight status (p < 0.01), this association was moderated by food switching (p < 0.01) such that the relationship was stronger for children who switch more frequently (p < 0.01). CONCLUSIONS: Frequent switching between foods was positively associated with EAH intake and mediated the relationship between reward-based eating and EAH. Moreover, reward-based eating was more strongly related to weight status in children who switched more frequently. Thus, food switching may contribute to overconsumption and be an important behavioral indicator of increased obesity risk in children. Studies across multiple meals and contexts will help determine if switching is a reliable behavioral phenotype.

Validation of computational models to characterize cumulative intake curves from video-coded meals.

Introduction: Observational coding of eating behaviors (e.g., bites, eating rate) captures behavioral characteristics but is limited in its ability to capture dynamic patterns (e.g., temporal changes) across a meal. While the Universal Eating Monitor captures dynamic patterns of eating through cumulative intake curves, it is not commonly used in children due to strict behavioral protocols. Therefore, the objective of this study was to test the ability of computational models to characterize cumulative intake curves from video-coded meals without the use of continuous meal weight measurement. Methods: Cumulative intake curves were estimated using Kisslieff's Quadratic model and Thomas's logistic ordinary differential equation (LODE) model. To test if cumulative intake curves could be characterized from video-coded meals, three different types of data were simulated: (1) Constant Bite: simplified cumulative intake data; (2) Variable Bite: continuously measured meal weight data; and (3) Bite Measurement Error: video-coded meals that require the use of average bite size rather than measured bite size. Results: Performance did not differ by condition, which was assessed by examining model parameter recovery, goodness of fit, and prediction error. Therefore, the additional error incurred by using average bite size as one would with video-coded meals did not impact the ability to accurately estimate cumulative intake curves. While the Quadratic and LODE models were comparable in their ability to characterize cumulative intake curves, the LODE model parameters were more distinct than the Quadradic model. Greater distinctness suggests the LODE model may be more sensitive to individual differences in cumulative intake curves. Discussion: Characterizing cumulative intake curves from video-coded meals expands our ability to capture dynamic patterns of eating behaviors in populations that are less amenable to strict protocols such as children and individuals with disordered eating. This will improve our ability to identify patterns of eating behavior associated with overconsumption and provide new opportunities for treatment.

Children with lower ratings of executive functions have a greater response to the portion size effect.

Deficits in executive functions (EFs), a set of cognitive processes related to self-regulation, are associated with the development of obesity. Prior studies from our group showed that lower food-cue related activation in brain regions implicated in self-regulation was related to a larger portion size effect. We tested the hypothesis that lower EFs in children would be positively related to the portion size effect. Healthy weight children aged 7-8 y (n = 88), who varied by maternal obesity status, participated in a prospective study. At baseline, the parent primarily in charge of feeding completed the Behavior Rating Inventory of Executive Function (BRIEF2) to assess child EFs, including Behavioral (BRI), Emotional (ERI), and Cognitive (CRI) indices. At 4 baseline sessions, children consumed meals in which the portion sizes of foods (pasta, chicken nuggets, broccoli, and grapes) varied by visit (total meal weight of 769, 1011, 1256, or 1492g). Intake increased with increasing portions in a linear trajectory (p < 0.001). EFs moderated the portion size effect such that lower BRI (p = 0.003) and ERI (p = 0.006) were associated with steeper increases in intake as portions increased. As amount of food increased, children in the lowest functioning tertiles for BRI and ERI increased intake by 35% and 36%, respectively, compared to children in the higher tertiles. Increases in intake among children with lower EFs were for higher- but not lower-energy-dense foods. Thus, in healthy weight children who varied by obesity risk, lower parentally reported EFs were associated with a larger portion size effect, and these results were independent of child and parent weight status. Therefore, EFs may be target behaviors that could be strengthened to help children moderate excess intake in response to large portions of energy-dense foods.

Loss of control eating in children is associated with altered cortical and subcortical brain structure.

