DATA MINING AND NEURAL NETWORK SIMULATIONS CAN HELP TO IMPROVE DEEP BRAIN STIMULATION EFFECTS IN PARKINSON’S DISEASE | Zendy

Szymanski Artur | Zendy; K. Gillespie Anna | Zendy; Andrzej W. Przybyszewski | Zendy

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DATA MINING AND NEURAL NETWORK SIMULATIONS CAN HELP TO IMPROVE DEEP BRAIN STIMULATION EFFECTS IN PARKINSON’S DISEASE

Author(s) -

Szymanski Artur,

K. Gillespie Anna,

Andrzej W. Przybyszewski

Publication year - 2015

Publication title -

computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.145

H-Index - 5

eISSN - 2300-7036

pISSN - 1508-2806

DOI - 10.7494/csci.2015.16.2.199

Subject(s) - subthalamic nucleus , deep brain stimulation , neuroscience , parkinson's disease , local field potential , basal ganglia , substantia nigra , excitatory postsynaptic potential , stimulation , computer science , dopamine , inhibitory postsynaptic potential , disease , medicine , psychology , central nervous system , pathology , dopaminergic

Parkinson's Disease (PD) is primary related to substantia nigra degeneration and, thus, dopamine insuciency. of stimulation related to the interruption of pathological oscillation in the basal ganglia found in PD. Our model represents possible STN neural population with inhibitory and excitatory connections that have patho- logically synchronized oscillations. High-frequency electrical stimulation has interrupted synchronization. something that is also observed in PD patients.

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