المؤلفون: Darbandi, Seyed Samie Alizadeh, Fornito, Alex, Ghasemi, Abdorasoul

مصطلحات موضوعية: Computer Science - Computational Engineering, Finance, and Science

الوصف: Network control theory can be used to model how one should steer the brain between different states by driving a specific region with an input. The needed energy to control a network is often used to quantify its controllability, and controlling brain networks requires diverse energy depending on the selected input region. We use the theory of how input node placement affects the longest control chain (LCC) in the controllability of brain networks to study the role of the architecture of white matter fibers in the required control energy. We show that the energy needed to control human brain networks is related to the LCC, i.e., the longest distance between the input region and other regions in the network. We indicate that regions that control brain networks with lower energy have small LCCs. These regions align with areas that can steer the brain around the state space smoothly. By contrast, regions that need higher energy to move the brain toward different target states have larger LCCs. We also investigate the role of the number of paths between regions in the control energy. Our results show that the more paths between regions, the lower cost needed to control brain networks. We evaluate the number of paths by counting specific motifs in brain networks since determining all paths in graphs is a difficult problem.
Comment: 14 pages, 8 figures

الوصول الحر: http://arxiv.org/abs/2308.00160Test

المؤلفون: Kirschner, Matthias, Hodzic-Santor, Benazir, Antoniades, Mathilde, Nenadic, Igor, Kircher, Tilo, Krug, Axel, Meller, Tina, Grotegerd, Dominik, Fornito, Alex, Arnatkeviciute, Aurina, Bellgrove, Mark A, Tiego, Jeggan, Dannlowski, Udo, Koch, Katharina, Hülsmann, Carina, Kugel, Harald, Enneking, Verena, Klug, Melissa, Leehr, Elisabeth J, Böhnlein, Joscha, Gruber, Marius, Mehler, David, DeRosse, Pamela, Moyett, Ashley, Baune, Bernhard T, Green, Melissa, Quidé, Yann, Pantelis, Christos, Chan, Raymond, Wang, Yi, Ettinger, Ulrich, Debbané, Martin, Derome, Melodie, Gaser, Christian, Besteher, Bianca, Diederen, Kelly, Spencer, Tom J, Fletcher, Paul, Rössler, Wulf, Smigielski, Lukasz, Kumari, Veena, Premkumar, Preethi, Park, Haeme RP, Wiebels, Kristina, Lemmers-Jansen, Imke, Gilleen, James, Allen, Paul, Kozhuharova, Petya, Marsman, Jan-Bernard, Lebedeva, Irina, Tomyshev, Alexander, Mukhorina, Anna, Kaiser, Stefan, Fett, Anne-Kathrin, Sommer, Iris, Schuite-Koops, Sanne, Paquola, Casey, Larivière, Sara, Bernhardt, Boris, Dagher, Alain, Grant, Phillip, van Erp, Theo GM, Turner, Jessica A, Thompson, Paul M, Aleman, André, Modinos, Gemma

المصدر: Molecular Psychiatry. 27(2)

مصطلحات موضوعية: Biological Psychology, Biomedical and Clinical Sciences, Psychology, Brain Disorders, Neurosciences, Serious Mental Illness, Schizophrenia, Clinical Research, Mental Health, Mental health, Good Health and Well Being, Bipolar Disorder, Female, Humans, Magnetic Resonance Imaging, Male, Psychotic Disorders, Schizotypal Personality Disorder, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology

