Probabilistic Models of Natural Stimuli and Neural Populations
| Abstract |
Both natural stimuli and neural recordings can exhibit complex statistical structure. Therefore, flexible
statistical models are needed for capturing this complexity in a quantitative manner. In particular, probabilistic methods provide a principled framework
for comparing and evaluating different models. In the morning session of the
tutorial, we will discuss model classes for describing the statistical structure
of natural images and their relevance for sensory coding. The afternoon session
will consist of a self-contained introduction to probabilistic models of spiking neurons.
Our focus will be on the generalized linear model framework and related model classes. In each session we will aim to point out relationships and commonalities between
different approaches.
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