Quentin J M Huys

Summary

Affiliation: University of Cambridge
Country: UK

Publications

  1. ncbi request reprint The role of learning-related dopamine signals in addiction vulnerability
    Quentin J M Huys
    Translational Neuromodeling Unit, Department of Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland Department of Psychiatry, Psychosomatics and Psychotherapy, Hospital of Psychiatry, University of Zurich, Zurich, Switzerland Electronic address
    Prog Brain Res 211:31-77. 2014
  2. pmc Mapping anhedonia onto reinforcement learning: a behavioural meta-analysis
    Quentin Jm Huys
    Gatsby Computational Neuroscience Unit, UCL, London, UK
    Biol Mood Anxiety Disord 3:12. 2013
  3. pmc Bonsai trees in your head: how the pavlovian system sculpts goal-directed choices by pruning decision trees
    Quentin J M Huys
    Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom
    PLoS Comput Biol 8:e1002410. 2012
  4. pmc Disentangling the roles of approach, activation and valence in instrumental and pavlovian responding
    Quentin J M Huys
    Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom
    PLoS Comput Biol 7:e1002028. 2011
  5. doi request reprint Are computational models of any use to psychiatry?
    Quentin J M Huys
    Wellcome Trust Centre for Neuroimaging, Gatsby Computational Neuroscience Unit and Medical School, UCL, United Kingdom
    Neural Netw 24:544-51. 2011
  6. pmc Smoothing of, and parameter estimation from, noisy biophysical recordings
    Quentin J M Huys
    Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom
    PLoS Comput Biol 5:e1000379. 2009
  7. ncbi request reprint A Bayesian formulation of behavioral control
    Quentin J M Huys
    Gatsby Computational Neuroscience Unit, UCL, 17 Queen Square, London WC1N3AR, UK
    Cognition 113:314-28. 2009
  8. ncbi request reprint Fast population coding
    Quentin J M Huys
    Gatsby Computational Neuroscience Unit, University College London, London WC1N 3AR, UK
    Neural Comput 19:404-41. 2007
  9. pmc Go and no-go learning in reward and punishment: interactions between affect and effect
    Marc Guitart-Masip
    Institute of Cognitive Neuroscience, University College London, London, W1CN 4AR, UK
    Neuroimage 62:154-66. 2012
  10. pmc Serotonin, inhibition, and negative mood
    Peter Dayan
    Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom
    PLoS Comput Biol 4:e4. 2008

