Psychological Network Analysis of General Self-Efficacy in High vs. Low Resilient Functioning Healthy Adults.

Resilience to stress has gained increasing interest by researchers from the field of mental health and illness and some recent studies have investigated resilience from a network perspective. General self-efficacy constitutes an important resilience factor. High levels of self-efficacy have shown to promote resilience by serving as a stress buffer. However, little is known about the role of network connectivity of self-efficacy in the context of stress resilience. The present study aims at filling this gap by using psychological network analysis to study self-efficacy and resilience. Based on individual resilient functioning scores, we divided a sample of 875 mentally healthy adults into a high and low resilient functioning group. To compute these scores, we applied a novel approach based on Partial Least Squares Regression on self-reported stress and mental health measures. Separately for both groups, we then estimated regularized partial correlation networks of a ten-item self-efficacy questionnaire. We compared three different global connectivity measures-strength, expected influence, and shortest path length-as well as absolute levels of self-efficacy between the groups. Our results supported our hypothesis that stronger network connectivity of self-efficacy would be present in the highly resilient functioning group compared to the low resilient functioning group. In addition, the former showed higher absolute levels of general self-efficacy. Future research could consider using partial least squares regression to quantify resilient functioning to stress and to study the association between network connectivity and resilient functioning in other resilience factors

Development of human functional and structural brain networks in adolescence and its relevance to psychiatric disorders

The human brain undergoes various phases of active development during the lifespan. While these neurodevelopmental processes are fundamental to the emergence of new cognitive and social capacities, they also coincide with a period of increased risk of neuropsychiatric disorders, which generally have their highest rates of clinical incidence in the first two decades. Since many neuropsychiatric disorders display sex differences in both prevalence or clinical presentation, this raises the question of whether there are underlying sex differences in processes of adolescent brain development. In this thesis, functional and structural magnetic resonance imaging (MRI) is used to map normative brain development, in adolescence and later life, which might differentially predispose men and women to different levels of risk for adolescent and adult mental illness. First, Chapter 1 reviews relevant research on understanding developmental changes in the brain during adolescence, focusing on prior studies of normative sexual differentiation of neurodevelopmental trajectories, and vulnerabilities associated with developmental changes. Chapter 2 investigates whether there are sex differences in normative adolescent development of *functional* connectivity networks, using an accelerated longitudinal cohort of healthy adolescents aged 14-25 years (N=298), comprising 2 or 3 repeated scans on most participants. Sexually divergent development of functional connectivity was identified in the default mode network, limbic cortex, and subcortical structures. In these regions, females were shown to have a more “disruptive” pattern of development, whereby weak functional connectivity at age 14 became stronger during adolescence, specifically in a cortico-subcortical system including many areas of the default mode network. Using open data on whole genome transcription at multiple sites in adult post mortem brains (provided by the Allen Brain Institute), this fMRI-derived map of sexually divergent brain network development was found to be spatially co-located with brain regions where transcription was enriched for genes on the X chromosome and neurodevelopmentally relevant genes. Chapter 3 starts from the hypothesis that the known sex difference in the prevalence of major depressive disorder (MDD), with increased rates of diagnosis in adolescent females compared to males, could be the psychological or clinical representation of underlying sex differences in adolescent brain network development. To test this hypothesis, the sexually differentiated fMRI network identified in the previous chapter was further contextualized. The fMRI-derived map of sexually divergent brain network development was found to be co- located with prior loci of reward-related brain activation; a map of functional dysconnectivity in major depressive disorder derived from a prior, independent case-control study of adult MDD; and an adult brain gene transcriptional profile enriched for MDD risk genes, as defined by prior genome-wide association studies of MDD. These results collectively suggested that normative sexual divergence in adolescent development of a cortico-subcortical brain functional network was psychologically, anatomically and genetically relevant to depression. Chapter 4 reviews literature on similarity-based *structural* brain networks. Subsequently, Chapter 5 investigates adolescent changes in structural brain network development using morphometric similarity networks derived from the same accelerated longitudinal cohort of healthy adolescents previously used for analysis of functional network development. Morphometric similarity was found to increase during adolescence in insula and limbic regions and to decrease elsewhere in the brain. This profile of decreasing morphometric similarity, or increasing dissimilarity, was associated with the well-known adolescent process of cortical shrinkage, i.e., reduced macro-structural measures of cortical thickness, and with increased magnetization transfer, a micro-structural measure of intra-cortical myelination. Regional nodes of the morphometric similarity networks that became more dissimilar, putatively more differentiated in terms of their cyto- and myelo-architectonics during adolescence, were also found to de-couple from brain functional connectivity, suggesting that increasing morphometric dissimilarity may reflect adolescent development of functional independence. In an effort to move from group level to subject-specific analyses, and acknowledging that brain development is not restricted to adolescence but is a continuous process throughout life, in Chapter 6 a total of 41 prior studies, including a total of 90,000 structural MRI scans, were aggregated to estimate lifespan trajectories of normative subcortical development from 180 days post conception to 100 years of age. This analysis identified novel milestones of subcortical volume development; in particular a set of subcortical regions was defined that reached peak grey matter volume during adolescence. Furthermore, subject-specific deviations from normative, non-linear neurodevelopmental trajectories? were derived and used to estimate case-control differences in subcortical volume across the lifespan in multiple neuropsychiatric disorders, demonstrating the potential clinical applications of these normative subcortical growth charts. In Chapter 7, these new experimental results on adolescent and life-span development of functional and structural brain networks, and subcortical grey matter volume were summarised and drawn together, highlighting how these insights are aligned with each other and with the existing scientific literature on brain development, sexual differentiation and risk of psychiatric disorders.Gates Cambridg

