Artifact-Free Neurostimulator with Arbitrary Waveform Generation for High-Channel, High-Density Bidirectional Neural Interfaces

Abstract

To achieve greater specificity in neurostimulation, bidirectional neural interfaces are required to verify the recorded neural response after stimulation. The specific neural interface targeted in this thesis is the epiretinal implant. Due to the heterogeneity of the retinal ganglion cells (RGCs), high-fidelity vision is only possible when all the types of RGCs near the neurostimulator are mapped. This necessitates the bidirectionality of the implant and poses significant difficulties, as large stimulation artifacts obscure the small neural response that needs to be recorded. Furthermore, in order to cover a large area of the retina, a channel count in the order of 10⁴ will be required. Scaling existing neurostimulators would lead to chips that are >30mm², which is too large.

The aim of this thesis is therefore to design a neurostimulator for the epiretinal implant that is capable of implementing artifact-reducing algorithms, and is smaller than the current state-of-the-art. The proposed system makes use of a mismatch-based digital-to-analog converter (DAC), and has been optimized for an output range of 0-6 μA at an effective resolution of 8-bits. Furthermore, in order to decrease the amount of stimulation units required, waveform interleaving has been proposed, where the anodic and cathodic stimulator are separated. A voltage compliance monitor is also designed to ensure proper stimulation output. The designed system has been fabricated and occupies 0.0003mm² for two channels. Scaling this directly to 10⁴ channels would result in an area of 1.645mm². This area can be reduced even further via electrode multiplexing, which the designed system readily allows for. An output availability (i.e. how many input codes are possible after calibrating) of 99.2% and 97.3% is reported for the anodic and cathodic stimulator at an 8-bit resolution over the full output range.