Functional activity of the caudate mediates the relation between early childhood microstructural variations and elevated metabolic syndrome scores
暂无分享,去创建一个
C. L. Wee | K. Ang | Y. Chong | M. Fortier | M. Tint | Y. Lee | F. Yap | Yu Fu | Jenny Casey Eriksson | Zhen Ming Ngoh | W. Han | Ai Peng Tan | Michael Meaney | P. Gluckman | A. P. Tan | Pei Huang | Marissa R. Lee | Peter Gluckman | Michael J Meaney
[1] P. Gluckman,et al. Functional connectivity analysis of childhood depressive symptoms , 2023, NeuroImage: Clinical.
[2] L. Mazzone,et al. Exploring the Link between ADHD and Obesity: A Focus on Temperament , 2022, Brain sciences.
[3] J. Zhou,et al. Structure-function coupling within the reward network in preschool children predicts executive functioning in later childhood , 2022, Developmental Cognitive Neuroscience.
[4] Lauren L. Cloutman,et al. Combination of structural and functional connectivity explains unique variation in specific domains of cognitive function , 2021, NeuroImage.
[5] V. Mahajan,et al. Systematic Review of Different Neuroimaging Correlates in Mild Cognitive Impairment and Alzheimer’s Disease , 2021, Clinical Neuroradiology.
[6] P. Gluckman,et al. Association of increased abdominal adiposity at birth with altered ventral caudate microstructure , 2021, International Journal of Obesity.
[7] A. Dagher,et al. Spontaneous neural activity changes after bariatric surgery: A resting-state fMRI study , 2021, NeuroImage.
[8] H. Garavan,et al. Multimodal brain predictors of current weight and weight gain in children enrolled in the ABCD study ® , 2021, Developmental Cognitive Neuroscience.
[9] P. Weiss,et al. Control of response interference: caudate nucleus contributes to selective inhibition , 2020, Scientific Reports.
[10] Sachiyo Ozawa,et al. Caudate Functional Connectivity Associated With Weight Change in Adolescents , 2020, Frontiers in Human Neuroscience.
[11] Paul C Fletcher,et al. Childhood Obesity, Cortical Structure, and Executive Function in Healthy Children , 2019, Cerebral cortex.
[12] Alain Dagher,et al. Age-related differences in the structural and effective connectivity of cognitive control: a combined fMRI and DTI study of mental arithmetic , 2019, Neurobiology of Aging.
[13] S. Cortese. The Association between ADHD and Obesity: Intriguing, Progressively More Investigated, but Still Puzzling , 2019, Brain sciences.
[14] N. Amidu,et al. Comparative Abilities of Body Mass Index, Waist Circumference, Abdominal Volume Index, Body Adiposity Index, and Conicity Index as Predictive Screening Tools for Metabolic Syndrome among Apparently Healthy Ghanaian Adults , 2019, Journal of obesity.
[15] M. Verhoye,et al. Early functional connectivity deficits and progressive microstructural alterations in the TgF344-AD rat model of Alzheimer’s Disease: A longitudinal MRI study , 2019, Neurobiology of Disease.
[16] Sean P. Fitzgibbon,et al. Automated quality control for within and between studies diffusion MRI data using a non-parametric framework for movement and distortion correction , 2019, NeuroImage.
[17] L. Velloso,et al. Hypothalamic Microglial Activation in Obesity: A Mini-Review , 2018, Front. Neurosci..
[18] Catherine Lebel,et al. The development of brain white matter microstructure , 2018, NeuroImage.
[19] C. Geier,et al. Is brain response to food rewards related to overeating? A test of the reward surfeit model of overeating in children , 2018, Appetite.
[20] C. Kroenke. Using diffusion anisotropy to study cerebral cortical gray matter development. , 2018, Journal of magnetic resonance.
[21] Massimo Filippi,et al. Changes in functional and structural brain connectome along the Alzheimer’s disease continuum , 2018, Molecular Psychiatry.
[22] John H. Gilmore,et al. Imaging structural and functional brain development in early childhood , 2018, Nature Reviews Neuroscience.
[23] X. Kong,et al. Diabetes Mellitus is Associated with More Severe Brain Spontaneous Activity Impairment and Gray Matter Loss in Patients with Cirrhosis , 2017, Scientific Reports.
[24] Section On Endocrinology,et al. The Metabolic Syndrome in Children and Adolescents: Shifting the Focus to Cardiometabolic Risk Factor Clustering , 2017, Pediatric Clinical Practice Guidelines & Policies.
