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Item does not contain fulltext, Urbanicity is a growing environmental challenge for mental health. Here, we investigate correlations of urbanicity with brain structure and function, neuropsychology and mental illness symptoms in young people from China and Europe (total n = 3,867). We developed a remote-sensing satellite measure (UrbanSat) to quantify population density at any point on Earth. UrbanSat estimates of urbanicity were correlated with brain volume, cortical surface area and brain network connectivity in the medial prefrontal cortex and cerebellum. UrbanSat was also associated with perspective-taking and depression symptoms, and this was mediated by neural variables. Urbanicity effects were greatest when urban exposure occurred in childhood for the cerebellum, and from childhood to adolescence for the prefrontal cortex. As UrbanSat can be generalized to different geographies, it may enable assessments of correlations of urbanicity with mental illness and resilience globally.

Item does not contain fulltext, Urbanicity is a growing environmental challenge for mental health. Here, we investigate correlations of urbanicity with brain structure and function, neuropsychology and mental illness symptoms in young people from China and Europe (total n = 3,867). We developed a remote-sensing satellite measure (UrbanSat) to quantify population density at any point on Earth. UrbanSat estimates of urbanicity were correlated with brain volume, cortical surface area and brain network connectivity in the medial prefrontal cortex and cerebellum. UrbanSat was also associated with perspective-taking and depression symptoms, and this was mediated by neural variables. Urbanicity effects were greatest when urban exposure occurred in childhood for the cerebellum, and from childhood to adolescence for the prefrontal cortex. As UrbanSat can be generalized to different geographies, it may enable assessments of correlations of urbanicity with mental illness and resilience globally.

Item does not contain fulltext, Most psychopathological disorders develop in adolescence. The biological basis for this development is poorly understood. To enhance diagnostic characterization and develop improved targeted interventions, it is critical to identify behavioural symptom groups that share neural substrates. We ran analyses to find relationships between behavioural symptoms and neuroimaging measures of brain structure and function in adolescence. We found two symptom groups, consisting of anxiety/depression and executive dysfunction symptoms, respectively, that correlated with distinct sets of brain regions and inter-regional connections, measured by structural and functional neuroimaging modalities. We found that the neural correlates of these symptom groups were present before behavioural symptoms had developed. These neural correlates showed case-control differences in corresponding psychiatric disorders, depression and attention deficit hyperactivity disorder in independent clinical samples. By characterizing behavioural symptom groups based on shared neural mechanisms, our results provide a framework for developing a classification system for psychiatric illness that is based on quantitative neurobehavioural measures.

Item does not contain fulltext, Most psychopathological disorders develop in adolescence. The biological basis for this development is poorly understood. To enhance diagnostic characterization and develop improved targeted interventions, it is critical to identify behavioural symptom groups that share neural substrates. We ran analyses to find relationships between behavioural symptoms and neuroimaging measures of brain structure and function in adolescence. We found two symptom groups, consisting of anxiety/depression and executive dysfunction symptoms, respectively, that correlated with distinct sets of brain regions and inter-regional connections, measured by structural and functional neuroimaging modalities. We found that the neural correlates of these symptom groups were present before behavioural symptoms had developed. These neural correlates showed case-control differences in corresponding psychiatric disorders, depression and attention deficit hyperactivity disorder in independent clinical samples. By characterizing behavioural symptom groups based on shared neural mechanisms, our results provide a framework for developing a classification system for psychiatric illness that is based on quantitative neurobehavioural measures.

Item does not contain fulltext, OBJECTIVE: The authors sought to explore how conduct, hyperactivity/inattention, and emotional symptoms are associated with neural reactivity to social-emotional stimuli, and the extent to which psychosocial stress modulates these relationships. METHOD: Participants were community adolescents recruited as part of the European IMAGEN study. Bilateral amygdala regions of interest were used to assess the relationship between the three symptom domains and functional MRI neural reactivity during passive viewing of dynamic angry and neutral facial expressions. Exploratory functional connectivity and whole brain multiple regression approaches were used to analyze how the symptoms and psychosocial stress relate to other brain regions. RESULTS: In response to the social-emotional stimuli, adolescents with high levels of conduct or hyperactivity/inattention symptoms who had also experienced a greater number of stressful life events showed hyperactivity of the amygdala and several regions across the brain. This effect was not observed with emotional symptoms. A cluster in the midcingulate was found to be common to both conduct problems and hyperactivity symptoms. Exploratory functional connectivity analyses suggested that amygdala-precuneus connectivity is associated with hyperactivity/inattention symptoms. CONCLUSIONS: The results link hyperactive amygdala responses and regions critical for top-down emotional processing with high levels of psychosocial stress in individuals with greater conduct and hyperactivity/inattention symptoms. This work highlights the importance of studying how psychosocial stress affects functional brain responses to social-emotional stimuli, particularly in adolescents with externalizing symptoms.

