Computational Neuroscience Lecture Series from Models to Applications

A. General overview: Anatomical and physiological basis of neuroscience (2 lectures, Luksch) B. Modeling: Neural dynamics and coding (4 lectures, Herz, Leibold) C. Towards integration in the nervous system (4 lectures, Flanagin, Glasauer, MacNeilage, Sirota) D. Engineering for Neuroscience and Neuroprothetics (3-4 lectures, Glasauer, Kleinsteuber, Seeber, Sirota) Students take part in the lecture and additionally learn the course content during self study with the materials provided by the lecturers (Handouts, further reading advice). The lecture will be presented by several experts in their respective fields. Students will receive an overview of the various aspects pertaining to computational neuroscience, beginning with the neurobiological foundation and the mathematical tools and extending to applied fields such as auditory prostheses and clinical examinations. In the written examination, an overview of the various aspects of computational neuroscience will be tested. Knowledge-based learning outcomes from the lecture as well as the understanding and ability to solve (practical) problems will be assessed in a 60 min written examination with questions set and corrected by the respective lecturers. Basic knowledge of biology and mathematics recommended. This interdisciplinary lecture series taught by neurosience experts from TUM and LMU provides an introduction to computational neuroscience. After taking part in this course students are familiar with basic neuroanatomy and the neural processes in different sensory system (visual, auditory, vestibular). Students will learn the fundamental methods for modelling neural behaviour on the cell and the systemic level and how data to fit those models can be obtained from experiments. Additionally, students will learn how such models can be used for engineering neural systems.

Glasauer, Stefan , Prof. Dr. LMU München SoSe 2015 Dr. rer. nat. Flanagin Virginia.