{"title":"A modeling study of spinal motoneuron recruitment regulated by ionic channels during fictive locomotion.","authors":"Qiang Zhang, Yue Dai","doi":"10.1007/s10827-020-00763-4","DOIUrl":null,"url":null,"abstract":"<p><p>During fictive locomotion cat lumbar motoneurons exhibit changes in membrane proprieties including a decrease in voltage threshold (V<sub>th</sub>), afterhyperpolarization (AHP) and input resistance (R<sub>in</sub>) and an increase in non-linear membrane property. The impact of these changes on the motoneuron recruitment remains unknown. Using modeling approach we investigated the channel mechanism regulating the motoneuron recruitment. Three types of motoneuron pools including slow (S), fatigue-resistant (FR) and fast-fatigable (FF) motoneurons were constructed based on the membrane proprieties of cat lumbar motoneurons. The transient sodium (NaT), persistent sodium (NaP), delayed-rectifier potassium [K(DR)], Ca<sup>2+</sup>-dependent K<sup>+</sup> [K(AHP)] and L-type calcium (Ca<sub>L</sub>) channels were included in the models. Simulation results showed that (1) Strengthening synaptic inputs increased the number of recruitments in all three types of motoneurons following the size principle. (2) Increasing NaT or NaP or decreasing K(DR) or K(AHP) lowered rheobase of spike generation thus increased recruitment of motoneuron pools. (3) Decreasing R<sub>in</sub> reduced recruitment in all three types of motoneurons. (4) The FF-type motoneuron pool, followed by FR- and S-type, were the most sensitive to increase of synaptic inputs, reduction of R<sub>in</sub>, upregulation of NaT and NaP, and downregulation of K(DR) and K(AHP). (5) Increasing Ca<sub>L</sub> enhanced overall discharge rate of motoneuron pools with little effect on the recruitment. Simulation results suggested that modulation of ionic channels altered the output of motoneuron pools with either modulating the number of recruited motoneurons or regulating the overall discharge rate of motoneuron pools. Multiple channels contributed to the recruitment of motoneurons with interaction of excitatory and inhibitory synaptic inputs during walking.</p>","PeriodicalId":54857,"journal":{"name":"Journal of Computational Neuroscience","volume":"48 4","pages":"409-428"},"PeriodicalIF":1.5000,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s10827-020-00763-4","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s10827-020-00763-4","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2020/9/8 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 4
Abstract
During fictive locomotion cat lumbar motoneurons exhibit changes in membrane proprieties including a decrease in voltage threshold (Vth), afterhyperpolarization (AHP) and input resistance (Rin) and an increase in non-linear membrane property. The impact of these changes on the motoneuron recruitment remains unknown. Using modeling approach we investigated the channel mechanism regulating the motoneuron recruitment. Three types of motoneuron pools including slow (S), fatigue-resistant (FR) and fast-fatigable (FF) motoneurons were constructed based on the membrane proprieties of cat lumbar motoneurons. The transient sodium (NaT), persistent sodium (NaP), delayed-rectifier potassium [K(DR)], Ca2+-dependent K+ [K(AHP)] and L-type calcium (CaL) channels were included in the models. Simulation results showed that (1) Strengthening synaptic inputs increased the number of recruitments in all three types of motoneurons following the size principle. (2) Increasing NaT or NaP or decreasing K(DR) or K(AHP) lowered rheobase of spike generation thus increased recruitment of motoneuron pools. (3) Decreasing Rin reduced recruitment in all three types of motoneurons. (4) The FF-type motoneuron pool, followed by FR- and S-type, were the most sensitive to increase of synaptic inputs, reduction of Rin, upregulation of NaT and NaP, and downregulation of K(DR) and K(AHP). (5) Increasing CaL enhanced overall discharge rate of motoneuron pools with little effect on the recruitment. Simulation results suggested that modulation of ionic channels altered the output of motoneuron pools with either modulating the number of recruited motoneurons or regulating the overall discharge rate of motoneuron pools. Multiple channels contributed to the recruitment of motoneurons with interaction of excitatory and inhibitory synaptic inputs during walking.
期刊介绍:
The Journal of Computational Neuroscience provides a forum for papers that fit the interface between computational and experimental work in the neurosciences. The Journal of Computational Neuroscience publishes full length original papers, rapid communications and review articles describing theoretical and experimental work relevant to computations in the brain and nervous system. Papers that combine theoretical and experimental work are especially encouraged. Primarily theoretical papers should deal with issues of obvious relevance to biological nervous systems. Experimental papers should have implications for the computational function of the nervous system, and may report results using any of a variety of approaches including anatomy, electrophysiology, biophysics, imaging, and molecular biology. Papers investigating the physiological mechanisms underlying pathologies of the nervous system, or papers that report novel technologies of interest to researchers in computational neuroscience, including advances in neural data analysis methods yielding insights into the function of the nervous system, are also welcomed (in this case, methodological papers should include an application of the new method, exemplifying the insights that it yields).It is anticipated that all levels of analysis from cognitive to cellular will be represented in the Journal of Computational Neuroscience.