Hybrid design principles and time constants in the construction of Brain-based robotics: A real-time simulator of oscillatory neural networks interacting with the real environment via robotic devices

Abstract

One of most important concepts in robotics and artificial intelligence is the embodied approach, focusing on the importance of having a body that functionally connects to the external world. This setup suggests that the intelligence develops through sensorimotor skills and through situations that would actually be confronted in the environment. We support this concept and propose to further extend it to embodiment in the time domain. Nervous systems have variable processing times. The different time courses proceed in the nervous system in parallel, and individual circuits independently and cooperatively work under the constraints of temporal properties. We here propose an experimental platform of oscillatory neural networks having real-time communication with the environment through the robot's body. The synchronization mechanism of oscillations in neural activities have the advantage of synthetic controls known in motor coordination, but we extend this to circuits for cognitive functions like episodic memory formation and decision making of the robotic behavior by using the theta phase coding mechanism. A slow oscillation, like the theta rhythm, enables behavioral temporal sequences to be compressed in sequential firings during each oscillation cycle, and this helps to represent cognitive information in episodes composed of past-present-future structures. The temporal structure is crucial for recognition of the current context and adaptability in dynamic environments, and it smoothly controls sensorimotor local circuits with faster time scales. This work represents a tiny step towards constructing the brain by focusing on the temporal structure, yet this approach may elucidate the new nature of the brain-based intelligence. © 2009 Springer Berlin Heidelberg.