ArticleeLife2022
Mathematical relationships between spinal motoneuron properties.
Article in eLife, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 0 citations in OpenAlex.
- Probabilistic inference of homonymous and heteronymous recurrent inhibition in human muscles from large-scale motor neuron recordings.Science advances · 2026Article
- Adaptation of motor unit synergies in the synergetic ankle plantarflexors in ambulatory persons with incomplete spinal cord injury.Journal of neuroengineering and rehabilitation · 2026Article
- Biologically-constrained spiking neural network for neuromodulation in locomotor recovery after spinal cord injury.PLoS computational biology · 2026Article
- In vivo estimation of motor unit intrinsic properties in individuals with spinal cord injury.Journal of neuroengineering and rehabilitation · 2025Article
- 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
- Article
- NeuroMotion: Open-source platform with neuromechanical and deep network modules to generate surface EMG signals during voluntary movement.PLoS computational biology · 2024Article
- Motoneuron-driven computational muscle modelling with motor unit resolution and subject-specific musculoskeletal anatomy.PLoS computational biology · 2023Article
- Article
- Common synaptic input, synergies and size principle: Control of spinal motor neurons for movement generation.The Journal of physiology · 2023Review
- Estimation of the firing behaviour of a complete motoneuron pool by combining electromyography signal decomposition and realistic motoneuron modelling.PLoS computational biology · 2022Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Our understanding of the behaviour of spinal alpha-motoneurons (MNs) in mammals partly relies on our knowledge of the relationships between MN membrane properties, such as MN size, resistance, rheobase, capacitance, time constant, axonal conduction velocity, and afterhyperpolarization duration. We reprocessed the data from 40 experimental studies in adult cat, rat, and mouse MN preparations to empirically derive a set of quantitative mathematical relationships between these MN electrophysiological and anatomical properties. This validated mathematical framework, which supports past findings that the MN membrane properties are all related to each other and clarifies the nature of their associations, is besides consistent with the Henneman's size principle and Rall's cable theory. The derived mathematical relationships provide a convenient tool for neuroscientists and experimenters to complete experimental datasets, explore the relationships between pairs of MN properties never concurrently observed in previous experiments, or investigate inter-mammalian-species variations in MN membrane properties. Using this mathematical framework, modellers can build profiles of inter-consistent MN-specific properties to scale pools of MN models, with consequences on the accuracy and the interpretability of the simulations.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.