Computational Neuroscience has shown a tremendous development in the last decades, and we think it is ripe to contribute substantially to computational neurology. In selected cases, large-scale and multi-scale models encompassing sensory receptors, neurons, muscles, bones, joints and other structures can be modeled to represent different degrees of dysfunction of a specific subsystem associated with a given neurological pathology. The model simulations can shed light to early signs of the disease (earlier detection than with current diagnosis techniques) and provide estimates of the progression of disease as a function of different treatment courses. We show in a recent paper published in the Journal of Neural Engineering [ https://iopscience.iop.org/article/10.1088/1741-2552/ac91f8/pdf] how neuropathies associated with Guillain-Barré Syndrome can affect functional aspects of the control of foot movement in a controlled setting, which is suitable for clinical evaluation. Muscle electrical activity also was shown to be a useful quantifier of the demyelination process. The multi-scale model encompasses neuronal ionic channels of spinal cord neurons up to a model of the foot and its muscles acting around the ankle joint when controlling force and foot position in a controlled lab experiment. The extension of such an approach to other peripheral nervous disorders or to spinal cord related pathologies (e.g., motoneuron diseases) seems quite feasible, provided that parameter data from patients are available to realize a biologically compatible model.
Andre Fabio Kohn, Ph.D., Professor of Biomedical Engineering, University of Sao Paulo
