The human sense of touch integrates feedback from a multitude of touch receptors, but
how this information is represented in the neural responses such that it can be extracted
quickly and reliably is still largely an open question. At the same time, dexterous
robots equipped with touch sensors are becoming more common, necessitating better
methods for representing sequentially updated information and new control strategies
that aid in extracting relevant features for object manipulation from the data. This
thesis uses information theoretic methods for two main aims: First, the neural code
for tactile processing in humans is analyzed with res...