Clinical trial NCT06642519: Brain-Machine Interface for Freezing of Gait
Official title: Adaptive Cortical Neuromodulation Using a Brain-machine Interface to Treat Freezing of Gait in Parkinson's Disease.
Study type: INTERVENTIONAL
Overall status: NOT_YET_RECRUITING
Phase: NA
Conditions: Parkinson Disease
Freezing of Gait Symptoms in Parkinson&#39;s Disease
Keywords: Brain-Machine interface
Freezing of Gait
Triggered stimulation
Adaptive Stimulation
Lead sponsor: University of Toronto
Sponsor class: OTHER
First posted: 2024-10-15
Enrollment: 10
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NA
Intervention model: SINGLE_GROUP
Primary purpose: TREATMENT

Brief summary: Gait problems in Parkinson's disease (PD), especially freezing of gait (FOG), greatly affect quality of life. While deep brain stimulation (DBS) is a highly effective treatment for many motor symptoms of PD, it is less effective for, or can even worsen, gait issues. The primary motor cortex (M1) plays a crucial role in the network that controls gait, particularly in initiating movement. Changes in local field potentials (LFPs) from the subthalamic nucleus (STN) are associated with different aspects of gait. However, detecting abnormal brain activity related to FOG requires a method called electrocorticography (ECoG), which has revealed that during FOG, there is increased beta-gamma phase amplitude coupling (PAC) in the M1.

Brain-machine interfaces (BMIs) have shown promise in understanding motor functions by decoding brain activity. It is believed that BMIs could provide both accurate indicators of FOG and targeted treatments for it in PD.

Our objectives are to use a high-density ECoG-based BMI to both record and stimulate brain activity during real-world gait and FOG in PD patients who are undergoing standard DBS procedures. Our goals are to improve our understanding of the brain's role in FOG and normal gait in PD and to develop new treatments based on cortical stimulation.

Aim 1 - Identify gait biomarkers: brain activity from the M1/SMA cortex during different phases of walking and during FOG episodes, both with and without medication will be recorded. Machine learning will be used to identify the brain patterns linked to FOG.

Aim 2 - Use cortical stimulation to stop FOG: Cortical stimulation and its effects on leg and trunk movements will be studied by measuring muscle activity, movement, and posture during different states, such as resting, standing, walking, and during FOG episodes. The type of stimulation which is most effective at stopping FOG will be identified.


Eligibility criteria: Inclusion Criteria:

* PD fulfilling standard criteria for bilateral STN/GPi DBS surgery
* Debilitating FOG in the off-medication condition with only partial response to levodopa (defined as the witnessed occurrence of FOG during the on phase of the pre-DBS L-dopa challenge)
* Clinically established FOG (i.e. reported by patient/caregiver AND seen by the examiner in the clinic)
* Able to provide informed consent, comply with study protocol

Exclusion Criteria:

* Prior ischemic stroke, intracranial hemorrhage, or intracerebral mass
* Previous brain surgery
* Other disorders potentially biasing assessment
* Absence of FOG in the medication on condition (a population already manageable with current standard of treatment).

Primary outcomes:
measure: Number and Duration FOG episodes
timeFrame: 7-day experiment
Secondary outcomes:
measure: Measurement of Chronic Coupling between Cortex and Basal Ganglia
timeFrame: 7-day experiment
measure: Exploring BMI Control to Trigger and Study FOG
timeFrame: 7-day experiment
Other outcomes:
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