Long-term bidirectional neuron interfaces for robotic control, and in vitro learning studies

Abstract

There are two fundamentally different goals for neural interfacing. On the biology side, to interface living neurons to external electronics allows the observation and manipulation of neural circuits to elucidate their fundamental mechanisms. On the engineering side, neural interfaces in animals, people, or in cell culture have the potential to restore missing functionality, or someday, to enhance existing functionality. At the Laboratory for NeuroEngineering at Georgia Tech, we are developing new technologies to help make both goals attainable. We culture dissociated mammalian neurons on multielectrode arrays, and use them as the brain of a 'Hybrot', or hybrid neural-robotic system. Distributed neural activity patterns are used to control mobile robots. We have created the hardware and software necessary to feed the robots' sensory inputs back to the cultures in real time, as electrical stimuli. By embodying cultured networks, we study learning and memory at the cellular and network level, using 2-photon laser-scanning microscopy to image plasticity while it happens. We have observed a very rich dynamical landscape of activity patterns in networks of only a few thousand cells. We can alter this landscape via electrical stimuli, and use the hybrot system to study the emergent properties of networks in vitro.