Subjects: Psychology >> Developmental Psychology submitted time 2024-01-17
Abstract： Picky eating is a common dietary issue among children characterized by lack of variety of foods consumed due to rejection of familiar (or unfamiliar) foods. The influencing factor model of picky eating behavior in children indicates that environmental and cognitive factors are key elements influencing this. Studies have found that instrumental feeding exacerbates picky eating behavior in children. However, due to the relatively young age of children in previous studies, research on the relationship between instrumental feeding and picky eating behaviors in school-aged children is insufficient. Furthermore, the brain plays a central role in guiding eating behavior; however, to date, limited neuroscientific research on the neural basis of picky eating behaviors in school-aged children exists. This study aimed to utilize resting-state functional magnetic resonance imaging (rs-fMRI) data combined with a machine learning method to explore the neural basis of picky eating behaviors in children. Additionally, it attempted to show the neural mechanisms through which instrumental feeding influences picky eating behavior.
A total of 139 children were recruited for this study. Instrumental feeding and picky eating behaviors were assessed through parent-reported measurements and rs-fMRI was conducted. A total of 87 children were included in the formal analyses as those who did not participate in the two behavioral measurements and with unqualified rs-fMRI scans were excluded. This study utilized regional homogeneity and functional connectivity to evaluate the resting-state neural substrates of picky eating behaviors. Subsequently, a machine learning method is employed to validate the stability of our results. Additionally, a mediation model was constructed to investigate the mediating role of resting-state neural substrates in the relationship between instrumental feeding and picky eating behavior.
Results showed that picky eating behavior was positively correlated with regional homogeneity in the right caudate. Functional connectivity results showed that picky eating behavior was positively correlated with functional connectivity between the right caudate and left putamen. A prediction analysis based on a cross-validation machine learning method indicated a significant correlation between picky eating behavior scores predicted by the aforementioned neural substrates (i.e., regional homogeneity in the right caudate and functional connectivity between the right caudate and left putamen) and the actual observed picky eating behavior scores. The mediation model further suggested that functional connectivity between the right caudate and left putamen could mediate the relationship between instrumental feeding and picky eating behavior. Specifically, instrumental feeding might negatively influence the functional connectivity between the right caudate and left putamen, and further reduce picky eating behavior.
By combining resting-state regional homogeneity and functional connectivity analyses, this study detected altered functional brain activity related to picky eating behaviors in children aged 9 to 12. Specifically, hyperactive neural interactions within the brain areas involved in sensory sensitivity and reward processing may explain the manifestation of picky eating behavior in children. Additionally, instrumental feeding negatively influences picky eating behavior through brain activity in regions involved in sensory sensitivity and reward processing. This study provides new insights into the resting-state neural substrates of children's picky eating behavior, extends the influencing factor model of children's picky eating behavior, and provides theoretical support for interventions to improve poor picky eating behavior in children through parental feeding practices.
Subjects: Psychology >> Social Psychology submitted time 2023-03-27 Cooperative journals: 《心理学报》
Abstract： Early life stress (ELS) has been used to describe a broad spectrum of adverse and stressful events, including childhood trauma occurring during neonatal life, early and late childhood, and adolescence. Childhood is a vulnerable time point for stressful events due to an immature brain, which increases the risk of psychopathology in later life. However, to date, studies have focused almost exclusively on adolescents and adults, and little is known about the relationship between ELS and the structural and functional brain changes in children. Here, we adopted a multimodal approach combining voxel-based morphometry (VBM) and functional connectivity (FC) to examine the neural substrates of ELS in children aged 9~12 years.A total of 139 children were recruited for this study. For each participant, the ELS level was assessed and an 8-minute rs-fMRI scan was performed using a 3T Trio scanner. Participants with unqualified data were excluded, resulting in a final sample of 78 participants (39 females; mean age = 10.18). For statistical analysis, we used the gray matter volume (GMV) and FC to explore the brain structural and functional correlates of children’s ELS and then used a machine learning method to investigate whether and how structural connectivity profiles in predefined brain networks can predict ELS levels. Additionally, exploratory analyses were performed to investigate potential sex differences and age characteristics in GMV and FC associated with children’s ELS. VBM analysis showed that greater ELS was associated with a larger GMV in the left medial orbitofrontal cortex, right insular cortex, left superior temporal gyrus, and left supplementary motor area. Subsequently, we used these clusters as seed regions to analyze the correlation between FC and stress in children. We found that greater ELS was associated with lower insular-inferior parietal lobule (IPL) connectivity. The results were not influenced by sex, age, total intracranial volume, or head motion. Furthermore, the predictive analysis of machine learning reported that the sensorimotor, frontoparietal, salience, visual, and cerebellar networks could marginally predict ELS scores. Finally, exploratory analyses showed that there were no significant sex differences in the GMV or FC associated with ELS and that significant correlations of ELS with the GMV of the inferior occipital gyrus were mainly manifested in 9-year-old children. Using VBM and FC analyses, we detected structural and functional brain alterations associated with ELS in children aged 9~12 years. Specifically, the VBM analysis mainly reflected that children with high ELS may have abnormal emotional and cognitive functions, such as hypersensitivity to emotional stimuli and over-monitoring of their own behavior. In addition, FC analysis indicated that aberrant interaction of internal and external information may contribute to high ELS in childhood. This study not only provides unique insights into the neural substrates of ELS but may also help identify children who are susceptible to ELS within the general population, which may be advantageous for early prevention strategies and interventions for children.