الوصف: Neuroanatomical abnormalities have been reported along a continuum from at-risk stages, including high schizotypy, to early and chronic psychosis. However, a comprehensive neuroanatomical mapping of schizotypy remains to be established. The authors conducted the first large-scale meta-analyses of cortical and subcortical morphometric patterns of schizotypy in healthy individuals, and compared these patterns with neuroanatomical abnormalities observed in major psychiatric disorders. The sample comprised 3004 unmedicated healthy individuals (12-68 years, 46.5% male) from 29 cohorts of the worldwide ENIGMA Schizotypy working group. Cortical and subcortical effect size maps with schizotypy scores were generated using standardized methods. Pattern similarities were assessed between the schizotypy-related cortical and subcortical maps and effect size maps from comparisons of schizophrenia (SZ), bipolar disorder (BD) and major depression (MDD) patients with controls. Thicker right medial orbitofrontal/ventromedial prefrontal cortex (mOFC/vmPFC) was associated with higher schizotypy scores (r = 0.067, pFDR = 0.02). The cortical thickness profile in schizotypy was positively correlated with cortical abnormalities in SZ (r = 0.285, pspin = 0.024), but not BD (r = 0.166, pspin = 0.205) or MDD (r = -0.274, pspin = 0.073). The schizotypy-related subcortical volume pattern was negatively correlated with subcortical abnormalities in SZ (rho = -0.690, pspin = 0.006), BD (rho = -0.672, pspin = 0.009), and MDD (rho = -0.692, pspin = 0.004). Comprehensive mapping of schizotypy-related brain morphometry in the general population revealed a significant relationship between higher schizotypy and thicker mOFC/vmPFC, in the absence of confounding effects due to antipsychotic medication or disease chronicity. The cortical pattern similarity between schizotypy and schizophrenia yields new insights into a dimensional neurobiological continuity across the extended psychosis phenotype.

وصف الملف: application/pdf

الوصول الحر: https://escholarship.org/uc/item/1rd7c365Test

المؤلفون: Mahlberg, Justin, Giddens, Emily, Tiego, Jeggan, Bellgrove, Mark, Fornito, Alex, Verdejo‐Garcia, Antonio

المساهمون: National Health and Medical Research Council

المصدر: International Journal of Eating Disorders ; ISSN 0276-3478 1098-108X

الوصف: Objective Reward‐based eating drives are putative mechanisms of uncontrolled eating implicated in obesity and disordered eating (e.g., binge eating). Uncovering the genetic and environmental contributions to reward‐related eating, and their genetic correlation with BMI, could shed light on key mechanisms underlying eating and weight‐related disorders. Method We conducted a classical twin study to examine how much variance in uncontrolled eating phenotypes and body mass index (BMI) was explained by genetic factors, and the extent that these phenotypes shared common genetic factors. 353 monozygotic twins and 128 dizygotic twins completed the Reward‐based Eating Drive 13 scale, which measures three distinct uncontrolled eating phenotypes (loss of control over eating, preoccupation with thoughts about food, and lack of satiety), and a demographic questionnaire which included height and weight for BMI calculation. We estimated additive genetic (A), common environmental (C), and unique environmental (E) factors for each phenotype, as well as their genetic correlations, with a multivariate ACE model. A common pathway model also estimated whether genetic variance in the uncontrolled eating phenotypes was better explained by a common latent uncontrolled eating factor. Results There were moderate genetic correlations between uncontrolled eating phenotypes and BMI (.26–.41). Variance from the uncontrolled eating phenotypes was also best explained by a common latent uncontrolled eating factor that was explained by additive genetic factors (52%). Discussion These results suggest that uncontrolled eating phenotypes are heritable traits that also share genetic variance with BMI. This has implications for understanding the cognitive mechanisms that underpin obesity and disordered eating. Public Significance Our study clarifies the degree to which uncontrolled eating phenotypes and BMI are influenced by shared genetics and shows that vulnerability to uncontrolled eating traits is impacted by common genetic factors.

الإتاحة: https://doi.org/10.1002/eat.24179Test

المؤلفون: Cao, Trang, Pang, James C., Segal, Ashlea, Chen, Yu‐Chi, Aquino, Kevin M., Breakspear, Michael, Fornito, Alex

المساهمون: National Health and Medical Research Council, Sylvia and Charles Viertel Charitable Foundation, Australian Research Council

المصدر: Human Brain Mapping ; volume 45, issue 4 ; ISSN 1065-9471 1097-0193

الوصف: Voxel‐based morphometry (VBM) and surface‐based morphometry (SBM) are two widely used neuroimaging techniques for investigating brain anatomy. These techniques rely on statistical inferences at individual points (voxels or vertices), clusters of points, or a priori regions‐of‐interest. They are powerful tools for describing brain anatomy, but offer little insights into the generative processes that shape a particular set of findings. Moreover, they are restricted to a single spatial resolution scale, precluding the opportunity to distinguish anatomical variations that are expressed across multiple scales. Drawing on concepts from classical physics, here we develop an approach, called mode‐based morphometry (MBM), that can describe any empirical map of anatomical variations in terms of the fundamental, resonant modes—eigenmodes—of brain anatomy, each tied to a specific spatial scale. Hence, MBM naturally yields a multiscale characterization of the empirical map, affording new opportunities for investigating the spatial frequency content of neuroanatomical variability. Using simulated and empirical data, we show that the validity and reliability of MBM are either comparable or superior to classical vertex‐based SBM for capturing differences in cortical thickness maps between two experimental groups. Our approach thus offers a robust, accurate, and informative method for characterizing empirical maps of neuroanatomical variability that can be directly linked to a generative physical process.

