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Brain Signals Linked to Movement and Mood Changes in Parkinson's Disease

Studies brain wave recordings during levodopa and deep brain stimulation in people with Parkinson's disease.

Plain-language title generated from the registry record
Registry title: Neural Correlates of Motor and Psychiatric Fluctuations in Parkinson's Disease

Key facts

Where
Geneva, SwitzerlandSee the site

Could this be for you?

Answer for yourself. This is not a decision: only the study team can say whether you can take part.

  • Are you between 18 and 80 years old?

Source: NCT07404241, who can take part

Where in Switzerland

  • Geneva University HospitalGeneva, SwitzerlandTaking people

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Trial details

Who runs it
University Hospital, Geneva
Trial code
NCT07404241
Record updated
11 February 2026
Original description
This study explores the electrophysiological mechanisms underlying motor and non-motor fluctuations (NMF) in Parkinson's disease (PD), focusing on cortical and subthalamic dynamics during acute dopaminergic stimulation.Read full original descriptionShow less

Subthalamic and Cortical Electrophysiological Correlates of Motor and Neuropsychiatric Fluctuations in Parkinson's Disease

This study explores the electrophysiological mechanisms underlying motor and non-motor fluctuations (NMF) in Parkinson's disease (PD), focusing on cortical and subthalamic dynamics during acute dopaminergic stimulation.

PD is characterized by both motor symptoms and disabling non-motor symptoms-including neuropsychiatric fluctuations that remain poorly understood. While local field potentials (LFP) recorded from the subthalamic nucleus (STN) via deep brain stimulation (DBS) have revealed beta-band abnormalities linked to motor dysfunction, little is known about the oscillatory signatures of NMF. Preliminary data from our group suggested that gamma-band EEG activity in frontotemporal regions may correlate with neuropsychiatric fluctuations.

This Swiss, two-center, prospective observational study aims to investigate resting-state electroencephalogram (EEG) and STN-LFP correlates of motor and non-motor symptoms during a modified levodopa challenge in 30 PD patients with STN-DBS. Using high-density EEG and chronically implanted Medtronic Percept™ DBS devices, electrophysiological data will be collected across five clinical states (combinations of ON/OFF levodopa and DBS). Clinical symptoms will be assessed alongside electrophysiological activity to identify frequency-specific cortical-STN biomarkers. Machine learning models (e.g., LASSO regression) will be used to predict motor and non-motor states from EEG and LFP data, enabling the identification of dynamic oscillatory markers. This could inform future adaptive DBS strategies.

The study leverages advanced methods in neurophysiology, imaging, and machine learning to deepen our understanding of PD fluctuations. It also proposes the first detailed electrophysiological mapping of NMF, which could improve patient stratification and neuromodulation therapies. Anatomical validation of DBS lead placement will be performed using standard neuroimaging toolkits.

Inclusion: Diagnosis of Parkinson's disease (PD) based on United Kingdom Parkinson's Disease Society Brain Bank Criteria; Patients candidate for STN-DBS in the PD phase called fluctuations stage; Presence of fluctuations (motor and/or non-motor) are based on the pre-surgical DBS assessment:; To be on dopaminergic therapy; Patients who have undergone STN-DBS implantation within 4 to 8 weeks before electrophysiological acquisition.

Exclusion: Patients with OFF-drug state so severe that it prevents study tests from being carried out (e.g acute painful dystonia, intolerable non-motor symptoms such as pain, anxiety),; Dementia (defined by a MOCA score ≤24),; Any clinically meaningful non-stable physical diseases,; Patients with an age greater than 80 years,; Active psychosis or depression with suicidal ideation,; Participating in a pharmacological study,; Inability to provide informed consent (legal guardianship).

ClinicalTrials.gov NCT07404241