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 >> Developmental Psychology submitted time 2023-12-25
Abstract： This research is a breakthrough from the traditional cognitive intervention in which older adults are the targets of help, and uses volunteering as the intervention approach and older adults as the subjects of help to explore the effects and mechanisms of cognitive, physical, and social activities involved in the process of helping older adults, which in turn affects their own cognitive function. To achieve these goals, the study will use randomized controlled trials, functional magnetic resonance imaging, and data modeling techniques to examine the neuropsychological mechanisms of volunteering on cognitive function in older adults, from the perspective of the hot-cold dual system. In addition, the study aims to develop a predictive model to explore the fitness of different older adults who participate in volunteering to improve their cognitive function. By focusing on the scientific aspects of volunteering for cognitive function in older adults, this research aims to increase the sustainability of the interventions, while utilizing the subjective initiative of older adults to provide a reality-based intervention for the protection of cognitive function in later life.
Subjects: Psychology >> Social Psychology submitted time 2023-03-28 Cooperative journals: 《心理科学进展》
Abstract： The development of natural language processing has offered reliable and valid research methods for exploring the relationship between semantic distance and creative thinking. There are more and more studies in this direction in recent years. However, the research findings are inconsistent in this line of research. It remains unknown whether semantic distance could predict creative thinking and whether this relationship is influenced by other potential factors. Therefore, a more comprehensive study is necessary to investigate the relationship between semantic distance and creativity. To fulfill such a research gap, the present study, based on the Associative Theory of Creativity and the Spreading-Activation Model, has investigated the relationship between semantic distance and creative thinking by using a meta-analysis method. The reasons for the inconsistency of previous studies in this line of research were also analyzed. The current research has involved 14 studies and extracted 53 independent effect sizes from 4729 subjects. Since the heterogeneity test showed that there was significant heterogeneity (I2 = 92.21), the random effect model was used for the meta-analysis. Results of funnel plots, Egger's test of regression, and Fail-Safe Number (Nfs) showed that there were low levels of publication bias in the selected publications. The sensitivity analysis also suggested that the meta-analysis in the present study had acceptable reliability. The main effect analysis suggested that there was a moderate level of correlation between semantic distance and creative thinking (r = 0.379, 95% CI [0.300, 0.452]). Further meta-regression analysis found that the correlation was moderated by the age of participants and dimensions of creative thinking. Specifically, the results suggested that the correlation between semantic distance and creative thinking decreased with the increase in the age of participants. In addition, the flexibility (r = 0.473, 95%CI [0.180, 0.688]) had a higher correlation coefficient with semantic distance than originality (r = 0.328, 95%CI [0.197, 0.447]) and fluency (r = 0.447, 95%CI [0.338, 0.545]). However, elaboration had a negative correlation with semantic distance (r = -0.533, 95%CI [-0.664, -0.372]). The current study showed that semantic distance was associated with creative thinking. It has been suggested that the moderation effects of the age of participants and dimensions of creative thinking might be the potential reasons for the inconsistent results in previous studies. In theory, the present study provides new perspectives and explanations for exploring cognitive and neural mechanisms of creativity. It contributes to the exploration of the relationship between semantic distance and creative thinking. The current study offers better scientific evidence and important implications for interpreting, predicting, and improving creativity. In practice, the current study contributes to quantifying creative thinking by using semantic distance. Future explorations should investigate the relationships between semantic distance and domain-specific creativity (e.g., scientific creativity and artistic creativity), as well as the influence of other higher cognitive functions (e.g., cognitive control) on these relationships.
