Estimating the neural spike train from an unfused tetanic signal of low-threshold motor units using convolutive blind source separation

BioMedical Engineering OnLine

Research

Christian Antfolk¹  Jonathan Lundsberg¹  Robin Rohlén² 

[1] Department of Biomedical Engineering, Lund University, 221 00, Lund, Sweden;Department of Biomedical Engineering, Lund University, 221 00, Lund, Sweden;Department of Radiation Sciences, Biomedical Engineering, Radiation Physics, Umeå University, Umeå, Sweden;

关键词: Convolutive blind source separation;    Spike train;    Unfused tetanus;    Twitch;    Motor unit;    Motoneuron;   

DOI  :  10.1186/s12938-023-01076-0

 received in 2022-10-24, accepted in 2023-01-30,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundIndividual motor units have been imaged using ultrafast ultrasound based on separating ultrasound images into motor unit twitches (unfused tetanus) evoked by the motoneuronal spike train. Currently, the spike train is estimated from the unfused tetanic signal using a Haar wavelet method (HWM). Although this ultrasound technique has great potential to provide comprehensive access to the neural drive to muscles for a large population of motor units simultaneously, the method has a limited identification rate of the active motor units. The estimation of spikes partly explains the limitation. Since the HWM may be sensitive to noise and unfused tetanic signals often are noisy, we must consider alternative methods with at least similar performance and robust against noise, among other factors.ResultsThis study aimed to estimate spike trains from simulated and experimental unfused tetani using a convolutive blind source separation (CBSS) algorithm and compare it against HWM. We evaluated the parameters of CBSS using simulations and compared the performance of CBSS against the HWM using simulated and experimental unfused tetanic signals from voluntary contractions of humans and evoked contraction of rats. We found that CBSS had a higher performance than HWM with respect to the simulated firings than HWM (97.5 ± 2.7 vs 96.9 ± 3.3, p < 0.001). In addition, we found that the estimated spike trains from CBSS and HWM highly agreed with the experimental spike trains (98.0% and 96.4%).ConclusionsThis result implies that CBSS can be used to estimate the spike train of an unfused tetanic signal and can be used directly within the current ultrasound-based motor unit identification pipeline. Extending this approach to decomposing ultrasound images into spike trains directly is promising. However, it remains to be investigated in future studies where spatial information is inevitable as a discriminating factor.

【 授权许可】

CC BY   
© The Author(s) 2023

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