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cs.LG2025
An energy-efficient spiking neural network with continuous learning for self-adaptive brain-machine interface
Zhou Biyan, Arindam Basu
The number of simultaneously recorded neurons follows an exponentially increasing trend in implantable brain-machine interfaces (iBMIs). Integrating the neural decoder in the impla…
eess.SP2025
Event-based Neural Spike Detection Using Spiking Neural Networks for Neuromorphic iBMI Systems
Chanwook Hwang, Biyan Zhou, Ye Ke +3
Implantable brain-machine interfaces (iBMIs) are evolving to record from thousands of neurons wirelessly but face challenges in data bandwidth, power consumption, and implant size.…
cs.LG2025
Architectural Exploration of Hybrid Neural Decoders for Neuromorphic Implantable BMI
Vivek Mohan, Biyan Zhou, Zhou Wang +3
This work presents an efficient decoding pipeline for neuromorphic implantable brain-machine interfaces (Neu-iBMI), leveraging sparse neural event data from an event-based neural s…