Altered dynamics between neural systems sub-serving decisions for unhealthy food

Abstract

Using BOLD functional magnetic resonance imaging (fMRI) techniques, we examined the relationships between activities in the neural systems elicited by the decision stage of the Iowa Gambling Task (IGT), and food choices of either vegetables or snacks high in fat and sugar. Twenty-three healthy normal weight adolescents and young adults, ranging in age from 14 to 21, were studied. Neural systems implicated in decision-making and inhibitory control were engaged by having participants perform the IGT during fMRI scanning. The Youth/Adolescent Questionnaire, a food frequency questionnaire, was used to obtain daily food choices. Higher consumption of vegetables correlated with higher activity in prefrontal cortical regions, namely the left superior frontal gyrus (SFG), and lower activity in sub-cortical regions, namely the right insular cortex. In contrast, higher consumption of fatty and sugary snacks correlated with lower activity in the prefrontal regions, combined with higher activity in the sub-cortical, insular cortex. These results provide preliminary support for our hypotheses that unhealthy food choices in real life are reflected by neuronal changes in key neural systems involved in habits, decision-making and self-control processes. These findings have implications for the creation of decision-making based intervention strategies that promote healthier eating.

Emotional eating and routine restraint scores are associated with activity in brain regions involved in urge and self-control

“…These brain regions are also engaged by non-food rewards including money [34], alcohol [35], and drugs [8, 36]. Recent work using a monetary task to engage neural activity found associations between activation of brain regions involved in reward processing, self-control, and urges and participants’ actual consumption of vegetables and high-calorie foods [40]. Similarly, youth at risk for obesity show elevated reward circuitry responses to both food and monetary rewards [41].…”

Does traditional asian vegetables (ulam) consumption correlate with brain activity using fMRI? A study among aging adults from low‐income households

“…23 The sample size of this study was also calculated and justified sufficiently, where the investigation on the association between ulam consumption and brain activation had been successfully conducted through the use of the fMRI; hence, corresponding to several previous studies that were conducted on the nutrients intake and brain activation with a small sample (n = 15-30). 6,13,37 The neuroimaging approach that was complemented with the neuropsychological batteries for the evaluation of cognitive domains such as working memory and cognitive flexibility can thus be regarded as a strength of this investigation, since the variations in brain functions that arose from the initial signs of Alzheimer's disease could be examined by this sort of MRI.…”

“…The basic health profiles and medical history were obtained by referring to a personal medical book and self‐reported by the subjects. The sample size was calculated using the formula: in which Zα = confidence interval 95% = 1.96; Zβ = 80% power = 0.842; C = 0.5*ln[(1 + r)/(1‐r)] = 0.61; r = correlation coefficient = 0.55, and additional dropout 20%; thus, the total sample size was 32 subjects. The fMRI scan had been carried out at the selected hospital by a trained fMRI radiographer with ethical approval (NN‐2018‐097) granted from the Institutional Research and Ethics Committee.…”

Neural predictors of eating behavior and dietary change

“…Several recent studies have also focused on the relationship between regulation, including inhibitory control 114 and cognitive reappraisal, 53,60,115 and individual differences in BMI. Additional work has investigated the relationship between decision making and retrospective food consumption 116 and BMI. 117 However, none of these studies assessed concurrent or prospective food consumption.…”