Item does not contain fulltext, OBJECTIVE: The authors sought to explore how conduct, hyperactivity/inattention, and emotional symptoms are associated with neural reactivity to social-emotional stimuli, and the extent to which psychosocial stress modulates these relationships. METHOD: Participants were community adolescents recruited as part of the European IMAGEN study. Bilateral amygdala regions of interest were used to assess the relationship between the three symptom domains and functional MRI neural reactivity during passive viewing of dynamic angry and neutral facial expressions. Exploratory functional connectivity and whole brain multiple regression approaches were used to analyze how the symptoms and psychosocial stress relate to other brain regions. RESULTS: In response to the social-emotional stimuli, adolescents with high levels of conduct or hyperactivity/inattention symptoms who had also experienced a greater number of stressful life events showed hyperactivity of the amygdala and several regions across the brain. This effect was not observed with emotional symptoms. A cluster in the midcingulate was found to be common to both conduct problems and hyperactivity symptoms. Exploratory functional connectivity analyses suggested that amygdala-precuneus connectivity is associated with hyperactivity/inattention symptoms. CONCLUSIONS: The results link hyperactive amygdala responses and regions critical for top-down emotional processing with high levels of psychosocial stress in individuals with greater conduct and hyperactivity/inattention symptoms. This work highlights the importance of studying how psychosocial stress affects functional brain responses to social-emotional stimuli, particularly in adolescents with externalizing symptoms.

Item does not contain fulltext, OBJECTIVE: The authors sought to explore how conduct, hyperactivity/inattention, and emotional symptoms are associated with neural reactivity to social-emotional stimuli, and the extent to which psychosocial stress modulates these relationships. METHOD: Participants were community adolescents recruited as part of the European IMAGEN study. Bilateral amygdala regions of interest were used to assess the relationship between the three symptom domains and functional MRI neural reactivity during passive viewing of dynamic angry and neutral facial expressions. Exploratory functional connectivity and whole brain multiple regression approaches were used to analyze how the symptoms and psychosocial stress relate to other brain regions. RESULTS: In response to the social-emotional stimuli, adolescents with high levels of conduct or hyperactivity/inattention symptoms who had also experienced a greater number of stressful life events showed hyperactivity of the amygdala and several regions across the brain. This effect was not observed with emotional symptoms. A cluster in the midcingulate was found to be common to both conduct problems and hyperactivity symptoms. Exploratory functional connectivity analyses suggested that amygdala-precuneus connectivity is associated with hyperactivity/inattention symptoms. CONCLUSIONS: The results link hyperactive amygdala responses and regions critical for top-down emotional processing with high levels of psychosocial stress in individuals with greater conduct and hyperactivity/inattention symptoms. This work highlights the importance of studying how psychosocial stress affects functional brain responses to social-emotional stimuli, particularly in adolescents with externalizing symptoms.

Contains fulltext : 110133.pdf (publisher's version ) (Open Access), Few studies have looked at the potential of using diffusion tensor imaging (DTI) in conjunction with machine learning algorithms in order to automate the classification of healthy older subjects and subjects with mild cognitive impairment (MCI). Here we apply DTI to 40 healthy older subjects and 33 MCI subjects in order to derive values for multiple indices of diffusion within the white matter voxels of each subject. DTI measures were then used together with support vector machines (SVMs) to classify control and MCI subjects. Greater than 90% sensitivity and specificity was achieved using this method, demonstrating the potential of a joint DTI and SVM pipeline for fast, objective classification of healthy older and MCI subjects. Such tools may be useful for large scale drug trials in Alzheimer's disease where the early identification of subjects with MCI is critical.

