Closed-Loop Deep Brain Stimulation Effects on Parkinsonian Motor Symptoms in a Non-Human Primate – Is Beta Enough?

doi:10.1016/j.brs.2016.06.051

Brain Stimulation

Volume 9, Issue 6, November–December 2016, Pages 892-896

https://doi.org/10.1016/j.brs.2016.06.051 Get rights and content

Highlights

•
Excessive beta oscillations in the subthalamic nucleus (STN) have been proposed as a biomarker for closed-loop DBS (CL-DBS).
•
Beta-triggered CL-DBS was compared to traditional DBS in a non-human primate model of Parkinson’s disease. CL-DBS reduced the stimulation duty cycle and was comparable and in some cases better than traditional DBS at reducing rigidity. Only traditional DBS improved bradykinesia during a reaching task.
•
Reach-related reductions in beta amplitude influenced the timing and duration of stimulation in the CL-DBS condition.
•
Our results illustrate the promising utility of closed-loop DBS for PD based on STN beta LFP levels. Closed-loop DBS systems may need alternate biomarkers and/or algorithms to reach their full therapeutic potential.

Abstract

Background

Incorporating feedback controls based on real-time measures of pathological brain activity may improve deep brain stimulation (DBS) approaches for the treatment of Parkinson's disease (PD). Excessive beta oscillations in subthalamic nucleus (STN) local field potentials (LFP) have been proposed as a potential biomarker for closed-loop DBS (CL-DBS).

Objective

In a non-human primate PD model we compared CL-DBS, which delivered stimulation only when STN LFP beta activity was elevated, to traditional continuous DBS (tDBS).

Methods

Therapeutic effects of CL-DBS and tDBS relative to the Off-DBS condition were evaluated via a clinical rating scale and objective measures of movement speed during a cued reaching task.

Results

CL-DBS was comparable to tDBS at reducing rigidity, while reducing the amount of time DBS was on by ≈50%; however, only tDBS improved bradykinesia during the reaching behavior. This was likely due to reach-related reductions in beta amplitude that influence the timing and duration of stimulation in the CL-DBS condition.

Conclusion

These results illustrate the potential utility of closed-loop DBS devices for PD based on STN beta LFP levels. They also point to possible consequences in behavioral tasks when restricting real-time sensing to a single LFP frequency that itself is modulated during performance of such tasks. The present study provides data that suggest alternate algorithms or more than one physiological biomarker may be required to optimize the performance of behavioral tasks and demonstrates the value of using multiple objective measures when evaluating the efficacy of closed-loop DBS systems.

Introduction

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective surgical treatment for advanced Parkinson's disease (PD) [1]. While traditional DBS systems are always on, continually delivering pulsed stimulation at high rate (i.e., >100 Hz) regardless of the clinical state, a promising approach to improve DBS therapy is to incorporate feedback control of the stimulation based on measures of pathological brain activity that reflect a patient's moment-by-moment fluctuations in symptoms [2]. Such a strategy would have the advantage of stimulating only when necessary, potentially reducing negative side effects of prolonged stimulation [3] and increasing device battery life.

Prominent synchronization of beta (~13–30 Hz) oscillations in STN local field potentials (LFPs) has been identified in PD patients [4], [5], [6] and animal models of PD [7], [8]. Several groups report that beta activity is markedly reduced following dopaminergic treatment [9], [10], [11] and during DBS [12], [13], [14]. In some cases, this reduction has been correlated with clinical improvement of PD symptoms such as rigidity and bradykinesia [6], leading to the hypothesis that STN beta LFPs may be an effective programming biomarker for real-time, closed-loop control of DBS [2], [15], [16], [17], [18].

In this study we implemented a closed-loop DBS (CL-DBS) strategy that delivers STN stimulation based on the level of beta activity in the LFP recorded directly from the STN DBS lead implanted in a parkinsonian non-human primate. We hypothesized that CL-DBS would be more effective than traditional DBS (tDBS) at improving rigidity and bradykinesia while operating at a reduced stimulation duty cycle.

