Book

 R. Frackowiak, K. Friston, C. Frith, R. Dolan, J. Asburner, C. Price, J. Ashburner, W. Penny and S. Zeki (2003) Human Brain Function. 2nd Edition, Academic Press. Available from Elsevier.

Abstracts

 HBM Abstracts

Papers and Technical Reports

2005
  • W.Penny, N. Trujillo-Bareto and K. Friston (2005). Bayesian fMRI time series analysis with spatial priors . NeuroImage 24(2), 350-362.

    2004
  • W. Penny and K.Friston (2004) Classical and Bayesian Inference in fMRI. To appear in L. Landini (Ed.) Advanced Image Processing in Magnetic Resonance Imaging, Marcel Dekker.

  • K. Stephan, L. Harrison, W. Penny and K. Friston (2004) Biophysical models of fMRI responses Current Opinion in Neurobiology, 14(5), 629-635.

  • K. Friston, W. Penny and O. David (2004) Modelling brain responses Int. Rev. Neurobiology.
    Figures: brain_responses.ppt

  • W. Penny, K. Stephan, A. Mechelli and K.Friston. (2004) Modelling Functional Integration: A comparison of structural equation and dynamic causal models. Neuroimage, Accepted for publication.

  • N. Ramnani, T.E.J. Behrens, W. Penny and P.M. Matthews (2004) New Approaches for Exploring Anatomic and Functional Connectivity in the Human Brain. Biological Psychiatry, In Press.

  • W. Penny, K. Stephan, A. Mechelli and K. Friston (2004) Comparing Dynamic Causal Models. NeuroImage, 22 (3), pp. 1157-1172. The paper cdcm.pdf is an earlier, longer version.
    These are the release notes that accompany the software updates DCM_updates.doc

  • E. Curran, P. Sykacek, M.Stokes, S.J. Roberts, W. Penny, I. Johnsrude and A.M. Owen (2004) Cognitive Tasks for Driving a Brain Computer Interfacing System: A Pilot Study. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 12(1),pp. 48-54.

    2003
  • R. Henson and W. Penny (2003) ANOVAs and SPM . Technical Report.
    This is a new version (as of Nov 2003) with a mistake in eq. 40 now corrected. The numerical examples in this paper were implemented using the matlab script rik_anovas.m

  • K. Friston, L. Harrison and W. Penny (2003) Dynamic causal modelling . Neuroimage, 19(4), pages 1273-1302.

  • K. Friston and W. Penny (2003) Posterior Probability Maps and SPMs. Neuroimage, 19(3), pages 1240-1249.

  • JB. Poline, F. Kherif and W. Penny (2003) Contrasts and Classical Inference . To appear in Frackowiak et al. (Eds), Human Brain Function II, Elsevier.

  • W. Penny and A. Holmes(2003) Random Effects Analysis . To appear in Frackowiak et al. (Eds), Human Brain Function II, Elsevier.

  • W. Penny and K.J Friston (2003) Hierarchical Models . To appear in Frackowiak et al. (Eds), Human Brain Function II, Elsevier.

  • M. Brett, W. Penny and S. Kiebel(2003) Introduction to Random Field Theory . To appear in Frackowiak et al. (Eds), Human Brain Function II, Elsevier.

  • K.J. Friston and W. Penny (2003) Classical and Bayesian Inference . To appear in Frackowiak et al. (Eds), Human Brain Function II, Elsevier.

  • W.D. Penny, S. Kiebel, K. Friston (2003) Variational Bayesian Inference for fMRI time series. Neuroimage 19 (3), 727-741.

  • L. Harrison, W.D. Penny and K. Friston (2003) Multivariate Autoregressive Modelling of fMRI time series. Neuroimage 19 (4), 1477-1491.

  • D.R. Gitelman, W. Penny, J. Ashburner and K. Friston (2003) Modelling regional and psychophysiologic interactions in fMRI: The importance of hemodynamic deconvolution. Neuroimage, 19(1), pages 200-207.

  • W.D. Penny and K.J. Friston (2003) Mixtures of General Linear Models for Functional Neuroimaging IEEE Transactions on Medical Imaging, 22(4), pages 504-514.

    2002
  • K.J. Friston and W.D. Penny (2002) Bayesian Inference and Posterior Probability Maps. Proceedings of the 9th International Conference on Neural Information Processing (ICONIP'02), pages 413-417, Volume I, IEEE Press. Word Format , Longer version also in Word Format.

    .
  • S.J. Roberts and W.D. Penny (2002) Variational Bayes for Generalised Autoregressive Models IEEE Transactions on Signal Processing, 50(9), pp. 2245-2257 .

  • M. Cassidy and W.D. Penny (2002) Bayesian nonstationary autoregressive models for biomedical signal analysis IEEE Transactions on Biomedical Engineering, 49(10), Oct, pp 1142-1152.

  • W.D. Penny. S.J. Kiebel, J.M. Kilner and M.D. Rugg (2002) Event-related brain dynamics Trends in Neuroscience, Vol. 25, No. 8, pp 387-389.

