Invited seminars and talks

2013

  • Learning processes in the development of addiction
  • 24.5.2013 Dopamine conference, Alghero, Sardinia
  • Re-using thoughts: making habits efficient?
  • 25.4.2013 Berlin Einstein Symposium, Berlin, Germany
  • pdf Modelling behavioural data
  • 13.2.2013 Zürich SPM Course Tutorial, Zürich, Switzerland
  • A generative account of emotional dysfunctions
  • 29.1.2013 Departmental seminar, Universitäre Psychiatrische Dienste, Berne, Switzerland

2012

  • Defective aversion: using computational methods to dissect decision making in mood disorders
  • 16.1.12 Universitätsklinik für Neurologie, Magdeburg, Germany
  • Mathematizing Madness
  • 27.1.12 Inauguration symposium for Prof. Roshan Cools. Donders Institute, Nijmegen, Netherlands
  • Defective aversion: using computational methods to dissect decision making in mood disorders
  • 14.2.12 Technische Universität Berlin, Germany
  • Defective aversion: the contribution of serotonin
  • 18.6.2012 Devanx final meeting, Paris, France
  • pdf Reinforcement learning I: theory
  • 14.8.2012 EU Advanced Course on Computational Neuroscience, Bedlewo, Poland
  • pdf Reinforcement learning II: biology
  • 15.8.2012 EU Advanced Course on Computational Neuroscience, Bedlewo, Poland
  • Explaining away emotional dysfunctions
  • 14.9.2012 Bernstein Center for Computational Neuroscience annual meeting, München, Germany
  • pdf Modelling behavioural data
  • 17.9.2012 UCL-MPS Symposium on Computational Psychiatry and Aging, Ringberg Castle, Germany
  • Dopamine and learning dysfunctions in addition: a crash course
  • 18.10.2012 Annual meeting of the World Psychiatric Association
  • Computational approaches to the disordered mind
  • 27.11.2012 Departmental Seminar, Institute of biomedical engineering, ETH Zürich, Switzerland

2011

2010

  • Affective influences on visual choices.
  • 14.01.10 Rank Prize Meeting in honour of Roger Carpenter: What determines where we look, Grasmere, UK
  • Mapping affective decisions in depression.
  • 27.04.10 Psychiatrische Universitätsklinik, Zürich
  • Using RL tools to map affective decisions in depression.
  • 5.05.10 Wolpert lab, Cambridge University, UK
  • Affective asymmetries. The serotonergic stop signal.
  • 27.05.10 University of Zürich, Switzerland
  • Affective asymmetries. The serotonergic stop signal.
  • 18.06.10 Ecole Normale Superieure, Paris, France

2009

  • Computational Psychiatry. An application to depression.
  • 5.1.09 Bergman lab, Hebrew University, Israel
  • Behavioural measurements and definitions of anhedonia and helplessness
  • 9.2.09 Charite Hospital, Berlin, Germany
  • A generative model of mood disorders
  • 19.2.09 University of Edinburgh, UK
  • Computational thoughts
  • 30.3.09 Donders Institute, Nijmegen, Netherlands
  • Knowledge and the limits of rationality
  • 28.5.09 Gresham College, UK video
  • RL crash course
  • 20.6.09 University of Magdeburg, Germany. Slides are here

2008

  • Applying reinforcement learning to mood disorders--an example task.
  • 1.2.08 Gatsby meeting, Center for Theoretical Neuroscience, Columbia University
  • Depression, 5HT and DA: Insights from computational modelling.
  • 21.2.08 Albert Einstein College of Medicine
  • Automatically fitting detailed biophysical models
  • 3.3.08 Comp. Sys. Neurosci. Workshop on Data sharing and modeling challenges in neuroscience
  • Serotonin in reinforcement learning.
  • 26.5.08 Institute Gulbenkian Champalimaud, Portugal
  • Applying reinforcement learning to Depression: a behavioural test
  • 29.5.08 Computational Psychiatry Symposium, IGC, Portugal
  • Applying reinforcement learning to Depression: a behavioural test.
  • 2.6.08 Salzman lab, Columbia University
  • Applying reinforcement learning to Depression: a validation.
  • 12.6.08 Brain Stimulation Division, Columbia University
  • Depression: a computational formulation and a behavioural test.
  • 18.6.08 Department of Neuroscience, NYU
  • Understanding Disorders of the Mind through Neuroimaging: Developing new paradigms.
  • 8.9.08 Wellcome Trust, London

2007

  • Normative psychiatry.
  • 11.1.07 Neuroeconomics group, UCL
  • Building detailed single-cell models from biophysical data
  • 25.1.07 Michael Häusser lab, UCL
  • Optimal learning: a route to depression?
  • 22.2.07 Comp. Sys. Neurosci. meeting short presentation
  • Depression: attempting a computational dissection.
  • 15.3.07 Functional Imaging Lab, UCL, London
  • Serotonin, inhibition and depression
  • 18.4.07 Cold Spring Harbor Lab
  • Depression -- towards a computational aetiology
  • 28.4.07 NYSPI, Columbia University, New York
  • Parameter inference as a convex problem
  • 25.6.07 EPFL workshop on quantitative neuron models, CH
  • Dopamine: reporting control in depression and mania?
  • 5.9.07 Workshop on Neural bases reward decision making, Institute Gulbenkian Champalimaud, Portugal
  • pdf Serotonin, inhibition and negative moods
  • 5.10.07 Workshop: Theoretical and experimental perspectives on serotonin function, Institute Gulbenkian Champalimaud, Portugal
  • Computational approaches to psychiatry. An application to depression
  • 1.11.07 Symposium: Computational Models in Biological Psychiatry; Computational Cognitive Neuroscience Conference (SfN Satellite);

2006

  • Fast population coding
  • 15.3.06 Andersen lab, California Institute of Technology, Los Angeles
  • pdf EEG / MEG analysis
  • 28.6.06 Functional Imagning lab, UCL, London
  • pdf Fast population coding
  • 16.7.06 CNS main meeting
  • pdf Inference in stochastic neurones
  • 19.7.06 CNS stochastic dynamics workshop
  • Depression, analgesia and optimality
  • 16.8.06 Max-Planck Institute Tübingen
  • Optimal helplessness. Normative models of depression.
  • 29.8.06 Neurosci. and Psychiatry Unit, Manchester
  • Optimal models of depression.
  • 5.9.06 Maier/Watkins lab,Boulder, Colorado
  • Optimal models of depression.
  • 20.9.06 Mood disorders unit CAMH, Toronto

2005

  • Fast population coding
  • 5.12.05 Max-Planck Institut für Biologische Kybernetik, Tübingen, Germany
  • Single-cell models
  • 21.11.05 Center for Theoretical Neuroscience, Columbia University, New York
  • Fast population coding
  • 18.11.05 Learning Group, University of Toronto
  • Fast population coding
  • 17.11.05 Becker lab, McMaster University, Hamilton, Canada
  • Efficient infernce of single-cell models
  • 21.10.05 UNIC, CNRS, Gif-sur-Yvette, France
  • Fast population coding
  • 20.10.05 Denève and Gutkin lab, École Normale Superieure, Paris