Neuromodulation is the alternation of nerve activity through targeted delivery of a stimulus, such as electrical stimulation, to specific sites in the body. Deep brain stimulation (DBS) is a commonly-used neuromodulation treatment for neurological ailments when traditional methods, such as surgery, medication or psychotherapy, fail. DBS is performed by sending controlled electrical pulses into the brain to evoke the desired response. However, existing DBS systems can only administer open-loop stimulation over a limited number of channels. Future neuromodulation systems require a multi-channel closed-loop platform that can provide high spatial precision, and automatically adjust stimulation parameters based on feedback from recorded neural signals. This multi-channel, closed-loop system poses new challenges for brain-sensing circuit and system design. To enable closed-loop operation, the sensing circuit needs to work with concurrent stimulation. Therefore, it needs to provide a large input range to prevent saturation under stimulation artifacts. In addition, the sensing circuit should simultaneously meet device/patient safety constraints. Current state-of-the-art neural sensing circuits, however, do not meet these requirements.

This work presents an implantable VCO-based neural-sensing front-end design intended for multi-channel, closed-loop neuromodulation applications. Specifically, it converts the input voltage into the phase domain, and performs direct digitization without any voltage-domain amplification, thus preventing saturation. The phase-domain processing allows a large input range that can comprise both stimulation artifacts and the neural signals. Four techniques have been implemented to overcome design challenges: (1) in the high-pass filter, we utilize a multi-rate duty-cycled resistor as a reliable solution to attenuate electrode-offsets; (2) inside of the VCO, chopping is applied to lower circuit noise; (3) at the analog-digital interface, we employ a new glitch-free quantizer; and (4) after digitization, circuit linearity is restored through the digital non-linearity correction. With these techniques, the design achieves 10x linear range and 2-3 bit ENOB improvement over prior-art with comparable power and noise performance.

This work also presents a 32/64-channel sensing chip based on the proposed front-end design. The chip is assembled on a miniaturized PCB to achieve a fully integrated neuromodulation system. Sensing performance and function under concurrent stimulation have been verified in bench-top and in-vitro environments. This allows further development of a complete multi-channel closed-loop neuromodulation implant.