Srikanth Ryali

Summary

Affiliation: Stanford University
Country: USA

Publications

  1. pmc Development, validation, and comparison of ICA-based gradient artifact reduction algorithms for simultaneous EEG-spiral in/out and echo-planar fMRI recordings
    S Ryali
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305 5778, USA
    Neuroimage 48:348-61. 2009
  2. 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
  3. 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
  4. 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
  5. pmc Development and validation of consensus clustering-based framework for brain segmentation using resting fMRI
    Srikanth Ryali
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, United States Electronic address
    J Neurosci Methods 240:128-40. 2015
  6. 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
  7. 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
  8. 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
  9. pmc Inter-subject synchronization of brain responses during natural music listening
    Daniel A Abrams
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA
    Eur J Neurosci 37:1458-69. 2013
  10. 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

Detail Information

Publications21

  1. pmc Development, validation, and comparison of ICA-based gradient artifact reduction algorithms for simultaneous EEG-spiral in/out and echo-planar fMRI recordings
    S Ryali
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305 5778, USA
    Neuroimage 48:348-61. 2009
    ..We provide new insights into the strengths and weaknesses of each method using a unified subspace framework...
  2. 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...
  3. 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...
  4. 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. ..
  5. pmc Development and validation of consensus clustering-based framework for brain segmentation using resting fMRI
    Srikanth Ryali
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, United States Electronic address
    J Neurosci Methods 240:128-40. 2015
    ..However, these methods are highly sensitive to the (i) precise algorithms employed, (ii) their initializations, and (iii) metrics used for uncovering the optimal number of clusters from the data...
  6. 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...
  7. 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...
  8. 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...
  9. pmc Inter-subject synchronization of brain responses during natural music listening
    Daniel A Abrams
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA
    Eur J Neurosci 37:1458-69. 2013
    ....
  10. 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. ..
  11. 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...
  12. pmc Hippocampal-prefrontal engagement and dynamic causal interactions in the maturation of children's fact retrieval
    Soohyun Cho
    Stanford University, Stanford, CA, USA
    J Cogn Neurosci 24:1849-66. 2012
    ....
  13. pmc Neural circuits underlying mother's voice perception predict social communication abilities in children
    Daniel A Abrams
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305
    Proc Natl Acad Sci U S A 113:6295-300. 2016
    ..Our findings provide a novel neurobiological template for investigation of typical social development as well as clinical disorders, such as autism, in which perception of biologically and socially salient voices may be impaired...
  14. pmc Multivariate activation and connectivity patterns discriminate speech intelligibility in Wernicke's, Broca's, and Geschwind's areas
    Daniel A Abrams
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
    Cereb Cortex 23:1703-14. 2013
    ....
  15. 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...
  16. pmc Estimation of resting-state functional connectivity using random subspace based partial correlation: a novel method for reducing global artifacts
    Tianwen Chen
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
    Neuroimage 82:87-100. 2013
    ..Our results suggest that RSMFC is an effective method for minimizing the effects of global artifacts and artificial negative correlations, while accurately recovering intrinsic functional brain networks. ..
  17. pmc Dynamic reconfiguration of structural and functional connectivity across core neurocognitive brain networks with development
    Lucina Q Uddin
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California 94305, USA
    J Neurosci 31:18578-89. 2011
    ....
  18. 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...
  19. 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
    ....
  20. pmc Decoding temporal structure in music and speech relies on shared brain resources but elicits different fine-scale spatial patterns
    Daniel A Abrams
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305 5778, USA
    Cereb Cortex 21:1507-18. 2011
    ....
  21. pmc How does a child solve 7 + 8? Decoding brain activity patterns associated with counting and retrieval strategies
    Soohyun Cho
    Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305 5719, USA
    Dev Sci 14:989-1001. 2011
    ..More generally, our study illustrates how brain imaging and developmental research can be integrated to investigate fundamental aspects of neurocognitive development...