کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
404308 677412 2011 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
The pedunculopontine nucleus as an additional target for deep brain stimulation
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
The pedunculopontine nucleus as an additional target for deep brain stimulation
چکیده انگلیسی

The pedunculopontine nucleus has been suggested as a target for DBS. In this paper we propose a single compartment computational model for a PPN Type I cell and compare its dynamic behavior with experimental data. The model shows bursts after a period of hyperpolarization and spontaneous firing at 8 Hz. Bifurcation analysis of the single PPN cell shows bistability of fast and slow spiking solutions for a range of applied currents. A network model for STN, GPe and GPi produces basal ganglia output that is used as input for the PPN cell. The conductances for projections from the STN and the GPi to the PPN are determined from experimental data. The resulting behavior of the PPN cell is studied under normal and Parkinsonian conditions of the basal ganglia network. The effect of high frequency stimulation of the STN is considered as well as the effect of combined high frequency stimulation of the STN and the PPN at various frequencies. The relay properties of the PPN cell demonstrate that the combined high frequency stimulation of STN and low frequency (10 Hz, 25 Hz, 40 Hz) stimulation of PPN hardly improves the effect of exclusive STN stimulation. Moreover, PPN–DBS at low stimulation amplitude has a better effect than at higher stimulation amplitude. The effect of PPN output on the basal ganglia is investigated, in particular the effect of STN–DBS and/or PPN–DBS on the pathological firing pattern of STN and GPe cells. PPN–DBS eliminates the pathological firing pattern of STN and GPe cells, whereas STN–DBS and combined STN–DBS and PPN–DBS eliminate the pathological firing pattern only from STN cells.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neural Networks - Volume 24, Issue 6, August 2011, Pages 617–630
نویسندگان
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