W D Penny
- Comparing dynamic causal modelsW 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...
- Modelling functional integration: a comparison of structural equation and dynamic causal modelsW 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...
- Robust Bayesian General Linear ModelsW 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...
- Testing for nested oscillationW 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...
- Multivariate autoregressive modeling of fMRI time seriesL 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...