Automated Daytime Adaptive Deep Brain Stimulation Parameter Optimization in Patients Implanted With Percept Neurostimulator

Automated Daytime Adaptive Deep Brain Stimulation Parameter Optimization in Patients Implanted With Percept Neurostimulator

Parkinson's disease (PD) affects ~1% of people over 60 years old, is highly disabling and represents a large economic burden. While dopaminergic medications effectively treat motor symptoms early in the disease, most patients develop complications, including motor fluctuations and dyskinesias, which can be partially managed by deep brain stimulation (DBS). This surgical therapy consists of delivering continuous electrical stimulation through electrodes permanently implanted in basal ganglia nuclei, with a pulse generator and battery unit implanted in the chest. However, conventional DBS therapy is delivered with constant stimulation parameters, referred to as constant deep brain stimulation (cDBS), that are unresponsive to patient activities or to variations in the severity of symptoms during daily life. This leaves many patients under- or over-stimulated during parts of the day.

To address the shortcomings of cDBS, adaptive DBS (aDBS) uses real-time detection of neural signals to automatically adjust stimulation amplitude or other parameters in response to patients' dynamic clinical needs. aDBS was approved by the U.S. Food and Drugs Administration (FDA) for clinical treatment of PD in the Percept PC and RC (Medtronic) device in February 2025.

Fully leveraging this therapy in the real world is limited by technical challenges, in particular the fact that: while the investigators developed a consistent pipeline for implementing aDBS, there were several critical control parameters that strongly influenced algorithm performance and required prolonged trial-and-error based testing, to achieve successful control. In this new study, the investigators seek to significantly extend this work and address the major barriers to widespread, easy adoption of aDBS by groups without specialized knowledge of neurophysiology or feedback control. Here the investigators aim to test an automated, data-driven pipeline for the recommendation of the adaptive control parameters.

Parkinson's disease (PD) affects ~1% of people over 60 years old, is highly disabling and represents a large economic burden. While dopaminergic medications effectively treat motor symptoms early in the disease, most patients develop complications, including motor fluctuations and dyskinesias, which can be partially managed by deep brain stimulation (DBS). This surgical therapy consists of delivering continuous electrical stimulation through electrodes permanently implanted in basal ganglia nuclei, with a pulse generator and battery unit implanted in the chest. DBS devices have been implanted in ~200,000 PD patients worldwide and most PD patients will become surgical candidates during their disease. Further, DBS is an approved treatment for essential tremor and isolated dystonia, and a potential treatment for other brain disorders, including major depression. Thus, the potential impact of improvements in DBS systems is high. However, conventional DBS therapy is delivered with constant stimulation parameters, referred to as constant deep brain stimulation (cDBS), that are unresponsive to patient activities or to variations in the severity of symptoms during daily life. This leaves many patients under- or over-stimulated during parts of the day. To address the shortcomings of cDBS, adaptive DBS (aDBS) uses real-time detection of neural signals to automatically adjust stimulation amplitude or other parameters in response to patients' dynamic clinical needs. aDBS was approved by the U.S. Food and Drugs Administration (FDA) for clinical treatment of PD in the Percept PC and RC (Medtronic) device in February 2025.

The original studies of aDBS in PD were performed peri-operatively, with externalized brain leads attached to a large equipment rack. Fully implantable bidirectional neural interfaces, which can sense neural activity during stimulation and have circuitry to implement feedback control, have recently been available for investigational use only in the US. Medtronic Percept PC is a commercial neurostimulator that has chronic brain sensing enabled as a standard feature. Its adaptive DBS capability is now commercially available following a pivotal trial that demonstrated safety. A rechargeable version of Percept (Percept RC) was released in January 2024. Until recently, most aDBS studies using these devices have been performed in clinic, for short durations only, often in a "distributed mode" in which neural signals are routed through an external computer. While useful for therapy development, distributed mode aDBS would be cumbersome to use in patients going about their normal daily lives, given the need for close proximity to an external computer. As a result of our group's recently completed NIH funded study, "Closed loop deep brain stimulation in Parkinson's disease", the investigators achieved the first demonstration that chronic personalized embedded aDBS improves parkinsonian motor signs more than fully optimized cDBS. The investigators have implanted 12 subjects with bilateral subthalamic depth leads, for stimulation and sensing, and chronic bilateral subdural cortical paddle-type leads, for sensing only. These were attached to an investigational pulse generator, enabled for sensing and aDBS, Summit RC+S (Medtronic). Patients were first clinically optimized in cDBS by a movement disorders neurologist for up to 1 year. A subset of patients, following clinical optimization, had bothersome residual motor signs (bradykinesia, dyskinesia, or dystonia), despite optimal cDBS. The investigators developed a method of aDBS based on the detection of individualized cortical or subcortical oscillatory activities that served as markers of hyperkinetic or hypokinetic states. The investigators implemented a control policy that automatically adjusted stimulation levels between predefined upper and lower limits, smoothing out residual motor fluctuations. In a first randomized, blinded study design comparing personalized aDBS to clinically optimized cDBS, aDBS significantly reduced the patient's most bothersome residual motor fluctuations, assessed both in blinded daily self-assessments, and objectively by wearable monitors, and improved quality of life. One other formal clinical trial of chronic adaptive DBS was recently completed (the Medtronic ADAPT study in North America and Europe, utilizing the Percept PC), and another one is recruiting (a study sponsored by Newronica, Inc., in Europe only, utilizing the AlphaDBS device). Both trials aim to adjust stimulation amplitude using basal ganglia beta band activity. In results of these unblinded, uncontrolled, studies, aDBS is only shown to be approximately equivalent, rather than significantly superior to cDBS.

