Neural representations of food: Disentangling the unprocessed and processed dimension

Food is fuel for life. Our feeding behaviors are guided by both homeostatic and hedonic (or reward-based) mechanisms. By simply inspecting visually presented food stimuli, our brain extracts information such as edibility or caloric content, as described by the results of the meta-analysis. However, whether such ability extends to the discrimination between unprocessed and processed foods is to date unknown. Therefore, the aim of the present thesis is to understand whether this particular dimension, that has been hypothesized to have a central role in human evolution (Cooking hypothesis), has a brain signature and how it affects food preferences and choices. All these aspects are introduced in Chapter 1 of my thesis while in the following ones (Chapters 2-4) I will report original studies in which I used different techniques. In Study 1, explicit and implicit evaluations towards foods have been investigated using explicit ratings and the Implicit Association Test (IAT), in order to explore whether evaluations differed based on the food type (unprocessed vs processed) (Chapter 2). The results of Study 1 showed that both at the explicit and implicit level normal-weight participants held different evaluations towards the stimuli depending on the food type. Also, participants\u2019 hunger level, BMI and gender were found to modulate participants\u2019 evaluations, but only at the explicit level. Interestingly, a strong influence of participants\u2019 dietary habits was found at the implicit level. Using electroencephalography (EEG), in Study 2 I aimed at investigating whether the difference between unprocessed and processed foods had a detectable neural signature and whether the brain rapidly discriminates between these food types as an adaptive behavior (Chapter 3). The spatio-temporal dynamics of the distinction between unprocessed and processed foods in normal-weight individuals showed that as early as 130 ms post-stimulus onset differences in amplitude emerged. Other within-category discriminations involving food stimuli (i.e. caloric content), as well as other biologically relevant stimuli such as faces or animals, have been observed within this time window. This study is the first to show distinct brain responses to unprocessed and processed foods in a simple food vs non-food categorization task. In Study 3 I used functional magnetic resonance imaging (fMRI) with the aim of disentangling the brain responses to different foods in the regions which greatly respond to foods compared to other non-edible objects (Chapter 4). Moreover, the results show how different brain regions responded to unprocessed and processed foods while normal-weight individuals were performing a simple one-back task. In final chapter I discussed the main findings obtained in my studies in the light of the extant literature, with particular emphasis on the processed-unprocessed dimension (Chapter 5)

The role of associative learning in healthy and sustainable food evaluations : An event-related potential study

Individuals in industrialized societies frequently include processed foods in their diet. However, overconsumption of heavily processed foods leads to imbalanced calorie intakes as well as negative health consequences and environmental impacts. In the present study, normal-weight healthy individuals were recruited in order to test whether associative learning (Evaluative Conditioning, EC) could strengthen the association between food-types (minimally processed and heavily processed foods) and concepts (e.g., healthiness), and whether these changes would be reflected at the implicit associations, at the explicit ratings and in behavioral choices. A Semantic Congruency task (SC) during electroencephalography recordings was used to examine the neural signature of newly acquired associations between foods and concepts. The accuracy after EC towards minimally processed food (MP-food) in the SC task significantly increased, indicating strengthened associations between MP-food and the concept of healthiness through EC. At the neural level, a more negative amplitude of the N400 waveform, which reflects semantic incongruency, was shown in response to MP-foods paired with the concept of unhealthiness in proximity of the dorsal lateral prefrontal cortex (DLPFC). This implied the possible role of the left DLPFC in changing food representations by integrating stimuli’s features with existing food-relevant information. Finally, the N400 effect was modulated by individuals’ attentional impulsivity as well as restrained eating behavior

Implicit and explicit evaluations of foods: The natural and transformed dimension

In Western societies, choosing what to eat can be a demanding task due to the excessive availability of food. To make our feeding decisions more complex, our explicit and implicit evaluations of foods may differ as they are multi-attribute stimuli. Previous research has focused on investigating implicit and explicit evaluations towards high and low energy dense foods, the main finding being that participants’ hunger level and dietary habits (restrained eating) modulate such evaluations. In the present study, we investigated whether normal-weight healthy individuals assigned different values to natural and transformed foods depending on implicit (assessed with the Implicit Association Test) or explicit measures (assessed with explicit ratings), and whether participants’ hunger level or dietary habits modulated the responses at both levels. Our results showed that while for natural foods implicit and explicit measures (healthiness) seemed to converge, dietary habits or hunger level did not affect such evaluations. For transformed foods, a dissociation between implicit and explicit measures (healthiness) seemed to emerge, along with a strong modulation of dietary habits and hunger level on the evaluations of such foods. Thus, these findings reveal how the type of food can modulate evaluations at both the implicit and explicit level and highlight a critical role of long-term health consequences and eating patterns in food evaluations

Median RT (ms) as a function of Cue-Target spatial congruency and Status in Experiment 1.

<p>Error bars represent SEM. Asterisk denotes <i>p</i><.05.</p

Median RT (ms) and percentage of errors (%) for each condition in Experiment 1 and 2.

<p>Values in brackets are SEM. C =  congruent trials; I =  incongruent trials.</p