Multichannel electrophysiological sensors and stimulators—particularly those used to study the nervous system—are usually based on monolithic microelectrode arrays. However, the architecture of such arrays limits flexibility in electrode placement and scaling to a large number of nodes, especially across non-contiguous locations. Here we report wirelessly networked and powered electronic microchips that can autonomously perform neural sensing and electrical microstimulation. The microchips, which we term neurograins, have an ~1 GHz electromagnetic transcutaneous link to an external telecom hub, providing bidirectional communication and control at the individual device level. To illustrate the potential of the approach, we show that 48 neurograins can be individually addressed on a rat cortical surface and used for the acute recording of neural activity. Theoretical calculations and experimental measurements show that the link configuration could potentially be scaled to 770 neurograins using a customized time-division multiple access protocol.

ABSTRACTMultichannel electrophysiological sensors and stimulators, especially those used for studying the nervous system, are most commonly based on monolithic microelectrode arrays. Such architecture limits the spatial flexibility of individual electrode placement, posing constraints for scaling to a large number of nodes, particularly across non-contiguous locations. We describe the design and fabrication of sub-millimeter size electronic microchips (“Neurograins”) which autonomously perform neural sensing or electrical microstimulation, with emphasis on their wireless networking and powering. An ∼1 GHz electromagnetic transcutaneous link to an external telecom hub enables bidirectional communication and control at the individual neurograin level. The link operates on a customized time division multiple access (TDMA) protocol designed to scale up to 1000 neurograins. The system is demonstrated as a cortical implant in a small animal (rat) model with anatomical limitations restricting the implant to 48 neurograins. We suggest that the neurograin approach can be generalized to overcome many scalability issues for wireless sensors and actuators as implantable microsystems.