About the course:
Computational Neuroscience is a rapidly evolving field whose methods and techniques are critical for understanding and modelling the brain, and also for designing and interpreting experiments. Mathematical modeling is an essential tool to cut through the vast
complexity of neurobiological systems and their many interacting elements.
This three-weeks school teaches the central ideas, methods, and practice of modern computational neuroscience through a combination of lectures and hands-on project work. Each morning is devoted to lectures given by distinguished international faculty on topics
across the breadth of experimental and computational neuroscience. During the rest of the day, students work on research projects in teams of 2-3 people under the close supervision of expert tutors and faculty. Research projects will be proposed by faculty
before the course, and will include the modeling of neurons, neural systems, and behavior, the analysis of state-of-the-art neural data (behavioral data, multi-electrode recordings, calcium imaging data, connectomics data, etc.), and the development of theories
to explain experimental observations.
The course is designed for graduate students and postdoctoral fellows from a variety of disciplines, including neuroscience, physics, electrical engineering, computer science, mathematics and psychology. Students are expected to have a keen interest and basic
background in neurobiology, a solid foundation in mathematics, as well as some computer experience. A four-day pre-school in mathematics and programming is offered for students that want to catch up on their math and programming skills. A maximum of 24 students
will be accepted. Students of any nationality can apply. We specifically encourage applications from researchers who work in the developing world. Stipends are available.