Introduction: Loss of control (LOC) eating is the perceived inability to control how much is eaten, regardless of actual amount consumed. Childhood LOC-eating is a risk factor for the development of binge-eating disorder (BED), but its neurobiological basis is poorly understood. Studies in children with BED have shown both increased gray matter volume in regions related to top-down cognitive control (e.g., dorsolateral prefrontal cortex) and reward-related decision making (e.g., orbital frontal cortex) relative to healthy controls. However, no studies have examined brain structure in children with LOC-eating. To identify potential neurobiological precursors of BED, we conducted secondary analysis of five studies that conducted T1 MPRAGE scans. Methods: A total of 143, 7-12-year-old children (M = 8.9 years, 70 boys) were included in the study, 26% of which (n = 37) reported LOC-eating (semi-structured interview). Age, sex, and obesity status did not differ by LOC-eating. Differences between children with and without LOC were examined for gray matter volume, cortical thickness, gyrification, sulci depth, and cortical complexity after adjusting for age, sex, total intercranial volume, weight status, and study. Results: Children with LOC, relative to those without, had greater gray matter volume in right orbital frontal cortex but lower gray matter volume in right parahippocampal gyrus, left CA4/dentate gyrus, and left cerebellar lobule VI. While there were no differences in cortical thickness or gyrification, children with LOC-eating had great sulci depth in left anterior cingulate cortex and cuneus and greater cortical complexity in right insular cortex. Discussion: Together, this indicates that children with LOC-eating have structural differences in regions related to cognitive control, reward-related decision-making, and regulation of eating behaviors.

The role of reinforcement learning and value-based decision-making frameworks in understanding food choice and eating behaviors.

The obesogenic food environment includes easy access to highly-palatable, energy-dense, "ultra-processed" foods that are heavily marketed to consumers; therefore, it is critical to understand the neurocognitive processes the underlie overeating in response to environmental food-cues (e.g., food images, food branding/advertisements). Eating habits are learned through reinforcement, which is the process through which environmental food cues become valued and influence behavior. This process is supported by multiple behavioral control systems (e.g., Pavlovian, Habitual, Goal-Directed). Therefore, using neurocognitive frameworks for reinforcement learning and value-based decision-making can improve our understanding of food-choice and eating behaviors. Specifically, the role of reinforcement learning in eating behaviors was considered using the frameworks of (1) Sign-versus Goal-Tracking Phenotypes; (2) Model-Free versus Model-Based; and (3) the Utility or Value-Based Model. The sign-and goal-tracking phenotypes may contribute a mechanistic insight on the role of food-cue incentive salience in two prevailing models of overconsumption-the Extended Behavioral Susceptibility Theory and the Reactivity to Embedded Food Cues in Advertising Model. Similarly, the model-free versus model-based framework may contribute insight to the Extended Behavioral Susceptibility Theory and the Healthy Food Promotion Model. Finally, the value-based model provides a framework for understanding how all three learning systems are integrated to influence food choice. Together, these frameworks can provide mechanistic insight to existing models of food choice and overconsumption and may contribute to the development of future prevention and treatment efforts.

Heterogeneity in PFC-amygdala connectivity in middle childhood, and concurrent interrelations with inhibitory control and anxiety symptoms.

The prefrontal cortex (PFC) is a key brain area in considering adaptive regulatory behaviors. This includes regulatory projections to regions of the limbic system such as the amygdala, where the nature of functional connections may confer lower risk for anxiety disorders. The PFC is also associated with behaviors like executive functioning. Inhibitory control is a behavior encompassed by executive functioning and is generally viewed favorably for adaptive socioemotional development. Yet, some research suggests that high levels of inhibitory control may actually be a risk factor for some maladaptive developmental outcomes, like anxiety disorders. In a sample of 51 children ranging from 7 to 9 years old, we examined resting state functional connectivity between regions of the PFC and the amygdala. We used Subgrouping Group Iterative Multiple Model Estimation (S-GIMME) to identify and characterize data-driven subgroups of individuals with similar networks of connectivity between these brain regions. Generated subgroups were collapsed into children characterized by the presence or absence of recovered connections between the PFC and amygdala. For subsets of children with available data (N = 38-44), we then tested whether inhibitory control, as measured by a stop signal task, moderated the relation between these subgroups and child-reported anxiety symptoms. We found an inverse relation between stop-signal reaction times and reported count of anxiety symptoms when covarying for connectivity group, suggesting that greater inhibitory control was actually related to greater anxiety symptoms, but only when accounting for patterns of PFC-amygdala connectivity. These data suggest that there is a great deal of heterogeneity in the nature of functional connections between the PFC and amygdala during this stage of development. The findings also provide support for the notion of high levels of inhibitory control as a risk factor for anxiety, but trait-level biopsychosocial factors may be important to consider in assessing the nature of risk.

Influence of exclusive breastfeeding on hippocampal structure, satiety responsiveness, and weight status.

