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’ hunger level, BMI and gender were found to modulate participants’ evaluations, but only at the explicit level. Interestingly, a strong influence of participants’ 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).
Neural representations of food: Disentangling the unprocessed and processed dimension / Coricelli, Carol. - (2018 Jan 19).
Neural representations of food: Disentangling the unprocessed and processed dimension
Coricelli, Carol
2018-01-19
Abstract
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’ hunger level, BMI and gender were found to modulate participants’ evaluations, but only at the explicit level. Interestingly, a strong influence of participants’ 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).File | Dimensione | Formato | |
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