Kaustubh Supekar

Summary

Affiliation: Stanford University
Country: USA

Publications

  1. pmc Remediation of Childhood Math Anxiety and Associated Neural Circuits through Cognitive Tutoring
    Kaustubh Supekar
    Departments of Psychiatry and Behavioral Sciences and
    J Neurosci 35:12574-83. 2015
  2. pmc Brain hyperconnectivity in children with autism and its links to social deficits
    Kaustubh Supekar
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA Electronic address
    Cell Rep 5:738-47. 2013
  3. pmc Neural predictors of individual differences in response to math tutoring in primary-grade school children
    Kaustubh Supekar
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA
    Proc Natl Acad Sci U S A 110:8230-5. 2013
  4. pmc Developmental maturation of dynamic causal control signals in higher-order cognition: a neurocognitive network model
    Kaustubh Supekar
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California, USA
    PLoS Comput Biol 8:e1002374. 2012
  5. pmc Development of large-scale functional brain networks in children
    Kaustubh Supekar
    Graduate Program in Biomedical Informatics, Stanford University School of Medicine, Stanford, California, USA
    PLoS Biol 7:e1000157. 2009
  6. pmc Development of functional and structural connectivity within the default mode network in young children
    Kaustubh Supekar
    Graduate Program in Biomedical Informatics, Stanford University School of Medicine, Stanford, CA 94304, USA
    Neuroimage 52:290-301. 2010
  7. pmc Underconnectivity between voice-selective cortex and reward circuitry in children with autism
    Daniel A Abrams
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA 94304, USA
    Proc Natl Acad Sci U S A 110:12060-5. 2013
  8. pmc Default mode network in childhood autism: posteromedial cortex heterogeneity and relationship with social deficits
    Charles J Lynch
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California, USA
    Biol Psychiatry 74:212-9. 2013
  9. pmc Parietal hyper-connectivity, aberrant brain organization, and circuit-based biomarkers in children with mathematical disabilities
    Dietsje Jolles
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, USA
    Dev Sci 19:613-31. 2016
  10. pmc Salience network-based classification and prediction of symptom severity in children with autism
    Lucina Q Uddin
    Department of Psychiatry, Stanford University School of Medicine, Stanford, California 94305, USA
    JAMA Psychiatry 70:869-79. 2013

