Dual threshold neural closed loop deep brain stimulation in Parkinson disease patients

Velisar, Anca; Syrkin-Nikolau, Judy; Blumenfeld, Zack; Trager, Megan H.; Afzal, Muhammad Furqan; Prabhakar, Varsha; Brontë‐Stewart, Helen

doi:10.1016/j.brs.2019.02.020

Cited by 187 publications

(221 citation statements)

References 24 publications

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“…1 The protocol and tests were modified after the inclusion of this patient, who was therefore excluded. Findings have been reported in [17]. 2 This patient was operated in the GPi, and therefore the results were reported separately in [39] 3,4 These randomisation orders belong to the same patient (PD01).…”

Section: Resultsmentioning

confidence: 99%

“…In particular, tremor may be suppressed by the microlesion effect, and the effect, or lack of effect, of stimulation on this symptom thereby masked. However, it is feasible to investigate the utility of aDBS in chronically implanted patients using externalised electrodes [17], and in patients implanted with bidirectional devices [18]. Nevertheless, whether there is additional benefit over cDBS, particularly with respect to side-effects, remains unclear.…”

Section: Introductionmentioning

confidence: 99%

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Acute effects of Adaptive Deep Brain Stimulation in Parkinson’s disease

Piña-Fuentes

Dijk

Zijl

et al. 2019

Preprint

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249 Full text: 2804 Number of figures/tables: 4 Number of references: 39 Abstract Background: Beta-based adaptive Deep Brain Stimulation (aDBS) is effective in Parkinson's disease (PD), when assessed in the immediate post-implantation phase. However, the potential benefits of aDBS in chronically implanted patients, in whom the benefits of the microlesion effect have disappeared, are yet to be assessed. Methods: To determine the effectiveness and side-effect profile of aDBS in PD compared to conventional continuous DBS (cDBS) and no stimulation (NoStim) in the chronically implanted state. 13 PD patients undergoing battery replacement were pseudo-randomised in a crossover fashion, into three conditions (NoStim, aDBS or cDBS). Patient videos were blindly evaluated using a short version of the Unified Parkinson's Disease Rating Scale (subUPDRS) and the Speech Intelligibility Test (SIT). Results: Patients had a mean disease duration of 16 years, and the mean time since DBS implantation was 6.9 years. subUPDRS scores (11 patients tested) were significantly lower both in aDBS (p=<.001), and cDBS (p=.001), when compared to NoStim. Bradykinesia subscores were significantly lower in aDBS (p=.002), but not in cDBS (p=.08), when compared to NoStim. SIT scores of patients with stimulation-induced dysarthria (11 patients tested) significantly worsened in cDBS (p=.009), but not in aDBS (p=.407), when compared to NoStim. Overall, stimulation was applied 48.8% of the time during aDBS. Conclusion: Beta oscillations remain informative of the clinical state in patients with advanced PD, after several years of DBS implantation. Beta-based aDBS is as effective as cDBS for PD in chronically implanted patients, but delivers less stimulation, and has a more favourable speech side-effect profile.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Acute effects of Adaptive Deep Brain Stimulation in Parkinson’s disease

Piña-Fuentes

Dijk

Zijl

et al. 2019

Preprint

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“…This growing body of evidence supports the hypothesis that longer duration beta bursts in subcortical structures, equating to longer periods of beta oscillations and synchrony, represent pathological or impaired sensorimotor processing in Parkinson's disease (Anidi et al, 2018;Cagnan et al, 2019;Deffains et al, 2018;Lofredi et al, 2019b;Tinkhauser et al, 2018Tinkhauser et al, , 2017aTinkhauser et al, , 2017b and that one mechanism of STN DBS is to remove pathological sensorimotor network processing, while leaving intact normal physiological processing (Anidi et al, 2018;Holt et al, 2019;Tinkhauser et al, 2017a;Torrecillos et al, 2018). The discovery that averaged beta band power was attenuated during increasing intensities of DBS led to its successful use as the control variable in closed loop DBS studies Eusebio et al, 2011;Little et al, 2016aLittle et al, , 2016bLittle et al, , 2013Piña-Fuentes et al, 2019Rosa et al, 2017Rosa et al, , 2015Syrkin-Nikolau et al, 2017;Velisar et al, 2019;Whitmer et al, 2012). Similarly, the accumulating evidence suggests that beta burst duration will be a functionally relevant, patient specific control variable for closed loop DBS.…”