  • W.D. Penny and S.J. Roberts (2002) Bayesian Multivariate Autoregressive Models with Structured Priors IEE Proceedings on Vision, Image and Signal Processing, 149(1), pp. 33-41
    This paper won the 2003 IEE Institution Premium Award

  • K.J. Friston, W. Penny, C. Phillips, S. Kiebel, G. Hinton and J. Ashburner (2002) Classical and Bayesian Inference in Neuroimaging: Theory Neuroimage, 16, pp. 465-483.

  • W. Penny (2002) An EM algorithm for Gaussian Markov Random Fields Technical Report, Wellcome Department of Imaging Neuroscience, UCL.

  • W. Penny (2002) Wavelet smoothing of fMRI activation images Technical Report, Wellcome Department of Imaging Neuroscience, UCL.

  • A. Mechelli, W. Penny, C.J. Price, D.R. Gitelman and K.J. Friston (2002) Effective connectivity and inter-subject variability: using a multi-subject network to test differences and commonalities Neuroimage, 17(3), pp. 1459-1469.

    2001
  • W.D. Penny, J. Ashburner, S. Kiebel, R. Henson, D.E. Glaser, C. Phillips and K. Friston (2001) Statistical Parametric Mapping: An Annotated Bibliography. Wellcome Department of Cognitive Neurology, 2001 PDF , Postscript , HTML or Text

  • W.D. Penny (2001) Notes on Random Effects Analysis. Wellcome Department of Cognitive Neurology, 2001 Postscript .

  • W.D. Penny (2001) The Normal, Chi^2, t and F Probability Distributions. Wellcome Department of Cognitive Neurology, 2001 Postscript

  • W.D. Penny (2001) Kullback-Liebler Divergences of Normal, Gamma, Dirichlet and Wishart Densities. Wellcome Department of Cognitive Neurology, 2001 Postscript ,

  • M.R. Johnson, C.D. Good, W.D. Penny, P.R.J. Barnes and J.W. Scadding (2001) Playing the odds in clinical decision making: lessons from berry aneuryisms undetected by magnetic resonance angiography British Medical Journal 322, 2 June 2001, pp. 1347-1349.

  • S.J. Roberts and W.D. Penny (2001) Mixtures of Independent Component Analysers Proceedings of ICANN 2001, Vienna.

  • W.D. Penny (2001) Variational Bayes for d-dimensional Gaussian mixture models Wellcome Department of Cognitive Neurology, University College London.

    2000
  • W.D. Penny and S.J. Roberts (2000) Notes on Variational Learning Technical Report PARG-00-1, Department of Engineering Science, Oxford University.

  • W.D. Penny and S.J. Roberts (2000) Variational Bayes for 1-dimensional mixture models Technical Report PARG-00-2, Department of Engineering Science, Oxford University. An earlier version of this paper contained an incorrect expression for the KL divergence between two Dirichlet densities. This version contains the correct expression.

  • W.D. Penny and S.J. Roberts (2000) Bayesian Methods for Autoregressive Models IEEE Workshop on Neural Networks for Signal Processing, Sydney Australia, December 2000.

  • W.D. Penny and S.J. Roberts (2000) Variational Bayes for Non-Gaussian Autoregressive Models IEEE Workshop on Neural Networks for Signal Processing, Sydney Australia, December 2000. The paper that appears in the actual conference proceedings contains an incorrect expression for the KL divergence between two Dirichlet densities. This version contains the correct expression.

  • R. Choudrey, W.D. Penny and S.J. Roberts (2000) An Ensemble Learning Approach to Independent Component Analysis IEEE Workshop on Neural Networks for Signal Processing, Sydney Australia, December 2000.

  • W.D. Penny, S.J. Roberts and R. Everson (2000) ICA: Model-order selection and dynamic source models In S.J. Roberts and R. Everson (Eds.) ICA: Principles and Practice, Cambridge University Press, pp. 299-314.

  • W.D. Penny, R. Everson and S.J. Roberts (2000) Hidden Markov Independent Component Analysis In M Girolami (Ed.) Advances in Independent Component Analysis, Springer.

  • W.D. Penny, S.J. Roberts and R. Everson (2000) Hidden Markov Independent Components for Biosignal Analysis Proceedings of MEDSIP-2000, International Conference on Advances in Medical Signal and Information Processing, IEE, pp. 244-250.

  • S.J. Roberts and W.D. Penny (2000) Real-time Brain Computer Interfacing: a preliminary study using Bayesian learning Medical and Biological Engineering and Computing , Vol 38, No. 1, pp.56-61, 2000.

  • W.D. Penny, S.J. Roberts, E. Curran and M. Stokes(2000) EEG-based communication: a pattern recognition approach IEEE Transactions on Rehabilitation Engineering, Vol 8, No. 2, June.

    1999
  • W.D. Penny, D. Husmeier and S.J. Roberts (1999) The Bayesian Paradigm: second generation neural computing In P. Lisboa (Ed.) Artificial Neural Networks in Biomedicine , Springer-Verlag.

