Adaptive Deep Brain Stimulation for Movement Disorders: The Long Road to Clinical Therapy

Continuous high-frequency DBS is an established treatment for essential tremor and Parkinson's disease. Current developments focus on trying to widen the therapeutic window of DBS. Adaptive DBS (aDBS), where stimulation is dynamically controlled by feedback from biomarkers of pathological brain circuit activity, is one such development. Relevant biomarkers may be central, such as local field potential activity, or peripheral, such as inertial tremor data. Moreover, stimulation may be directed by the amplitude or the phase (timing) of the biomarker signal. In this review, we evaluate existing aDBS studies as proof-of-principle, discuss their limitations, most of which stem from their acute nature, and propose what is needed to take aDBS into a chronic setting. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Societ

Local field potential activity dynamics in response to deep brain stimulation of the subthalamic nucleus in Parkinson's disease.

Local field potentials (LFPs) may afford insight into the mechanisms of action of deep brain stimulation (DBS) and potential feedback signals for adaptive DBS. In Parkinson's disease (PD) DBS of the subthalamic nucleus (STN) suppresses spontaneous activity in the beta band and drives evoked resonant neural activity (ERNA). Here, we investigate how STN LFP activities change over time following the onset and offset of DBS. To this end we recorded LFPs from the STN in 14 PD patients during long (mean: 181.2 s) and short (14.2 s) blocks of continuous stimulation at 130 Hz. LFP activities were evaluated in the temporal and spectral domains. During long stimulation blocks, the frequency and amplitude of the ERNA decreased before reaching a steady state after ~70 s. Maximal ERNA amplitudes diminished over repeated stimulation blocks. Upon DBS cessation, the ERNA was revealed as an under-damped oscillation, and was more marked and lasted longer after short duration stimulation blocks. In contrast, activity in the beta band suppressed within 0.5 s of continuous DBS onset and drifted less over time. Spontaneous activity was also suppressed in the low gamma band, suggesting that the effects of high frequency stimulation on spontaneous oscillations may not be selective for pathological beta activity. High frequency oscillations were present in only six STN recordings before stimulation onset and their frequency was depressed by stimulation. The different dynamics of the ERNA and beta activity with stimulation imply different DBS mechanisms and may impact how these activities may be used in adaptive feedback

Mechanisms Underlying Decision-Making as Revealed by Deep-Brain Stimulation in Patients with Parkinson's Disease

To optimally balance opposing demands of speed and accuracy during decision-making, we must flexibly adapt how much evidence we require before making a choice. Such adjustments in decision thresholds have been linked to the subthalamic nucleus (STN), and therapeutic STN deep-brain stimulation (DBS) has been shown to interfere with this function. Here, we performed continuous as well as closed-loop DBS of the STN while Parkinson’s disease patients performed a perceptual decision-making task. Closed-loop STN DBS allowed temporally patterned STN stimulation and simultaneous recordings of STN activity. This revealed that DBS only affected patients’ ability to adjust decision thresholds if applied in a specific temporally confined time window during deliberation. Only stimulation in that window diminished the normal slowing of response times that occurred on difficult trials when DBS was turned off. Furthermore, DBS eliminated a relative, time-specific increase in STN beta oscillations and compromised its functional relationship with trial-by-trial adjustments in decision thresholds. Together, these results provide causal evidence that the STN is involved in adjusting decision thresholds in distinct, time-limited processing windows during deliberation

Balance between competing spectral states in subthalamic nucleus is linked to motor impairment in Parkinson's disease

Exaggerated bursts of activity at frequencies in the low beta band are a well-established phenomenon in the subthalamic nucleus (STN) of patients with Parkinson's disease. However, such activity is only moderately correlated with motor impairment. Here we test the hypothesis that beta bursts are just one of several dynamic states in the STN local field potential (LFP) in Parkinson's disease, and that together these different states predict motor impairment with high fidelity. LFPs were recorded in 32 patients (64 hemispheres) undergoing deep brain stimulation surgery targeting the STN. Recordings were performed following overnight withdrawal of anti-parkinsonian medication, and after administration of levodopa. LFPs were analysed using Hidden Markov Modelling to identify transient spectral states with frequencies under 40 Hz. Findings in the low beta frequency band were similar to those previously reported; levodopa reduced occurrence rate and duration of low beta states, and the greater the reductions, the greater the improvement in motor impairment. However, additional LFP states were distinguished in the theta, alpha and high beta bands, and these behaved in an opposite manner. They were increased in occurrence rate and duration by levodopa, and the greater the increases, the greater the improvement in motor impairment. In addition, levodopa favoured the transition of low beta states to other spectral states. When all LFP states and corresponding features were considered in a multivariate model it was possible to predict 50% of the variance in patients' hemibody impairment OFF medication, and in the change in hemibody impairment following levodopa. This only improved slightly if signal amplitude or gamma band features were also included in the multivariate model. In addition, it compares with a prediction of only 16% of the variance when using beta bursts alone. We conclude that multiple spectral states in the STN LFP have a bearing on motor impairment, and that levodopa-induced shifts in the balance between these states can predict clinical change with high fidelity. This is important in suggesting that some states might be upregulated to improve parkinsonism and in suggesting how LFP feedback can be made more informative in closed-loop deep brain stimulation systems

