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Restrained eaters do not eat less than their unrestrained counterparts. Proposed underlying mechanisms are that restrained eaters are more reward sensitive and that they have worse inhibitory control. Although fMRI studies assessed these mechanisms, it is unknown how brain anatomy relates to dietary restraint. Voxel-based morphometry was performed on anatomical scans from 155 normal-weight females to investigate how regional grey matter volume correlates with restraint. A positive correlation was found in several areas, including the parahippocampal gyrus, hippocampus, striatum and the amygdala (bilaterally, p<0.05, corrected). A negative correlation was found in several areas, including the inferior frontal gyrus, superior frontal gyrus, supplementary motor area, middle cingulate cortex and precentral gyrus (p<0.05, corrected). That higher restraint relates to higher grey matter volume in reward-related areas and lower grey matter volume in regions involved in inhibition, provides a neuroanatomical underpinning of theories relating restraint to increased reward sensitivity and reduced inhibitory capacity., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Impulsivity is a personality trait that is linked to unhealthy eating and overweight. A few studies assessed how impulsivity relates to neural responses to anticipating and tasting food, but it is unknown how impulsivity relates to neural responses during food choice. Although impulsivity is a multi-faceted construct, it is unknown whether impulsivity subtypes have different underlying neural mechanisms. We investigated how impulsivity correlates with brain responses during food choice and in how far different impulsivity subtypes modulate brain responses during food choice differently. Twenty weight-concerned females performed an fMRI task in which they indicated for high and low energy snacks whether or not they wanted to eat them. Impulsivity subtypes were measured by the monetary delay discounting task and the Barratt Impulsiveness Scale (total BIS-11 and subscales). Only temporal subtypes of impulsivity, namely delay discounting and the BIS-11 non-planning subscale, modulated responses to food choice; both measures correlated positively with striatum activation during high versus low energy choices. However, only delay discounting predicted high energy choices, whereas BIS-11 non-planning independently related to a striatum region that reflects subjective stimulus value. To conclude, the brain mechanisms underlying subtypes of impulsivity have a common ground but differ in specific aspects of food-related decision-making. The findings advance our understanding of the neural correlates of different impulsivity subtypes in the food domain., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Food cues are omnipresent and may enhance overconsumption. In the last two decades the prevalence of childhood obesity has increased dramatically all over the world, largely due to overconsumption. Understanding children's neural responses to food may help to develop better interventions for preventing or reducing overconsumption. We aimed to determine which brain regions are concurrently activated in children/adolescents in response to viewing food pictures, and how these relate to adult findings. Two activation likelihood estimation (ALE) meta-analyses were performed: one with studies in normal weight children/adolescents (aged 8-18, 8 studies, 137 foci) and one with studies in normal weight adults (aged 18-45, 16 studies, 178 foci). A contrast analysis was performed for children/adolescents vs. adults. In children/adolescents, the most concurrent clusters were in the left lateral orbitofrontal cortex (OFC), the bilateral fusiform gyrus, and the right superior parietal lobule. In adults, clusters in similar areas were found. Although the number of studies for a direct statistical comparison between the groups was relatively low, there were indications that children/adolescents may not activate areas important for cognitive control. Overall, the number of studies that contributed to the significant clusters was moderate (6-75%). In summary, the brain areas most consistently activated in children/adolescents by food viewing are part of the appetitive brain network and overlap with those found in adults. However, the age range of the children studied was rather broad. This study offers important recommendations for future research; studies making a direct comparison between adults and children in a sufficiently narrow age range would further elucidate how neural responses to food cues change during development., (Copyright © 2014 Elsevier Inc. All rights reserved.)

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