Models of information theory describe the behavior and neural dynamics in intelligent agents. They have arisen through fruitful interactions between mathematical psychology, cognitive neuroscience and other fields. However, opportunities for such interactions seem to be few at the moment. This workshop aims to fill this gap by bringing together researchers with different backgrounds but a common goal: to understand information processing in the human and animal brain.

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The workshop will discuss information sampling, encoding and decoding during sensory processing, time perception and higher cognitive functions. It will review state of the art techniques based on deep neural networks, probabilistic inference and dynamical systems. It will also provide updates about recent results using these techniques to understand the biology and behavior of intelligent information processing.

The workshop will be of interest to members of the CNS community who are keen on model-driven explanations of sensory perception and higher cognition.