Section snippets

Animal preparation

All methods were approved by the Institutional Animal Care and Use Committee. Data were collected from one female rhesus macaque (25 years) rendered parkinsonian by two intra-carotid and two systemic injections of the neurotoxin 1-methyl-4-phenyl-1,2,3,6 tetrahydropyridine (MPTP) and implanted in the STN with a 4-contact scaled version of a human DBS lead (NuMed) using standard approaches described elsewhere [19]. The animal's overall severity was determined using a modified Unified Parkinson's

Results

Both CL-DBS and tDBS significantly reduced rigidity scores compared to Off-DBS (Fig. 1E). Elbow rigidity was lower during CL-DBS compared to tDBS, and mean total rigidity scores for CL-DBS trended lower than tDBS, though this difference did not reach significance. These results suggest that CL-DBS has similar if not better therapeutic effect on rigidity compared to tDBS, even though during rigidity assessment CL-DBS was found to be on only 52.6% of the time, compared to 100% during tDBS.

Discussion

We found that CL-DBS can operate at a reduced stimulation duty cycle and still be equally or more effective than tDBS at alleviating rigidity, one of the cardinal motor symptoms of PD. These results support the findings of Little and colleagues [15] who implemented a similar STN beta-triggered DBS paradigm in PD patients and found superior clinical effectiveness based on composite tremor, rigidity and finger tapping UPDRS scores. A recent case study by Rosa et al. [16] showed that a closed-loop

Grants

This study was funded in part by the National Institutes of Health, National Institute of Neurological Disorders and Stroke (NS-037019). Postdoctoral fellowship for Basic Scientists from the Parkinson's Disease Foundation was awarded to to A.M. and a MnDRIVE (Minnesota Discovery, Research and InnoVation Economy) Initiative Neuromodulation Post-doctoral Fellowship to L.A.J.

Acknowledgements

We thank Eunkyoung Park for assistance with in-vitro testing of the closed-loop system. Thanks also to Greg Molnar and David Escobar for helpful comments on the manuscript revision.

References (30)

A.L. Benabid
Deep brain stimulation for Parkinson's disease
Curr Opin Neurobiol
(2003)
S. Little et al.
What brain signals are suitable for feedback control of deep brain stimulation in Parkinson's disease?
Ann N Y Acad Sci
(2012)
ChenC.C. et al.
Deep brain stimulation of the subthalamic nucleus: a two-edged sword
Curr Biol
(2006)
P. Brown
Oscillatory nature of human basal ganglia activity: relationship to the pathophysiology of Parkinson's disease
Mov Disord
(2003)
A. Priori et al.
Rhythm-specific pharmacological modulation of subthalamic activity in Parkinson's disease
Exp Neurol
(2004)
A.A. Kuhn et al.
Pathological synchronisation in the subthalamic nucleus of patients with Parkinson's disease relates to both bradykinesia and rigidity
Exp Neurol
(2009)
N. Mallet et al.
Parkinsonian beta oscillations in the external globus pallidus and their relationship with subthalamic nucleus activity
J Neurosci
(2008)
A. Sharott et al.
Dopamine depletion increases the power and coherence of β-oscillations in the cerebral cortex and subthalamic nucleus of the awake rat
Eur J Neurosci
(2005)
J.F. Marsden et al.
Subthalamic nucleus, sensorimotor cortex and muscle interrelationships in Parkinson's disease
Brain
(2001)
P. Brown et al.
Dopamine dependency of oscillations between subthalamic nucleus and pallidum in Parkinson's disease
J Neurosci
(2001)

R. Levy et al.

Dependence of subthalamic nucleus oscillations on movement and dopamine in Parkinson's disease

Brain

(2002)

G. Giannicola et al.

The effects of levodopa and ongoing deep brain stimulation on subthalamic beta oscillations in Parkinson's disease

Exp Neurol

(2010)

A. Eusebio et al.

Deep brain stimulation can suppress pathological synchronisation in parkinsonian patients

J Neurol Neurosurg Psychiatry

(2011)

D. Whitmer et al.

High frequency deep brain stimulation attenuates subthalamic and cortical rhythms in Parkinson's disease

Front Hum Neurosci

(2012)

S. Little et al.

Adaptive deep brain stimulation in advanced Parkinson disease

Ann Neurol

(2013)

