Entry requirements
Only open to MSc Psychology (research) students.
Students should have basic programming skills in R, and have the R software installed before the start of the course. It is strongly recommended to follow the elective ‘Introduction to R’.
If this is not possible, please contact the course coordinator before the course starts.
Description
Computational models are widely used in psychology, cognitive science, economics, neuroscience and artificial intelligence to better understand the processes that give rise to intelligent behavior. They describe the algorithms underlying cognitive processes such as attention, learning and decision-making, and can often be linked to specific processes in the brain.
In this course, we will discuss computational models of reinforcement learning and perceptual decision-making, and apply them to empirical data. We will also discuss the neural mechanisms that have inspired the development of these computational models. Specific topics include sequential sampling models of perceptual decision-making, Markov decision processes, Q-learning and the exploration-exploitation tradeoff.
Each student will investigate a current issue in the computational modelling literature on reinforcement learning and decision-making. Students will also gain hands-on experience with implementing computational models, fitting them to data and interpreting the results. These abilities respond to the fast-growing demand for skills related to programming and computational modelling in- and outside of academia.
Course objectives
At the end of the course, students:
will be familiar with the key paradigms and models employed in the fields of reinforcement learning and decision-making;
can understand and program computational models, and fit them to experimental data.
can interpret their model fitting findings, and present their conclusions to a scientific audience.
Timetable
For the timetable of this course please refer to MyTimetable
Registration
Education
Students must register themselves for all course components (lectures, tutorials and practicals) they wish to follow. You can register up to 5 days prior to the start of the course.
Exams
You must register for each exam in My Studymap at least 10 days before the exam date. You cannot take an exam without a valid registration in My Studymap. Carefully read all information about the procedures and deadlines for registering for courses and exams.
Exchange students and external guest students will be informed by the education administration about the current registration procedure.
Mode of instruction
The sessions are a mix of seminars that present theoretical background, hands-on practical sessions to implement computational models, and a poster session. The course is held in English.
Attendance at the workgroup/seminar meetings is mandatory. See Brightspace for more information.
Assessment method
The assessment of the course is based on:
50% written assignment;
50% hands-on model fitting excercise, resulting in a poster presentation
The Institute of Psychology follows the policy of the Faculty of Social and Behavioural Sciences to systematically check student papers for plagiarism with the help of software. All students are required to take and pass the Scientific Integrity Test with a score of 100% in order to learn about the practice of integrity in scientific writing. Students are given access to the quiz via a module on Brightspace. Disciplinary measures will be taken when fraud is detected. Students are expected to be familiar with and understand the implications of this fraud policy.
Reading list
Reading materials will be made available via BrightSpace.
Contact information
Prof. Dr. S.T. Nieuwenhuis s.nieuwenhuis@fsw.leidenuniv.nl