Subjects: Psychology >> Social Psychology submitted time 2023-03-27 Cooperative journals: 《心理学报》
Abstract： The majority of research on eating behaviors has been limited to an almost exclusive focus on pathology and is centered on the female group. Recently, one form of adaptive eating that has gained recognition is “intuitive eating”, which is defined as eating according to internal physiological cues of hunger and satiety rather than external or emotional signals. That is, individuals who eat intuitively are not preoccupied by food and dieting. They often choose food that helps their bodies function well and is pleasing to their palate. They do not ignore hunger cues or classify food into acceptable or unacceptable categories. Therefore, intuitive eating was found to be linked with greater unconditional self-regard and body satisfaction, as well as lower levels of both depression and disordered eating. Adolescence, in particular, acts as a critical period in the development of eating attitudes and behaviors. Adolescents devote a great deal of attention to physical appearance, and are inclined to engage in unhealthy eating behaviors to reduce an unsatisfactory body image; this has a negative impact on their physical and mental health. Due to these circumstances, it is essential to identify the key factors influencing adolescents’ healthy eating behaviors. Using the perspectives of attachment theory and the acceptance model of intuitive eating, this study aimed to investigate the effect of friendship quality on intuitive eating among Chinese adolescents, and the potential mediating role of self-compassion and positive body image on this association, as well as explore a possible gender difference. This research not only provides suggestions for parents and educators to increase adolescents’ intuitive eating, but it also identifies significant factors that influence intuitive eating in order to foster relevant practical prevention strategies and interventions.Participants were 2438 students (M = 13.14 years, SD = 1.08) recruited from three middle schools (Grades 7 to 9) in Wuhan, Hubei Province, China. There were 1162 girls (47.7%) and 1276 boys (52.3%). They completed a set of self-report measures on friendship quality, self-compassion, positive body image, and intuitive eating. All the measures have acceptable reliability and validity. The results indicated that after controlling for age, gender, and body mass index, friendship quality was positively associated with intuitive eating. Self-compassion and positive body image mediated this association, which contained three significant mediating pathways: the separate mediating effects of (a) self-compassion and (b) positive body image, and the serial mediating effect of (c) self-compassion and positive body image. In addition, significant differences in mediating effects per gender were only found in the relationship between friendship quality and the dimensions of intuitive eating (“unconditional permission to eat” and “eating for physical rather than emotional reasons”).Our findings highlight the relevance of friendship quality, self-compassion, and positive body image in the understanding of adolescents’ intuitive eating. This study suggests that parents should create a warm and friendly family atmosphere which will contribute to adolescents’ peer relationships and friendships. Educators should direct students to be compassionate toward their own shortcomings and failures to improve levels of body appreciation and body satisfaction. These factors will play important roles in promoting intuitive eating. Moreover, future interventions for intuitive eating should be designed to increase adolescents’ self-compassion and positive body image through effective intervention approaches and measures.
Subjects: Psychology >> Social Psychology submitted time 2023-03-27 Cooperative journals: 《心理学报》
Abstract： Heterogeneity among mental health issues has always attracted considerable attention, thereby restricting research on mental health and cognitive neuroscience. Additionally, the person-centred approach to personality research, which emphasizes population heterogeneity, has received more attention. On the other hand, the heterogeneity among depressive patients has been a problem that cannot be ignored (most studies ignored the actual situation and directly assumed sample homogeneity). A large number of empirical studies have provided evidence that isolated personality traits are often associated with depression. Only a few studies have considered the probable effect from a taxonomy perspective. Moreover, the neural mechanisms of personality types in depression remain unclear. This study aimed to reveal different personality subtypes of depressive disorders and elucidate subtypes from the perspective of resting-state functional connectivity.Personality and resting-state functional imaging data of 135 depressive patients and 133 controls were collected. First, combined with “depression diagnosis”, the personality types in depressive patients and controls were identified through functional random forest. Specifically, neuroticism and extraversion (input features) were fitted with the diagnosis of depression by a random forest model. The random seeds were set to 1234, and 500 decision trees were fitted. The performance of the model was evaluated by tenfold cross-validation. Subsequently, the random forest algorithm generated a proximity matrix that represented the similarity between paired participants. Then, based on the proximity matrix, community detection clustering analysis was conducted on depressive patients and controls, and personality types associated with depression diagnosis were obtained. Finally, we selected nodes of the subcortical network as regions of interest according to the power-264 template and calculated the functional connectivity map of the region of interest to the whole brain. Based on the functional connectivity map, the differences in resting-state functional connectivity between the main types were compared.Personality and resting-state functional imaging data of 159 depressive patients and 156 controls were collected. First, combined with “depression diagnosis”, the personality types in depressive patients and controls were identified through functional random forest. Specifically, neuroticism and extraversion (input features) were fitted with the diagnosis of depression by a random forest model. The random seeds were set to 1234, and 500 decision trees were fitted. The performance of the model was evaluated by tenfold cross-validation. Subsequently, the random forest algorithm generated a proximity matrix that represented the similarity between paired participants. Then, based on the proximity matrix, community detection clustering analysis was conducted on depressive patients and controls, and personality types associated with depression diagnosis were obtained. Finally, we selected the amygdala, hippocampus, insula (AAL atlas) and limbic network, default network, and control network (Schaefer-Yeo template) as regions of interest and calculated the functional connectivity of the subcortical regions to the networks. ANOVA was used to compare resting-state functional connectivity between the personality types.The results showed the following. (1) Depression was more common among individuals with high neuroticism and low extraversion tendencies, but there were also individuals with low neuroticism and high extraversion tendencies. The controls were more likely to be individuals with low neuroticism and high extraversion. (2) The results of resting-state functional connectivity showed no significant difference between depression and controls. (3) The functional connectivity strength of the left amygdala/insula-limbic network was significantly different across personality subtypes.In summary, the personality subtypes of depression identified by person-centred perspectives are more in line with reality and individual cognitive patterns, and they have potential clinical adaptive value. The findings of this study enhance the understanding of heterogeneity among depressive disorders.
