University of Twente Student Theses
Assessing Motoneuron Model Optimization and Parameter Sensitivity by Gamma-Factor
Mooiweer, R.A.E. (2024) Assessing Motoneuron Model Optimization and Parameter Sensitivity by Gamma-Factor.
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| Abstract: | The physiological properties of alpha-motoneurons (MNs) can be estimated by computational models. These models represent a person-specific tool for the assessment of neuronal adaptations after spinal cord injury (SCI). This study characterizes the sensitivity of MN model parameters and evaluates changes in the model optimization set-up to maximize the performance of neural data-driven optimization frameworks for capturing the in vivo firing characters of human MNs in healthy conditions. The model performance is assessed by a spike-by-spike comparison metric called gamma-factor. While an extended region of optimization and additional filtering techniques did not yield significant improvements to the simulated spike train derived from experimental data, the study reveals that the sensitivity of gamma-factor to model parameters is dependent on the size of the MN. These findings contribute to the development of computational tools translatable to the clinical setting for assessing lesion-specific adaptations and neurorehabilitation interventions. |
| Item Type: | Essay (Bachelor) |
| Faculty: | TNW: Science and Technology |
| Programme: | Biomedical Technology BSc (56226) |
| Link to this item: | https://purl.utwente.nl/essays/98119 |
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