A 5.7μW/channel folded-current-mirror-based reconfigurable multimodal neural recording IC with improved hardware availability

Abstract

This paper presents a multimodal neural recording system incorporating reconfigurable neural recording front-ends to improve hardware availability. The proposed neural recording front-end utilizing the reconfigurable signal conveyor based on the folded-current-mirror structure is configured to process either voltage or current input signal, depending on the targeted experiment scenario, given experiment setup, and varying status of the recording environment. Thus, out of the total number of recording channels, how many channels are used for voltage and current recording can be set as desired, which maximizes the flexibility of the experiment and the usefulness of the recording system. The implemented system is successfully applied to the in vivo recording experiment conducted in the hippocampus area of a mouse brain. The neural recording front-end achieves input-referred noise performances of 2.4 μVrms and 5.19 pArms in the voltage and current recording modes, respectively. The power consumed by each recording channel is 5.718 μW, and only 54 nW is used to operate the reconfigurable signal conveyor.