The characteristics of pallidal low-frequency and beta bursts could help implementing adaptive brain stimulation in the parkinsonian and dystonic internal globus pallidus

INTRODUCTION: Adaptive deep brain stimulation (aDBS) has been applied in Parkinson’s disease (PD), based on the presence of brief high-amplitude beta (13-35 Hz) oscillation bursts in the subthalamic nucleus (STN), which correlate with symptom severity. Analogously, average low-frequency (LF) oscillatory power (4-12 Hz) in the internal globus pallidus (GPi) correlates with dystonic symptoms and might be a suitable physiomarker for aDBS in dystonia. Characterization of pallidal bursts could facilitate the implementation of aDBS in the GPi of PD and dystonia patients. OBJECTIVE AND METHODS: We aimed to describe the bursting behaviour of LF and beta oscillations in a cohort of five GPi-DBS PD patients and compare their amplitude and length with a cohort of seven GPi-DBS dystonia, and six STN-DBS PD patients (n electrodes = 34). Furthermore, we used the information obtained to set up aDBS and test it in the GPi of both a dystonia and a PD patient (n=2), using either LF (dystonia) or beta oscillations (PD) asfeedback signals. RESULTS: LF and beta oscillations in the dystonic and parkinsonian GPi occur as phasic, short-lived bursts, similarly to the parkinsonian STN. The amplitude profile of such bursts however, differed significantly. Dystonia showed higher LF burst amplitudes, while PD presented higher beta burst amplitudes. Burst characteristics in the parkinsonian GPi and STN were similar. Furthermore, aDBS applied in the GPi was feasible and well tolerated in both diseases. CONCLUSION: Pallidal LF and beta burst amplitudes have different characteristics in PD and dystonia. The presence of increased burst amplitudes could be employed as feedback for GPiaDBS

Subthalamic deep brain stimulation induces finely-tuned gamma oscillations in the absence of levodopa.

Finely-tuned gamma (FTG) oscillations can be recorded from cortex or the subthalamic nucleus (STN) in patients with Parkinson's disease (PD) on dopaminergic medication, and have been associated with dyskinesias. When recorded during deep brain stimulation (DBS) on medication the FTG is entrained to half the stimulation frequency. We investigated whether these characteristics are shared off medication by recording local field potentials (LFP) from the STN from externalised DBS leads in 14 PD patients after overnight withdrawal of medication. FTG was induced de-novo by DBS in the absence of dyskinesias in a third of our cohort. The FTG could outlast stimulation or arise only after DBS ceased. FTG frequencies decreased during and across consecutive DBS blocks, but did not shift with changing stimulation frequency off medication. Together with the sustained after-effects this argues against simple entrainment by DBS in the off medication state. We also found significant coherence between STN-LFP and electroencephalogram (EEG) signals at FTG frequencies. We conclude that FTG is a network phenomenon that behaves differently in the off medication state, when it is neither associated with dyskinesias nor susceptible to entrainment

Subthalamic beta-targeted neurofeedback speeds up movement initiation but increases tremor in Parkinsonian patients

Previous studies have explored neurofeedback training for Parkinsonian patients to suppress beta oscillations in the subthalamic nucleus (STN). However, its impacts on movements and Parkinsonian tremor are unclear. We developed a neurofeedback paradigm targeting STN beta bursts and investigated whether neurofeedback training could improve motor initiation in Parkinson’s disease compared to passive observation. Our task additionally allowed us to test which endogenous changes in oscillatory STN activities are associated with trial-to-trial motor performance. Neurofeedback training reduced beta synchrony and increased gamma activity within the STN, and reduced beta band coupling between the STN and motor cortex. These changes were accompanied by reduced reaction times in subsequently cued movements. However, in Parkinsonian patients with pre-existing symptoms of tremor, successful volitional beta suppression was associated with an amplification of tremor which correlated with theta band activity in STN local field potentials, suggesting an additional cross-frequency interaction between STN beta and theta activities