Characterizing the nonlinear dynamics of the levodopa transition in the subthalamic nucleus oscillatory activity in patients with Parkinson's disease

Parkinson's disease (PD) is the second most common neurodegenerative disorder in the US, with a prevalence of 1% in the population over 60 years old and an annual economic impact estimated in 23 billion dollars in direct costs only. Deep Brain Stimulation (DBS) is an e ffective surgical treatment for advanced PD in patients who developed a resistance to the pharmacological medication. DBS procedure allows the recording of electrophysiological signals known as Local Field Potentials (LFP) from deep brain structures such as the Subthalamic Nucleus (STN). LFPs represent the synchronized activity of a relatively large population of neurons and have been shown to correlate with many PD symptoms and contribute with their use to the success of DBS practice. However, the pathophysiology of PD remains unclear. In this work, long-term STN LFP recordings of ten PD patients were analyzed using classical as well as recently developed methods to investigate the spatial distribution of spectral activity and nonlinear cross-frequency coupling in the STN in medicated and unmedicated conditions, and the correlation of features extracted from LFPs with clinical scores and sensory data during resting state and movement execution. The main findings showed that cross-frequency coupling is stronger in the superior part of STN and is not modulated by voluntary movement. The results support and integrate existing evidence that LFPs analysis may assist in the target localization during DBS surgery and contribute to the development of smarter algorithms for next generation closed-loop DBS applications.