Computational model of dopaminergic neurons
November 2013
University of Tuebingen, Tübingen, Germany
Parkinson's disease is a devastating neurodegenerative disorder that is characterized by a progressive death of dopaminergic neurons that leads to motor and cognitive deficits and, ultimately, death. Despite having identified several pathological features of the disease, the mechanisms that cause the onset remains unknown. Here, the researchers propose a computational model of dopaminergic neurons based on several sub-models that include cellular processes involved in the homeostatic and pathological mechanisms present in Parkinson's disease. The model was investigated to find steady model states through the modulation of several experiments. The results show that this model can predict neuronal outcomes that fit previous observations and can be used to study how the manipulation of different cellular processes affect the pathological outcome in the cell. This study provides an in silico platform to simulate the behaviour of dopaminergic neurons and predict the outcome of potential dysregulations that are present in pathologies such as Parkinson's disease.
Parkinson’s disease: dopaminergic nerve cell model is consistent with experimental finding of increased extracellular transport of α-synuclein
Finja Büchel
Added on: 09-30-2021
[1] https://bmcneurosci.biomedcentral.com/articles/10.1186/1471-2202-14-136[2] https://data.jrc.ec.europa.eu/dataset/a8fd26ef-b113-47ab-92ba-fd2be449c7eb
