Biophysical model of muscle spindle encoding

Stephen Nicholas Housley* (Corresponding Author), Randall K Powers, Paul J Nardelli, Sebinne Lee, Kyle Blum, Guy Bewick, Robert William Banks, Timothy Cope

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
7 Downloads (Pure)


New Findings
What is the central question of the study?

How does the neuronal architecture and asymmetric distribution of voltage-gated channels influence mechanosensory encoding by muscle spindle afferents?

What is the main finding and its importance?

The results predict that neuronal architecture and the distribution and ratios of voltage-gated ion channels are a complementary and, in some instances, orthogonal means to regulate Ia encoding. The importance of these findings highlights the integral role of peripheral neuronal structure and ion channel expression in mechanosensory signalling. Generally, our computational approach offers an integrative means to generate testable hypotheses and prioritize targets for future mechanistic studies.

Muscle spindles encode mechanosensory information by mechanisms that remain only partially understood. Their complexity is expressed in mounting evidence of various molecular mechanisms that play essential roles in muscle mechanics, mechanotransduction and intrinsic modulation of muscle spindle firing behaviour. Biophysical modelling provides a tractable approach to achieve more comprehensive mechanistic understanding of such complex systems that would be difficult/impossible by more traditional, reductionist means. Our objective here was to construct the first integrative biophysical model of muscle spindle firing. We leveraged current knowledge of muscle spindle neuroanatomy and in vivo electrophysiology to develop and validate a biophysical model that reproduces key in vivo muscle spindle encoding characteristics. Crucially, to our knowledge, this is the first computational model of mammalian muscle spindle that integrates the asymmetric distribution of known voltage-gated ion channels (VGCs) with neuronal architecture to generate realistic firing profiles, both of which seem likely to be of great biophysical importance. Results predict that particular features of neuronal architecture regulate specific characteristics of Ia encoding. Computational simulations also predict that the asymmetric distribution and ratios of VGCs is a complementary and, in some instances, orthogonal means to regulate Ia encoding. These results generate testable hypotheses and highlight the integral role of peripheral neuronal structure and ion channel composition and distribution in somatosensory signalling.
Original languageEnglish
Pages (from-to)55-65
Number of pages11
JournalExperimental Physiology
Issue number1
Early online date26 Mar 2023
Publication statusPublished - 1 Jan 2024
Event Mechanotransduction, Muscle Spindles and Proprioception - Ludwig Maximilian University, Munich, Germany
Duration: 25 Jul 202228 Jul 2022

Bibliographical note

Research Funding
National Center for Medical Rehabilitation Research (NCMRR). Grant Number: R01HD090642
National Cancer Institute (NCI). Grant Number: R01CA221363
Northside Hospital Foundation, Inc.


  • biophysical modelling
  • muscle spindle firing
  • sensory encoding
  • voltage-gated ion channels


Dive into the research topics of 'Biophysical model of muscle spindle encoding'. Together they form a unique fingerprint.

Cite this