A 1,024-Channel, 64-Interconnect, Capacitive Neural Interface Using a Cross-Coupled Microelectrode Array and 2-Dimensional Code-Division Multiplexing

This paper presents a neural interface that senses the electrical double layer (EDL) capacitance as a function of the ion concentration produced by neurons firing action potentials (AP). Unlike conventional microelectrode arrays (MEAs) detecting voltage, capacitance sensing allows access to multiple recording sites with a single wire using code-division multiplexing (CDM), thereby significantly reducing the number of required interconnects. In this work, we implemented 32 drivers and 32 analog front-end circuits (AFEs) to realize 1,024 channel concurrent neural recordings while using a total of 64 interconnects and improving area efficiency for large-scale integration. This work achieves $9.7 \mu \mathrm{W}$ power/ch and 0.005mm
²
area/ch efficiency with the highest electrode density of 10,000mm
^-2
, and the fewest interconnects to the authors’ best knowledge.