The genetic relationships between brain structure and schizophrenia

Abstract Genetic risks for schizophrenia are theoretically mediated by genetic effects on brain structure but it has been unclear which genes are associated with both schizophrenia and cortical phenotypes. We accessed genome-wide association studies (GWAS) of schizophrenia (N = 69,369 cases; 236,642 controls), and of three magnetic resonance imaging (MRI) metrics (surface area, cortical thickness, neurite density index) measured at 180 cortical areas (N = 36,843, UK Biobank). Using Hi-C-coupled MAGMA, 61 genes were significantly associated with both schizophrenia and one or more MRI metrics. Whole genome analysis with partial least squares demonstrated significant genetic covariation between schizophrenia and area or thickness of most cortical regions. Genetic similarity between cortical areas was strongly coupled to their phenotypic covariance, and genetic covariation between schizophrenia and brain phenotypes was strongest in the hubs of structural covariance networks. Pleiotropically associated genes were enriched for neurodevelopmental processes and positionally concentrated in chromosomes 3p21, 17q21 and 11p11. Mendelian randomization analysis indicated that genetically determined variation in a posterior cingulate cortical area could be causal for schizophrenia. Parallel analyses of GWAS on bipolar disorder, Alzheimer’s disease and height showed that pleiotropic association with MRI metrics was stronger for schizophrenia compared to other disorders

