Abstract
Our ability to evaluate long-term goals over immediate rewards is manifested in the brain’s decision circuit. Simplistically, it can be divided into a fast, impulsive, reward “system 1” and a slow, deliberate, control “system 2.” In a noisy eating environment, our cognitive resources may get depleted, potentially leading to cognitive overload, emotional arousal, and consequently more rash decisions, such as unhealthy food choices. Here, we investigated the combined impact of cognitive regulation and ambient noise on food cravings through neurophysiological activity. Thirty-seven participants were recruited for an adapted version of the Regulation of Craving (ROC) task. All participants underwent two sessions of the ROC task; once with soft ambient restaurant noise (∼50 dB) and once with loud ambient restaurant noise (∼70 dB), while data from electroencephalography (EEG), electrodermal activity (EDA), and self-reported craving were collected for all palatable food images presented in the task. The results indicated that thinking about future (“later”) consequences vs. immediate (“now”) sensations associated with the food decreased cravings, which were mediated by frontal EEG alpha power. Likewise, “later” trials also increased frontal alpha asymmetry (FAA) —an index for emotional motivation. Furthermore, loud (vs. soft) noise increased alpha, beta, and theta activity, but for theta activity, this was solely occurring during “later” trials. Similarly, EDA signal peak probability was also higher during loud noise. Collectively, our findings suggest that the presence of loud ambient noise in conjunction with prospective thinking can lead to the highest emotional arousal and cognitive load as measured by EDA and EEG, respectively, both of which are important in regulating cravings and decisions. Thus, exploring the combined effects of interoceptive regulation and exteroceptive cues on food-related decision-making could be methodologically advantageous in consumer neuroscience and entail theoretical, commercial, and managerial implications.
Highlights
Value-Based Decision-MakingOur ability to evaluate long-term goals over immediate rewards is encoded in an array of complex computational processes in the brain (Rangel et al, 2008; Levin et al, 2012)
We examined the power spectral density (PSD) in the theta, alpha, and beta frequency bands in the fronto-cortical areas, frontal alpha asymmetry (FAA), as well as electrodermal activity (EDA) during cognitive regulation in the presence of ambient noise and visual food presentation
The generalized linear mixed models (GLMMs) did not detect any significant interaction, but a main effect of decision perspective was observed with food cravings being reportedly significantly stronger in -trials [F(1, 4222) = 1,032.92; p < 0.001; Table 2 and Figure 4]
Summary
Our ability to evaluate long-term goals over immediate rewards is encoded in an array of complex computational processes in the brain (Rangel et al, 2008; Levin et al, 2012) These include resisting the impulse of consuming palatable foods, foreseeing the future potential health consequences associated, and at the same time being able to delay one’s gratification by valuing the “rational” alternative despite temporal discounting (Volkow and Baler, 2015; Cai et al, 2019). Our choices and decisions ought to fulfill both immediate needs and those that are better served for future gains (Motoki et al, 2019) To evolutionarily optimize such balanced utilitarian behaviors, the neural circuitry of human decisionmaking can simplistically be divided into two neuroanatomically and -functionally distinctive systems—an automatic, emotional, impulsive system (bottom-up) and a deliberate, reflective, control system (top-down)—popularly referred to as a fast “system 1” and a slow “system 2” (Evans, 2007; Chen et al, 2018). Without cognitive inhibition of system 2, the mere presence of appetitive and salient food cues reinforces anticipatory reward (“wanting”) responses through sensitized neural firing of dopamine, potentially leading to excess food consumption, weight gain, and even addictive behaviors (Burger and Stice, 2012; Schulte et al, 2016; Coccurello and Maccarrone, 2018; Nguyen et al, 2021)
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