EEG Recordings and Analysis in Parkinson's Patients: Towards Adaptive Deep Brain Stimulation by Machine Learning

NCT ID: NCT05284526

Last Updated: 2023-08-23

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 30 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2022-05-09
• Study Completion Date: 2023-04-21

Brief Summary

The objective of this protocol is to obtain on Parkinson's disease more accessible therapeutic targets than deep brain stimulation (HFS-STN), the neurosurgical treatment for this pathology. This study will pave the way for new forms of adaptive processing for the HFS-STN. It could become functionally coupled to a minimalist EEG centred on the motor cortex and to software for decoding, live or slightly delayed, classes of movements performed. On the one hand, this device could be used as a sensor of the quality of the information transmitted by the cortical network, thus allowing the selection of the optimal parameters of the HFS-STN on the basis of the movement decoding score. On the other hand, this device could lead to adapting the HFS-STN treatment over time by regularly calculating the recognition scores of the different movements performed and comparing them to the initial scores.

Detailed Description

One of the therapies for Parkinson's disease, a condition affecting nearly 150,000 patients in France, is the invasive neurosurgical implantation of high-frequency deep brain stimulation of the subthalamic nuclei (HFS-STN). Although HFS-STN is very effective, the underlying mechanisms are still relatively poorly understood, particularly at the cortical level, a region that could become an alternative therapeutic target because it is easier to access. This study aims to measure the changes induced by the antiparkinsonian drug treatment and the HFS-STN on the encoding and transmission of motor information at the level of the motor cortex, thanks to the recording of the electroencephalogram of patients. These recordings, made during the performance of certain movements, will be subjected to an analysis using "machine learning" methods that will make it possible to decode the identity of the movement performed more or less efficiently.

Conditions

Parkinson Disease

Study Design

• Allocation Method: NON_RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: DIAGNOSTIC
• Blinding Strategy: NONE

Study Groups

parkinsonian patients with and without dopaminergic drug treatment

Electroencephalogram (EEG) of 10 parkinsonian subjects with and without dopaminergic drug treatment during the preparation and execution of movements

Group Type: EXPERIMENTAL

electroencephalogram (EEG) of control and parkinsonian subjects during the preparation and execution of movements

Intervention Type: OTHER

electroencephalogram (EEG) of control and parkinsonian subjects during the preparation and execution of movements

parkinsonian patients with and without High-frequency stimulation of the subthalamic nucleus

Electroencephalogram (EEG) of 10 parkinsonian subjects with and without High-frequency stimulation (HFS) of the subthalamic nucleus (STN) during the preparation and execution of movements

Group Type: EXPERIMENTAL

electroencephalogram (EEG) of control and parkinsonian subjects during the preparation and execution of movements

Intervention Type: OTHER

electroencephalogram (EEG) of control and parkinsonian subjects during the preparation and execution of movements

control subjects

Electroencephalogram (EEG) of control subjects during the preparation and execution of movements

Group Type: ACTIVE_COMPARATOR

electroencephalogram (EEG) of control and parkinsonian subjects during the preparation and execution of movements

Intervention Type: OTHER

electroencephalogram (EEG) of control and parkinsonian subjects during the preparation and execution of movements

Interventions

electroencephalogram (EEG) of control and parkinsonian subjects during the preparation and execution of movements

electroencephalogram (EEG) of control and parkinsonian subjects during the preparation and execution of movements

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

Patients :

1. Patient over 18 years of age

2. Patient meeting the clinical diagnostic criteria for Parkinson's disease (Postuma et al, Mov Dis, 2015)

3. Signed consent to participate in the study

4. Absence of cognitive impairment (MoCA>24)

5. Affiliation to a French social security scheme

Healthy volunteer :

1. Healthy volunteer over 18 years of age

2. Signed consent to participate in the study

3. Absence of cognitive disorders (MoCA>24)

4. Affiliation to a French social security system

Exclusion Criteria

Patients :

1. Patient refusal to participate

2. Pregnancy or breastfeeding in progress

3. Participation in another therapeutic interventional study

4. Patient under guardianship or curatorship

5. Person subject to a legal protection measure

Healthy volunteers :

1. Refusal of the healthy volunteer to participate

2. Pregnancy or breastfeeding in progress

3. Participation in another therapeutic interventional study.

4. Patient under guardianship or curatorship

5. Person subject to a legal protection measure

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Institut National de la Santé Et de la Recherche Médicale, France

OTHER_GOV

Sponsor Role: collaborator

Assistance Publique - Hôpitaux de Paris

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Locations

DEGOS

Bobigny, , France

Countries

France

References

Ashkan K, Rogers P, Bergman H, Ughratdar I. Insights into the mechanisms of deep brain stimulation. Nat Rev Neurol. 2017 Sep;13(9):548-554. doi: 10.1038/nrneurol.2017.105. Epub 2017 Jul 28.

Reference Type: BACKGROUND

PMID: 28752857 (View on PubMed)

Liao K, Xiao R, Gonzalez J, Ding L. Decoding individual finger movements from one hand using human EEG signals. PLoS One. 2014 Jan 8;9(1):e85192. doi: 10.1371/journal.pone.0085192. eCollection 2014.

Reference Type: BACKGROUND

PMID: 24416360 (View on PubMed)

Limousin P, Pollak P, Benazzouz A, Hoffmann D, Le Bas JF, Broussolle E, Perret JE, Benabid AL. Effect of parkinsonian signs and symptoms of bilateral subthalamic nucleus stimulation. Lancet. 1995 Jan 14;345(8942):91-5. doi: 10.1016/s0140-6736(95)90062-4.

Reference Type: BACKGROUND

PMID: 7815888 (View on PubMed)

Other Identifiers

APHP211327

Identifier Type: -

Identifier Source: org_study_id