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Updated: Jul 27, 2026

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
Published on: March 2, 2015
A Scalable, Programmable Neural Stimulator for Enhancing Generalizability in Neural Interface Applications
Meng Yin1,2, Xiao Wang1,2, Liuxindai Zhang1,2
1State Key Laboratory of Digital Medical Engineering, School of Biomedical Engineering, Hainan University, Haikou 570228, China.
Abstract:
Each application of neurostimulators requires unique stimulation parameter specifications to achieve effective stimulation. Balancing the current magnitude with stimulation resolution, waveform, size, and channel count is challenging, leading to a loss of generalizability across broad neural interfaces. To address this, this paper proposes a highly scalable, programmable neurostimulator with a System-on-Chip (SOC) capable of 32 channels of independent stimulation. The compliance voltage reaches up to ±22.5 V. A pair of 8-bit current-mode DACs support independent waveforms for source and sink operations and feature a user-selectable dual range for low-current intraparenchymal microstimulation with a resolution of 4.31 μA/bit, as well as high current stimulation for spinal cord and DBS applications with a resolution of 48.00 μA/bit, achieving a wide stimulation range of 12.24 mA while maintaining high-resolution biological stimulation. A dedicated communication protocol enables full programmable control of stimulation waveforms, effectively improving the range of stimulation parameters. In vivo electrophysiological experiments successfully validate the functionality of the proposed stimulator. This flexible stimulator architecture aims to enhance its generality across a wide range of neural interfaces and will provide more diverse and refined stimulation strategies.
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