The DOI matches its Crossref record.
Relationship of firing intervals of human motor units to the trajectory of post‐spike after‐hyperpolarization and synaptic noise.
Open accessAbstract
1. Interspike interval distributions from human motor units of a variety of muscles were analysed to assess the role of synaptic noise in excitation. The time course of the underlying post‐spike after‐hyperpolarization (AHP) was deduced by applying a specially developed transform to the interval data. Different firing rates were studied both by varying the firing voluntarily, and by selecting subpopulations of spikes for a given firing rate from long recordings with slight variations in frequency. 2. At low firing rates the interval histograms had an exponential tail. Thus at long intervals, the motoneurone was randomly excited by noise and its post‐spike AHP was complete. This contrasts with the firing produced by intracellular current injection in the cat, when the membrane potential increases linearly until threshold is reached. The interval histogram was therefore analysed with the aid of a model of synaptic excitation to deduce the mean ‘trajectory’ of membrane voltage in the last part of the interspike interval. 3. The computer model, described in the Appendix, was used to determine the effect of the mean level of membrane potential on the probability of a spike being excited, per unit time, during an on‐going interspike interval. All variables were treated as voltages, with synaptic noise simulated by time‐smoothed Gaussian noise. This enabled an interval distribution to be transformed into a segment of the underlying trajectory of the membrane potential; the potential was expressed in terms of the noise amplitude and the spike threshold. 4. At low firing rates, the equilibrium value of the membrane voltage trajectory lay well below threshold; the deviation typically corresponded to the standard deviation of the noise or more. The noise standard deviation was estimated to be about 2 mV. 5. With increasing mean firing rate, the near‐threshold portion of the trajectory obtainable from the histogram occurred earlier, was steeper and rose to a higher level. Trajectories for different firing rates fell on the same curve after shifting them vertically by varying amounts. The curve was taken to represent the AHP of the motoneurone and was closely exponential. The shift of the trajectory gave its mean synaptic drive. The duration of the AHP varied between units and was longer than average for units from soleus muscle. 6. Further modelling showed that summation of noise with the AHP can explain the well‐known changes in discharge variability that occur as firing rate increases. 7. It is concluded that synaptic noise plays a major role in the excitation of tonically firing human motoneurones and that the noiseless motoneurone with a linear trajectory provides an inadequate model for the conscious human. This is of interest in relation to various standard measures of human motor unit activity such as short‐term synchronization.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Signal-dependent noise determines motor planning
Harris, C. M., & Wolpert, D. M. (1998) · Nature · doi:10.1038/29528 · Cited by 2,498
Heckman, C. J., & Enoka, R. M. (2012) · Comprehensive Physiology · doi:10.1002/cphy.c100087 · Cited by 414
Probabilistic models in human sensorimotor control
Wolpert, D. M. (2007) · Human Movement Science · doi:10.1016/j.humov.2007.05.005 · Cited by 212
Christie, A., & Kamen, G. (2010) · Muscle & Nerve · doi:10.1002/mus.21539 · Cited by 123
Gallego, J. A., Dideriksen, J. L., Holobar, A., Ibanez, J., Glaser, V., Romero, J. P., Benito-Leon, J., Pons, J. L., Rocon, E., & Farina, D. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.0106-15.2015 · Cited by 67
Metadata
- Authors
- Matthews, P. B.
- Venue
- The Journal of Physiology
- Publisher
- Wiley
- Published
- 1996-04-15
- Volume
- 492
- Issue
- 2
- Pages
- 597-628
- ISSN
- 0022-3751 (ISSN-L)
- 1469-7793
- OpenAlex
- W2145460573
- Cited by
- 325
- References
- 0
- FWCI
- 8.12
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Relationship of firing intervals of human motor units to the trajectory of post‐spike after‐hyperpolarization and synaptic noise. https://app.cochat.ai/papers/10.1113/jphysiol.1996.sp021332
- The paper
- Matthews, P. B. (1996). Relationship of firing intervals of human motor units to the trajectory of post‐spike after‐hyperpolarization and synaptic noise. The Journal of Physiology. https://doi.org/10.1113/jphysiol.1996.sp021332
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.