Detail Information

Publications15

  1. ncbi request reprint The role of learning-related dopamine signals in addiction vulnerability
    Quentin J M Huys
    Translational Neuromodeling Unit, Department of Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland Department of Psychiatry, Psychosomatics and Psychotherapy, Hospital of Psychiatry, University of Zurich, Zurich, Switzerland Electronic address
    Prog Brain Res 211:31-77. 2014
    ..We argue that this provides a computationally coherent account of some features of addiction. ..
  2. pmc Mapping anhedonia onto reinforcement learning: a behavioural meta-analysis
    Quentin Jm Huys
    Gatsby Computational Neuroscience Unit, UCL, London, UK
    Biol Mood Anxiety Disord 3:12. 2013
    ..We attempted to disentangle these factors with respect to anhedonia in the context of stress, Major Depressive Disorder (MDD), Bipolar Disorder (BPD) and a dopaminergic challenge...
  3. pmc Bonsai trees in your head: how the pavlovian system sculpts goal-directed choices by pruning decision trees
    Quentin J M Huys
    Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom
    PLoS Comput Biol 8:e1002410. 2012
    ..We conclude that Pavlovian behavioural inhibition shapes highly flexible, goal-directed choices in a manner that may be important for theories of decision-making in mood disorders...
  4. pmc Disentangling the roles of approach, activation and valence in instrumental and pavlovian responding
    Quentin J M Huys
    Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom
    PLoS Comput Biol 7:e1002028. 2011
    ..Our findings argue for a view of the Pavlovian system as a constraint or prior, facilitating learning by alleviating computational costs that come with increased flexibility...
  5. doi request reprint Are computational models of any use to psychiatry?
    Quentin J M Huys
    Wellcome Trust Centre for Neuroimaging, Gatsby Computational Neuroscience Unit and Medical School, UCL, United Kingdom
    Neural Netw 24:544-51. 2011
    ..But it also identifies areas in which the contributions of CMs will likely be pivotal, like an understanding of social influences in psychiatry, and of the co-morbidity structure of psychiatric diseases...
  6. pmc Smoothing of, and parameter estimation from, noisy biophysical recordings
    Quentin J M Huys
    Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom
    PLoS Comput Biol 5:e1000379. 2009
    ..Overall, we find that model-based smoothing is a powerful, robust technique for smoothing of noisy biophysical data and for inference of biophysical parameters in the face of recording noise...
  7. ncbi request reprint A Bayesian formulation of behavioral control
    Quentin J M Huys
    Gatsby Computational Neuroscience Unit, UCL, 17 Queen Square, London WC1N3AR, UK
    Cognition 113:314-28. 2009
    ..These results are discussed with reference to depression and animal models thereof...
  8. ncbi request reprint Fast population coding
    Quentin J M Huys
    Gatsby Computational Neuroscience Unit, University College London, London WC1N 3AR, UK
    Neural Comput 19:404-41. 2007
    ..We suggest this as an appropriate foundation for understanding time-varying population codes. Furthermore, we show how adaptation to temporal stimulus statistics emerges directly from the demands of simple decoding...
  9. pmc Go and no-go learning in reward and punishment: interactions between affect and effect
    Marc Guitart-Masip
    Institute of Cognitive Neuroscience, University College London, London, W1CN 4AR, UK
    Neuroimage 62:154-66. 2012
    ....
  10. pmc Serotonin, inhibition, and negative mood
    Peter Dayan
    Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom
    PLoS Comput Biol 4:e4. 2008
    ....
  11. doi request reprint Serotonin and aversive Pavlovian control of instrumental behavior in humans
    Dirk E M Geurts
    Radboud University Nijmegen Medical Centre, Donders Institute for Brain, Cognition and Behavior, Centre for Cognitive Neuroimaging and Department of Psychiatry, 6500 HB, Nijmegen, The Netherlands, Gatsby Computational Neuroscience Unit and Wellcome Trust Centre for Neuroimaging, UCL, WC1N 3AR, London, United Kingdom, Translational Neuromodeling Unit, ETH, University of Zurich, CH 8032 Zurich, Switzerland, and Psychiatry, Psychotherapy and Psychosomatics, University Hospital of Psychiatry Zurich, CH 8032 Zurich, Switzerland
    J Neurosci 33:18932-9. 2013
    ....
  12. ncbi request reprint Efficient estimation of detailed single-neuron models
    Quentin J M Huys
    Gatsby Computational Neuroscience Unit, University College London, UK
    J Neurophysiol 96:872-90. 2006
    ....
  13. ncbi request reprint Serotonin in affective control
    Peter Dayan
    Gatsby Computational Neuroscience Unit, University College London, London WC1N3AR, UK
    Annu Rev Neurosci 32:95-126. 2009
    ..Finally, we suggest that it is only a partial reflection of dopamine because of essential asymmetries between the natural statistics of rewards and punishments...
  14. pmc Action dominates valence in anticipatory representations in the human striatum and dopaminergic midbrain
    Marc Guitart-Masip
    Institute of Cognitive Neuroscience, University College London, London, W1CN 4AR, United Kingdom
    J Neurosci 31:7867-75. 2011
    ..This dominant influence of action requires an enriched notion of opponency between reward and punishment...
  15. doi request reprint Encoding and decoding spikes for dynamic stimuli
    Rama Natarajan
    Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
    Neural Comput 20:2325-60. 2008
    ..We show that this network can be learned in a supervised manner by a simple local learning rule...