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

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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
Paper

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

2022
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Overview
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. Competing Interest Statement The authors have declared no competing interest.
Publisher
Cold Spring Harbor Laboratory Press,Cold Spring Harbor Laboratory