الإتاحة: https://doi.org/10.1002/hbm.26640Test

المؤلفون: Petrican, Raluca, Fornito, Alex, Boyland, Emma

المساهمون: Sylvia and Charles Viertel Charitable Foundation, National Health and Medical Research Council, National Institutes of Health

المصدر: Biological Psychiatry ; volume 95, issue 5, page 453-464 ; ISSN 0006-3223

مصطلحات موضوعية: Biological Psychiatry

الإتاحة: https://doi.org/10.1016/j.biopsych.2023.06.023Test
https://api.elsevier.com/content/article/PII:S0006322323013963?httpAccept=text/xmlTest
https://api.elsevier.com/content/article/PII:S0006322323013963?httpAccept=text/plainTest

المؤلفون: Bian, Lingbin, Cui, Tiangang, Yeo, B. T. Thomas, Fornito, Alex, Razi, Adeel, Keith, Jonathan

مصطلحات موضوعية: Quantitative Biology - Neurons and Cognition, Statistics - Machine Learning

الوصف: Brain function relies on a precisely coordinated and dynamic balance between the functional integration and segregation of distinct neural systems. Characterizing the way in which neural systems reconfigure their interactions to give rise to distinct but hidden brain states remains an open challenge. In this paper, we propose a Bayesian model-based characterization of latent brain states and showcase a novel method based on posterior predictive discrepancy using the latent block model to detect transitions between latent brain states in blood oxygen level-dependent (BOLD) time series. The set of estimated parameters in the model includes a latent label vector that assigns network nodes to communities, and also block model parameters that reflect the weighted connectivity within and between communities. Besides extensive in-silico model evaluation, we also provide empirical validation (and replication) using the Human Connectome Project (HCP) dataset of 100 healthy adults. Our results obtained through an analysis of task-fMRI data during working memory performance show appropriate lags between external task demands and change-points between brain states, with distinctive community patterns distinguishing fixation, low-demand and high-demand task conditions.

الوصول الحر: http://arxiv.org/abs/2101.10617Test

المؤلفون: Arenella, Martina, Cadby, Gemma, De Witte, Ward, Jones, Rachel M., Whitehouse, Andrew J. O., Moses, Eric K., Fornito, Alex, Bellgrove, Mark A., Hawi, Ziarih, Johnson, Beth, Tiego, Jeggan, Buitelaar, Jan K., Kiemeney, Lambertus A., Poelmans, Geert, Bralten, Janita (ORCID 0000-0003-1440-8675)

المصدر: Autism: The International Journal of Research and Practice. Feb 2022 26(2):361-372.

تمت مراجعته من قبل الزملاء: Y

Page Count: 12

الواصفات: Autism, Pervasive Developmental Disorders, Genetics, Symptoms (Individual Disorders), Attention, Etiology, Imagination, Cognitive Processes, Interpersonal Competence

مستخلص: The clinical heterogeneity of autism spectrum disorders majorly challenges their genetic study. Autism spectrum disorders symptoms occur in milder forms in the general population, as autistic-like traits, and share genetic factors with autism spectrum disorders. Here, we investigate the genetics of individual autistic-like traits to improve our understanding of autism spectrum disorders. We meta-analysed four population-based genome-wide association studies investigating four autistic-like traits -- 'attention-to-detail', 'imagination', 'rigidity' and 'social-skills' (n = 4600). Using autism spectrum disorder summary statistics from the Psychiatric Genomic Consortium (N = 46,350), we applied polygenic risk score analyses to understand the genetic relationship between autism spectrum disorders and autistic-like traits. Using MAGMA, we performed gene-based and gene co-expression network analyses to delineate involved genes and pathways. We identified two novel genome-wide significant loci -- rs6125844 and rs3731197 -- associated with 'attention-to-detail'. We demonstrated shared genetic aetiology between autism spectrum disorders and 'rigidity'. Analysing top variants and genes, we demonstrated a role of the immune-related genes "RNF114," "CDKN2A," "KAZN," "SPATA2" and "ZNF816A" in autistic-like traits. Brain-based genetic expression analyses further linked autistic-like traits to genes involved in immune functioning, and neuronal and synaptic signalling. Overall, our findings highlight the potential of the autistic-like trait-based approach to address the challenges of genetic research in autism spectrum disorders. We provide novel insights showing a potential role of the immune system in specific autism spectrum disorder dimensions.

