Dynamic analysis of beta oscillations in Parkinsonian neural networks with the pedunculopontine nucleus under optogenetic control

Clinical experiments have proven that the pedunculopontine nucleus (PPN) plays a crucial role in the modulation of beta oscillations in Parkinson's disease (PD). Here, we propose a new computational framework by introducing the PPN and related synaptic connections to the classic basal ganglia-thalamo-cortical model. Fascinatingly, the improved model can not only simulate the basic saturated and beta activities mentioned in previous studies but also produce the normal alpha rhythm that is much closer to physiological phenomena. Specifically, the results show that Parkinsonian oscillation activities can be controlled and modulated by the connection strength between the PPN and the globus pallidus internal nucleus (GPi) and the subthalamic nucleus (STN), supporting the fact that PPN is overinhibited in PD. Meanwhile, the internal mechanism underlying these state transitions is further explained from the perspective of dynamics. Additionally, both deep brain stimulation (DBS) and optogenetic technology are considered effective in terms of abnormal oscillations. Especially when a low-frequency DBS is added to the PPN, beta oscillations can be suppressed, but it is excited again as the DBS's frequency gradually increases to a larger value. These results coincide with the experimental results that low-frequency stimulation of the PPN is effective, and verify the rationality of the model. Furthermore, we show that optogenetic stimulation of the globus pallidus external (GPe) expressing excitatory channelrhodopsin (ChR2) can effectively inhibit beta oscillations, whereas exciting the STN and PPN has a limited effect. These results are consistent with experimental reports suggesting that the symptoms of PD's movement disorder can be alleviated under the GPe-ChR2, but not STN-ChR2, situation. Although the functional role of the PPN and the feasibility of optogenetic stimulation remain to be clinically explored, the results obtained help us understand the mechanisms of beta oscillations in PD.