  • D. Husmeier, W. D. Penny and S. J. Roberts (1999). An Empirical Evaluation of Bayesian Sampling with Hybrid Monte Carlo for Training Neural Network Classifiers. Neural Networks Vol 12, pp. 677-705.

  • W.D. Penny and S.J. Roberts (1999) Dynamic models for nonstationary signal segmentation . Computers and Biomedical Research. Vol 32, No.6, December,pp.483-502. A longer technical report version is available here.

  • W.D. Penny, S.J. Roberts (1999) Dynamic Logistic Regression In Proceedings IJCNN'99 .

  • W.D. Penny, S.J. Roberts (1999) Nonstationary Logistic Regression Technical Report, Department of Electrical Engineering, Imperial College.

  • W.D. Penny, D. Husmeier and S.J. Roberts (1999). Covariance-based weighting for optimal combination of model predictions ICANN-99 , Vol 2, pp. 826-831. Longer, earlier technical report here .

  • W.D. Penny, S.J. Roberts and M. Stokes(1999) EEG-based communication: a pattern recognition approach Brain-Computer Interface Technology: Theory and practice. First International Meeting, Rensselaerville, New York, June 1999.

  • W.D. Penny and S.J. Roberts (1999) Experiments with an EEG-based computer interface Technical Report, Department of Electrical Engineering, Imperial College.

  • W.D. Penny, S.J. Roberts (1999) EEG-based communication via dynamic neural network models In Proceedings IJCNN'99 .

    1998
  • Stephen J. Roberts, Dirk Husmeier, Iead Rezek & Will Penny (1998). Bayesian Approaches to Gaussian Mixture Modelling. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol 20, No. 11, pp. 1133-1142.

  • Dirk Husmeier, William D. Penny, Stephen J. Roberts (1998). Empirical Evaluation of Bayesian Sampling for Neural Classifiers. in: L.Niklason, M.Boden, T.Ziemke (Eds.), ICANN 98: Proceedings of the 8th International Conference on Artificial Neural Networks , Springer Verlag, Perspectives in Neural Computing, pp. 323-328.

  • W.D. Penny and S.J. Roberts (1998). Bayesian neural networks for classification: how useful is the evidence framework ? Neural Networks , Vol 12, pp. 877-892.

  • W.D. Penny and S.J. Roberts (1998) Hidden Markov Models with Extended Observation Densities Technical Report TR-98-15, Department of Electrical Engineering, Imperial College.

  • W.D. Penny and S.J. Roberts (1998). Gaussian Observation Hidden Markov Models for EEG analysis. Technical Report TR-98-12, Department of Electrical Engineering, Imperial College.

  • W.D. Penny and S.J. Roberts (1998). Dynamic Linear Models, Recursive Least Squares and Steepest Descent Learning. Technical Report TR-98-13, Department of Electrical Engineering, Imperial College.

  • W.D. Penny and S.J. Roberts (1998). Error bars for linear and nonlinear neural network regression models. Technical Report, Department of Electrical Engineering, Imperial College.

  • W.D. Penny, S.J. Roberts and M.J. Stokes (1998). Imagined Hand Movements Identified from the EEG Mu-Rhythm. Technical Report. Department of Electrical Engineering, Imperial College .

  • S.J. Roberts, W. Penny & I.Rezek (1998). Temporal and Spatial Complexity measures for EEG-based Brain-Computer Interfacing. Medical & Biological Engineering and Computing, Vol 37, No. 1, pp. 93-99.

    1997

  • W.D.Penny and D.Frost (1997). Neural network modelling of the level of observation decision in an acute psychiatric ward. Computers and Biomedical Research , 30, 1-17.

  • W.D. Penny and S.J. Roberts (1997). Bayesian neural networks for detection of imagined finger movements from single-trial EEG. Technical Report, Department of Electrical Engineering, Imperial College.

    1996
  • W.D.Penny and D.Frost (1996). Modelling psychiatric decisions with linear regression and neural networks. In J.Taylor (Ed.) Neural networks and their applications , John Wiley.

  • S.J. Roberts & W.D. Penny (1996). Neural Networks : Friends or Foes? Sensor Review . 17(1),64-70.

  • W.D.Penny and D.Frost (1996). Neural networks in clinical medicine. Medical Decision Making , 16(4),386-398.

  • S.J. Roberts and W.D. Penny (1996). A Maximum Certainty Approach to Feedforward Neural Networks. Electronic Letters , 29(15),1340-1341.

  • S.J. Roberts, W.D. Penny, D. Pillot (1996) Novelty, Confidence & Errors in Connectionist Systems. Proceedings of IEE Colloquium on Intelligent Sensors and Fault Detection , September 1996, 1996/261 : 10/1-10/6.

    1995
  • W.D.Penny and T.J.Stonham (1995). Generalization in multilayer sigma-pi networks. IEEE transactions on Neural Networks , 6(2), 506-508.

    1994

     A slack year.

    1993

  • W.D.Penny and T.J.Stonham (1993) Storage capacity of multilayer boolean neural networks. Electronics Letters , 29(15), 1340-1341.