Syllabus database for doctoral courses
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Syllabus database for doctoral courses
SYLLABI FOR DOCTORAL COURSES
| Swedish title | Beräkningsmodellering för forskning inom kognitiv neurovetenskap och psykiatri |
|---|---|
| English title | Computational Modelling for Cognitive Neuroscience and Psychiatry Research |
| Course number | 5567 |
| Credits | 1.5 |
| Responsible KI department | Institutionen för neurobiologi, vårdvetenskap och samhälle |
| Specific entry requirements | Background in medicine, biomedicine, biology, psychology, cognitive science, medical imaging, computational biology or similar. Basic knowledge on statistics and programming will be needed in the course. |
| Grading | Passed /Not passed |
| Established by | The Committee for Doctoral Education |
| Established | 2022-03-02 |
| Purpose of the course | The purpose of the course is to introduce doctoral students to computational techniques for modelling and analyzing behavioral data for cognitive neuroscience and psychiatry research, providing them with practical experience applying these techniques. |
| Intended learning outcomes | After successful course completion, the students will be acquainted with several key computational models and have enough understanding to enable them to 1) critically interpret the results of the studies in the field; and 2) identify and choose the most appropriate methods to model their data. |
| Contents of the course | Basic concepts in computational modelling such as parameter fitting and model comparison; introduction to reinforcement learning; classical models for decision-making tasks (drift diffusion model, intertemporal choice, two-armed bandit). Applications in psychiatry: psychosis, addiction, depression, anxiety. |
| Teaching and learning activities | Lectures, hands-on practical sessions, article discussion in seminars. |
| Compulsory elements | Attending the lectures, seminars, and hands-on sessions is mandatory. Absence from a lecture may be compensated by writing an essay on the corresponding topic. The examination is compulsory (seminars, as well as report and presentation of the practical assignment). |
| Examination | The examination consists of two moments: 1) presentation and active discussion in the seminars; 2) a practical assignment where students will define a problem in cognitive neuroscience or psychiatry and describe how to study it with the approaches explained in the course (theoretical framework, experiments, modelling and analysis, expected outcomes). The assignments will be presented in front of the other students in the last session. |
| Literature and other teaching material | Recommended literature:
1. Sutton, R.S. and A.G. Barto, Reinforcement learning: an introduction. 1998, Cambridge, Massachusetts: The MIT Press. 2. Daw, N., Trial-by-trial data analysis using computational models, in Decision Making, Affect, and Learning, M.R. Delgado, E.A. Phelps, and T.W. Robbins, Editors. 2011, Oxford University Press. 3. Piray, P., et al., Hierarchical Bayesian inference for concurrent model fitting and comparison for group studies. PLoS Comput Biol, 2019. 15(6): p. e1007043. 4. Wilson, R.C. and A.G. Collins, Ten simple rules for the computational modeling of behavioral data. Elife, 2019. 8. 5. Huys, Q.J., T.V. Maia, and M.J. Frank, Computational psychiatry as a bridge from neuroscience to clinical applications. Nat Neurosci, 2016. 19(3): p. 404-13. 6. Huys, Q.J., N.D. Daw, and P. Dayan, Depression: a decision-theoretic analysis. Annu Rev Neurosci, 2015. 38: p. 1-23. 7. Sterzer, P., et al., The Predictive Coding Account of Psychosis. Biol Psychiatry, 2018. 84(9): p. 634-643. |
Course responsible |
Marc Guitart-Masip Institutionen för neurobiologi, vårdvetenskap och samhälle marc.guitart-masip@ki.se |
| Contact person |
Andreas Olsson Institutionen för klinisk neurovetenskap 0852482459 andreas.olsson@ki.se Marc Guitart-Masip Institutionen för neurobiologi, vårdvetenskap och samhälle marc.guitart-masip@ki.se |