Longer exclusive breastfeeding duration has been associated with differences in neural development, better satiety responsiveness, and decreased risk for childhood obesity. Given hippocampus sensitivity to diet and potential role in the integration of satiety signals, hippocampus may play a role in these relationships. We conducted a secondary analysis of 149, 7-11-year-olds (73 males) who participated in one of five studies that assessed neural responses to food cues. Hippocampal grey matter volume was extracted from structural scans using CAT12, weight status was assessed using age- and sex-adjusted body mass index (%BMIp85 ), and parents reported exclusive breastfeeding duration and satiety responsiveness (Children's Eating Behaviour Questionnaire). Separate path models for left and right hippocampus tested: (1) the direct effect of exclusive breastfeeding on satiety responsiveness and its indirect effect through hippocampal grey matter volume; (2) the direct effect of hippocampal grey matter volume on %BMIp85 and its indirect effect through satiety responsiveness. %BMIp85 was adjusted for maternal education, yearly income, and premature birth while hippocampal grey matter volume was adjusted for total intercranial volume, age, and study from which data were extracted. Longer exclusive breastfeeding duration was associated with greater bilateral hippocampal grey matter volumes. In addition, better satiety responsiveness and greater left hippocampal grey matter volume were both associated with lower %BMIp85 . However, hippocampal grey matter volumes were not associated with satiety responsiveness. Although no relationship was found between breastfeeding and child weight status, these results highlight the potential impact of exclusive breastfeeding duration on the hippocampal structure.

Child meal microstructure and eating behaviors: A systematic review.

Observational coding of children's eating behaviors and meal microstructure (e.g., bites, chews) provides an opportunity to assess complex eating styles that may relate to individual differences in energy intake and weight status. Across studies, however, similar terms are often defined differently, which complicates the interpretation and replication of coding protocols. Therefore, this study aimed to compile methods of coding meal microstructure in children. To limit bias and ensure a comprehensive review, a systematic search was conducted in January 2021 across three databases (PubMed, PsychInfo, Web of Science) resulting in 46 studies that coded at least one meal-related behavior in healthy children (i.e., no medical/psychological disorders) who were able to self-feed (i.e., no spoon-, breast-, or bottle-feeding). While the majority of studies had good interrater reliability, the details reported about study foods and the clarity of the definitions used for behavioral coding varied considerably. In addition to reported microstructure behaviors, a non-exhaustive review of individual differences was included. While few studies reported individual differences related to age and sex, there was a larger literature related to weight status that provided evidence for an 'obesogenic' style of eating characterized by larger Bites, faster Eating and Bite Rates, and shorter Meal Durations. However, some studies may not have been optimally designed or powered to detect individual differences because they did not set out a priori to examine them. Based on this systematic review, best practices for the field are recommended and include reporting more details about foods served and coded eating behaviors to improve reproducibility. These suggestions will improve the ability to examine patterns of individual differences across studies, which may help identify novel targets for intervention.

Decision-Making Processes Related to Perseveration Are Indirectly Associated With Weight Status in Children Through Laboratory-Assessed Energy Intake.

Decision-making contributes to what and how much we consume, and deficits in decision-making have been associated with increased weight status in children. Nevertheless, the relationships between cognitive and affective processes underlying decision-making (i.e., decision-making processes) and laboratory food intake are unclear. We used data from a four-session, within-subjects laboratory study to investigate the relationships between decision-making processes, food intake, and weight status in 70 children 7-to-11-years-old. Decision-making was assessed with the Hungry Donkey Task (HDT), a child-friendly task where children make selections with unknown reward outcomes. Food intake was measured with three paradigms: (1) a standard ad libitum meal, (2) an eating in the absence of hunger (EAH) protocol, and (3) a palatable buffet meal. Individual differences related to decision-making processes during the HDT were quantified with a reinforcement learning model. Path analyses were used to test whether decision-making processes that contribute to children's (a) expected value of a choice and (b) tendency to perseverate (i.e., repeatedly make the same choice) were indirectly associated with weight status through their effects on intake (kcal). Results revealed that increases in the tendency to perseverate after a gain outcome were positively associated with intake at all three paradigms and indirectly associated with higher weight status through intake at both the standard and buffet meals. Increases in the tendency to perseverate after a loss outcome were positively associated with EAH, but only in children whose tendency to perseverate persistedacross trials. Results suggest that decision-making processes that shape children's tendencies to repeat a behavior (i.e., perseverate) are related to laboratory energy intake across multiple eating paradigms. Children who are more likely to repeat a choice after a positive outcome have a tendency to eat more at laboratory meals. If this generalizes to contexts outside the laboratory, these children may be susceptible to obesity. By using a reinforcement learning model not previously applied to the study of eating behaviors, this study elucidated potential determinants of excess energy intake in children, which may be useful for the development of childhood obesity interventions.