Abstractor: As Provided

المؤلفون: Oldham, Stuart, Fulcher, Ben, Parkes, Linden, Arnatkeviciute, Aurina, Suo, Chao, Fornito, Alex

مصطلحات موضوعية: Computer Science - Social and Information Networks

الوصف: The roles of different nodes within a network are often understood through centrality analysis, which aims to quantify the capacity of a node to influence, or be influenced by, other nodes via its connection topology. Many different centrality measures have been proposed, but the degree to which they offer unique information, and such whether it is advantageous to use multiple centrality measures to define node roles, is unclear. Here we calculate correlations between 17 different centrality measures across 212 diverse real-world networks, examine how these correlations relate to variations in network density and global topology, and investigate whether nodes can be clustered into distinct classes according to their centrality profiles. We find that centrality measures are generally positively correlated to each other, the strength of these correlations varies across networks, and network modularity plays a key role in driving these cross-network variations. Data-driven clustering of nodes based on centrality profiles can distinguish different roles, including topological cores of highly central nodes and peripheries of less central nodes. Our findings illustrate how network topology shapes the pattern of correlations between centrality measures and demonstrate how a comparative approach to network centrality can inform the interpretation of nodal roles in complex networks.
Comment: Main text (25 pages, 8 figures, 1 table), supplementary information (16 pages, 2 tables) and supplementary figures (17 figures)

الوصول الحر: http://arxiv.org/abs/1805.02375Test

المؤلفون: Ilioska, Iva, Oldehinkel, Marianne, Llera, Alberto, Chopra, Sidhant, Looden, Tristan, Chauvin, Roselyne, van Rooij, Daan, Floris, Dorothea L, Tillmann, Julian, Moessnang, Carolin, Banaschewski, Tobias, Holt, Rosemary J, Loth, Eva, Charman, Tony, Murphy, Declan G M, Ecker, Christine, Mennes, Maarten, Beckmann, Christian F, Fornito, Alex, Buitelaar, Jan K

المصدر: Ilioska, Iva; Oldehinkel, Marianne; Llera, Alberto; Chopra, Sidhant; Looden, Tristan; Chauvin, Roselyne; van Rooij, Daan; Floris, Dorothea L; Tillmann, Julian; Moessnang, Carolin; Banaschewski, Tobias; Holt, Rosemary J; Loth, Eva; Charman, Tony; Murphy, Declan G M; Ecker, Christine; Mennes, Maarten; Beckmann, Christian F; Fornito, Alex; Buitelaar, Jan K (2023). Connectome-wide Mega-analysis Reveals Robust Patterns of Atypical Functional Connectivity in Autism. Biological Psychiatry, 94(1):29-39.

مصطلحات موضوعية: Institute of Psychology, 150 Psychology, Canonical correlation, Functional connectivity, Hyperconnectivity, Networks, Resting-state

