Jean Daunizeau

Summary

Affiliation: University College London
Country: UK

Publications

  1. pmc Observing the observer (II): deciding when to decide
    Jean Daunizeau
    Wellcome Trust Centre for Neuroimaging, University College of London, London, United Kingdom
    PLoS ONE 5:e15555. 2010
  2. doi request reprint Bayesian multi-modal model comparison: a case study on the generators of the spike and the wave in generalized spike-wave complexes
    Jean Daunizeau
    Institute of Neurology, Wellcome Trust Centre for Neuroimaging, University College of London, 12 Queen Square, London, UK
    Neuroimage 49:656-67. 2010
  3. ncbi request reprint Symmetrical event-related EEG/fMRI information fusion in a variational Bayesian framework
    Jean Daunizeau
    Wellcome Department of Imaging Neuroscience, London, UK INSERM U678, Paris F 75013, France
    Neuroimage 36:69-87. 2007
  4. ncbi request reprint Dynamic causal modelling: a critical review of the biophysical and statistical foundations
    J Daunizeau
    Wellcome Trust Centre for Neuroimaging, University College of London, UK
    Neuroimage 58:312-22. 2011
  5. pmc Dynamic causal modelling of distributed electromagnetic responses
    Jean Daunizeau
    The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, UCL 12 Queen Square, London, WC1N 3BG UK
    Neuroimage 47:590-601. 2009
  6. pmc Observing the observer (I): meta-bayesian models of learning and decision-making
    Jean Daunizeau
    Wellcome Trust Centre for Neuroimaging, University College of London, London, United Kingdom
    PLoS ONE 5:e15554. 2010
  7. pmc EEG and MEG data analysis in SPM8
    Vladimir Litvak
    The Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, Queen Square, London, UK
    Comput Intell Neurosci 2011:852961. 2011
  8. pmc Striatal prediction error modulates cortical coupling
    Hanneke E M den Ouden
    Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, United Kingdom
    J Neurosci 30:3210-9. 2010
  9. ncbi request reprint Generalised filtering and stochastic DCM for fMRI
    Baojuan Li
    The Wellcome Trust Centre for Neuroimaging, University College London, Queen Square, London WC1N 3BG, UK
    Neuroimage 58:442-57. 2011
  10. doi request reprint The combination of EEG source imaging and EEG-correlated functional MRI to map epileptic networks
    Serge Vulliemoz
    Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, University College London, Queen Square, London, United Kingdom
    Epilepsia 51:491-505. 2010

