I-Spin live: An open-source software based on blind-source separation for decoding the activity of spinal alpha motor neurons in real-time

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 discharge 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 spinal motor neurons using a blind-source separation approach for multichannel EMG signal processing. Separation vectors (motor unit filters) are identified for each motor unit from a baseline contraction and then re-applied in real-time during test contractions. In this way, the discharge activity of multiple motor units can be provided as visual feedback in real-time. 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 tested the software on data collected using either grids of surface electrodes 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 interface 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. ### Competing Interest Statement DF is inventor of a patent (Neural Interface. UK Patent application no. GB1813762.0. August 23, 2018) and of a patent application (Neural interface. UK Patent application no. GB2014671.8. September 17, 2020), which are partly related to the methods and applications of this work. All other authors have no financial or other relationships that might lead to a conflict of interest.