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

Parkinson Disease Clinical Trial

— ElectroPARK  

Official title:

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

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT05284526
• Other study ID #: APHP211327
• Status: Completed
• Phase: N/A
• Start date: May 9, 2022
• Est. completion date: April 21, 2023

Study information

• Verified date: May 2022
• Source: Assistance Publique - Hôpitaux de Paris
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial 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.

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.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 30
• Est. completion date: April 21, 2023
• Est. primary completion date: May 9, 2022
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years and older

Eligibility

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

Related Conditions & MeSH terms

• Parkinson Disease

Intervention

Other:
• 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

Locations

Country	Name	City	State
France	DEGOS	Bobigny

Sponsors (2)

Lead Sponsor	Collaborator
Assistance Publique - Hôpitaux de Paris	Institut National de la Santé Et de la Recherche Médicale, France

Country where clinical trial is conducted

France, 

References & Publications (3)

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. — View Citation

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. — View Citation

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. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	measure the encoding capacity of the cortical networks of parkinsonian patients, with or without anti-parkinsonian drug treatment, and with or without High-frequency stimulation (HFS) of the subthalamic nucleus (STN).	comparison of the success scores of motion recognition, obtained by the decoding algorithms, which will highlight differences in the encoding and transmission capabilities of cortical information between the different experimental groups.	18 months