Estimating the time course of population excitatory postsynaptic potentials in motoneurons of spastic stroke survivors

Xiaogang Hu, Nina L. Suresh, William Z. Rymer

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8 Scopus citations

Abstract

Hyperexcitable motoneurons are likely to contribute to muscle hypertonia after a stroke injury; however, the origins of this hyperexcitability are not clear. One possibility is that the effective duration of the Ia excitatory postsynaptic potential (EPSP) is prolonged, increasing the potential for temporal summation of EPSPs, making action potential initiation easier. Accordingly, the purpose of this study was to quantify the time course of EPSPs in motoneurons of stroke survivors. The experimental protocol, which was based on parameters derived from simulation, involved sequential subthreshold electrical stimuli delivered to the median nerve of hemispheric stroke survivors. The resulting H-reflex responses were recorded in the flexor carpi radialis muscle. H-reflex response probability was then used to quantify the time course of the underlying EPSPs in the motoneuron pool. A population EPSP was estimated based on the probability of evoking an H reflex from the second electrical stimulus in the absence of a reflex response to the first stimulus. The accuracy of this time-course estimate was quantified using a computer simulation that explored a range of feasible EPSP parameters. Our experimental results showed that in all five hemispheric stroke survivors the rate of decay of the population EPSP was consistently slower in spastic compared with the contralateral motoneuron pools. We propose that one potential mechanism for hyperexcitability of motoneurons in spastic stroke survivors may be linked to this prolongation of the Ia EPSP time course. Our subthreshold double-stimulation approach also provides a noninvasive tool for quantifying the time course of EPSPs in both healthy and pathological conditions.

Original languageEnglish (US)
Pages (from-to)1952-1957
Number of pages6
JournalJournal of neurophysiology
Volume113
Issue number6
DOIs
StatePublished - Mar 15 2015

All Science Journal Classification (ASJC) codes

  • General Neuroscience
  • Physiology

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