Deep Neural Network Approaches for Closed-Loop Deep Brain Stimulation

Parkinson Disease Clinical Trial

Official title:

Deep Neural Network Approaches for Closed-Loop Deep Brain Stimulation

Clinical Trial Details — Status: Enrolling by invitation

Administrative data

• NCT number: NCT04277689
• Other study ID #: 2019P003874
• Status: Enrolling by invitation
• Phase: N/A
• Start date: June 10, 2021
• Est. completion date: February 2026

Study information

• Verified date: August 2023
• Source: Massachusetts General Hospital
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

In this research study the researchers want to learn more about brain activity related to speech perception and production in patients with Parkinson's Disease who are undergoing deep brain stimulation (DBS).

Description:

Deep brain stimulation (DBS) is the gold-standard treatment for patients with medication resistant motor complications of Parkinson's disease (PD) and provides the only opportunity to record and stimulate in the human basal ganglia. Most recently, the concurrent use of research electrocorticography (ECoG) during DBS surgery, including pioneering work from Pittsburgh, has further enabled basic neuroscience investigation of human cortical-subcortical network dynamics. The discovery that aberrant synchronization of rhythmic neuronal activity recorded in PD patients is suppressed by DBS has advanced the concept that measures associated with pathological activity may be used as biomarkers to control the delivery of DBS therapy. Pilot studies of aDBS in PD have reported promising clinical results from triggering DBS stimulation when the signal recorded from the DBS electrode showed a high level of oscillatory power in the beta frequency range (13 - 35 Hz). That approach, however, has important limitations. Most importantly, beta power recorded from the DBS lead is suppressed by movement including PD tremor, its detection is highly dependent on lead location and the recording montage needed to record during stimulation is incompatible with directional current steering, a recent innovation employing segmented stimulation contacts. The inherent complexity of the increased parameter space through DBS innovations also overwhelms standard programming techniques. Finally, use of additional biomarker signals (e.g., recorded from cortex) is likely to improve the ability to adaptively control DBS for disorders marked by complex multidimensional symptomatologies such as PD. The current proposal will establish methods for overcoming these limitations by developing techniques for multi-feature classification from ECoG recordings, using advanced machine learning algorithms.

Recruitment information / eligibility

• Status: Enrolling by invitation
• Enrollment: 30
• Est. completion date: February 2026
• Est. primary completion date: February 2025
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years to 85 Years

Eligibility

Inclusion Criteria:

1. Subjects scheduled for DBS implantation, as determined by the clinical multidisciplinary movement disorders board with definitive diagnosis of Parkinson's disease

2. Subjects able to provide informed consent and comply with task instructions.

3. Subjects 18-85 years old

Exclusion Criteria:

1. Non-English-speaking subjects

Related Conditions & MeSH terms

• Parkinson Disease

Intervention

Procedure:
• Brain signal data collection
Collection of speech related electrophysiological data at the time of DBS.

Locations

Country	Name	City	State
United States	Massachusetts General Hospital	Boston	Massachusetts

Sponsors (1)

Lead Sponsor	Collaborator
Massachusetts General Hospital

Country where clinical trial is conducted

United States, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	The number of subjects providing interpretable electrophysiological data during DBS surgery	The number of subjects providing interpretable electrophysiological data during DBS surgery	Duration of single DBS surgery