Models of passive and active dendrite motoneuron pools and their differences in muscle force control

Abstract

Motoneuron (MN) dendrites may be changed from a passive to an active state by increasing the levels of spinal cord neuromodulators, which activate persistent inward currents (PICs). These exert a powerful influence on MN behavior and modify the motor control both in normal and pathological conditions. Motoneuronal PICs are believed to induce nonlinear phenomena such as the genesis of extra torque and torque hysteresis in response to percutaneous electrical stimulation or tendon vibration in humans. An existing large-scale neuromuscular simulator was expanded to include MN models that have a capability to change their dynamic behaviors depending on the neuromodulation level. The simulation results indicated that the variability (standard deviation) of a maintained force depended on the level of neuromodulatory activity. A force with lower variability was obtained when the motoneuronal network was under a strong influence of PICs, suggesting a functional role in postural and precision tasks. In an additional set of simulations when PICs were active in the dendrites of the MN models, the results successfully reproduced experimental results reported from humans. Extra torque was evoked by the self-sustained discharge of spinal MNs, whereas differences in recruitment and de-recruitment levels of the MNs were the main reason behind torque and electromyogram (EMG) hysteresis. Finally, simulations were also used to study the influence of inhibitory inputs on a MN pool that was under the effect of PICs. The results showed that inhibition was of great importance in the production of a phasic force, requiring a reduced co-contraction of agonist and antagonist muscles. These results show the richness of functionally relevant behaviors that can arise from a MN pool under the action of PICs.

Web-based neuromuscular simulator applied to the teaching of principles of neuroscience

“…A complete description of the mathematical models implemented in the simulator may be found elsewhere (Cisi and Kohn, 2008;Elias et al, 2012a). Briefly, the simulator provides a detailed modeling of four spinal motor nuclei that command leg muscles responsible for ankle extension (Soleus -SOL; Gastrocnemius Medialis -GM; Gastrocnemius Lateralis -GL) and ankle flexion (Tibialis Anterior -TA).…”

“…Recently, an L-type Ca ++ channel was added to the dendritic compartment to account for the persistent inward current (PIC), which is activated by the presence of neuromodulators (e.g., serotonin and norepinephrine) in the spinal cord (Elias and Kohn, 2013;Heckman et al, 2009). The level of neuromodulation can be adjusted to set the PIC magnitude during the simulation of different motor tasks (Elias and Kohn, 2013;Elias et al, 2012a). In addition, synaptically activated conductances (excitatory and inhibitory) are included in both somatic and dendritic compartments.…”

“…Due to its inherent power, the simulator could be used also in courses on Neural Engineering, Motor Control or Computational Neuroscience, as well as in research (Cisi and Kohn, 2008;Elias et al, 2012a). The instructor may use ReMoto in real time during classes to illustrate specific topics that are being taught (this has been done in previous years in the Principles of Neuroscience course mentioned before).…”

Modelo Computacional Do Sistema Neuromuscular

“…Especificamente, para o sistema neuromuscular humano, modelos matemáticos multiescala (que representam mecanismos operando em níveis celulares e/ou moleculares até elementos macroscópicos, como os processos de geração e controle da força muscular) têm possibilitado estudos sobre os comportamentos dinâmicos de redes de motoneurônios alfa (MNs) controlando a geração de força muscular [1][2][3][4][5]. Estes estudos fornecem subsídios conceituais para uma maior compreensão de aspectos neurofisiológicos do controle motor, como, por exemplo: i) os papéis do recrutamento e da modulação da frequência de disparos de potenciais de ação (PAs) na relação força-EMG [1]; ii) a atuação de vias de realimentação sensorial no controle da força muscular [2]; iii) o efeito de condições patológicas no controle reflexo da força [3]; e iv) o efeito de entradas neuromodulatórias na atividade de MNs individuais e na variabilidade da força muscular [4]. Além destas aplicações científicas importantes, modelos computacionais do sistema nervoso e muscular podem ser utilizados como ferramentas didáticas em cursos de Neurociências e Controle Motor [5].…”

“…O primeiro está associado, em algum grau, à plausibilidade biológica do modelo e à sua eficiência computacional, enquanto o segundo está relacionado ao uso de linguagens de programação livres, versáteis, de fácil aprendizado e utilização para os pesquisadores das diferentes áreas do conhecimento. Do ponto de vista do sistema neuromuscular, alguns dos modelos citados anteriormente [1][2][3][4][5], embora apresentem uma boa fidelidade biológica, foram desenvolvidos em plataformas proprietárias (e.g. Matlab) ou em linguagens que não são tipicamente utilizadas atualmente por pesquisadores na área de Neurociências, criando, portanto, barreiras adicionais à ampla utilização destes modelos.…”