EEG Resting-state Microstate Dynamics in Children and Adolescents with Avoidant/Restrictive Food Intake Disorder (ARFID)

回避/限制性食物摄入障碍(ARFID)儿童和青少年脑电图静息态微状态动态

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Abstract

Avoidant/Restrictive Food Intake Disorder (ARFID) is a psychiatric condition characterized by extreme food avoidance and limited food intake, leading to nutritional deficiencies, weight loss, and and/or social impairment. Despite its clinical significance, there is a notable lack of research on the neurobiological basis of ARFID. To address this gap, we examined resting-state EEG brain activity in children and adolescents with ARFID, using microstate analysis to capture spatial configurations associated with large-scale brain networks, offering a novel perspective on brain network abnormalities in this population. Eighteen patients with full/subthreshold ARFID (mean age 12.78 ± 3.57) were compared to 18 age- and sex-matched healthy controls (HC) (mean age 14.56 ± 2.85). EEG data were recorded during eyes-closed resting-state and examined using microstate analysis. Four microstate maps were identified (A, B, C, D). Significant differences were observed between groups for Map C, with the ARFID group showing higher values for mean duration compared to the HC group (U = 254, p = 0.003). Additionally, a trend towards decreased transition probabilities from microstate B to A (p = 0.018) and increased transition probabilities from B to C (p = 0.023) were found in ARFID. Source imaging analyses further revealed increased activation in the right posterior cingulate cortex (p = 0.005) and decreased activation in the right inferior occipital cortex (p = 0.003) in the ARFID group compared to HC. These results suggest distinct patterns of brain activity in children and adolescents with ARFID, particularly involving microstate C, which may reflect atypical Default Mode Network functioning. This study provides preliminary evidence of altered brain network dynamics in ARFID, contributing to a better understanding of its neurobiological basis and offering potential avenues for neurophysiological interventions.

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