Learning proprioceptive and motor features

Learning features from sensory and motor information is an important step towards the autonomous acquisition of internal models in cognitive robotics. Here we study a neural model of orientation selective cells in the primary visual cortex, and ask whether it can also function as a feature detector for other somatosensory modalities. We apply this model to proprioceptive and motor information generated by a simulated walking robot and examine the resulting features.