Computational modeling of motor neurons to study the biophysical changes caused by the amyotrophic lateral sclerosis

Mathematical modeling and computer simulations have been widely used in the neural sciences to provide theoretical/conceptual foundations on the mechanisms involved in the functioning of the nervous system. Specifically, mathematical models of alpha motor neurons (MNs) have supported investigations on the dynamical behavior of individual cells under different experimental conditions. Also, a population of MN models has been used to represent motor nuclei so as to study the muscle force control. Recent computational neuroscience studies proposed complex mathematical models of MNs with morphological, biophysical, and electrophysiological features of animal models of amyotrophic lateral sclerosis (ALS). These MN models have aided the understanding of different mechanisms operating at the onset and during the progression of this neurodegenerative disease, which affects motor neurons. In this work, the objective was to develop new biologically plausible and computationally efficient MN models that encompass the main geometrical, electrotonic and electrophysiological characteristics of animal models of ALS. The developed models were able to represent with relative fidelity three phases of the ALS: hyperexcitability, no excitability alteration and hypoexcitability. These new models would advance the understanding of underlying mechanisms of ALS from a single-cell standpoint. Additionally, due to their computational efficiency these models may be used in future multi-scale models of the neuromuscular system intended to investigate the control/generation of muscle force in ALS patients (AU)