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 >> Developmental Psychology Subjects: Psychology >> Psychological Measurement submitted time 2022-11-20
Abstract：
The development of natural language processing has offered reliable and valid research methods for exploring the relationship between semantic distance and creative thinking. There are more and more studies in this direction in recent years. However, the research findings are inconsistent in this direction. Based on the Associative Theory of Creativity and the Spreading#2;Activation Model, the present study investigated the relationship between semantic distance and creative thinking by using a meta-analysis method. The reasons for the inconsistency of previous studies in this line of research were also analyzed. The current research involved 14 studies and extracted 53 effect sizes from 4729 subjects. The random effect model was used for the meta#2;analysis. The results showed that there was a moderate positive correlation between semantic distance and creative thinking (r = 0.379, 95%CI [0.300, 0.452]). The meta-regression analysis found that the correlation was moderated by the age of participants and dimensions of creative thinking. Specifically, the results suggested that the correlation between semantic distance and creative thinking decreased with the increase in the age of participants. In addition, flexibility had a higher correlation coefficient with semantic distance than originality and fluency. However, elaboration had a negative correlation with semantic distance. This is the potential reason for the inconsistent results in previous studies. The current study provides new perspectives and explanations for exploring cognitive and neural mechanisms of creativity. It contributes to the exploration of the relationship between semantic distance and creative thinking. The current study offers better scientific evidence and important implications for interpreting, predicting, and improving creativity.
Peer Review Status:
Awaiting Review
Subjects: Psychology >> Personality Psychology submitted time 2022-11-18
Abstract：
Heterogeneity among mental health issues has always attracted considerable attention, thereby restricting research on mental health and cognitive neuroscience. Additionally, the person-centred approach to personality research, which emphasizes population heterogeneity, has received more attention. On the other hand, the heterogeneity among depressive patients has been a problem that cannot be ignored (most studies ignored the actual situation and directly assumed sample homogeneity). A large number of empirical studies have provided evidence that isolated personality traits are often associated with depression. Only a few studies have considered the probable effect from a taxonomy perspective. Moreover, the neural mechanisms of personality types in depression remain unclear. This study aimed to reveal different personality subtypes of depressive disorders and elucidate subtypes from the perspective of resting-state functional connectivity. Personality and resting-state functional imaging data of 135 depressive patients and 133 controls were collected. First, combined with "depression diagnosis", the personality types in depressive patients and controls were identified through functional random forest. Specifically, neuroticism and extraversion (input features) were fitted with the diagnosis of depression by a random forest model. The random seeds were set to 1234, and 500 decision trees were fitted. The performance of the model was evaluated by tenfold cross-validation. Subsequently, the random forest algorithm generated a proximity matrix that represented the similarity between paired participants. Then, based on the proximity matrix, community detection clustering analysis was conducted on depressive patients and controls, and personality types associated with depression diagnosis were obtained. Finally, we selected nodes of the subcortical network as regions of interest according to the power-264 template and calculated the functional connectivity map of the region of interest to the whole brain. Based on the functional connectivity map, the differences in resting-state functional connectivity between the main types were compared. Personality and resting-state functional imaging data of 159 depressive patients and 156 controls were collected. First, combined with "depression diagnosis", the personality types in depressive patients and controls were identified through functional random forest. Specifically, neuroticism and extraversion (input features) were fitted with the diagnosis of depression by a random forest model. The random seeds were set to 1234, and 500 decision trees were fitted. The performance of the model was evaluated by tenfold cross-validation. Subsequently, the random forest algorithm generated a proximity matrix that represented the similarity between paired participants. Then, based on the proximity matrix, community detection clustering analysis was conducted on depressive patients and controls, and personality types associated with depression diagnosis were obtained. Finally, we selected the amygdala, hippocampus, insula (AAL atlas) and limbic network, default network, and control network (Schaefer-Yeo template) as regions of interest and calculated the functional connectivity of the subcortical regions to the networks. ANOVA was used to compare resting-state functional connectivity between the personality types. The results showed the following. (1) Depression was more common among individuals with high neuroticism and low extraversion tendencies, but there were also individuals with low neuroticism and high extraversion tendencies. The controls were more likely to be individuals with low neuroticism and high extraversion. (2) The results of resting-state functional connectivity showed no significant difference between depression and controls. (3) The functional connectivity strength of the left amygdala/insula-limbic network was significantly different across personality subtypes. In summary, the personality subtypes of depression identified by person-centred perspectives are more in line with reality and individual cognitive patterns, and they have potential clinical adaptive value. The findings of this study enhance the understanding of heterogeneity among depressive disorders.
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