The genetic relationships between brain structure and schizophrenia

Acknowledgements: E.-M.S. is supported by a PhD studentship awarded by the Friends of Peterhouse. This research was co-funded by the National Institute of Health Research (NIHR) Cambridge Biomedical Research Centre and a Marmaduke Sheild grant to R.A.I.B. and V.W. E.T.B. is an NIHR Senior Investigator. R.A.I.B. is supported by a British Academy Post-Doctoral fellowship and the Autism Research Trust. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. This research was possible due to an application to the UK Biobank (project 20904). We thank Dr Agoston Mihalik for his advice on partial least squares regression analysis.Funder: E.-M.S. is supported by a PhD studentship awarded by the Friends of Peterhouse. This research was co-funded by the National Institute of Health Research (NIHR) Cambridge Biomedical Research Centre and a Marmaduke Sheild grant to R.A.I.B. and V.W.Genetic risks for schizophrenia are theoretically mediated by genetic effects on brain structure but it has been unclear which genes are associated with both schizophrenia and cortical phenotypes. We accessed genome-wide association studies (GWAS) of schizophrenia (N = 69,369 cases; 236,642 controls), and of three magnetic resonance imaging (MRI) metrics (surface area, cortical thickness, neurite density index) measured at 180 cortical areas (N = 36,843, UK Biobank). Using Hi-C-coupled MAGMA, 61 genes were significantly associated with both schizophrenia and one or more MRI metrics. Whole genome analysis with partial least squares demonstrated significant genetic covariation between schizophrenia and area or thickness of most cortical regions. Genetic similarity between cortical areas was strongly coupled to their phenotypic covariance, and genetic covariation between schizophrenia and brain phenotypes was strongest in the hubs of structural covariance networks. Pleiotropically associated genes were enriched for neurodevelopmental processes and positionally concentrated in chromosomes 3p21, 17q21 and 11p11. Mendelian randomization analysis indicated that genetically determined variation in a posterior cingulate cortical area could be causal for schizophrenia. Parallel analyses of GWAS on bipolar disorder, Alzheimer’s disease and height showed that pleiotropic association with MRI metrics was stronger for schizophrenia compared to other disorders

Sexually divergent development of depression-related brain networks during healthy human adolescence.

Funder: MQ: Transforming Mental Health; Grant(s): MQF17_24Sexual differences in human brain development could be relevant to sex differences in the incidence of depression during adolescence. We tested for sex differences in parameters of normative brain network development using fMRI data on N = 298 healthy adolescents, aged 14 to 26 years, each scanned one to three times. Sexually divergent development of functional connectivity was located in the default mode network, limbic cortex, and subcortical nuclei. Females had a more "disruptive" pattern of development, where weak functional connectivity at age 14 became stronger during adolescence. This fMRI-derived map of sexually divergent brain network development was robustly colocated with i prior loci of reward-related brain activation ii a map of functional dysconnectivity in major depressive disorder (MDD), and iii an adult brain gene transcriptional pattern enriched for genes on the X chromosome, neurodevelopmental genes, and risk genes for MDD. We found normative sexual divergence in adolescent development of a cortico-subcortical brain functional network that is relevant to depression.Wellcome Trust collaborative award for the Neuroscience in Psychiatry Network at University College London and the University of Cambridge Wellcome Trust collaborative award for the Neuroimmunology of Mood Disorders and Alzheimer’s Disease (NIMA) (grant number: 104025/Z/14/Z), which was also funded by Janssen, GlaxoSmithKline, Lundbeck and Pfizer. National Institute of Health Research (NIHR) Cambridge Biomedical Research Centre (BRC-1215-20014) Mental Health Theme (ETB). National Institute of Health Research Senior Investigator award (ETB). Gates Cambridge Trust (LD) MQ: Transforming Mental Health grant MQF17_24 (PEV) Alan Turing Institute (SEM) and EPSRC grant EP/N510129/1 (PEV) British Academy Post-Doctoral fellowship (RAIB) Autism Research Trust (RAIB) Cambridge Philosophical Society Henslow Fellowship Lucy Cavendish College, University of Cambridge (SEM) UK Research and Innovation (UKRI) Data to Early Diagnosis and Precision Medicine Industrial Strategy Challenge Fund (FV) MRC Clinical Research Infra-structure award MR/M009041/

Brainhack: Developing a culture of open, inclusive, community-driven neuroscience

Brainhack is an innovative meeting format that promotes scientific collaboration and education in an open, inclusive environment. This NeuroView describes the myriad benefits for participants and the research community and how Brainhacks complement conventional formats to augment scientific progress

Brainhack: Developing a culture of open, inclusive, community-driven neuroscience

Brainhack is an innovative meeting format that promotes scientific collaboration and education in an open, inclusive environment. This NeuroView describes the myriad benefits for participants and the research community and how Brainhacks complement conventional formats to augment scientific progress

Brainhack: Developing a culture of open, inclusive, community-driven neuroscience

Brainhack is an innovative meeting format that promotes scientific collaboration and education in an open, inclusive environment. This NeuroView describes the myriad benefits for participants and the research community and how Brainhacks complement conventional formats to augment scientific progress