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Citation Excerpt :
Beta oscillations are excessively synchronized in the parkinsonian state and are believed to be associated with daytime motor complications since the suppression of beta oscillations generally leads to improvement in motor behavior (Feldmann et al., 2022; Giannicola et al., 2010; Kuhn et al., 2008; Neumann et al., 2016; Oswal et al., 2013). These findings have led to increased interest in the development of beta-based closed-loop DBS approaches for managing parkinsonian symptoms (Bocci et al., 2021; Johnson et al., 2016; Little et al., 2013). Aligned with this thought, previous sleep studies performed in PD patients also emphasized the STN beta oscillations to understand its pattern of modulation across wake and sleep states (Thompson et al., 2018; Urrestarazu et al., 2009; van Rheede et al., 2022).
Excessive daytime sleepiness is a recognized non-motor symptom that adversely impacts the quality of life of people with Parkinson's disease (PD), yet effective treatment options remain limited. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for PD motor signs. Reliable daytime sleep-wake classification using local field potentials (LFPs) recorded from DBS leads implanted in STN can inform the development of closed-loop DBS approaches for prompt detection and disruption of sleep-related neural oscillations. We performed STN DBS lead recordings in three nonhuman primates rendered parkinsonian by administrating neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Reference sleep-wake states were determined on a second-by-second basis by video monitoring of eyes (eyes-open, wake and eyes-closed, sleep). The spectral power in delta (1–4 Hz), theta (4–8 Hz), low-beta (8–20 Hz), high-beta (20–35 Hz), gamma (35–90 Hz), and high-frequency (200–400 Hz) bands were extracted from each wake and sleep epochs for training (70% data) and testing (30% data) a support vector machines classifier for each subject independently. The spectral features yielded reasonable daytime sleep-wake classification (sensitivity: 90.68 ± 1.28; specificity: 88.16 ± 1.08; accuracy: 89.42 ± 0.68; positive predictive value; 88.70 ± 0.89, n = 3). Our findings support the plausibility of monitoring daytime sleep-wake states using DBS lead recordings. These results could have future clinical implications in informing the development of closed-loop DBS approaches for automatic detection and disruption of sleep-related neural oscillations in people with PD to promote wakefulness.
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View full text

Closed-Loop Deep Brain Stimulation Effects on Parkinsonian Motor Symptoms in a Non-Human Primate – Is Beta Enough?

Highlights

Abstract

Background

Objective

Methods

Results

Conclusion

Introduction

Section snippets

Animal preparation

Results

Discussion

Grants

Acknowledgements

Deep brain stimulation for Parkinson's disease

Curr Opin Neurobiol

What brain signals are suitable for feedback control of deep brain stimulation in Parkinson's disease?

Ann N Y Acad Sci

Deep brain stimulation of the subthalamic nucleus: a two-edged sword

Curr Biol

Oscillatory nature of human basal ganglia activity: relationship to the pathophysiology of Parkinson's disease

Mov Disord

Rhythm-specific pharmacological modulation of subthalamic activity in Parkinson's disease

Exp Neurol

Pathological synchronisation in the subthalamic nucleus of patients with Parkinson's disease relates to both bradykinesia and rigidity

Exp Neurol

Parkinsonian beta oscillations in the external globus pallidus and their relationship with subthalamic nucleus activity

J Neurosci

Dopamine depletion increases the power and coherence of β-oscillations in the cerebral cortex and subthalamic nucleus of the awake rat

Eur J Neurosci

Subthalamic nucleus, sensorimotor cortex and muscle interrelationships in Parkinson's disease

Brain

Dopamine dependency of oscillations between subthalamic nucleus and pallidum in Parkinson's disease

J Neurosci

Dependence of subthalamic nucleus oscillations on movement and dopamine in Parkinson's disease

Brain

The effects of levodopa and ongoing deep brain stimulation on subthalamic beta oscillations in Parkinson's disease

Exp Neurol

Deep brain stimulation can suppress pathological synchronisation in parkinsonian patients

J Neurol Neurosurg Psychiatry

High frequency deep brain stimulation attenuates subthalamic and cortical rhythms in Parkinson's disease

Front Hum Neurosci

Adaptive deep brain stimulation in advanced Parkinson disease

Ann Neurol