Research Topics
| Kaustubh SupekarSummaryAffiliation: Stanford University Country: USA Publications
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Detail Information
Publications
Developmental maturation of dynamic causal control signals in higher-order cognition: a neurocognitive network modelKaustubh 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...- Development of functional and structural connectivity within the default mode network in young childrenKaustubh 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... - Development of large-scale functional brain networks in childrenKaustubh Supekar
Graduate Program in Biomedical Informatics, Stanford University School of Medicine, Stanford, California, USA
PLoS Biol 7:e1000157. 2009.... - Network analysis of intrinsic functional brain connectivity in Alzheimer's diseaseKaustubh 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... - Dissociable connectivity within human angular gyrus and intraparietal sulcus: evidence from functional and structural connectivityLucina Q Uddin
Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA
Cereb Cortex 20:2636-46. 2010.... - Immature integration and segregation of emotion-related brain circuitry in young childrenShaozheng 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... - Estimation of functional connectivity in fMRI data using stability selection-based sparse partial correlation with elastic net penaltySrikanth 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... - Resting-state functional connectivity reflects structural connectivity in the default mode networkMichael 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... 
Knowledge Zone: a public repository of peer-reviewed biomedical ontologiesKaustubh Supekar
Stanford Medical Informatics, Stanford University School of Medicine, USA
Stud Health Technol Inform 129:812-6. 2007....- A parcellation scheme based on von Mises-Fisher distributions and Markov random fields for segmenting brain regions using resting-state fMRISrikanth 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... - Multivariate dynamical systems models for estimating causal interactions in fMRISrikanth 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... - Typical and atypical development of functional human brain networks: insights from resting-state FMRILucina 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... - Sparse logistic regression for whole-brain classification of fMRI dataSrikanth 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...