Aspects of randomness in neural activity and information processing can be successfully analyzed in terms by stochastic models. This course gives an introduction to the models and measures of neural noise (or 'variability' as it is more often called) and should enable the student to follow the current literature on the subject on his/her own. To this end, some key concepts from nonlinear dynamics, stochastic processes, and information theory are outlined. Then a number of basic problems (see below) is addressed; here, the main emphasis is given to analytically tractable models, but simulation techniques are explained as well. As an outlook some more involved problems (ISI statistics under correlated ('colored') noise, with subthreshold oscillations, or with adaptation, stimulus-induced correlations) are sketched at the end of the course.
- Kursverantwortliche/r: Prof. Dr. Benjamin Lindner