| Date | Topic | Where |
| 16.1.12 | Defective aversion: using computational methods to dissect decision making in mood disorders. | Universitätsklinik für Neurologie, Magdeburg, Germany |
| 21.12.11 | The fight within: decision making in affective disorders. | Max-Planck Institute for Biological Cybernetics, Tübingen, Germany |
| 4.9.11 | The fight within: decision making in mood disorders. | INCF Neuroinformatics. Computational Psychiatry special session. Boston, USA. |
| 26.4.11 | Pavlovian influences on decision-making. A route towards psychiatric co-morbidities? | Einstein Meeting. Humboldt-Universität, Berlin, Germany |
| 6.03.11 | Pavlovian approach and inhibition. | Janelia Farm conference: Neural circuits of decision-making |
| 18.06.10 | Affective asymmetries. The serotonergic stop signal. | Ecole Normale Superieure, Paris, France |
| 27.05.10 | Affective asymmetries. The serotonergic stop signal. | University of Zürich, Switzerland |
| 5.05.10 | Using RL tools to map affective decisions in depression. | Wolpert lab, Cambridge University, UK |
| 27.04.10 | Mapping affective decisions in depression. | Psychiatrische Universitätsklinik, Zürich |
| 14.01.10 | Affective influences on visual choices. | Rank Prize Meeting in honour of Roger Carpenter: What determines where we look, Grasmere, UK |
| 20.6.09 | RL crash course | University of Magdeburg, Germany. Slides are here |
| 28.5.09 | Knowledge and the limits of rationality | Gresham College, UK Online talk & slides |
| 30.3.09 | Computational thoughts | Donders Institute, Nijmegen, Netherlands |
| 19.2.09 | A generative model of mood disorders | University of Edinburgh, UK |
| 9.2.09 | Behavioural measurements and definitions of anhedonia and helplessness | Charite Hospital, Berlin, Germany |
| 5.1.09 | Computational Psychiatry. An application to depression. | Bergman lab, Hebrew University, Israel |
| 8.9.08 | Understanding Disorders of the Mind through Neuroimaging: Developing new paradigms. | Wellcome Trust, London |
| 18.6.08 | Depression: a computational formulation and a behavioural test. | Department of Neuroscience, NYU |
| 12.6.08 | Applying reinforcement learning to Depression: a validation. | Brain Stimulation Division, Columbia University |
| 2.6.08 | Applying reinforcement learning to Depression: a behavioural test. | Salzman lab, Columbia University |
| 29.5.08 | Applying reinforcement learning to Depression: a behavioural test | Computational Psychiatry Symposium, IGC, Portugal |
| 26.5.08 | Serotonin in reinforcement learning. | Institute Gulbenkian Champalimaud, Portugal |
| 3.3.08 | Automatically fitting detailed biophysical models | Comp. Sys. Neurosci. Workshop on Data sharing and modeling challenges in neuroscience |
| 21.2.08 | Depression, 5HT and DA: Insights from computational modelling. | Albert Einstein College of Medicine |
| 1.2.08 | Applying reinforcement learning to mood disorders--an example task. | Gatsby meeting, Center for Theoretical Neuroscience, Columbia University |
| 1.11.07 | Computational approaches to psychiatry. An application to depression | Symposium: Computational Models in Biological Psychiatry; Computational Cognitive Neuroscience Conference (SfN Satellite); |
| 5.10.07 | Serotonin, inhibition and negative moods | Workshop: Theoretical and experimental perspectives on serotonin function, Institute Gulbenkian Champalimaud, Portugal |
| 5.9.07 | Dopamine: reporting control in depression and mania? | Workshop on Neural bases reward decision making, Institute Gulbenkian Champalimaud, Portugal |
| 25.6.07 | Parameter inference as a convex problem | EPFL workshop on quantitative neuron models, CH |
| 28.4.07 | Depression -- towards a computational aetiology | NYSPI, Columbia University, New York |
| 18.4.07 | Serotonin, inhibition and depression | Cold Spring Harbor Lab |
| 15.3.07 | Depression: attempting a computational dissection. | Functional Imaging Lab, UCL, London |
| 22.2.07 | Optimal learning: a route to depression? | Comp. Sys. Neurosci. meeting short presentation |
| 25.1.07 | Building detailed single-cell models from biophysical data | Michael Häusser lab, UCL |
| 11.1.07 | Normative psychiatry. | Neuroeconomics group, UCL |
| 20.9.06 | Optimal models of depression. | Mood disorders unit CAMH, Toronto |
| 5.9.06 | Optimal models of depression. | Maier/Watkins lab,Boulder, Colorado |
| 29.8.06 | Optimal helplessness. Normative models of depression. | Neurosci. and Psychiatry Unit, Manchester |
| 16.8.06 | Depression, analgesia and optimality | Max-Planck Institute Tübingen |
| 19.7.06 | Inference in stochastic neurones | CNS stochastic dynamics workshop [pdf] |
| 16.7.06 | Fast population coding | CNS main meeting [pdf] |
| 28.6.06 | EEG / MEG analysis | Functional Imagning lab, UCL, London [pdf] |
| 15.3.06 | Fast population coding | Andersen lab, California Institute of Technology, Los Angeles |
| 5.12.05 | Fast population coding | Max-Planck Institut für Biologische Kybernetik, Tübingen, Germany |
| 21.11.05 | Single-cell models | Center for Theoretical Neuroscience, Columbia University, New York |
| 18.11.05 | Fast population coding | Learning Group, University of Toronto |
| 17.11.05 | Fast population coding | Becker lab, McMaster University, Hamilton, Canada |
| 21.10.05 | Efficient infernce of single-cell models | UNIC, CNRS, Gif-sur-Yvette, France |
| 20.10.05 | Fast population coding | Denève and Gutkin lab, École Normale Superieure, Paris |