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Computational model-based identification of the critical alterations in parkinsonian basal ganglia’s physiology


George Tsirogiannis (Biomedical Simulations and Imaging Laboratory, National Technical University of Athens), Ioanna Chronaiou (Biomedical Simulations and Imaging Laboratory, National Technical University of Athens), George Tagaris (Department of Neurology, “G. Gennimatas” Athens General Hospital), Konstantina Nikita (Biomedical Simulations and Imaging Laboratory, National Technical University of Athens)

Parkinson’s disease (PD) is considered as a result of dopamine (DA) depletion in the basal ganglia. The objective of the present study is to contribute to the identification of the critical physiological alterations caused by DA depletion that lead to PD. Specifically it is assumed that DA modulates the power of postsynaptic potentials (PSPs) by altering not only their amplitude, but also their duration [Biol Cybern (2010) 102:155–176]. The validity of this hypothesis was assessed through a detailed multi-layer computational model of the basal ganglia, with the objective of reproducing the peak at the beta frequency range of the power spectral density function of subthalamic nucleus (STN) local field potential (LFP) activity, as the characteristic expression of PD.
The model’s neurons of the STN and the external and the internal segments of the globus pallidus (GPe and GPi, respectively) were based on a previous computational model [J Neurosci. (2002) 22(7):2963-76]. Cortical and striatal activity were modeled as random processes. On the network level, not only the classic direct-indirect pathways were incorporated, but also cortical projections to both segments of the striatum, a cortical projection to the STN, a connection from the STN to the GPe, a projection from GPe to GPi and two intra-nuclear projections within the GPe and the STN. Simulated LFP from the STN was reproduced as an output of the model through calculations on neuronal currents.
The model was simulated in supposed normal and parkinsonian conditions. The transition from the baseline, normal condition to the parkinsonian one was set by consistently modifying both the amplitude and the duration of the PSPs of all the synaptic connections of the model, according to our initial hypothesis. The model behavior was explored for different alteration magnitudes and the results were validated by considering only the plausible model states in terms of mean firing rates. The simulations showed that the peak at the beta frequency range occurred if, and only if, both the amplitude and the duration of PSPs were consistently altered.
These results confirm the considered hypothesis indicating that both the amplitude and duration of PSPs play an important role in the pathophysiology of the basal ganglia that produces the symptoms of PD. Moreover, they suggest that the absence of proper modulation of the properties of the synaptic connections by DA might be the main cause of parkinsonian expressions.
Preferred presentation format: Poster
Topic: Computational neuroscience