Subjects: Psychology >> Developmental Psychology submitted time 2023-03-28 Cooperative journals: 《心理科学进展》
Abstract： Language lateralization is one of the most obvious characteristics of brain functional lateralization. Previous neuroimaging studies identified numerous brain regions associated with language lateralization, such as the frontal and temporal lobes, the cingulate and fusiform gyrus, the supplementary motor area, and so on.This review synthesizes current published literature relevant to language lateralization, with an emphasis on handedness and functional connectivity. Our findings show that language lateralization is positively correlated with handedness and intra-hemisphere connectivity but is negatively correlated with inter-hemispheric connectivity. Moreover, the left- and right-handers exhibit different correlation profiles between language lateralization and functional connectivity. We discuss the relationship between language lateralization, handedness, and functional connectivity, and we propose areas for further research.
Subjects: Psychology >> Social Psychology submitted time 2023-03-27 Cooperative journals: 《心理学报》
Abstract： Impulsivity is a typical characteristic of drug addiction. In addition to the problems of inhibition and executive control, the driving force from multiple dimensions is also an important reason for impulsive drug use. The psychological drive stems from a variety of sources, including reward effect, S-R related cue response through conditioning. Low levels of inhibition are insufficient to resist the effects of the drive. This leads to an unbalanced state, which results in habitual behavior tendency. Impulsivity has both a behavioral and neural basis. Although impulsivity may be a precursor of drug use, long-term use may also damage brain structures and functions related to the inhibition of impulsive behavior. There is an open question about whether these structures and functions recover after withdrawal. In this research we used multiple imaging methods to study the extent of recovery in heroin addicts who had been abstinent for several years on average. Thirty-five abstinent heroin addicts (26 males; average period of abstinence = 43.55 months) and 26 healthy controls (26 males) were recruited using advertisements in the community. The heroin group and the healthy control group were compared on multiple measures of brain structure and function related to inhibition using the imaging methods of voxel-based morphometry (VBM), amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo). Based on the amplitude of low-frequency fluctuation (ALFF), right inferior frontal gyrus (15, 60, -6) was selected as the region of interest in which to study functional connectivity (FC). Heroin addicts showed damage in inhibition-related brain structures and functions an average of 44 months after withdrawal, and the extent of damage was correlated with lifetime dose. (1) Compared to the healthy control group, the heroin group had significantly (a) lower gray matter volume (p = 0.03) and lower whole-brain volume (p = 0.05); (b) lower gray matter in the right superior frontal gyrus (pAlphaSim < 0.01); (c) higher regional homogeneity in right posterior central gyrus and lower regional homogeneity in right middle frontal gyrus of the orbitofrontal cortex (pAlphaSim < 0.01); (d) lower amplitude of low-frequency fluctuation in right inferior frontal gyrus of the orbitofrontal cortex and left hippocampus (pAlphaSim < 0.01); (e) higher functional connectivity between right inferior frontal gyrus of the orbitofrontal cortex and the right caudate, and lower functional connectivity between the right inferior frontal gyrus and right middle temporal gyrus as well left precentral gyrus (pAlphaSim < 0.01). (2) Within the heroin group, higher lifetime dose of heroin was significantly associated with lower gray matter volume in the right middle temporal gyrus and left middle cingulate (pAlphaSim < 0.01). The results showed that compared to healthy controls, heroin addicts had significant damage in brain structure and functions related to impulsivity even after an average period of 44 months of abstinence. In addition, the extent of damage was correlated with the lifetime dose of heroin. These results suggest that heroin addicts could continue to show impulsive behavior even after several years of abstinence, perhaps explaining the high rate of relapse in this population. Future research could test this conclusion by examining correlations between brain damage in areas related to inhibition and behavioral measures of impulsivity after a period of abstinence. The current evidence underscores the need to take impulsivity into account in relapse prevention programs for heroin addicts.
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： Humans are a social species that are constantly involved in complex relationships, reacting to the actions of others, and intentionally or unintentionally changing our own behavior. Personality traits reflect the behavioral pattern of an individual's response to the environment, which also includes social behavior. In addition, the brain is also an important factor when discussing social networks. The brain provides biological mechanisms for human behavior, while social networks provide external triggers for these behaviors. Linking personality traits and brain activity to social networks can help us better understand the structure of group relationships, improve our understanding of individual human beings, and help us better predict individual social behaviors and find the rules of information transmission in interpersonal relationships. From the perspective of a network, we collected nine social networks from 94 undergraduate students in the same grade according to their different social needs. We used the graph theory and resting-state functional magnetic resonance imaging to explore the influence of personality traits on social networks based on individual popularity and closeness between individuals and the relationship between the similarity of brain resting-state functional connectivity and social distance between individuals. Specifically, regression analysis was carried out, with personality traits as the independent variables and the different degrees of social networks as the dependent variables. Then, a correlation analysis was performed for the social distance and similarity of personality traits. Finally, the correlation between the similarity of the brain networks and social distance was calculated. The results showed that (1) individuals with high conscientiousness were more popular in social networks requiring "trust" traits, while individuals with high agreeableness were more popular in social networks requiring "fun" traits. These findings showed that in the same group, there are different social networks according to social needs, and the popularity of individuals in different social networks is not similar as it will be affected by the corresponding personality traits; (2) In the social networks requiring "shared interests & values, " personality similarity and social distance between individuals were significantly negatively correlated. Personality similarity promotes interpersonal communication between individuals, which may be realized through interpersonal attraction induced by the similarity of values and interests; (3) In the same social network, there is a significantly negative correlation between similarities in functional connections (FCs) and social distance among individuals, and these FCs are mainly concentrated in the fronto-parietal task control network and the dorsal attention network. The similarity of resting brain FCs among individuals may promote interpersonal communication, possibly due to the similarity of individuals in cognitive control and environmental processing bias, which increases the interpersonal attraction and shortening the social distance between individuals. The results revealed the influence of personality traits on the structure of different social networks, the relationship between personality trait similarity among individuals, and the similarity between resting brain networks and social distance, which has important implications for understanding the structure of social networks, the formation rules, and the information transmission rules among them. In addition, this study discussed the relationship between the similarity of resting-state FC and social distance, providing new evidence for studies on brain synchronization in interpersonal communication and brain imaging evidence for the study of the relationship between the similarity of personality traits and social distance.#social networks, personality traits, resting-state functional connectivity
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 >> 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.
Peer Review Status:
Awaiting Review
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 >> Social Psychology submitted time 2021-07-27
Abstract： " "
Peer Review Status:Awaiting Review
Subjects: Psychology >> Applied Psychology Subjects: Psychology >> Clinical and Counseling Psychology submitted time 2021-03-26
Abstract： "
Peer Review Status:Awaiting Review
Hits
Hits
Downloads
Comment