Effects of severe obesity and sleeve gastrectomy on cortical thickness in adolescents.

OBJECTIVE: Neurocognitive differences in pediatric obesity may be underpinned by cortical structural alterations. Differences in cortical thickness associated with severe obesity were examined, and preliminary evidence was sought for changes following vertical sleeve gastrectomy (VSG). METHODS: A total of 18 adolescents with severe obesity (OB) and 17 without obesity (nOB), aged 14 to 21, underwent T1-weighted structural magnetic resonance imaging. A subset was scanned twice 5 months apart to compare cortical thickness following VSG (n = 6) with two control groups: wait-listed (n = 9) and nOB (n = 12). RESULTS: At baseline, OB had a thinner cortex than nOB in motor and superior parietal cortices. At follow-up, VSG adolescents lost weight, the wait-listed group gained weight, and nOB did not change. Group × Time interactions indicated that VSG had cortical thinning in orbitofrontal, primary sensorimotor, superior, and middle temporal cortices and thickening in lingual, fusiform, and lateral occipital cortices. Wait-listed and nOB groups largely did not change. CONCLUSIONS: Severe obesity is associated with a thinner cortex in motor and attentional function-associated regions. VSG resulted in cortical thinning in reward valuation, sensory, and perceptual regions and thickening in visual regions. Surgery-related changes in regions distinct from those associated with obesity suggest compensation, rather than normalization. These results provide preliminary evidence supporting structural neural alterations following sleeve gastrectomy.

Using association rules mining to characterize loss of control eating in childhood.

Childhood loss of control (LOC)-eating, the perceived inability to stop or control eating, is associated with increased risk for binge-eating disorder and obesity. However, the correlates of LOC-eating in childhood remain unclear. A secondary analysis of 177, 7-12-year-old children from five laboratory feeding studies was performed to investigate potential family (e.g., frequency of meals together, feeding practices), parental (e.g., education, weight status), and child (e.g., weight status, appetite traits) correlates of LOC-eating. Association rules mining (ARM1), a data-driven approach, was used to examine all characteristics that were common across studies to identify which were associated with LOC-eating. Results showed LOC-eating was characterized by a combination of child appetitive behaviors and parental feeding practices. In particular, LOC-eating was associated with low parental pressure to eat in combination with a high propensity to want to eat all the time and frequent refusal or dislike of novel foods. This pattern of both food approach (i.e., wanting to eat all the time) and avoidant behaviors (i.e., food fussiness) highlights the need for more research to characterize the complex patterns of appetitive traits associated with LOC-eating. In contrast, the absence of LOC-eating was associated with a low propensity to want to eat all the time, greater family income, and infrequent emotional overeating. Therefore, propensity to want to eat all the time, a single question from the Children's Eating Behavior Questionnaire, characterized both the presence and absence of LOC-eating, highlighting the need for more research to determine if this question captures clinically relevant individual differences. Future studies addressing these questions will advance our understanding of pediatric LOC-eating and may lead to interventions to reduce risk for more severe eating disorder symptomology.

Development and Pilot Testing of Standardized Food Images for Studying Eating Behaviors in Children.

Food images are routinely used to investigate the cognitive and neurobiological mechanisms of eating behaviors, but there is a lack of standardized image sets for use in children, which limits cross-study comparisons. To address this gap, we developed a set of age-appropriate images that included 30 high-energy-dense (ED) foods (>2.00 kcal/g), 30 low-ED foods (<1.75 kcal/g), and 30 office supplies photographed in two amounts (i.e., "larger" and "smaller"). Preliminary testing was conducted with children (6-10 years) to assess recognition, emotional valence (1 = very sad, 5 = very happy), and excitability (1 = very bored, 5 = very excited). After the initial testing, 10 images with low recognition were replaced; thus, differences between Image Set 1 and Image Set 2 were analyzed. Thirty (n = 30, mean age 8.3 ± 1.2 years) children rated Set 1, and a different cohort of 29 children (mean age 8.1 ± 1.1 years) rated Set 2. Changes made between image sets improved recognition of low-ED foods (Set 1 = 88.3 ± 10.5% vs. Set 2 = 95.6 ± 10.6%; p < 0.0001) and office supplies (83.7 ± 10.5 vs. 93.0 ± 10.6%; p < 0.0001). For the revised image set, children recognized more high-ED foods (98.4 ± 10.6%) than low-ED foods (95.6 ± 10.6%; p < 0.05) and office supplies (93.0 ± 10.6%; p < 0.0001). Recognition also improved with age (p < 0.001). Excitability and emotional valence scores were greater for high-ED foods compared with both low-ED foods and office supplies (p < 0.0001 for both). However, child fullness ratings influenced the relationship between excitability/emotional valence and category of item (p < 0.002). At the lowest fullness level, high-ED foods were rated the highest in both excitability and emotional valence, followed by low-ED foods and then office supplies. At the highest fullness level, high-ED foods remained the highest in excitability and emotional valence, but ratings for low-ED foods and office supplies were not different. This suggests that low-ED foods were more exciting and emotionally salient (relative to office supplies) when children were hungry. Ratings of recognition, excitability, and emotional valence did not differ by image amount. This new, freely available, image set showed high recognition and expected differences between image category for emotional valence and excitability. When investigating children's responsiveness to food cues, specifically energy density, it is essential for investigators to account for potential influences of child age and satiety level.