Fully leveraging this therapy in the real world is limited by technical challenges, in particular the fact that: while the investigators developed a consistent pipeline for implementing aDBS, there were several critical control parameters that strongly influenced algorithm performance and required prolonged trial-and-error based testing, to achieve successful control. Our initial study demonstrated that fully embedded, chronic aDBS improved neurostimulation therapy compared to highly optimized standard cDBS. In this new study, the investigators seek to significantly extend this work and address the major barriers to widespread, easy adoption of aDBS by groups without specialized knowledge of neurophysiology or feedback control. To address the barrier presented by the large new parameter space (8 additional parameters for finetuned control) created by the greatly expanded suite of aDBS control settings and the need for periodic adjustment, here the investigators aim to test an automated, data-driven pipeline for the recommendation of the adaptive control parameters.

Potential risks associated with the study include temporary worsening of symptoms associated with medication withholding and with adjusting stimulation, which might induce periods of over- and under-stimulation that could lead to temporary worsening of motor and non-motor symptoms that are usually not severe, and in rare cases could lead to suicidal ideation and severe non-motor symptoms such as temporary confusion. Other risks include increased battery drain due to neural data recording and stimulation adapting, and skin irritation due to using wearable monitors to track severity of PD symptoms. Benefits from the study include improved clinical management of PD symptoms, close follow-up with and improved understanding of PD conditions in the enrolled patients. The investigators will mitigate the risks by performing offline verification of all pipeline-suggested aDBS settings before their application and ensuring that stimulation amplitudes stay within the safe amplitude limits set by the clinician. Note that there is no direct or automated connection between the analysis pipeline and the Percept device. All parameter suggestions are reviewed by a clinical researcher and manually programmed if deemed appropriate. In addition, patients will always have the option to revert to their baseline DBS settings.

This study will consist of a Phase 0, randomized, blinded, counterbalanced, within-subject study design, evaluating the performance of adaptive DBS based on automatically derived parameters compared to standard cDBS, assessed according to objective and subjective measures.

The optimization pipeline consists of the following sub-modules: 1) the investigators developed a data simulation method based on inverse Fourier transform to simulate high-temporal resolution surrogate data that matches the at-home slow-timescale power averages while patients are on cDBS; 2) to accurately simulate the onboard signal processing and adaptive control, the investigators developed an in silico simulator called percept-sim; 3) the investigators implemented probability models, ("StimEffect" models), to model the interaction between the neural signal (here beta power) and the adaptive DBS stimulation; 4) the investigators designed numerical metrics that quantify the similarity between proportions of time spent with at the different motor states while on cDBS (i.e., prior patient symptom profile) and proportions of time at different adaptive stimulation amplitudes (i.e., stimulation distribution); 5) the investigators implemented an optimizer algorithm maximizing the distribution similarity between patient symptom profile and stimulation distribution.

Based on the optimization pipeline, aDBS parameters are recommended, reviewed by the research team clinician, and if deemed appropriate - manually programmed to the Percept device. There is no direct and/or automated connection between the optimization pipeline and the Percept device.

aDBS is a novel neuromodulation technique which uses real-time detection of neural signals to automatically adjust stimulation amplitude or other parameters in response to patients' dynamic clinical needs. It has been approved by the FDA for clinical treatment of PD in the Percept PC and RC devices, and has been suggested to be non-inferior to cDBS using the Percept PC/RC devices in a large, multi-center clinical trial. Treatment in the current study will be aDBS with stimulation parameters suggested by a data-driven pipeline based on at-home and in-clinic personalized, neural recordings.

For the current study, short-term administration of aDBS will commence at the later sessions (Sessions 3 and 4 - with possible repeats as needed) of the in-clinic study phase (Phase 1), where different pipeline-suggested aDBS settings will be assessed for up to several hours to allow researchers to evaluate clinical efficacy and safety of the aDBS settings. After confirming at least one pipeline-suggested aDBS setting is safe and effective, long-term administration of aDBS will commence during the at-home study phase (Phase 2), where patients will be on aDBS during awake hours. In Session 5, the research team will confirm the long-term safety and clinical efficacy of the selected aDBS settings using both subjective and objective reports of PD symptoms and quality of life measures, and will make adjustments if needed. In Session 6, the research team will compare aDBS and cDBS in a randomized, blinded clinical trial where patients will be alternating between aDBS and cDBS treatments in counterbalanced blocks. During any period when patients are on aDBS, patients will be able to switch their stimulation settings back to their baseline DBS settings using their patient programmer.

Inclusion Criteria:

1. Age 25-75.
2. Diagnosis of idiopathic PD.
3. Patient has undergone surgical intervention with deep brain stimulation (Percept device) for their disorder at least 2 months prior to recruitment.
4. Absence of significant cognitive impairment (score of 24 or greater on the Montreal Cognitive Assessment (MoCA)).
5. Signed informed consent.
6. Ability to comply with study follow-up visits for brain recording, testing of adaptive stimulation, and clinical assessment.
7. Patient has been on cDBS for at least two months and still experiences significant residual motor fluctuation while on cDBS. Consequently, patient is undergoing aDBS treatment currently or was recommended aDBS as part of clinical care to manage their residual motor fluctuation.
8. Has available cDBS Timeline LFP and stimulation data lasting at least 1 day.
9. To be enrolled in the clinical trial phase of the study, patient will need to consent to reverting back to their baseline cDBS settings for all required cDBS testings.

Exclusion Criteria:

1. Patient meets criteria for a psychogenic movement disorder.
2. Significant untreated depression (BDI-II score >20). History of suicidal attempt or active suicidal ideation (Yes to #2-5 on C-SSRS).
3. Any personality or mood symptoms that study personnel believe will interfere with study requirements.