[25] E. Goodman,et al. The Metabolic Syndrome in Children and Adolescents: Shifting the Focus to Cardiometabolic Risk Factor Clustering , 2017, Pediatrics.
[26] Michele T. Diaz,et al. Sources of disconnection in neurocognitive aging: cerebral white-matter integrity, resting-state functional connectivity, and white-matter hyperintensity volume , 2017, Neurobiology of Aging.
[27] G. Muccioli,et al. Obesity-Induced Neuroinflammation: Beyond the Hypothalamus , 2017, Trends in Neurosciences.
[28] Markus H. Sneve,et al. Relationship between structural and functional connectivity change across the adult lifespan: A longitudinal investigation , 2017 .
[29] Satrajit S. Ghosh,et al. Mindboggling morphometry of human brains , 2016, bioRxiv.
[30] Stamatios N. Sotiropoulos,et al. Incorporating outlier detection and replacement into a non-parametric framework for movement and distortion correction of diffusion MR images , 2016, NeuroImage.
[31] Jair C. Soares,et al. Inhibitory control in obesity and binge eating disorder: A systematic review and meta-analysis of neurocognitive and neuroimaging studies , 2016, Neuroscience & Biobehavioral Reviews.
[32] Stamatios N. Sotiropoulos,et al. An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging , 2016, NeuroImage.
[33] T. Verstynen,et al. rain volume and white matter in youth with type 2 diabetes ompared to obese and normal weight , non-diabetic peers : A pilot tudy , 2015 .
[34] V. Taylor,et al. An Overview of Links Between Obesity and Mental Health , 2015, Current Obesity Reports.
[35] R. Cabeza,et al. Cross-Hemispheric Collaboration and Segregation Associated with Task Difficulty as Revealed by Structural and Functional Connectivity , 2015, The Journal of Neuroscience.
[36] Martijn P. van den Heuvel,et al. Affected connectivity organization of the reward system structure in obesity , 2015, NeuroImage.
[37] L. Fellows,et al. Gender differences in the association between stop-signal reaction times, body mass indices and/or spontaneous food intake in pre-school children: an early model of compromised inhibitory control and obesity , 2014, International Journal of Obesity.
[38] Keith M Godfrey,et al. Cohort profile: Growing Up in Singapore Towards healthy Outcomes (GUSTO) birth cohort study. , 2014, International journal of epidemiology.
[39] I. Pigeot,et al. Metabolic syndrome in young children: definitions and results of the IDEFICS study , 2014, International Journal of Obesity.
[40] A. Darzi,et al. Neuropsychological assessment as a predictor of weight loss in obese adolescents , 2014, International Journal of Obesity.
[41] Karl J. Friston,et al. Structural and Functional Brain Networks: From Connections to Cognition , 2013, Science.
[42] D. Louis Collins,et al. Diffusion Weighted Image Denoising Using Overcomplete Local PCA , 2013, PloS one.
[43] M Mallar Chakravarty,et al. Alterations of Superficial White Matter in Schizophrenia and Relationship to Cognitive Performance , 2013, Neuropsychopharmacology.
[44] Fangfang Chen,et al. Association between Childhood Obesity and Metabolic Syndrome: Evidence from a Large Sample of Chinese Children and Adolescents , 2012, PloS one.
[45] Susan L. Whitfield-Gabrieli,et al. Conn: A Functional Connectivity Toolbox for Correlated and Anticorrelated Brain Networks , 2012, Brain Connect..
[46] O. Monchi,et al. Changes in regional and temporal patterns of activity associated with aging during the performance of a lexical set-shifting task. , 2012, Cerebral cortex.
[47] Yves Rosseel,et al. lavaan: An R Package for Structural Equation Modeling , 2012 .
[48] C. Lebel,et al. Diffusion tensor imaging of white matter tract evolution over the lifespan , 2012, NeuroImage.
[49] Abraham Z. Snyder,et al. Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion , 2012, NeuroImage.
[50] John C Schafer,et al. The Relationship Between Executive Function, AD/HD, Overeating, and Obesity , 2011, Western journal of nursing research.
[51] G. Šimić,et al. Extraordinary neoteny of synaptic spines in the human prefrontal cortex , 2011, Proceedings of the National Academy of Sciences.
[52] S. Chiplonkar,et al. Efficacy of a continuous metabolic syndrome score in Indian children for detecting subclinical atherosclerotic risk , 2011, International Journal of Obesity.
