[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100624023":3},{"organization":4,"outcomesModule":7,"designInfo":28,"detailedDescription":31,"studyPopulation":32,"armGroups":33,"interventions":27,"overallOfficials":27,"centralContacts":37,"locations":43,"responsibleParty":63,"collaborators":27,"id":66,"slug":27,"hasResults":67,"nctId":68,"briefTitle":69,"officialTitle":70,"acronym":71,"eligibilityCriteria":72,"healthyVolunteers":67,"sex":73,"minAge":74,"maxAge":75,"enrollmentInfo":76,"targetDuration":27,"studyType":79,"phases":27,"briefSummary":80,"conditions":81,"keywords":83,"overallStatus":46,"whyStopped":27,"lastUpdateSubmitDate":90,"lastUpdatePostDateStruct":91,"startDateStruct":94,"completionDateStruct":96,"leadSponsor":98,"locationsCount":99},{"fullName":5,"class":6},"University Hospital, Geneva","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":13,"otherOutcomes":27},[9],{"measure":10,"description":11,"timeFrame":12},"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)",[14,17,21,24],{"measure":15,"description":15,"timeFrame":16},"Temporal dynamics of motor and non-motor clinical scores","during the acute phase of levodopa administration",{"measure":18,"description":19,"timeFrame":20},"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",{"measure":22,"description":23,"timeFrame":20},"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",{"measure":25,"description":26,"timeFrame":20},"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",null,{"allocation":27,"interventionModel":27,"interventionModelDescription":27,"primaryPurpose":27,"observationalModel":29,"timePerspective":30,"maskingInfo":27},"COHORT","PROSPECTIVE","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.\n\n   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.\n\n   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.\n2. Objectives\n\n   Primary Objective:\n\n   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.\n\n   Secondary Objectives:\n\n   To determine the influence of STN-DBS on EEG\u002FLFP biomarkers. To investigate motor and non-motor temporal profiles after levodopa administration.\n\n   To characterize phase-coupling changes between STN and cortical networks. To use machine learning to identify spectral EEG\u002FLFP biomarkers predicting ON\u002FOFF states.\n\n   To explore anatomical correlates of LFP signals using post-op imaging and electrode localization.\n3. Design and Methodology\n\nDesign:\n\nProspective, observational, exploratory two-center study (HUG Geneva and CHUV Lausanne).\n\nParticipants:\n\n30 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.\n\nTimeline:\n\nTotal duration: \\~36 months\n\n24 months for recruitment and data collection 12 months for data analysis and dissemination\n\nStudy Visits:\n\nVisit 1: Baseline clinical and neuropsychological assessment in ON-drug\u002FON-DBS condition.\n\nVisit 2: Modified levodopa challenge with 5 successive conditions:\n\nOFF-drug\u002FON-DBS OFF-drug\u002FOFF-DBS Transition period post-levodopa (serial assessments) ON-drug\u002FOFF-DBS ON-drug\u002FON-DBS\n\nFor each condition: 10-min resting-state EEG, 5-min STN-LFP, and brief clinical assessment.\n\nLevodopa Administration:\n\n150% of usual morning dose (Madopar® LIQ), to ensure supramaximal response.\n\nNeurophysiological Recording:\n\nHigh-density EEG (256 channels, Philips EGI) STN-LFP using Medtronic PERCEPT™ system Synchronization via EMG trigger pulse\n\nClinical Assessments:\n\nMDS-UPDRS Part III (motor) Neuropsychiatric Fluctuation Scale (tablet-based) Stop-Signal Task (SSRT) Bradyphrenia scale\n\n4\\. Inclusion\u002FExclusion Criteria\n\nInclusion:\n\nIdiopathic PD diagnosis DBS candidate or post-DBS (within 4-8 weeks) Motor or non-motor fluctuations MOCA \\>24\u002F30 On stable dopaminergic therapy\n\nExclusion:\n\nAge \\>80 Dementia, active psychosis, unstable disease Severe OFF symptoms precluding testing Legal guardianship or participation in other drug studies\n\n6\\. 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.\n\nThe 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.\n\nUltimately, this project aims to bridge the neurophysiological understanding of motor and non-motor circuits in PD, enhancing the personalization of neuromodulatory treatments.","STN-DBS Parkinson's disease patients",[34],{"label":35,"type":27,"description":36,"interventionNames":27},"Parkinson's disease patients treated with STN-DBS","Prospective cohort",[38],{"name":39,"role":40,"phone":41,"phoneExt":27,"email":42},"Damien BENIS, PhD","CONTACT","+41223722311","damien.benis@hug.ch",[44],{"facility":45,"status":46,"city":47,"state":27,"zip":48,"country":49,"countryCode":50,"cosmosGeoPoint":51,"geoPoint":56,"contacts":57},"Geneva University Hospital","RECRUITING","Geneva","1211","Switzerland","CH",{"type":52,"coordinates":53},"Point",[54,55],6.14569,46.20222,{"lat":55,"lon":54},[58,60],{"name":59,"role":40,"phone":41,"phoneExt":27,"email":42},"Damien Benis, PhD",{"name":61,"role":62,"phone":27,"phoneExt":27,"email":27},"Vanessa Fleury, MD, PD","PRINCIPAL_INVESTIGATOR",{"type":62,"investigatorFullName":64,"investigatorTitle":65,"investigatorAffiliation":5,"oldNameTitle":27,"oldOrganization":27},"Vanessa Fleury","Dr","100624023",false,"NCT07404241","Neural Correlates of Motor and Psychiatric Fluctuations in Parkinson's Disease","Subthalamic and Cortical Electrophysiological Correlates of Motor and Neuropsychiatric Fluctuations in Parkinson's Disease","Transition STN","Inclusion Criteria:\n\n* Diagnosis of Parkinson's disease (PD) based on United Kingdom Parkinson's Disease Society Brain Bank Criteria.\n* Patients candidate for STN-DBS in the PD phase called fluctuations stage.\n* Presence of fluctuations (motor and\u002For non-motor) are based on the pre-surgical DBS assessment:\n* To be on dopaminergic therapy.\n* Patients who have undergone STN-DBS implantation within 4 to 8 weeks before electrophysiological acquisition.\n\nExclusion Criteria:\n\n* Patients with an age greater than 80 years,\n* Dementia (defined by a MOCA score ≤24),\n* Active psychosis or depression with suicidal ideation,\n* Any clinically meaningful non-stable physical diseases,\n* 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),\n* Participating in a pharmacological study,\n* Inability to provide informed consent (legal guardianship).","ALL","18 Years","80 Years",{"count":77,"type":78},30,"ESTIMATED","OBSERVATIONAL","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.\n\nPD 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.\n\nThis 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\u002FOFF 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.\n\nThe 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.",[82],"PARKINSON DISEASE (Disorder)",[84,85,86,87,88,89],"neuropsychiatric fluctuations","non-motor symptoms","Local field potentials","Electroencephalography","Deep brain stimulation","Subthalamic nucleus","2026-02-04",{"date":92,"type":93},"2026-02-11","ACTUAL",{"date":95,"type":93},"2025-06-01",{"date":97,"type":78},"2028-12-31",{"name":5,"class":6},1]