Contains fulltext : 109513.pdf (publisher's version ) (Open Access), Previous PET and MRI studies have indicated that the degree to which pathology translates into clinical symptoms is strongly dependent on sex with women more likely to express pathology as a diagnosis of AD, whereas men are more resistant to clinical symptoms in the face of the same degree of pathology. Here we use DTI to investigate the difference between male and female white matter tracts in healthy older participants (24 women, 16 men) and participants with mild cognitive impairment (21 women, 12 men). Differences between control and MCI participants were found in fractional anisotropy (FA), radial diffusion (DR), axial diffusion (DA) and mean diffusion (MD). A significant main effect of sex was also reported for FA, MD and DR indices, with male control and male MCI participants having significantly more microstructural damage than their female counterparts. There was no sex by diagnosis interaction. Male MCIs also had significantly less normalised grey matter (GM) volume than female MCIs. However, in terms of absolute brain volume, male controls had significantly more brain volume than female controls. Normalised GM and WM volumes were found to decrease significantly with age with no age by sex interaction. Overall, these data suggest that the same degree of cognitive impairment is associated with greater structural damage in men compared with women.

Contains fulltext : 110133.pdf (publisher's version ) (Open Access), Few studies have looked at the potential of using diffusion tensor imaging (DTI) in conjunction with machine learning algorithms in order to automate the classification of healthy older subjects and subjects with mild cognitive impairment (MCI). Here we apply DTI to 40 healthy older subjects and 33 MCI subjects in order to derive values for multiple indices of diffusion within the white matter voxels of each subject. DTI measures were then used together with support vector machines (SVMs) to classify control and MCI subjects. Greater than 90% sensitivity and specificity was achieved using this method, demonstrating the potential of a joint DTI and SVM pipeline for fast, objective classification of healthy older and MCI subjects. Such tools may be useful for large scale drug trials in Alzheimer's disease where the early identification of subjects with MCI is critical.

Contains fulltext : 109513.pdf (publisher's version ) (Open Access), Previous PET and MRI studies have indicated that the degree to which pathology translates into clinical symptoms is strongly dependent on sex with women more likely to express pathology as a diagnosis of AD, whereas men are more resistant to clinical symptoms in the face of the same degree of pathology. Here we use DTI to investigate the difference between male and female white matter tracts in healthy older participants (24 women, 16 men) and participants with mild cognitive impairment (21 women, 12 men). Differences between control and MCI participants were found in fractional anisotropy (FA), radial diffusion (DR), axial diffusion (DA) and mean diffusion (MD). A significant main effect of sex was also reported for FA, MD and DR indices, with male control and male MCI participants having significantly more microstructural damage than their female counterparts. There was no sex by diagnosis interaction. Male MCIs also had significantly less normalised grey matter (GM) volume than female MCIs. However, in terms of absolute brain volume, male controls had significantly more brain volume than female controls. Normalised GM and WM volumes were found to decrease significantly with age with no age by sex interaction. Overall, these data suggest that the same degree of cognitive impairment is associated with greater structural damage in men compared with women.

Contains fulltext : 109513.pdf (publisher's version ) (Open Access), Previous PET and MRI studies have indicated that the degree to which pathology translates into clinical symptoms is strongly dependent on sex with women more likely to express pathology as a diagnosis of AD, whereas men are more resistant to clinical symptoms in the face of the same degree of pathology. Here we use DTI to investigate the difference between male and female white matter tracts in healthy older participants (24 women, 16 men) and participants with mild cognitive impairment (21 women, 12 men). Differences between control and MCI participants were found in fractional anisotropy (FA), radial diffusion (DR), axial diffusion (DA) and mean diffusion (MD). A significant main effect of sex was also reported for FA, MD and DR indices, with male control and male MCI participants having significantly more microstructural damage than their female counterparts. There was no sex by diagnosis interaction. Male MCIs also had significantly less normalised grey matter (GM) volume than female MCIs. However, in terms of absolute brain volume, male controls had significantly more brain volume than female controls. Normalised GM and WM volumes were found to decrease significantly with age with no age by sex interaction. Overall, these data suggest that the same degree of cognitive impairment is associated with greater structural damage in men compared with women.

Contains fulltext : 110133.pdf (publisher's version ) (Open Access), Few studies have looked at the potential of using diffusion tensor imaging (DTI) in conjunction with machine learning algorithms in order to automate the classification of healthy older subjects and subjects with mild cognitive impairment (MCI). Here we apply DTI to 40 healthy older subjects and 33 MCI subjects in order to derive values for multiple indices of diffusion within the white matter voxels of each subject. DTI measures were then used together with support vector machines (SVMs) to classify control and MCI subjects. Greater than 90% sensitivity and specificity was achieved using this method, demonstrating the potential of a joint DTI and SVM pipeline for fast, objective classification of healthy older and MCI subjects. Such tools may be useful for large scale drug trials in Alzheimer's disease where the early identification of subjects with MCI is critical.