Journal of Computational Neuroscience

, Volume 31, Issue 3, pp 625–645 | Cite as

Motoneuron model of self-sustained firing after spinal cord injury



Under many conditions spinal motoneurons produce plateau potentials, resulting in self-sustained firing and providing a mechanism for translating short-lasting synaptic inputs into long-lasting motor output. During the acute-stage of spinal cord injury (SCI), the endogenous ability to generate plateaus is lost; however, during the chronic-stage of SCI, plateau potentials reappear with prolonged self-sustained firing that has been implicated in the development of spasticity. In this work, we extend previous modeling studies to systematically investigate the mechanisms underlying the generation of plateau potentials in motoneurons, including the influences of specific ionic currents, the morphological characteristics of the soma and dendrite, and the interactions between persistent inward currents and synaptic input. In particular, the goal of these computational studies is to explore the possible interactions between morphological and electrophysiological changes that occur after incomplete SCI. Model results predict that some of the morphological changes generally associated with the chronic-stage for some types of spinal cord injuries can cause a decrease in self-sustained firing. This and other computational results presented here suggest that the observed increases in self-sustained firing following some types of SCI may occur mainly due to changes in membrane conductances and changes in synaptic activity, particularly changes in the strength and timing of inhibition.


Motoneuron model Self-sustained firing Persistent inward current Spinal cord injury model 


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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.School of Mathematical and Statistical Sciences, Center for Adaptive Neural SystemsArizona State UniversityTempeUSA
  2. 2.School of Life Sciences, Center for Adaptive Neural SystemsArizona State UniversityTempeUSA
  3. 3.School of Biological and Health Systems Engineering, Center for Adaptive Neural SystemsArizona State UniversityTempeUSA

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