Detail Information

Publications32

  1. pmc Observing the observer (II): deciding when to decide
    Jean Daunizeau
    Wellcome Trust Centre for Neuroimaging, University College of London, London, United Kingdom
    PLoS ONE 5:e15555. 2010
    ..Finally, we illustrate how our approach can be used to quantify subjective beliefs and preferences that underlie inter-individual differences in behaviour...
  2. doi request reprint Bayesian multi-modal model comparison: a case study on the generators of the spike and the wave in generalized spike-wave complexes
    Jean Daunizeau
    Institute of Neurology, Wellcome Trust Centre for Neuroimaging, University College of London, 12 Queen Square, London, UK
    Neuroimage 49:656-67. 2010
    ..The result supports the hypothesis of different neurophysiological mechanisms underlying the generation of the spike versus wave components of GSW discharges...
  3. ncbi request reprint Symmetrical event-related EEG/fMRI information fusion in a variational Bayesian framework
    Jean Daunizeau
    Wellcome Department of Imaging Neuroscience, London, UK INSERM U678, Paris F 75013, France
    Neuroimage 36:69-87. 2007
    ..We apply the method on EEG/fMRI recordings from a patient with epilepsy, in order to identify brain areas involved during the generation of epileptic spikes. The results are validated using intracranial EEG measurements...
  4. ncbi request reprint Dynamic causal modelling: a critical review of the biophysical and statistical foundations
    J Daunizeau
    Wellcome Trust Centre for Neuroimaging, University College of London, UK
    Neuroimage 58:312-22. 2011
    ..Finally, we discuss potential extensions of the current DCM framework, such as stochastic DCMs, plastic DCMs and field DCMs...
  5. pmc Dynamic causal modelling of distributed electromagnetic responses
    Jean Daunizeau
    The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, UCL 12 Queen Square, London, WC1N 3BG UK
    Neuroimage 47:590-601. 2009
    ..Here, we describe the distributed spatial model and present a comparative evaluation with conventional equivalent current dipole (ECD) models of auditory processing, as measured with EEG...
  6. pmc Observing the observer (I): meta-bayesian models of learning and decision-making
    Jean Daunizeau
    Wellcome Trust Centre for Neuroimaging, University College of London, London, United Kingdom
    PLoS ONE 5:e15554. 2010
    ....
  7. pmc EEG and MEG data analysis in SPM8
    Vladimir Litvak
    The Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, Queen Square, London, UK
    Comput Intell Neurosci 2011:852961. 2011
    ....
  8. pmc Striatal prediction error modulates cortical coupling
    Hanneke E M den Ouden
    Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, United Kingdom
    J Neurosci 30:3210-9. 2010
    ..This finding substantially advances our understanding of striatal function and provides direct empirical evidence for formal learning theories that posit a central role for prediction error-dependent plasticity...
  9. ncbi request reprint Generalised filtering and stochastic DCM for fMRI
    Baojuan Li
    The Wellcome Trust Centre for Neuroimaging, University College London, Queen Square, London WC1N 3BG, UK
    Neuroimage 58:442-57. 2011
    ..Finally, we note that the ability to model endogenous or random fluctuations on hidden neuronal (and physiological) states provides a new and possibly more plausible perspective on how regionally specific signals in fMRI are generated...
  10. doi request reprint The combination of EEG source imaging and EEG-correlated functional MRI to map epileptic networks
    Serge Vulliemoz
    Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, University College London, Queen Square, London, United Kingdom
    Epilepsia 51:491-505. 2010
    ..We then discuss analysis strategies to combine both techniques by reviewing studies in epilepsy, current methodologic development, and future directions of this fast-developing field...
  11. ncbi request reprint Multiple sparse priors for the M/EEG inverse problem
    Karl Friston
    The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, UCL, 12 Queen Square, London, WC1N 3BG, UK
    Neuroimage 39:1104-20. 2008
    ..This means the approach automatically selects either a sparse or a distributed model, depending on the data. The scheme is compared with conventional applications of Bayesian solutions to quantify the improvement in performance...
  12. ncbi request reprint Localization Estimation Algorithm (LEA): a supervised prior-based approach for solving the EEG/MEG inverse problem
    Jeremie Mattout
    Institute of Cognitive Neuroscience, London, UK
    Inf Process Med Imaging 18:536-47. 2003
    ..LEA is evaluated through numerical simulations and compared to a classical Weighted Minimum Norm estimation...
  13. pmc Nonlinear dynamic causal models for fMRI
    Klaas Enno Stephan
    Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, UK
    Neuroimage 42:649-62. 2008
    ..In both practical examples, Bayesian model selection favoured the nonlinear models over corresponding bilinear ones...
  14. pmc Integrated Bayesian models of learning and decision making for saccadic eye movements
    Kay H Brodersen
    Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, UK
    Neural Netw 21:1247-60. 2008
    ....
  15. ncbi request reprint Population dynamics: variance and the sigmoid activation function
    André C Marreiros
    Wellcome Trust Centre for Neuroimaging, University College London, UK
    Neuroimage 42:147-57. 2008
    ..The importance of implicit variance in neuronal states for neural-mass models of cortical dynamics is illustrated using both synthetic data and real EEG measurements of sensory evoked responses...
