Estimation of contractile parameters of successive twitches in unfused tetanic contractions of single motor units – A proof-of-concept study using ultrafast ultrasound imaging in vivo

Rohlén, Robin; Raikova, Rositsa; Stålberg, Erik; Grönlund, Christer

doi:10.1016/j.jelekin.2022.102705

Cited by 11 publications

(13 citation statements)

References 57 publications

(86 reference statements)

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“…2 A) that were randomly sampled to generate varying twitch-shapes (Fig. 2 B) suitable for low-threshold MUs at low force levels [ 13 ] (see Additional file 1 : Table S1). The spike times were simulated using a Gaussian renewal process such that , where and is the mean ISI and coefficient of variation [ 18 ] (Fig.…”

Section: Methodsmentioning

confidence: 99%

“…2A) that were randomly sampled (1) to generate varying twitch-shapes (Fig. 2B) suitable for low-threshold MUs at low force levels [13] (see Additional file 1: Table S1). The n spike times � = (� 1 , � 2 , .…”

Section: Simulation Parametersmentioning

confidence: 99%

“…The estimation of spikes partly explains the current pipeline’s limited identification rate of active MUs from each estimated unfused tetanic signal that often is noisy [ 6 , 13 ]. Since HWM is based on large gradients, the noise in the unfused tetanic signals may induce false positives.…”

Section: Introductionmentioning

confidence: 99%

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

2023

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Background Individual 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. Results This 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%). Conclusions This 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.

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Section: Methodsmentioning

confidence: 99%

Section: Simulation Parametersmentioning

confidence: 99%

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

2023

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“…2A) that were randomly sampled to generate varying twitch-shapes (Fig. 2B) suitable for low threshold MUs at low force levels 18 (see Table S1, Supplementary Material). The n spike times Δ = (Δ 1 , Δ 2 , …, Δ n ) were simulated using a Gaussian renewal process such that Δ i +1 − Δ i ~ N ( μ ISI , CV), where μ ISI and is the mean ISI and coefficient of variation 19 (Fig.…”

Section: Methodsmentioning

confidence: 99%

“…2A) that were randomly sampled to generate varying twitch-shapes (Fig. 2B) suitable for low threshold MUs at low force levels 18 (see Table S1, Supplementary Material). The 𝑛 spike times ∆ = (∆ $ , ∆ & , … , ∆ " ) were simulated using a…”

Section: Simulation Parametersmentioning

confidence: 99%

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

Rohlén

Lundsberg

Antfolk

2022

Preprint

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The central nervous system initiates voluntary force production by providing excitatory inputs to spinal motor neurons, each connected to a set of muscle fibres to form a motor unit. Motor units have been imaged and analysed using ultrafast ultrasound based on the separation of ultrasound images. Although this method has great potential to identify regions and trains of motor unit twitches (unfused tetanus) evoked by the spike trains, it currently has a limited motor unit identification rate. One potential explanation is that the current method neglects the temporal information in the separation process of ultrasound images, and including it could lead to significant improvement. Here, we take the first step by asking if it is possible to estimate the spike train of an unfused tetanic signal from simulated and experimental signals using convolutive blind source separation. This finding will provide a direction for ultrasound-based method improvement. In this study, we found that the estimated spike trains highly agreed with the simulated and reference spike trains. This result implies that the convolutive blind source separation of an unfused tetanic signal can be used to estimate its spike train. Although extending this approach to ultrasound images is promising, the translation remains to be investigated in future studies where spatial information is inevitable as a discriminating factor between different motor units.

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Skeletal muscle models composed of motor units: A review

Raikova¹,

Krutki²,

Celichowski³

2023

Journal of Electromyography and Kinesiology

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Estimation of contractile parameters of successive twitches in unfused tetanic contractions of single motor units – A proof-of-concept study using ultrafast ultrasound imaging in vivo

Cited by 11 publications

References 57 publications

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

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

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

Skeletal muscle models composed of motor units: A review

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