Contribution of Intrinsic Properties and Synaptic Inputs to Motoneuron Discharge Patterns: A Simulation Study
Document Type
Article
Publication Date
2-2012
Abstract
Motoneuron discharge patterns reflect the interaction of synaptic inputs with intrinsic conductances. Recent work has focused on the contribution of conductances mediating persistent inward currents (PICs), which amplify and prolong the effects of synaptic inputs on motoneuron discharge. Certain features of human motor unit discharge are thought to reflect a relatively stereotyped activation of PICs by excitatory synaptic inputs; these features include rate saturation and de-recruitment at a lower level of net excitation than that required for recruitment. However, PIC activation is also influenced by the pattern and spatial distribution of inhibitory inputs that are activated concurrently with excitatory inputs. To estimate the potential contributions of PIC activation and synaptic input patterns to motor unit discharge patterns, we examined the responses of a set of cable motoneuron models to different patterns of excitatory and inhibitory inputs. The models were first tuned to approximate the current- and voltage-clamp responses of low- and medium-threshold spinal motoneurons studied in decerebrate cats and then driven with different patterns of excitatory and inhibitory inputs. The responses of the models to excitatory inputs reproduced a number of features of human motor unit discharge. However, the pattern of rate modulation was strongly influenced by the temporal and spatial pattern of concurrent inhibitory inputs. Thus, even though PIC activation is likely to exert a strong influence on firing rate modulation, PIC activation in combination with different patterns of excitatory and inhibitory synaptic inputs can produce a wide variety of motor unit discharge patterns.
Repository Citation
Powers, R. K.,
Elbasiouny, S. M.,
Rymer, W. Z.,
& Heckman, C. J.
(2012). Contribution of Intrinsic Properties and Synaptic Inputs to Motoneuron Discharge Patterns: A Simulation Study. Journal of Neurophysiology, 107 (3), 808-823.
https://corescholar.libraries.wright.edu/ncbp/66
DOI
10.1152/jn.00510.2011