Motor symptoms of Parkinson’s disease are associated with the excessive synchronized oscillatory activity in the beta frequency band (around 20Hz) in the basal ganglia and other parts of the brain. We study the dynamics of this synchrony in parkinsonian patients, as well as its potential mechanisms and functional implications with the computational models of basal ganglia circuits.

The study of neuronal units and LFP recorded in subthalamic nucleus of our group of patients revealed the specific temporal patterning of synchrony in time. If synchrony is present on the average, neural signals tend to go out of synch for a short (although potentially numerous) intervals. We developed time-series analysis approach, which quantifies this temporal patterning (and associated organization of the phase space), which allowed us to analyze the fine temporal structure of phase-locking in a realistic network model and match it with the experimental data. The experimentally observed intermittent synchrony can be generated just by moderately increased coupling strength in the basal ganglia circuits due to the lack of dopamine.

One particularly interesting aspect of this observed synchrony is the potential for desynchronizing deep brain stimulation. Recently, a lot of interest has been devoted to desynchronizing delayed feedback deep brain stimulation. This type of synchrony control was shown to destabilize synchronized state in networks of simple model oscillators as well as networks of coupled model neurons. However, the dynamics of the neural activity in Parkinson’s disease exhibits complex intermittent synchronous patterns, far from the idealized synchronous dynamics used to study the delayed feedback stimulation. When model parameters are such that the synchrony is unphysiologically strong, the feedback exerts desynchronizing action. However, when the network is tuned to reproduce the highly variable temporal patterns observed experimentally, the same kind of delayed feedback may increase the synchrony. As network parameters are changed from the range which produces complete synchrony to those favoring less synchronous dynamics, desynchronizing delayed feedback may gradually turn into synchronizing stimulation. This suggests that delayed feedback DBS in Parkinson’s disease may boost rather than suppress synchronization. This also indicates that in general, desynchronizing stimulation may not necessarily exhibit a desynchronization effect, when acting on a physiologically realistic partially synchronous dynamics.