  16. pmc Network discovery with DCM
    Karl J Friston
    The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, UK
    Neuroimage 56:1202-21. 2011
    ..We envisage that this approach will provide a useful complement to current analyses of functional connectivity for both activation and resting-state studies...
  17. 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...
  18. ncbi request reprint Variational Bayesian inversion of the equivalent current dipole model in EEG/MEG
    Stefan J Kiebel
    The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, UCL, 12 Queen Square, London, WC1N 3AR, UK
    Neuroimage 39:728-41. 2008
    ..We illustrate the advantage of our Bayesian scheme, using a multi-subject EEG auditory study, where we compare competing models for the generation of the N100 component...
  19. ncbi request reprint A mesostate-space model for EEG and MEG
    Jean Daunizeau
    The Wellcome Deparment of Imaging Neuroscience, Institute of Neurology, UCL, 12 Queen Square, London, UK
    Neuroimage 38:67-81. 2007
    ..The approach is evaluated and compared to standard inverse EEG techniques, using synthetic data and real data. The results demonstrate the added-value of the mesostate-space model and its variational inversion...
  20. pdf Action and behavior: a free-energy formulation
    Karl J Friston
    The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London, WC1N 3BG, UK
    Biol Cybern 102:227-60. 2010
    ..In short, the free-energy formulation may provide an alternative perspective on the motor control that places it in an intimate relationship with perception...
  21. ncbi request reprint Population dynamics under the Laplace assumption
    André C Marreiros
    The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, UK
    Neuroimage 44:701-14. 2009
    ..The mean-field model presented here will form the basis of a dynamic causal model of observed electromagnetic signals in future work...
  22. pmc Optimizing experimental design for comparing models of brain function
    Jean Daunizeau
    Wellcome Trust Centre for Neuroimaging, University College of London, London, UK
    PLoS Comput Biol 7:e1002280. 2011
    ..Finally, we discuss limitations and potential extensions of this work...
  23. pmc Dynamic causal modelling of anticipatory skin conductance responses
    Dominik R Bach
    Wellcome Trust Centre for Neuroimaging, University College London, 12 Queen Square, London, United Kingdom
    Biol Psychol 85:163-70. 2010
    ..The model furnishes a potentially powerful approach to characterising SCR that exploits knowledge about how these signals are generated...
  24. pmc Recognizing sequences of sequences
    Stefan J Kiebel
    Wellcome Trust Centre for Neuroimaging, London, UK
    PLoS Comput Biol 5:e1000464. 2009
    ..By presenting anomalous stimuli, we find that the resulting recognition dynamics disclose inference at multiple time scales and are reminiscent of neuronal dynamics seen in the real brain...
  25. pmc Reinforcement learning or active inference?
    Karl J Friston
    The Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom
    PLoS ONE 4:e6421. 2009
    ..The ensuing proof-of-concept may be important because the free-energy formulation furnishes a unified account of both action and perception and may speak to a reappraisal of the role of dopamine in the brain...
  26. pmc Bayesian model selection for group studies
    Klaas Enno Stephan
    Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, UK
    Neuroimage 46:1004-17. 2009
    ..g. comparing different source reconstruction methods for EEG/MEG or selecting among competing computational models of learning and decision-making...
  27. pmc A hierarchy of time-scales and the brain
    Stefan J Kiebel
    Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom
    PLoS Comput Biol 4:e1000209. 2008
    ..The framework provides predictions about, and principled constraints on, cortical structure-function relationships, which can be tested by manipulating the time-scales of sensory input...
  28. ncbi request reprint Model selection and gobbledygook: response to Lohmann et al
    Karl Friston
    The Wellcome Trust Centre for Neuroimaging, University College London, Queen Square, London WC1N 3BG, UK
    Neuroimage 75:275-8; discussion 279-81. 2013
    ..2010). In this response, we unpack their misconceptions and try to answer their questions...
  29. pmc Spatial attention, precision, and Bayesian inference: a study of saccadic response speed
    Simone Vossel
    Wellcome Trust Centre for Neuroimaging, University College London, WC1N 3BG London, UK
    Cereb Cortex 24:1436-50. 2014
    ..Our results provide empirical support for precision-dependent changes in beliefs about saccade target locations and motivate future neuroimaging and neuropharmacological studies of how Bayesian inference may determine spatial attention. ..
  30. pmc Subliminal instrumental conditioning demonstrated in the human brain
    Mathias Pessiglione
    Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London WC1N3BG, UK
    Neuron 59:561-7. 2008
    ..We conclude that, even without conscious processing of contextual cues, our brain can learn their reward value and use them to provide a bias on decision making...
  31. ncbi request reprint Bayesian spatio-temporal approach for EEG source reconstruction: conciliating ECD and distributed models
    Jean Daunizeau
    UMR 678 INSERM UPMC, Paris, France
    IEEE Trans Biomed Eng 53:503-16. 2006
    ..Using simulated EEG data, the proposed inverse approach is evaluated and compared with standard distributed methods using both classical criteria and ROC curves...