In this section
@article{Zhang:2023:10.1101/2023.01.10.523472,
author = {Zhang, Z and Constandinou, TG},
doi = {10.1101/2023.01.10.523472},
title = {Firing-rate-modulated spike detection and neural decoding co-design},
url = {http://dx.doi.org/10.1101/2023.01.10.523472},
year = {2023}
}
TY - JOUR
AB - <jats:title>Abstract</jats:title> <jats:sec> <jats:title>Objective</jats:title> <jats:p>Translational efforts on spike-signal-based implantable brain-machine interfaces (BMIs) are increasingly aiming to minimise bandwidth while maintaining decoding performance. Developing these BMIs requires advances in neuroscience and electronic technology, as well as using low-complexity spike detection algorithms and high-performance machine learning models. While some state-of-the-art BMI systems jointly design spike detection algorithms and machine learning models, it remains unclear how the detection performance affects decoding.</jats:p> </jats:sec> <jats:sec> <jats:title>Approach</jats:title> <jats:p>We propose the co-design of the neural decoder with an ultra-low complexity spike detection algorithm. The detection algorithm is designed to attain a target firing rate, which the decoder uses to modulate the input features preserving statistical invariance.</jats:p> </jats:sec> <jats:sec> <jats:title>Main results</jats:title> <jats:p>We demonstrate a multiplication-free fixed-point spike detection algorithm with nearly perfect detection accuracy and the lowest complexity among studies we have seen. By co-designing the system to incorporate statistically invariant features, we observe significantly improved long-term stability, with decoding accuracy degrading by less than 10% after 80 days of operation. Our analysis also reveals a nonlinear relationship between spike detection and decoding performance. Increasing the detection sensitivity improves decoding accuracy and long-term stability, which means the activity of more neurons is beneficial despite the detection of more noise. Reducing the spi
AU - Zhang,Z
AU - Constandinou,TG
DO - 10.1101/2023.01.10.523472
PY - 2023///
TI - Firing-rate-modulated spike detection and neural decoding co-design
UR - http://dx.doi.org/10.1101/2023.01.10.523472
UR - https://doi.org/10.1101/2023.01.10.523472
ER -