ArticleeLife2024
I-Spin live, an open-source software based on blind-source separation for real-time decoding of motor unit activity in humans.
Article in eLife, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Spiking neural network decoders of finger forces from high-density intramuscular microelectrode arrays.Nature communications · 2026Article
- Structured modulations in high-density EMG patterns from a single muscle enable simultaneous control of natural and extra degrees of freedom.Journal of neuroengineering and rehabilitation · 2026Article
- Non-homogeneous distribution of inhibitory inputs among motor units in response to nociceptive stimulation at moderate contraction intensity.The Journal of physiology · 2025Article
- Flexible control of motor units: is the multidimensionality of motor unit manifolds a sufficient condition?The Journal of physiology · 2025Article
- The Volitional Control of Individual Motor Units Is Constrained within Low-Dimensional Neural Manifolds by Common Inputs.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- Motoneuron-driven computational muscle modelling with motor unit resolution and subject-specific musculoskeletal anatomy.PLoS computational biology · 2023Article
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Authors and funding
7 authors.
Funding
Abstract
Decoding the activity of individual neural cells during natural behaviours allows neuroscientists to study how the nervous system generates and controls movements. Contrary to other neural cells, the activity of spinal motor neurons can be determined non-invasively (or minimally invasively) from the decomposition of electromyographic (EMG) signals into motor unit firing activities. For some interfacing and neuro-feedback investigations, EMG decomposition needs to be performed in real time. Here, we introduce an open-source software that performs real-time decoding of motor neurons using a blind-source separation approach for multichannel EMG signal processing. Separation vectors (motor unit filters) are optimised for each motor unit from baseline contractions and then re-applied in real time during test contractions. In this way, the firing activity of multiple motor neurons can be provided through different forms of visual feedback. We provide a complete framework with guidelines and examples of recordings to guide researchers who aim to study movement control at the motor neuron level. We first validated the software with synthetic EMG signals generated during a range of isometric contraction patterns. We then tested the software on data collected using either surface or intramuscular electrode arrays from five lower limb muscles (gastrocnemius lateralis and medialis, vastus lateralis and medialis, and tibialis anterior). We assessed how the muscle or variation of contraction intensity between the baseline contraction and the test contraction impacted the accuracy of the real-time decomposition. This open-source software provides a set of tools for neuroscientists to design experimental paradigms where participants can receive real-time feedback on the output of the spinal cord circuits.
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