Individual differences in the influence of taste and health impact successful dietary self-control: A mouse tracking food choice study in children.

In order to improve dietary quality among children, there is a need to understand how they make decisions about what foods to eat. This study used a mouse tracking food choice task to better understand how attributes such as health and taste contribute to food decisions among 70 children aged 7-to-11 years old. Children rated health, taste, and desire to eat for 76 common foods that varied in energy density and then used a computer mouse to select which of two presented foods they would like to eat. The presented food pairs were based on children's own ratings of taste and health so that some trials required self-control to choose the healthier option (i.e., healthy/not tasty paired with unhealthy/tasty). Children's body mass index (BMI) percentile was not associated with number of healthy choices. To examine mouse trajectories, we replicated previous analytic techniques and applied a novel technique, time-varying effects modeling (TVEM). Results showed that desire to eat impacted food decision-making sooner than taste and health during trials that required self-control, with TVEM showing that early discounting of desire to eat enabled healthier choices. However, these temporal dynamics varied by age, BMI percentile, and overall self-control performance in the task. When the less healthy food was chosen (i.e., self-control failure), older children and children with better overall self-control were more influenced by taste and desire to eat. However, children with higher BMI percentiles showed stronger discounting (i.e., negative influence) of taste when choosing the healthier food. Together this highlights how the influence of hedonic food attributes on food decision-making varies by individual child-level characteristics. Understanding individual differences in the cognitive processes that support healthy food choices in children may help identify targets for interventions aimed at improving child nutrition.

Altered neural correlates of episodic memory in adolescents with severe obesity.

Negative effects of obesity on memory and associated medial temporal circuitry have been noted in animal models, but the status in humans, particularly children, is not well established. Our study is the first to examine neural correlates of successful memory encoding of visual scenes and their associated context in adolescents with severe obesity (age 14-18 years, 43% male). Despite similar subsequent memory as adolescents without obesity (BMI for age and sex <95th percentile), those with severe obesity (BMI for age and sex 120% above the 95th percentile) showed reduced hippocampal, parahippocampal, frontal, and parietal engagement during encoding of remembered visual scenes and greater lateral temporal engagement during encoding of their associated context. Standardized testing revealed a trend level group difference in memory performance, with a larger magnitude of obesity-related difference in recollection-related memory that was mediated by individual differences in lateral temporal activation during contextual encoding. The observed widespread functional alterations are concerning in light of the importance of mnemonic processing for academic achievement and feeding behavior and underscore the need for prevention and intervention initiatives for pediatric obesity.

A Biopsychosocial Model of Sex Differences in Children's Eating Behaviors.

The prevalence of obesity and eating disorders varies by sex, but the extent to which sex influences eating behaviors, especially in childhood, has received less attention. The purpose of this paper is to critically discuss the literature on sex differences in eating behavior in children and present new findings supporting the role of sex in child appetitive traits and neural responses to food cues. In children, the literature shows sex differences in food acceptance, food intake, appetitive traits, eating-related compensation, and eating speed. New analyses demonstrate that sex interacts with child weight status to differentially influence appetitive traits. Further, results from neuroimaging suggest that obesity in female children is positively related to neural reactivity to higher-energy-dense food cues in regions involved with contextual processing and object recognition, while the opposite was found in males. In addition to differences in how the brain processes information about food, other factors that may contribute to sex differences include parental feeding practices, societal emphasis on dieting, and peer influences. Future studies are needed to confirm these findings, as they may have implications for the development of effective intervention programs to improve dietary behaviors and prevent obesity.