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: Other Disciplines >> Synthetic discipline submitted time 2023-10-09 Cooperative journals: 《心理科学进展》
Abstract： In 1997, the World Health Organization recognized obesity as a global epidemic. In China, the prevalence of overweight/obesity among adults has surpassed 50%, with unhealthy dietary behaviors accounting for 70% of the causes. Working memory has been shown to play a protective role in maintaining long-term healthy dietary goals by diverting attention from tempting stimuli. Therefore, this research project aims to investigate the role of food-specific working memory in individuals with overweight/obesity through cross-sectional, prospective, and intervention studies. The research will explore temporal dynamics, neural oscillations, brain spatial activation, and real-life implications. The project's objectives are as follows: (1) to explore the cognitive and neural mechanisms involved in food-specific working memory updating in overweight/obese individuals; (2) to examine the predictive function of food-specific working memory updating and related neural activity on an individual's dietary management and weight changes; (3) to investigate the effectiveness of food-specific inhibitory control training in enhancing food-specific working memory updating and promoting healthy dietary habits in individuals with overweight/obesity.Study 1 will employ electroencephalography (EEG) techniques to investigate the electrophysiological activity underlying working memory updating in overweight/obese individuals. This study will use a 2-back task with general and food-specific stimuli. The study will examine the temporal characteristics of brain activity associated with general and food-specific working memory updating in overweight/obese individuals and investigate whether there are similar behavioral and neural patterns between general and food-specific working memory updating. It is hypothesized that overweight/obese individuals will exhibit significantly different performance in the 2-back task compared to normal-weight individuals, and the neural correlates may involve changes in N2 amplitude, P3 amplitude, theta and alpha power, among others. Additionally, due to the rewarding effects of food, general and food-specific working memory updating in overweight/obese individuals may exhibit different neural patterns.Study 2 will focus on the relationship between food-specific working memory updating and related brain activity, and the development of overweight/obesity using functional magnetic resonance imaging (fMRI). This study will consist of two experiments—a cross-sectional study design and a prospective study design. The study will explore the predictive role of food-specific working memory updating and related brain activity on dietary management and changes in body weight in the overweight/obesity population. The study will first utilize food-specific 1-back tasks with inhibitory control and then collect data through follow-up surveys and body composition measurements. It is hypothesized that overweight/obese individuals will display poorer performance in the working memory task and exhibit less brain activation in control-related brain regions, as well as greater activation in reward-related brain regions, compared to normal-weight individuals during the task.Study 3 aims to explore effective interventions for overweight/obesity by employing food inhibition control training combined with fMRI techniques. The study will include a general and a food-specific inhibition control training delivered through general or food-specific go/no-go tests. Both trainings will be investigated, with the hypothesis that both types of training can improve food-specific working memory updating performance, and both trainings can enhance the activity in control-related brain regions involved in food-specific working memory in overweight/obese individuals, but food-specific training will yield better results. In summary, this project delves into the behavioral and neural mechanisms of working memory in individuals with overweight/obesity. By investigating the cognitive processing, spatial activation patterns, and the interplay between food-specific working memory and overweight/obesity, the research aims to provide reliable evidence and a comprehensive understanding of the cognitive and neural mechanisms in this population. The project will also examine the interdependent relationship between food-specific working memory and related brain activity, and the development of overweight/obesity, with the goal of obtaining a wholistic view of the underpinnings between working memory updating and overweight/obesity and providing evidence for the establishment of a more complete neurocognitive model. Furthermore, the project will employ inhibition control training as an intervention for overweight/obesity, laying a practical foundation for effective solutions to obesity-related issues and facilitate the innovative translation of basic research findings.
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.
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