MUniverse: A Simulation and Benchmarking Suite for Motor Unit Decomposition

Pranav Mamidanna, Thomas Klotz, Dimitrios Halatsis, Agnese Grison, Irene Mendez Guerra, Shihan Ma, Arnault H. Caillet, Simon Avrillon, Robin Rohlén, Dario Farina

Keywords: EMG decomposition, Neural signal processing, Blind source separation, Synthetic benchmark datasets

Abstract:

Neural source separation enables the extraction of individual spike trains from complex electrophysiological recordings. When applied to electromyographic (EMG) signals, it provides a unique window into the motor output of the nervous system by isolating the spiking activity of motor units (MUs). MU decomposition from EMG signals is currently the only scalable neural interfacing approach available in behaving humans and has become foundational in motor neuroscience and neuroprosthetics. However, unlike related domains such as spike sorting or electroencephalography (EEG) analysis, decomposition of EMG signals lacks open benchmarks that reflect the diversity of muscles, movement contexts, and noise sources encountered in practice.
To address this gap, we introduce MUniverse, a modular simulation and benchmarking suite for decomposing EMG signals into individual MU spiking activity. MUniverse provides: (1) a simulation stack with a user-friendly interface to a state-of-the-art EMG generator; (2) a curated library of datasets across synthetic, hybrid synthetic-real data with ground truth spikes, and experimental EMG; (3) a set of internal and external decomposition pipelines; and (4) a unified benchmark with well-defined tasks, standard evaluation metrics, and baseline results from established decomposition pipelines.
MUniverse is designed for extensibility, reproducibility, and community use, and all datasets are distributed with standardised metadata (Croissant, BIDS). By standardising evaluation and enabling dataset simulation at scale, MUniverse aims to catalyze progress on this long-standing neural signal processing problem.

Dataset URL: https://dataverse.harvard.edu/dataverse/muniverse-datasets

Code URL: https://github.com/dfarinagroup/muniverse

Primary Area: Data and Benchmarking scenarios in Neuroscience and cognitive science (e.g., neural coding, brain-computer interfaces)

Submission Number: 1735