Detail Information

Publications31

  1. pmc Remediation of Childhood Math Anxiety and Associated Neural Circuits through Cognitive Tutoring
    Kaustubh Supekar
    Departments of Psychiatry and Behavioral Sciences and
    J Neurosci 35:12574-83. 2015
    ....
  2. pmc Brain hyperconnectivity in children with autism and its links to social deficits
    Kaustubh Supekar
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA Electronic address
    Cell Rep 5:738-47. 2013
    ..Our findings provide unique insights into brain mechanisms underlying childhood autism. ..
  3. pmc Neural predictors of individual differences in response to math tutoring in primary-grade school children
    Kaustubh Supekar
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA
    Proc Natl Acad Sci U S A 110:8230-5. 2013
    ..More generally, our study suggests that quantitative measures of brain structure and intrinsic brain organization can provide a more sensitive marker of skill acquisition than behavioral measures...
  4. pmc Developmental maturation of dynamic causal control signals in higher-order cognition: a neurocognitive network model
    Kaustubh Supekar
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California, USA
    PLoS Comput Biol 8:e1002374. 2012
    ..The quantitative approach developed is likely to be useful in investigating neurodevelopmental disorders, in which control processes are impaired, such as autism and ADHD...
  5. pmc Development of large-scale functional brain networks in children
    Kaustubh Supekar
    Graduate Program in Biomedical Informatics, Stanford University School of Medicine, Stanford, California, USA
    PLoS Biol 7:e1000157. 2009
    ....
  6. pmc Development of functional and structural connectivity within the default mode network in young children
    Kaustubh Supekar
    Graduate Program in Biomedical Informatics, Stanford University School of Medicine, Stanford, CA 94304, USA
    Neuroimage 52:290-301. 2010
    ..More generally, our study demonstrates how quantitative multimodal analysis of anatomy and connectivity allows us to better characterize the heterogeneous development and maturation of brain networks...
  7. pmc Underconnectivity between voice-selective cortex and reward circuitry in children with autism
    Daniel A Abrams
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA 94304, USA
    Proc Natl Acad Sci U S A 110:12060-5. 2013
    ..Our study provides support for the social motivation theory of ASD. ..
  8. pmc Default mode network in childhood autism: posteromedial cortex heterogeneity and relationship with social deficits
    Charles J Lynch
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California, USA
    Biol Psychiatry 74:212-9. 2013
    ..Furthermore, the functionally heterogeneous profile of the posteromedial cortex raises questions regarding how altered connectivity manifests in specific functional modules within this brain region in children with ASD...
  9. pmc Parietal hyper-connectivity, aberrant brain organization, and circuit-based biomarkers in children with mathematical disabilities
    Dietsje Jolles
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, USA
    Dev Sci 19:613-31. 2016
    ....
  10. pmc Salience network-based classification and prediction of symptom severity in children with autism
    Lucina Q Uddin
    Department of Psychiatry, Stanford University School of Medicine, Stanford, California 94305, USA
    JAMA Psychiatry 70:869-79. 2013
    ..Autism spectrum disorder has been linked with atypical connectivity across multiple brain systems, yet the nature of these differences in young children with the disorder is not well understood...
  11. pmc Reconfiguration of parietal circuits with cognitive tutoring in elementary school children
    Dietsje Jolles
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA, United States Department of Education and Child Studies, Leiden University, Leiden, The Netherlands Electronic address
    Cortex 83:231-45. 2016
    ..Our findings provide new insights into plasticity of functional brain circuits associated with the development of specialized cognitive skills in children. ..
  12. pmc Dissociable connectivity within human angular gyrus and intraparietal sulcus: evidence from functional and structural connectivity
    Lucina Q Uddin
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA
    Cereb Cortex 20:2636-46. 2010
    ....
  13. pmc Network analysis of intrinsic functional brain connectivity in Alzheimer's disease
    Kaustubh Supekar
    Graduate Program in Biomedical Informatics, Stanford University School of Medicine, Stanford, California, USA
    PLoS Comput Biol 4:e1000100. 2008
    ..Small-world metrics can characterize the functional organization of the brain in AD, and our findings further suggest that these network measures may be useful as an imaging-based biomarker to distinguish AD from healthy aging...
  14. pmc Multivariate dynamical systems-based estimation of causal brain interactions in fMRI: Group-level validation using benchmark data, neurophysiological models and human connectome project data
    Srikanth Ryali
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, United States Electronic address
    J Neurosci Methods 268:142-53. 2016
    ..Causal estimation methods are increasingly being used to investigate functional brain networks in fMRI, but there are continuing concerns about the validity of these methods...
  15. pmc Cognitive tutoring induces widespread neuroplasticity and remediates brain function in children with mathematical learning disabilities
    Teresa Iuculano
    Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California 94305, USA
    Nat Commun 6:8453. 2015
    ..Our study identifies functional brain mechanisms underlying effective intervention in children with MLD and provides novel metrics for assessing response to intervention. ..
  16. pmc A parcellation scheme based on von Mises-Fisher distributions and Markov random fields for segmenting brain regions using resting-state fMRI
    Srikanth Ryali
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
    Neuroimage 65:83-96. 2013
