EEG Dynamics of Self-Regulatory Strategies in Dietary Decision Making

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Description: Optimal decision making requires self-regulation (i.e., the use of attention, working memory, and executive control to alter one’s behaviour). For many individuals, choosing a plate of broccoli over a bar of KitKat is a challenging decision even when they want to maintain a healthy diet. Humans may use a number of different strategies to regulate their decisions in order to maintain their goals. For example, one can try to maintain a healthy diet by focussing on the healthiness of food items or by avoiding eating food in general. Previous functional magnetic resonance imaging studies suggest that self-regulation during decision making elicit changes in activation in the ventromedial and dorsolateral parts of the prefrontal cortex (Hare, Camerer, & Rangel, 2009) but how these regions interact and the precise roles they perform during self-regulation are still debated (Hare, Malmaud, & Rangel, 2011; Hutcherson, Plassmann, Gross, & Rangel, 2012; Tusche & Hutcherson, 2012). Studies on the temporal dynamics of dietary decision making using mouse-tracking, electroencephalogram (EEG), and diffusion drift-diffusion models (DDM) also provide evidence that different attributes of a food option such as its healthiness and tastiness are processed in different speeds (Sullivan, Hutcherson, Harris, & Rangel, 2015) and this process is likely modulated by regulation (Harris, Hare, & Rangel, 2013). However whether different regulation strategies are driven by distinct temporal dynamics is an open question. In this project as a follow-up to Hutcherson et al. (2012) we aim to use EEG to study the neural and temporal dynamics underlying two different regulation strategies in dietary decision making: focusing on the healthiness of food versus more generally decreasing one’s desire for all food. We will use a food choice paradigm (Harris et al., 2013; Hutcherson et al., 2012) adapted to EEG and apply several analysis methods (see analysis section for details) to investigate the neural and temporal dynamics of these decision strategies. Our goal is to answer two complementary questions: 1) How and why do different regulatory strategies differ in their implementation and effectiveness during choice? 2) Do these regulatory strategies result in sustained changes to food valuation beyond the moment of regulation, and if so, what predicts such change?

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  • EEG data

    Raw EEG data; recorded during the choice task

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  • Behavioural data

    Raw behavioural data; choice task and ratings

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