Robotic Interval Timing based on Active Oscillations

Interval timing is crucially involved in many of the daily activities of humans and animals. However, the cognitive mechanisms enabling the encoding and processing of time in the brain remain largely unknown. In the present work, we follow a self- organized modeling approach to study unconventional representations of time in neural network based cognitive system. A particularly interesting feature of our study regards the implementation of a single computational model to accomplish two different robotic behavioral tasks, which assume diverse manipulation of time intervals. The examination of the implemented cognitive system revealed that it is possible to integrate the two main theoretical models of time representation existing today - the dedicated and intrinsic representations - into a new theory that effectively combines their key characteristics.