Neural Correlates of Motor and Psychiatric Fluctuations in Parkinson's Disease (Transition STN)

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.

Study Overview

• Status: Recruiting
• Conditions: PARKINSON DISEASE (Disorder)

Detailed Description

1. Background and Rationale Parkinson's disease (PD) is a common neurodegenerative disorder affecting 2% of individuals over 65 years. Beyond classical motor symptoms like bradykinesia, rigidity, and tremor, PD is increasingly recognized for its debilitating non-motor symptoms (NMS), which include depression, anxiety, fatigue, apathy, and bradyphrenia. These NMS fluctuate alongside motor symptoms, particularly in later disease stages when dopaminergic treatments become pulsatile. Neuropsychiatric fluctuations (NMF) significantly reduce patients' quality of life, yet their pathophysiology is not well understood.

   While EEG studies have characterized motor fluctuations and impulse control disorders through frequency-specific changes, few studies have systematically examined the EEG or intracranial electrophysiological substrates of NMF. STN-DBS offers the opportunity to record local field potentials (LFPs) directly from the subthalamic nucleus (STN). Beta oscillations in STN have been consistently associated with akinesia, while recent studies suggest that alpha and gamma band activities may relate to non-motor and neuropsychiatric features.

   Technological advances, such as Medtronic's PERCEPT™ PC DBS system, now enable chronic LFP recordings postoperatively. Coupling these with high-density EEG enables real-time exploration of cortical-subcortical interactions. Our pilot data show distinct EEG dynamics between motor and neuropsychiatric fluctuations following levodopa challenge, supporting a differential spatio-spectral signature for these symptoms.

2. Objectives

   Primary Objective:

   To characterize the temporal dynamics of cortical EEG and STN LFP oscillatory activity and coherence during the acute levodopa response, and their correlation with motor and non-motor fluctuations in PD.

   Secondary Objectives:

   To determine the influence of STN-DBS on EEG/LFP biomarkers. To investigate motor and non-motor temporal profiles after levodopa administration.

   To characterize phase-coupling changes between STN and cortical networks. To use machine learning to identify spectral EEG/LFP biomarkers predicting ON/OFF states.

   To explore anatomical correlates of LFP signals using post-op imaging and electrode localization.

3. Design and Methodology

Design:

Prospective, observational, exploratory two-center study (HUG Geneva and CHUV Lausanne).

Participants:

30 patients with idiopathic PD (per UK Brain Bank Criteria), in the fluctuations stage, treated or candidates for STN-DBS, on dopaminergic therapy, and without dementia.

Timeline:

Total duration: ~36 months

24 months for recruitment and data collection 12 months for data analysis and dissemination

Study Visits:

Visit 1: Baseline clinical and neuropsychological assessment in ON-drug/ON-DBS condition.

Visit 2: Modified levodopa challenge with 5 successive conditions:

OFF-drug/ON-DBS OFF-drug/OFF-DBS Transition period post-levodopa (serial assessments) ON-drug/OFF-DBS ON-drug/ON-DBS

For each condition: 10-min resting-state EEG, 5-min STN-LFP, and brief clinical assessment.

Levodopa Administration:

150% of usual morning dose (Madopar® LIQ), to ensure supramaximal response.

Neurophysiological Recording:

High-density EEG (256 channels, Philips EGI) STN-LFP using Medtronic PERCEPT™ system Synchronization via EMG trigger pulse

Clinical Assessments:

MDS-UPDRS Part III (motor) Neuropsychiatric Fluctuation Scale (tablet-based) Stop-Signal Task (SSRT) Bradyphrenia scale

4. Inclusion/Exclusion Criteria

Inclusion:

Idiopathic PD diagnosis DBS candidate or post-DBS (within 4-8 weeks) Motor or non-motor fluctuations MOCA >24/30 On stable dopaminergic therapy

Exclusion:

Age >80 Dementia, active psychosis, unstable disease Severe OFF symptoms precluding testing Legal guardianship or participation in other drug studies

6. Impact and Perspectives This study addresses an unmet need in PD: the poor understanding and characterization of neuropsychiatric fluctuations. By correlating motor and non-motor symptom dynamics with LFP and EEG signatures, it will provide pathophysiological insights and biomarkers to guide future adaptive DBS (aDBS). It will also inform clinical management of NMFs and open avenues for biomarker-driven neuromodulation strategies.