الوصف: Background Neuroimaging studies of functional connectivity (FC) in autism have been hampered by small sample sizes and inconsistent findings with regard to whether connectivity is increased or decreased in individuals with autism, whether these alterations affect focal systems or reflect a brain-wide pattern, and whether these are age and/or sex dependent. Methods The study included resting-state functional magnetic resonance imaging and clinical data from the EU-AIMS LEAP (European Autism Interventions Longitudinal European Autism Project) and the ABIDE (Autism Brain Imaging Data Exchange) 1 and 2 initiatives of 1824 (796 with autism) participants with an age range of 5–58 years. Between-group differences in FC were assessed, and associations between FC and clinical symptom ratings were investigated through canonical correlation analysis. Results Autism was associated with a brainwide pattern of hypo- and hyperconnectivity. Hypoconnectivity predominantly affected sensory and higher-order attentional networks and correlated with social impairments, restrictive and repetitive behavior, and sensory processing. Hyperconnectivity was observed primarily between the default mode network and the rest of the brain and between cortical and subcortical systems. This pattern was strongly associated with social impairments and sensory processing. Interactions between diagnosis and age or sex were not statistically significant. Conclusions The FC alterations observed, which primarily involve hypoconnectivity of primary sensory and attention networks and hyperconnectivity of the default mode network and subcortex with the rest of the brain, do not appear to be age or sex dependent and correlate with clinical dimensions of social difficulties, restrictive and repetitive behaviors, and alterations in sensory processing. These findings suggest that the observed connectivity alterations are stable, trait-like features of autism that are related to the main symptom domains of the condition.

وصف الملف: application/pdf

العلاقة: https://www.zora.uzh.ch/id/eprint/255767/1/1_s2.0_S0006322322018522_main.pdfTest; info:pmid/36925414; urn:issn:0006-3223

الإتاحة: https://doi.org/10.5167/uzh-25576710.1016/j.biopsych.2022.12.018Test
https://www.zora.uzh.ch/id/eprint/255767Test/
https://www.zora.uzh.ch/id/eprint/255767/1/1_s2.0_S0006322322018522_main.pdfTest

المؤلفون: Segal, Ashlea, Parkes, Linden, Aquino, Kevin, Kia, Seyed Mostafa, Wolfers, Thomas, Franke, Barbara, Hoogman, Martine, Beckmann, Christian F., Westlye, Lars T., Andreassen, Ole A., Zalesky, Andrew, Harrison, Ben J., Davey, Christopher G., Soriano-Mas, Carles, Cardoner, Narcís, Tiego, Jeggan, Yücel, Murat, Braganza, Leah, Suo, Chao, Berk, Michael, Cotton, Sue, Bellgrove, Mark A., Marquand, Andre F., Fornito, Alex

المصدر: Segal , A , Parkes , L , Aquino , K , Kia , S M , Wolfers , T , Franke , B , Hoogman , M , Beckmann , C F , Westlye , L T , Andreassen , O A , Zalesky , A , Harrison , B J , Davey , C G , Soriano-Mas , C , Cardoner , N , Tiego , J , Yücel , M , Braganza , L , Suo , C , Berk , M , Cotton , S , Bellgrove , M A , Marquand , A F ....

مصطلحات موضوعية: Attention Deficit Disorder with Hyperactivity, Autism Spectrum Disorder, Bipolar Disorder, Brain, Gray Matter, Humans, Magnetic Resonance Imaging, Obsessive-Compulsive Disorder

الوصف: The substantial individual heterogeneity that characterizes people with mental illness is often ignored by classical case–control research, which relies on group mean comparisons. Here we present a comprehensive, multiscale characterization of the heterogeneity of gray matter volume (GMV) differences in 1,294 cases diagnosed with one of six conditions (attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, depression, obsessive–compulsive disorder and schizophrenia) and 1,465 matched controls. Normative models indicated that person-specific deviations from population expectations for regional GMV were highly heterogeneous, affecting the same area in <7% of people with the same diagnosis. However, these deviations were embedded within common functional circuits and networks in up to 56% of cases. The salience–ventral attention system was implicated transdiagnostically, with other systems selectively involved in depression, bipolar disorder, schizophrenia and attention-deficit/hyperactivity disorder. Phenotypic differences between cases assigned the same diagnosis may thus arise from the heterogeneous localization of specific regional deviations, whereas phenotypic similarities may be attributable to the dysfunction of common functional circuits and networks.

العلاقة: https://research.tilburguniversity.edu/en/publications/4c483f6e-ada5-4d69-ae96-33dfb4367a9cTest

الإتاحة: https://doi.org/10.1038/s41593-023-01404-6Test
https://research.tilburguniversity.edu/en/publications/4c483f6e-ada5-4d69-ae96-33dfb4367a9cTest
http://www.scopus.com/inward/record.url?scp=85168113319&partnerID=8YFLogxKTest