Characterizing Deep Brain Stimulation effects in computationally efficient neural network models |
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Authors: | Alberta Latteri Paolo Arena Paolo Mazzone |
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Institution: | 1.DIEEI - Università di Catania,Catania,Italy;2.C.T.O. "A. Alesini" via S. Nemesio,Roma,Italy |
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Abstract: | Background Recent studies on the medical treatment of Parkinson's disease (PD) led to the introduction of the so called Deep Brain Stimulation
(DBS) technique. This particular therapy allows to contrast actively the pathological activity of various Deep Brain structures,
responsible for the well known PD symptoms. This technique, frequently joined to dopaminergic drugs administration, replaces
the surgical interventions implemented to contrast the activity of specific brain nuclei, called Basal Ganglia (BG). This
clinical protocol gave the possibility to analyse and inspect signals measured from the electrodes implanted into the deep
brain regions. The analysis of these signals led to the possibility to study the PD as a specific case of dynamical synchronization
in biological neural networks, with the advantage to apply the theoretical analysis developed in such scientific field to
find efficient treatments to face with this important disease. Experimental results in fact show that the PD neurological
diseases are characterized by a pathological signal synchronization in BG. Parkinsonian tremor, for example, is ascribed to
be caused by neuron populations of the Thalamic and Striatal structures that undergo an abnormal synchronization. On the contrary,
in normal conditions, the activity of the same neuron populations do not appear to be correlated and synchronized. |
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