    ..Taken together, our findings suggest that our method is a powerful tool for investigating functional subdivisions in the human brain...
  17. pmc Combining optogenetic stimulation and fMRI to validate a multivariate dynamical systems model for estimating causal brain interactions
    Srikanth Ryali
    Stanford University School of Medicine, Stanford, USA Electronic address
    Neuroimage 132:398-405. 2016
    ..More generally, our study demonstrates that the combined use of optogenetics and fMRI provides a powerful new tool for evaluating computational methods designed to estimate causal interactions between distributed brain regions. ..
  18. pmc Distinct Global Brain Dynamics and Spatiotemporal Organization of the Salience Network
    Tianwen Chen
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford University, Stanford, California, United States of America
    PLoS Biol 14:e1002469. 2016
    ....
  19. pmc Large-scale intrinsic functional network organization along the long axis of the human medial temporal lobe
    Shaozheng Qin
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Rd, Stanford, CA, 94304, USA
    Brain Struct Funct 221:3237-58. 2016
    ..The implications of our findings for a principledunderstanding of distributed pathways that support memory and cognition are discussed. ..
  20. pmc Temporal Dynamics and Developmental Maturation of Salience, Default and Central-Executive Network Interactions Revealed by Variational Bayes Hidden Markov Modeling
    Srikanth Ryali
    Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, United States of America
    PLoS Comput Biol 12:e1005138. 2016
    ..Our computational techniques provide new insights into human brain network dynamics and its maturation with development...
  21. pmc Plasticity of left perisylvian white-matter tracts is associated with individual differences in math learning
    Dietsje Jolles
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 1070 Arastradero Road, Suite 220, Palo Alto, CA, 94304, USA
    Brain Struct Funct 221:1337-51. 2016
    ..More generally, our quantitative approach will be useful for future studies examining longitudinal changes in white matter integrity associated with cognitive skill development...
  22. pmc Amygdala subregional structure and intrinsic functional connectivity predicts individual differences in anxiety during early childhood
    Shaozheng Qin
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California Electronic address
    Biol Psychiatry 75:892-900. 2014
    ..Even less is known about the neurodevelopmental origins of individual differences in childhood anxiety...
  23. pmc Estimation of functional connectivity in fMRI data using stability selection-based sparse partial correlation with elastic net penalty
    Srikanth Ryali
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
    Neuroimage 59:3852-61. 2012
    ..Taken together, our findings suggest that SPC-EN provides a powerful tool for characterizing connectivity involving a large number of correlated regions that span the entire brain...
  24. pmc Immature integration and segregation of emotion-related brain circuitry in young children
    Shaozheng Qin
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA
    Proc Natl Acad Sci U S A 109:7941-6. 2012
    ..These immature patterns of amygdala connectivity have important implications for understanding typical and atypical development of emotion-related brain circuitry...
  25. pmc Resting-state functional connectivity reflects structural connectivity in the default mode network
    Michael D Greicius
    Department of Neurology, Stanford University School of Medicine, Stanford, CA 94304, USA
    Cereb Cortex 19:72-8. 2009
    ..The results demonstrate that resting-state functional connectivity reflects structural connectivity and that combining modalities can enrich our understanding of these canonical brain networks...
  26. ncbi request reprint Knowledge Zone: a public repository of peer-reviewed biomedical ontologies
    Kaustubh Supekar
    Stanford Medical Informatics, Stanford University School of Medicine, USA
    Stud Health Technol Inform 129:812-6. 2007
    ....
  27. pmc Aberrant Cross-Brain Network Interaction in Children With Attention-Deficit/Hyperactivity Disorder and Its Relation to Attention Deficits: A Multisite and Cross-Site Replication Study
    Weidong Cai
    Departments of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California Electronic address
    Biol Psychiatry . 2015
    ..We also determined whether network dysregulation measures can differentiate children with ADHD from control subjects across multisite datasets and predict clinical symptoms...
  28. pmc Role of the anterior insular cortex in integrative causal signaling during multisensory auditory-visual attention
    Tianwen Chen
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Road, Stanford, CA, 94305, USA
    Eur J Neurosci 41:264-74. 2015
    ..Our study provides new insights into the dynamic causal mechanisms by which the AI facilitates multisensory attention...
  29. pmc Multivariate dynamical systems models for estimating causal interactions in fMRI
    Srikanth Ryali
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305 5778, USA
    Neuroimage 54:807-23. 2011
    ..Our study suggests that VB estimation of MDS provides a robust method for estimating and interpreting causal network interactions in fMRI data...
  30. pmc Typical and atypical development of functional human brain networks: insights from resting-state FMRI
    Lucina Q Uddin
    Stanford Cognitive and Systems Neuroscience Laboratory, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine Stanford, CA, USA
    Front Syst Neurosci 4:21. 2010
    ..We conclude by identifying critical gaps in the current literature, discussing methodological issues, and suggesting avenues for future research...
  31. pmc Sparse logistic regression for whole-brain classification of fMRI data
    Srikanth Ryali
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
    Neuroimage 51:752-64. 2010
    ..These findings suggest that our method is not only computationally efficient, but it also achieves the twin objectives of identifying relevant discriminative brain regions and accurately classifying fMRI data...