Literature DB >> 31427753

Prediction of neurocognition in youth from resting state fMRI.

Chandra Sripada1, Saige Rutherford2, Mike Angstadt2, Wesley K Thompson3, Monica Luciana4, Alexander Weigard2, Luke H Hyde5, Mary Heitzeg2.   

Abstract

Difficulties with higher-order cognitive functions in youth are a potentially important vulnerability factor for the emergence of problematic behaviors and a range of psychopathologies. This study examined 2013 9-10 year olds in the first data release from the Adolescent Brain Cognitive Development 21-site consortium study in order to identify resting state functional connectivity patterns that predict individual-differences in three domains of higher-order cognitive functions: General Ability, Speed/Flexibility, and Learning/Memory. For General Ability scores in particular, we observed consistent cross-site generalizability, with statistically significant predictions in 14 out of 15 held-out sites. These results survived several tests for robustness including replication in split-half analysis and in a low head motion subsample. We additionally found that connectivity patterns involving task control networks and default mode network were prominently implicated in predicting differences in General Ability across participants. These findings demonstrate that resting state connectivity can be leveraged to produce generalizable markers of neurocognitive functioning. Additionally, they highlight the importance of task control-default mode network interconnections as a major locus of individual differences in cognitive functioning in early adolescence.

Entities:  

Mesh:

Year:  2019        PMID: 31427753      PMCID: PMC7055722          DOI: 10.1038/s41380-019-0481-6

Source DB:  PubMed          Journal:  Mol Psychiatry        ISSN: 1359-4184            Impact factor:   15.992


  51 in total

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Journal:  Am J Psychiatry       Date:  2017-03-21       Impact factor: 18.112

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Authors:  P Fossati; A M Ergis; J F Allilaire
Journal:  Encephale       Date:  2002 Mar-Apr       Impact factor: 1.291

7.  An examination of the cognitive processes involved in childhood obsessive-compulsive disorder.

Authors:  Paula M Barrett; Lara J Healy
Journal:  Behav Res Ther       Date:  2003-03

Review 8.  Cognitive control mechanisms, emotion and memory: a neural perspective with implications for psychopathology.

Authors:  Marie T Banich; Kristen L Mackiewicz; Brendan E Depue; Anson J Whitmer; Gregory A Miller; Wendy Heller
Journal:  Neurosci Biobehav Rev       Date:  2008-10-02       Impact factor: 8.989

Review 9.  Why do many psychiatric disorders emerge during adolescence?

Authors:  Tomás Paus; Matcheri Keshavan; Jay N Giedd
Journal:  Nat Rev Neurosci       Date:  2008-11-12       Impact factor: 34.870

10.  Identification of a common neurobiological substrate for mental illness.

Authors:  Madeleine Goodkind; Simon B Eickhoff; Desmond J Oathes; Ying Jiang; Andrew Chang; Laura B Jones-Hagata; Brissa N Ortega; Yevgeniya V Zaiko; Erika L Roach; Mayuresh S Korgaonkar; Stuart M Grieve; Isaac Galatzer-Levy; Peter T Fox; Amit Etkin
Journal:  JAMA Psychiatry       Date:  2015-04       Impact factor: 21.596

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  20 in total

1.  Cognitive Modeling Informs Interpretation of Go/No-Go Task-Related Neural Activations and Their Links to Externalizing Psychopathology.

Authors:  Alexander Weigard; Mary Soules; Bailey Ferris; Robert A Zucker; Chandra Sripada; Mary Heitzeg
Journal:  Biol Psychiatry Cogn Neurosci Neuroimaging       Date:  2019-12-10

2.  Evidence from "big data" for the default-mode hypothesis of ADHD: a mega-analysis of multiple large samples.

Authors:  Luke J Norman; Gustavo Sudre; Jolie Price; Gauri G Shastri; Philip Shaw
Journal:  Neuropsychopharmacology       Date:  2022-09-13       Impact factor: 8.294

3.  Bayesian interaction selection model for multimodal neuroimaging data analysis.

Authors:  Yize Zhao; Ben Wu; Jian Kang
Journal:  Biometrics       Date:  2022-02-27       Impact factor: 1.701

4.  Boost in Test-Retest Reliability in Resting State fMRI with Predictive Modeling.

Authors:  Aman Taxali; Mike Angstadt; Saige Rutherford; Chandra Sripada
Journal:  Cereb Cortex       Date:  2021-05-10       Impact factor: 5.357

Review 5.  Neuroimaging-based Individualized Prediction of Cognition and Behavior for Mental Disorders and Health: Methods and Promises.

Authors:  Jing Sui; Rongtao Jiang; Juan Bustillo; Vince Calhoun
Journal:  Biol Psychiatry       Date:  2020-02-27       Impact factor: 13.382

Review 6.  Brain Mechanisms Supporting Flexible Cognition and Behavior in Adolescents With Autism Spectrum Disorder.

Authors:  Lucina Q Uddin
Journal:  Biol Psychiatry       Date:  2020-05-20       Impact factor: 13.382

7.  Individual Differences in Cognitive Performance Are Better Predicted by Global Rather Than Localized BOLD Activity Patterns Across the Cortex.

Authors:  Weiqi Zhao; Clare E Palmer; Wesley K Thompson; Bader Chaarani; Hugh P Garavan; B J Casey; Terry L Jernigan; Anders M Dale; Chun Chieh Fan
Journal:  Cereb Cortex       Date:  2021-02-05       Impact factor: 4.861

8.  Toward a "treadmill test" for cognition: Improved prediction of general cognitive ability from the task activated brain.

Authors:  Chandra Sripada; Mike Angstadt; Saige Rutherford; Aman Taxali; Kerby Shedden
Journal:  Hum Brain Mapp       Date:  2020-05-04       Impact factor: 5.038

9.  Partitioning heritability analyses unveil the genetic architecture of human brain multidimensional functional connectivity patterns.

Authors:  Junjiao Feng; Chunhui Chen; Ying Cai; Zhifang Ye; Kanyin Feng; Jing Liu; Liang Zhang; Qinghao Yang; Anqi Li; Jintao Sheng; Bi Zhu; Zhaoxia Yu; Chuansheng Chen; Qi Dong; Gui Xue
Journal:  Hum Brain Mapp       Date:  2020-04-24       Impact factor: 5.038

10.  Multi-Paradigm fMRI Fusion via Sparse Tensor Decomposition in Brain Functional Connectivity Study.

Authors:  Yipu Zhang; Li Xiao; Gemeng Zhang; Biao Cai; Julia M Stephen; Tony W Wilson; Vince D Calhoun; Yu-Ping Wang
Journal:  IEEE J Biomed Health Inform       Date:  2021-05-11       Impact factor: 5.772

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