Neural Mechanisms in Eating Behaviors: A Pilot fMRI Study of Emotional Processing

Abstract

Objective Emotional processing dysfunction evident in eating disorders (ED) such as anorexia nervosa (AN) and bulimia nervosa (BN), is considered relevant to the development and maintenance of these disorders. The purpose of the current functional magnetic resonance imaging (fMRI) study was to pilot a comparison of the activity of the fronto-limbic and fronto-striatal brain areas during an emotion processing task in persons with ED.Methods 24 women patients with ED were scanned, while showing emotionally stimulating (pleasant, unpleasant) and neutral images from the International Affective Picture System (IAPS).Results During the pleasant condition, significant differences in Dorsolateral Prefrontal Cortex (DLPFC) activations were found with AN participants presenting greater activation compared to BN and ED comorbid groups (EDc) and healthy controls also showing greater activation of this brain area compared to BN and EDc. Left putamen was less activated in EDc compared to both controls (C) and AN. During the unpleasant condition, AN participants showed hyperactivation of the Orbito-frontal Cortex (OFC) when compared to EDc.Conclusion This study highlights the potential functional relevance of brain areas that have been associated with self-control. These findings should help advance understanding the neural substrate of ED, though they should be considered as preliminary and be cautiously interpreted.

Topological features of functional brain networks and subclinical impulsivity: an investigation in younger and older adults

“…Speculatively, this might reflect a deficit in correctly processing and integrating emotional stimuli within circuits subserving emotion regulation. Notably, these circuits are known to be responsible for reward, emotional processing and regulation (Harada et al 2021; Kebets et al 2021 ; Molina-Ruiz et al 2020 , Morein-Zamir and Robbins 2015 ). Indeed, the effective processing and regulation of emotional stimuli is fundamental to properly implement goal-directed behaviors and to prevent negative consequences (Miller and Racine 2022 ; Pruessner et al 2020 ).…”

Noradrenergic control of neurobehavior in human binge‐eating disorder and obesity (NOBEAD): A smartphone‐supported behavioral emotion regulation intervention study protocol integrating molecular brain imaging

“…Between memory trials, participants will be engaged in a 30‐sec spatial perceptual task in order to minimize self‐reflection or autobiographical memory retrieval (Doré et al, 2018). The 2nd part of the experiment will encompass 24 neutral pictures and pictures with moderately negative valence from The International Affective Picture System (IAPS, National Institute of Mental Health Center for Emotion and Attention, University of Florida) per previous fMRI studies in ED and OB (e.g., Molina‐Ruiz et al, 2020; Seidel et al, 2018; Steward et al, 2019). Each trial will start with a 5‐s interval, followed by a 2‐sec display of the instruction (“watch” or “distance,” for simple observation, or downregulation of any elicited feeling to evoke distance), followed by a 2–4 s jittered ISI and 8‐s presentation of the picture using a mirror system.…”

A new COVID-19 intubation prediction strategy using an intelligent feature selection and K-NN method

“…The use of intelligent optimization methods has provided an effective help in solving these problems. Therefore, it can be said that one of the most effective and constructive problem solving algorithms is the selection of features and their dependencies, the use of meta-heuristic optimization methods and evolutionary algorithms [ 41 , 42 ]. Meta-heuristic algorithms are a type of wrapper-based feature selection model in which ML algorithms are used to select optimal features.…”

“…In this paper, several well-known meta-heuristic algorithms including Horse herd Optimization Algorithm (HOA), Particle Swarm Optimization (PSO) [ 41 ], Genetic Algorithm (GA) [ 42 ], Grey Wolf Optimization (GWO) [ 42 ], Differential Evolution (DE) [ 43 ] and Harris Hawks Optimization(HHO) [ 44 ] have been used for feature selection. Feature selection can be considered as solution vectors whose length is equal to the total number of features and the values of its components are “0” or “1”.…”