The collaboration between two major Swiss centers ensures feasibility and access to a representative PD cohort. Use of standardized procedures and machine learning ensures translatability to larger future trials.

Ultimately, this project aims to bridge the neurophysiological understanding of motor and non-motor circuits in PD, enhancing the personalization of neuromodulatory treatments.

• Study Type: Observational
• Enrollment (Estimated): 30

Contacts and Locations

• Study Contact: Name: Damien Benis, PhD; Phone Number: +41223722311; Email: damien.benis@hug.ch

Study Locations

• Switzerland
  • Geneva, Switzerland, 1211
    • Recruiting
    • Geneva University Hospital
    • Contact: Damien Benis, PhD; Phone Number: +41223722311; Email: damien.benis@hug.ch
    • Principal Investigator: Vanessa Fleury, MD, PD

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

STN-DBS Parkinson's disease patients

Description

Inclusion Criteria:

• 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 Criteria:

• Patients with an age greater than 80 years,
• Dementia (defined by a MOCA score ≤24),
• Active psychosis or depression with suicidal ideation,
• Any clinically meaningful non-stable physical diseases,
• 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),
• Participating in a pharmacological study,
• Inability to provide informed consent (legal guardianship).

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort
Parkinson's disease patients treated with STN-DBS; Prospective cohort

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Correlation over-time of STN intracranial LFP activity and EEG resting-state oscillatory activity	Correlation over-time of STN intracranial LFP activity and EEG resting-state oscillatory activity (spectral, temporal and spatial features as well as cortical-subcortical and cortico-cortical coherence) with the temporal dynamics of motor and non-motor clinical scores	during the acute phase of levodopa administration (120 min)

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Temporal dynamics of motor and non-motor clinical scores	Temporal dynamics of motor and non-motor clinical scores	during the acute phase of levodopa administration
Correlation of EEG and STN LFP markers of motor and non-motor response to levodopa	Correlation of EEG and STN LFP markers of motor and non-motor response to levodopa with the extensive ON-OFF-DRT motor, cognitive and emotional clinical scores response to levodopa.	120 min
Dynamic modulations of the oscillatory coupling between the STN and the cortex	Dynamic modulations of the oscillatory coupling between the STN and the cortex in the canonical frequency bands and their correlation with the temporal dynamics of motor and non-motor clinical scores during the acute phase following levodopa administration	120 min
Difference in resting-state EEG power in frequency bands linked to motor and non-motor symptoms improvement, between different DBS conditions	Difference in resting-state EEG power in frequency bands linked to motor and non-motor symptoms improvement, between ON-DBS and OFF-DBS in the ON-drug and OFF-drug conditions, and correlation with motor and non-motor symptoms improvement secondary to DBS	120 min

Collaborators and Investigators

• Sponsor: University Hospital, Geneva

Study record dates

Study Major Dates

• Study Start (Actual): June 1, 2025
• Primary Completion (Estimated): December 31, 2027
• Study Completion (Estimated): December 31, 2028

Study Registration Dates

• First Submitted: February 4, 2026
• First Submitted That Met QC Criteria: February 4, 2026
• First Posted (Actual): February 11, 2026

Study Record Updates

• Last Update Posted (Actual): February 11, 2026
• Last Update Submitted That Met QC Criteria: February 4, 2026
• Last Verified: February 1, 2026

More Information

Terms related to this study

• Keywords: Subthalamic nucleus; Electroencephalography; Deep brain stimulation; non-motor symptoms; Local field potentials; neuropsychiatric fluctuations
• Additional Relevant MeSH Terms: Synucleinopathies; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Neurodegenerative Diseases; Movement Disorders; Parkinsonian Disorders; Basal Ganglia Diseases; Parkinson Disease
• Other Study ID Numbers: 2024-02324

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No