Computational Neuroscience (MTAT.03.291)
Disclaimer: This course will be exclusively online. Recordings of lectures and practices will be uploaded as the course progresses.
Lectures: Tuesdays 14:15
Practices: Wednesday 14:15, via zoom
Questions:
- Raul Vicente (raulvicente@gmail.com)
- Marharyta Domnich (marharyta.domnich@gmail.com)
- Farid Hasanov (faridhasanov@protonmail.com)
- Kristjan Kaup (kaup.kristjan@gmail.com)
- http://neuro.cs.ut.ee
About the course
The purpose of this course is to familiarize students without biological background with the field of neuroscience and study how mathematics and computer science are used to solve questions arising in this field. The following topics will be covered during the course:
- Basic organization of the brain and nervous system
- Approaches to explore the brain
- Data analysis
- Single neuron models
- Network models
- Learning and plasticity
- Memory
- Cognitive functions
In the practice sessions, we are going to
- Try out concepts discussed in the lectures.
- Solve exercises from the field.
- Analyse data using Python.
- Conduct demonstrations/experiments.
Grading
Your final grade will consist of:
- Homework assignments (30%)
- Project (40%)
- Exam (30%)
- And bonus exercises (~5-7%)
You can collect up to 105/107 points, 90+ will give you A, 80+ B, 70+ C and so on. However to pass the course you are required to at least get 50% of each component (homework, project, and exam).
Materials
Course materials from last years are available at Github repository
Also, homework exercises for this semester will be put there as we go.