[53] L. Epstein,et al. Youth at Risk for Obesity Show Greater Activation of Striatal and Somatosensory Regions to Food , 2011, The Journal of Neuroscience.
[54] N. D. Yanez,et al. Waist Circumference, Body Mass Index, and Other Measures of Adiposity in Predicting Cardiovascular Disease Risk Factors among Peruvian Adults , 2011, International journal of hypertension.
[55] Michael W. Weiner,et al. Obesity is linked with lower brain volume in 700 AD and MCI patients , 2010, Neurobiology of Aging.
[56] V. Hirschler,et al. Relationship between obesity and metabolic syndrome among Argentinean elementary school children. , 2010, Clinical biochemistry.
[57] Andrew K Knutsen,et al. Regional patterns of cerebral cortical differentiation determined by diffusion tensor MRI. , 2009, Cerebral cortex.
[58] R. Morris,et al. Diffusion tensor imaging detects age related white matter change over a 2 year follow-up which is associated with working memory decline , 2009, Journal of Neurology, Neurosurgery & Psychiatry.
[59] Chaozhe Zhu,et al. An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: Fractional ALFF , 2008, Journal of Neuroscience Methods.
[60] Jonathan S. Adelstein,et al. Residual functional connectivity in the split-brain revealed with resting-state functional MRI , 2008, Neuroreport.
[61] Justin L. Vincent,et al. Disruption of Large-Scale Brain Systems in Advanced Aging , 2007, Neuron.
[62] S. Pocock,et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. , 2007, Preventive medicine.
[63] M. Fox,et al. Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging , 2007, Nature Reviews Neuroscience.
[64] J. Morrison,et al. Metabolic Syndrome in Childhood Predicts Adult Cardiovascular Disease 25 Years Later: The Princeton Lipid Research Clinics Follow-up Study , 2007, Pediatrics.
[65] J. Després,et al. Abdominal obesity and metabolic syndrome , 2006, Nature.
[66] Karl J. Friston,et al. Unified segmentation , 2005, NeuroImage.
[67] Mark W. Woolrich,et al. Advances in functional and structural MR image analysis and implementation as FSL , 2004, NeuroImage.
[68] Stefan Skare,et al. How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging , 2003, NeuroImage.
[69] T. Robbins,et al. Inhibition of subliminally primed responses is mediated by the caudate and thalamus: evidence from functional MRI and Huntington's disease. , 2003, Brain : a journal of neurology.
[70] P. Shrout,et al. Mediation in experimental and nonexperimental studies: new procedures and recommendations. , 2002, Psychological methods.
[71] Stephen M Smith,et al. Fast robust automated brain extraction , 2002, Human brain mapping.
[72] L. Moreno,et al. Leptin and Metabolic Syndrome in Obese and Non-Obese Children , 2002, Hormone and metabolic research = Hormon- und Stoffwechselforschung = Hormones et metabolisme.
[73] M. Petrides,et al. Wisconsin Card Sorting Revisited: Distinct Neural Circuits Participating in Different Stages of the Task Identified by Event-Related Functional Magnetic Resonance Imaging , 2001, The Journal of Neuroscience.
[74] Karl J. Friston,et al. Modelling Geometric Deformations in Epi Time Series , 2022 .
[75] E. Rimm,et al. Clustering of cardiovascular disease risk factors among obese schoolchildren: the Taipei Children Heart Study. , 1998, The American journal of clinical nutrition.
[76] Robert W. Thatcher,et al. Cyclic cortical reorganization during early childhood , 1992, Brain and Cognition.
[77] R. Turner,et al. Homeostasis model assessment: insulin resistance and β-cell function from fasting plasma glucose and insulin concentrations in man , 1985, Diabetologia.
[78] J. L. Conel,et al. The cortex of the four-year child , 1963 .
[79] S. Ferrari,et al. Author contributions , 2021 .
[80] A. Engin,et al. The Definition and Prevalence of Obesity and Metabolic Syndrome. , 2017, Advances in experimental medicine and biology.
[81] C. Hillman,et al. Cognitive control in preadolescent children with risk factors for metabolic syndrome. , 2015, Health psychology : official journal of the Division of Health Psychology, American Psychological Association.
[82] M. Greicius,et al. Resting-state functional connectivity reflects structural connectivity in the default mode network. , 2009, Cerebral cortex.
[83] J. Mckenney,et al. Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III). , 2001, JAMA.
[84] Karl J. Friston,et al. The slice-timing problem in event-related fMRI , 1999 .