Imaging patterns of brain development and their relationship to cognition.
about
Multivariate Analyses Applied to Healthy Neurodevelopment in Fetal, Neonatal, and Pediatric MRIBeyond Lumping and Splitting: A Review of Computational Approaches for Stratifying Psychiatric DisordersLoad-related brain activation predicts spatial working memory performance in youth aged 9-12 and is associated with executive function at earlier ages.Use of resting-state functional MRI to study brain development and injury in neonatesDistinct multivariate brain morphological patterns and their added predictive value with cognitive and polygenic risk scores in mental disorders.Unraveling the miswired connectome: a developmental perspectiveFinding imaging patterns of structural covariance via Non-Negative Matrix Factorization.Investigating the use of support vector machine classification on structural brain images of preterm-born teenagers as a biological markerDesign and methods of the NiCK study: neurocognitive assessment and magnetic resonance imaging analysis of children and young adults with chronic kidney disease.White matter microstructure among youth with perinatally acquired HIV is associated with disease severity.The Philadelphia Neurodevelopmental Cohort: A publicly available resource for the study of normal and abnormal brain development in youth.The National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) Waves 1 and 2: review and summary of findingsUsing clinically acquired MRI to construct age-specific ADC atlases: Quantifying spatiotemporal ADC changes from birth to 6-year old.Neuroanatomical anomalies of dyslexia: Disambiguating the effects of disorder, performance, and maturation.MUSE: MUlti-atlas region Segmentation utilizing Ensembles of registration algorithms and parameters, and locally optimal atlas selection.Global fractional anisotropy and mean diffusivity together with segmented brain volumes assemble a predictive discriminant model for young and elderly healthy brains: a pilot study at 3T.Brain extraction in pediatric ADC maps, toward characterizing neuro-development in multi-platform and multi-institution clinical images.Understanding Heterogeneity in Clinical Cohorts Using Normative Models: Beyond Case-Control StudiesStructural Brain Abnormalities in Youth With Psychosis Spectrum Symptoms.Multivariate dynamical modelling of structural change during development.Brain structure, working memory and response inhibition in childhood leukemia survivors.An integrative model of the maturation of cognitive control.Microstructural Changes of the Human Brain from Early to Mid-AdulthoodJoint prediction of longitudinal development of cortical surfaces and white matter fibers from neonatal MRI.Enhancing the Informativeness and Replicability of Imaging Genomics Studies.Comparative evaluation of registration algorithms in different brain databases with varying difficulty: results and insights.Sex and Diffusion Tensor Imaging of White Matter in Schizophrenia: A Systematic Review Plus Meta-analysis of the Corpus Callosum.Prediction of brain maturity in infants using machine-learning algorithms.Modelling neuroanatomical variation during childhood and adolescence with neighbourhood-preserving embedding.A pediatric structural MRI analysis of healthy brain development from newborns to young adults.Reorganization of the somatosensory cortex in hemiplegic cerebral palsy associated with impaired sensory tracts.Association of Heritable Cognitive Ability and Psychopathology With White Matter Properties in Children and