Subjects: Psychology >> Other Disciplines of Psychology submitted time 2022-09-08
Abstract：
Early life stress (ELS) has been used to describe a broad spectrum of adverse and stressful events, including childhood trauma occurring during neonatal life, early and late childhood, and adolescence. Childhood is a vulnerable time point for stressful events due to an immature brain, which increases the risk of psychopathology in later life. However, to date, studies have focused almost exclusively on adolescents and adults, and little is known about the relationship between ELS and the structural and functional brain changes in children. Here, we adopted a multimodal approach combining voxel-based morphometry (VBM) and functional connectivity (FC) to examine the neural substrates of ELS in children aged 9~12 years.
A total of 139 children were recruited for this study. For each participant, the ELS level was assessed and an 8-minute rs-fMRI scan was performed using a 3T Trio scanner. Participants with unqualified data were excluded, resulting in a final sample of 78 participants (39 females; mean age = 10.18). For statistical analysis, we used the gray matter volume (GMV) and FC to explore the brain structural and functional correlates of children’s ELS and then used a machine learning method to investigate whether and how structural connectivity profiles in predefined brain networks can predict ELS levels. Additionally, exploratory analyses were performed to investigate potential sex differences and age characteristics in GMV and FC associated with children’s ELS.
VBM analysis showed that greater ELS was associated with a larger GMV in the left medial orbitofrontal cortex, right insular cortex, left superior temporal gyrus, and left supplementary motor area. Subsequently, we used these clusters as seed regions to analyze the correlation between FC and stress in children. We found that greater ELS was associated with lower insular-inferior parietal lobule (IPL) connectivity. The results were not influenced by sex, age, total intracranial volume, or head motion. Furthermore, the predictive analysis of machine learning reported that the sensorimotor, frontoparietal, salience, visual, and cerebellar networks could marginally predict ELS scores. Finally, exploratory analyses showed that there were no significant sex differences in the GMV or FC associated with ELS and that significant correlations of ELS with the GMV of the inferior occipital gyrus were mainly manifested in 9-year-old children.
Using VBM and FC analyses, we detected structural and functional brain alterations associated with ELS in children aged 9~12 years. Specifically, the VBM analysis mainly reflected that children with high ELS may have abnormal emotional and cognitive functions, such as hypersensitivity to emotional stimuli and over-monitoring of their own behavior. In addition, FC analysis indicated that aberrant interaction of internal and external information may contribute to high ELS in childhood. This study not only provides unique insights into the neural substrates of ELS but may also help identify children who are susceptible to ELS within the general population, which may be advantageous for early prevention strategies and interventions for children.
Peer Review Status:
Awaiting Review
Subjects: Psychology >> Cognitive Psychology submitted time 2022-07-09
Abstract：
[Objective] The current study used the Think/No-Think paradigm combined with fMRI techniques to explore the cognitive and brain mechanisms of food memory retrieval inhibition and its reward devaluation effects among restrained eaters.
[Methods] Forty participants (all female) aged between 18-24 were recruited for this study, 21 of whom were restrained eaters and 19 were unrestrained eaters. Participants completed a food version TNT task, which consisted of learning phase, TNT phase and test phase. The TNT phase was completed in a 3.0T Siemens Prisma MRI scanner. Before and after the whole three phases of TNT task, participants rated the subjective value of the food items in the pictures.
[Results] Behavioral results revealed no significant differences in memory retrieval inhibition effect between restrained eaters and unrestrained eaters. However, restrained eating scores were negatively correlated with the effect of reward devaluation of inhibited food items. Neuroimaging data showed that restrained eaters had greater activation of dorsolateral prefrontal cortex (dlPFC) and lower activation of reward and memory areas than unrestrained eaters during inhibiting food-related memories. In addition, PPI analysis showed that the connectivity strength of dlPFC with hippocampus, parahippocampus, thalamus and posterior cingulate cortex were negatively corrected with restrained eating scores. Further analysis showed that connectivity strength between dlPFC and thalamic mediated the negative association between restrained eating scores and the reward devaluation effects of memory inhibition.
[Limitations] The subjects in this study were all healthy university students whose performance in executive functioning was at its peak, therefore a ceiling effect may have occurred.
[Conclusion]The current observations support the goal conflict model from the perspective of memory retrieval inhibition, whereby restrained eater has difficulty in successfully regulating conflict between inhibition and food reward by devaluation food reward. This kind of deficiency in reward devaluation due to deficits in memory inhibition may further increase the risk of uncontrolled food intake in food-rich environments of restrained eaters.
Peer Review Status:Awaiting Review
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