W D Penny

Summary

Affiliation: University College London
Country: UK

Publications

  1. pmc A dynamical pattern recognition model of γ activity in auditory cortex
    M Zavaglia
    Department of Electronics, Computer Science and Systems DEIS, Via Venezia 52, 47023 Cesena, Italy
    Neural Netw 28:1-14. 2012
  2. pmc Dynamic Causal Models for phase coupling
    W D Penny
    Wellcome Trust Centre for Neuroimaging, University College, 12 Queen Square, London WC1N 3BG, UK
    J Neurosci Methods 183:19-30. 2009
  3. ncbi request reprint Modelling functional integration: a comparison of structural equation and dynamic causal models
    W D Penny
    Wellcome Department of Imaging Neuroscience, University College London, London, United Kingdom
    Neuroimage 23:S264-74. 2004
  4. ncbi request reprint Robust Bayesian General Linear Models
    W D Penny
    Wellcome Department of Imaging Neuroscience, University College London, London WC1N 3BG, UK
    Neuroimage 36:661-71. 2007
  5. pmc Testing for nested oscillation
    W D Penny
    Wellcome Trust Centre for Neuroimaging, University College, London, UK
    J Neurosci Methods 174:50-61. 2008
  6. pmc Comparing dynamic causal models using AIC, BIC and free energy
    W D Penny
    Wellcome Trust Centre for Neuroimaging, University College, London WC1N 3BG, UK
    Neuroimage 59:319-30. 2012
  7. pmc Comparing families of dynamic causal models
    Will D Penny
    Wellcome Trust Centre for Neuroimaging, University College, London, United Kingdom
    PLoS Comput Biol 6:e1000709. 2010
  8. ncbi request reprint Multivariate autoregressive modeling of fMRI time series
    L Harrison
    Wellcome Department of Imaging Neuroscience, University College London, 12 Queen Square, London WC1N 3BG, UK
    Neuroimage 19:1477-91. 2003
  9. ncbi request reprint Comparing dynamic causal models
    W D Penny
    Wellcome Department of Imaging Neuroscience, University College London, London, UK
    Neuroimage 22:1157-72. 2004
  10. ncbi request reprint Decoding oscillatory representations and mechanisms in memory
    A Jafarpour
    Institute of Cognitive Neurology and Dementia Research, Otto von Guericke University, Magdeburg, Germany
    Neuropsychologia 51:772-80. 2013

Detail Information

Publications11

  1. pmc A dynamical pattern recognition model of γ activity in auditory cortex
    M Zavaglia
    Department of Electronics, Computer Science and Systems DEIS, Via Venezia 52, 47023 Cesena, Italy
    Neural Netw 28:1-14. 2012
    ..Quantitative model fits allow us to make inferences about parameters governing pattern recognition dynamics in the brain...
  2. pmc Dynamic Causal Models for phase coupling
    W D Penny
    Wellcome Trust Centre for Neuroimaging, University College, 12 Queen Square, London WC1N 3BG, UK
    J Neurosci Methods 183:19-30. 2009
    ..For example, whether activity is driven by master-slave versus mutual entrainment mechanisms. Results are presented on synthetic data from physiological models and on MEG data from a study of visual working memory...
  3. ncbi request reprint Modelling functional integration: a comparison of structural equation and dynamic causal models
    W D Penny
    Wellcome Department of Imaging Neuroscience, University College London, London, United Kingdom
    Neuroimage 23:S264-74. 2004
    ..This review focuses on the underlying assumptions and limitations of each model and demonstrates their application to data from a study of attention to visual motion...
  4. ncbi request reprint Robust Bayesian General Linear Models
    W D Penny
    Wellcome Department of Imaging Neuroscience, University College London, London WC1N 3BG, UK
    Neuroimage 36:661-71. 2007
    ..This allows the RGLM to default to the usual GLM when robustness is not required. The method is compared to other robust regression methods and applied to synthetic data and fMRI...
  5. pmc Testing for nested oscillation
    W D Penny
    Wellcome Trust Centre for Neuroimaging, University College, London, UK
    J Neurosci Methods 174:50-61. 2008
    ..Our overall conclusion is that the GLM measure is the best all-round approach for detecting nested oscillation...
  6. pmc Comparing dynamic causal models using AIC, BIC and free energy
    W D Penny
    Wellcome Trust Centre for Neuroimaging, University College, London WC1N 3BG, UK
    Neuroimage 59:319-30. 2012
    ..Differences in performance are examined in the context of General Linear Models (GLMs) and Dynamic Causal Models (DCMs). We find that the Free Energy has the best model selection ability and recommend it be used for comparison of DCMs...
  7. pmc Comparing families of dynamic causal models
    Will D Penny
    Wellcome Trust Centre for Neuroimaging, University College, London, United Kingdom
    PLoS Comput Biol 6:e1000709. 2010
    ..We illustrate the methods using Dynamic Causal Models of brain imaging data...
  8. ncbi request reprint Multivariate autoregressive modeling of fMRI time series
    L Harrison
    Wellcome Department of Imaging Neuroscience, University College London, 12 Queen Square, London WC1N 3BG, UK
    Neuroimage 19:1477-91. 2003
    ..A further benefit of the MAR approach is that connectivity maps may contain loops, yet exact inference can proceed within a linear framework. Model order selection and parameter estimation are implemented by using Bayesian methods...
  9. ncbi request reprint Comparing dynamic causal models
    W D Penny
    Wellcome Department of Imaging Neuroscience, University College London, London, UK
    Neuroimage 22:1157-72. 2004
    ..The combined use of Bayes factors and DCM thus allows one to evaluate competing scientific theories about the architecture of large-scale neural networks and the neuronal interactions that mediate perception and cognition...
  10. ncbi request reprint Decoding oscillatory representations and mechanisms in memory
    A Jafarpour
    Institute of Cognitive Neurology and Dementia Research, Otto von Guericke University, Magdeburg, Germany
    Neuropsychologia 51:772-80. 2013
    ..We conclude that despite its infancy and existing methodological challenges, MVPC of EEG and MEG data is a powerful tool with which to assess mechanistic models of memory...
  11. ncbi request reprint Efficient gradient computation for dynamical models
    B Sengupta
    Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, UK Electronic address
    Neuroimage 98:521-7. 2014
    ..In the context of neuroimaging, adjoint based inversion of dynamical causal models (DCMs) can, in principle, enable the study of models with large numbers of nodes and parameters. ..