Adolescents.Development of subcortical volumes across adolescence in males and females: A multisample study of longitudinal changes.Chronnectome fingerprinting: Identifying individuals and predicting higher cognitive functions using dynamic brain connectivity patterns.Individualized Prediction of Reading Comprehension Ability Using Gray Matter Volume.The developmental relationship between specific cognitive domains and grey matter in the cerebellum.Why monkeys do not get multiple sclerosis (spontaneously): An evolutionary approach.Evaluation of non-negative matrix factorization of grey matter in age prediction.White Matter Pathways and Social Cognition.A Nonlinear Simulation Framework Supports Adjusting for Age When Analyzing BrainAGE
P2860
Q26772824-1F168553-BD10-432F-B374-6624AA876E04Q28075280-4E115D19-1801-4210-A682-50C842F1BD96Q30701678-F946CD33-B7AC-482F-BA1D-C50000FD1A4DQ30917283-E168A1E8-9311-4DBA-9080-19B771069C5AQ33854087-9B94B53E-04F0-46A9-A393-22ECA98B5FF9Q34213589-5B0C5A97-25FA-4723-BD84-0B7DF0DF862AQ35170127-EA994443-33FA-43D5-8176-7CC45B94ED93Q35250909-39CD5D80-4D01-4462-A4ED-B7F0700DE00BQ35568910-DA246CBB-9C7B-4F09-A424-716AD5383F4BQ35804781-96C2B1AF-2454-43E9-85BD-B28CDB5403C9Q36113158-B37F2B9D-64AB-4A99-B734-3265678B015AQ36200016-4CACD18A-4DAE-4C09-A7C2-59CE8348F8A5Q36332748-25D4EC27-5518-4C89-9FF3-3D9F3EF191E0Q36683805-23E565E3-235F-4AC9-8915-565A7B1EFF85Q36725416-246122B9-5F55-4420-8423-6DF0002374A6Q36762528-F70E53A7-743E-4E39-A8D5-8843D433AD0EQ37138315-88F3D805-F5B1-4EF4-B053-5FFD7A707535Q37256060-45FAFB53-4236-4081-A57F-CAAF9AF2D05EQ37307646-712714A1-9661-4762-BF9C-40557BEAF5B9Q37649824-14817E7A-FC18-46A7-8FB4-2D977212725CQ37653619-682C626F-4041-4D81-9570-6433EB5E76BEQ38543999-62DDC061-4D22-4A10-872C-BD2FD60119F2Q38616821-85D258DE-59FB-44C1-808E-CA98F7E648C6Q38913230-5F63DC04-EAC8-4854-BDD9-75CAAF96BE3CQ38993924-DD18F83D-886A-48D3-A2A0-6D60334CF28BQ39172366-BEEB8EEE-31BF-448D-AA12-97CE574F7E70Q39267100-4E8224E6-7E63-4420-B7A8-9BCA7992A798Q39766129-D1113D77-E174-49FA-A02F-1E847E6B6B73Q47127702-CD8E27E6-8B6D-4473-A18A-D2C6F1CA694BQ47128493-EFC4EF9C-FECF-4919-9719-7BD0D394622BQ47159995-FCA6CFC8-6085-46FE-9AE0-E87F1FA20920Q47552376-E6432D9F-516F-466C-BEA7-08AABCE08C8DQ47553675-22733210-E082-4196-98B3-6D5EDEC8A8C8Q47588293-A46DA91B-7140-4118-89E4-D97029463BF0Q47818633-C516486B-D79D-4A16-8210-BAE6886590BCQ48356900-F1FE0AE4-1E09-450D-BB14-D749D2403A90Q50317600-DAD18DCC-6219-4D3F-B888-A364070FACBAQ51742783-08CFCFB9-5A34-4807-8DC3-F6C1E223EAD2Q52569804-9AE5504A-DDB6-48DE-AAF9-F47D0B16731DQ58566352-A235A2F0-D324-44DA-A318-75A148336197
P2860
Imaging patterns of brain development and their relationship to cognition.
description
2014 nî lūn-bûn
@nan
2014年の論文
@ja
2014年論文
@yue
2014年論文
@zh-hant
2014年論文
@zh-hk
2014年論文
@zh-mo
2014年論文
@zh-tw
2014年论文
@wuu
2014年论文
@zh
2014年论文
@zh-cn
name
Imaging patterns of brain development and their relationship to cognition.
@ast
Imaging patterns of brain development and their relationship to cognition.
@en
type
label
Imaging patterns of brain development and their relationship to cognition.
@ast
Imaging patterns of brain development and their relationship to cognition.
@en
prefLabel
Imaging patterns of brain development and their relationship to cognition.
@ast
Imaging patterns of brain development and their relationship to cognition.
@en
P2093
P2860
P50
P356
P1433
P1476
Imaging patterns of brain development and their relationship to cognition.
@en
P2093
Guray Erus
Hakon Hakonarson
Harsha Battapady
P2860
P304
P356
10.1093/CERCOR/BHT425
P577
2014-01-12T00:00:00Z