Food is an integral part of our life and what and how much we eat crucially affects our health. Our food choices largely depend on how we perceive certain characteristics of food, such as whether it is healthy, delicious or if it qualifies as a salad. But these perceptions differ from person to person and one person's "single lettuce leaf" might be another person's "side salad". Studying how food is perceived in relation to what it actually is typically involves a laboratory setup. Here we propose to use recent advances in image recognition to tackle this problem. Concretely, we use data for 1.9 million images from Instagram from the US to look at systematic differences in how a machine would objectively label an image compared to how a human subjectively does. We show that this difference, which we call the "perception gap", relates to a number of health outcomes observed at the county level. To the best of our knowledge, this is the first time that image recognition is being used to study the "misalignment" of how people describe food images vs. what they actually depict.
@cite_44 examined the relationship between goal-directed valuations of food images by both lean and overweight people in an MRI scanner and food consumption at a subsequent all-you-can-eat buffet. They observed that both lean and overweight participants showed similar patterns of value-based neural responses to health and taste attributes of foods. This suggests that a shift in obesity may lie in how the presence of food overcomes prior value-based decision-making.
@cite_44
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To develop more ecologically valid models of the neurobiology of obesity, it is critical to determine how the neural processes involved in food-related decision-making translate into real-world eating behaviors. We examined the relationship between goal-directed valuations of food images in the MRI scanner and food consumption at a subsequent ad libitum buffet meal. We observed that 23 lean and 40 overweight human participants showed similar patterns of value-based neural responses to health and taste attributes of foods. In both groups, these value-based responses in the ventromedial PFC were predictive of subsequent consumption at the buffet. However, overweight participants consumed a greater proportion of unhealthy foods. This was not predicted by in-scanner choices or neural response. Moreover, in overweight participants alone, impulsivity scores predicted greater consumption of unhealthy foods. Overall, our findings suggest that, while the hypothetical valuation of the health of foods is predictive of eating behavior in both lean and overweight people, it is only the real-world food choices that clearly distinguish them. Little is known about the relationship between weight status and reward-related brain activity in normal weight humans.We correlated orbitofrontal and anterior cingulate cortex activity as measured by functional magnetic resonance imaging with body mass index in 13 healthy, normal-weight adult women as they viewed images of high-calorie and low-calorie foods, and dining-related utensils. Body mass index correlated negatively with both cingulate and orbitofrontal activity during high-calorie viewing, negatively with orbitofrontal activity during low-calorie viewing, and positively with orbitofrontal activity during presentations of nonedible utensils.With greater body mass, activity was reduced in brain regions important for evaluating and modifying learned stimulus^ reward associations, suggesting a relationship between weight status and responsiveness of the orbitofrontal cortex to rewarding food images. NeuroReport 16:859^ 863 � c 2005 Lippincott Williams & Wilkins. Abstract Sixteen normal-weight subjects rated the perceived intensity of sweetness, fatness, and creaminess of 20 different mixtures of milk, cream, and sugar, and assigned an overall pleasantness (hedonic) rating to each sample. Intensity estimates increased as power functions of ingredient concentration and no significant mixture suppression effect was observed. In contrast, hedonic responses strongly depended on the relative proportions of sucrose and fat in the samples tasted. Hedonic preference ratings first rose and then declined with increasing sucrose concentration, but continued to rise with increasing dairy fat content. The addition of sucrose greatly enhanced hedonic ratings for high-fat stimuli. Changes in hedonic responsiveness were monitored using a mathematical modelling technique known as the Response Surface Method, which allows computerized simulation of the hedonic response surface as a function of perceived ingredient levels. Overnight fasting did not affect the perception or hedonics for sweet or “fatty” tastes. The observed preference for sweetened high-fat foods may have implications for the development of dietary-induced obesity in man. Increased hunger and food intake during attempts to maintain weight loss are a critical problem in clinical management of obesity. To determine whether reduced body weight maintenance is accompanied by leptin-sensitive changes in neural activity in brain regions affecting regulatory and hedonic aspects of energy homeostasis, we examined brain region–specific neural activity elicited by food-related visual cues using functional MRI in 6 inpatient obese subjects. Subjects were assessed at their usual weight and, following stabilization at a 10 reduced body weight, while receiving either twice daily subcutaneous injections of leptin or placebo. Following weight loss, there were predictable changes in neural activity, many of which were reversed by leptin, in brain areas known to be involved in the regulatory, emotional, and cognitive control of food intake. Specifically, following weight loss there were leptin-reversible increases in neural activity in response to visual food cues in the brainstem, culmen, parahippocampal gyrus, inferior and middle frontal gyri, middle temporal gyrus, and lingual gyrus. There were also leptin-reversible decreases in activity in response to food cues in the hypothalamus, cingulate gyrus, and middle frontal gyrus. These data are consistent with a model of the weight-reduced state as one of relative leptin deficiency.