Towards a computational model for stimulation of the Pedunculopontine nucleus

The pedunculopontine nucleus (PPN) has recently been suggested as a new therapeutic target for deep brain stimulation (DBS) in patients suffering from Parkinson's disease, particularly those with severe gait and postural impairment [1]. Stimulation at this site is typically delivered at low frequencies in contrast to the high frequency stimulation required for therapeutic benefit in the subthalamic nucleus (STN) [1]. Despite real therapeutic successes, the fundamental physiological mechanisms underlying the effect of DBS are still not understood. A hypothesis is that DBS masks the pathological synchronized firing patterns of the basal ganglia that characterize the Parkinsonian state with a regularized firing pattern. It remains unclear why stimulation of PPN should be applied with low frequency in contrast to the high frequency stimulation of STN. To get a better understanding of PPN stimulation we construct a computational model for the PPN Type I neurons in a network