Section: Beta Burst Duration As a Biomarker Of The Efficacy Of Therapmentioning

confidence: 72%

“…Physiological neural activity consists of short duration (40 -120 ms) neuronal oscillations and synchrony that represent normal signal processing in the sensorimotor network (Courtemanche et al, 2003;Feingold et al, 2015;Fetz, 1996, 1992). Elevated power above the physiological 1/f spectrum within the alpha/beta band represents an averaged measure of a state of higher probability of exaggerated neuronal oscillations and neural synchrony, which are pathophysiological markers of the hypokinetic state in Parkinson's disease (PD) (Anidi et al, 2018;Bergman et al, 1994;Brown, 2003;Deffains et al, 2018;Hammond et al, 2007;Kühn et al, 2008Kühn et al, , 2006Velisar et al, 2019;Whitmer et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

A Novel Method for Calculating Beta Band Burst Durations in Parkinson’s Disease Using a Physiological Baseline

Anderson

Neuville

Kehnemouyi

et al. 2020

Preprint

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Parkinson's disease, Deep Brain Stimulation HighlightsA novel method for measuring variability in subthalamic local field potential oscillations in Parkinson's disease using a physiological baseline of power.Modeling normal brain activity using a physiological 1/f spectrum.Burst durations depend on choice of bandwidth and center frequency.Defining an inert frequency band whose mean burst duration overlap the physiological 1/f spectrum, from which the baseline was determined.Burst durations progressively shortened during increasing intensities of deep brain stimulation. ABSTRACT BackgroundPathological bursts of neural activity in Parkinson's disease present as exaggerated subthalamic neuronal oscillations in the 8-30 Hz frequency range and are related to motor impairment. New MethodThis study introduces a novel method for determining burst dynamics using a baseline that matches physiological 1/f spectrum activity. We used resting state local field potentials from people with Parkinson's disease and a simulated 1/f signal to measure beta burst durations, to demonstrate how tuning parameters (i.e., bandwidth and center frequency) affect burst durations, to compare this with high power threshold methods, and to study the effect of increasing neurostimulation intensities on burst duration. ResultsBurst durations calculated using the Anderson method captured the longest and broadest distribution of burst durations in a pathological beta band compared to previous methods. Mean beta band burst durations were significantly shorter on compared to off neurostimulation (p = 0.011), and their distribution was shifted towards that of the physiological 1/f spectrum during increasing intensities of stimulation. Comparison with Existing MethodExisting methods of measuring local field potential power either lack temporal specificity to detect bursts (power spectral density diagrams and spectrograms) or include only higher power bursts and portions of the neural signal. ConclusionsWe suggest that this novel method is well suited to quantify the full range of fluctuations in beta band neural activity in the Parkinsonian brain. This method may reveal more relevant feedback biomarkers than averaged beta band power for future closed loop algorithms.

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“…A promising approach to minimize those side-effects is to reduce the stimulation time using a closed-loop system, in which the stimulation parameters are adapted in real-time based on biomarkers reflecting the clinical state of the patient. One of such biomarkers for closed-loop deep brain stimulation (CLDBS) is the level of beta frequency (~13-30 Hz) activity in the subthalamic nucleus (STN) of PD patients (Little et al, 2013;Yamamoto et al, 2013;Arlotti et al, 2018;Velisar et al, 2019), which has been shown to correlate with the severity of motor symptoms (Neumann et al, 2016;Martin et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Beta-driven closed-loop deep brain stimulation can compromise human motor behavior in Parkinson’s Disease

Iturrate

Martin

Chavarriaga

et al. 2019

Preprint

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Closed-loop or adaptive deep brain stimulation (DBS) for Parkinson's Disease (PD) has shown comparable clinical improvements to continuous stimulation, yet with less stimulation times and side effects. In this form of control, stimulation is driven by pathological beta oscillations recorded from the subthalamic nucleus, which have been shown to correlate with PD motor symptoms. An important consideration is that beta activity is itself modulated during volitional movements, yet it is unknown the impact that these volitional modulations may have on the efficacy of closed-loop systems. Here, three PD patients performed a functional reaching task during closed-loop stimulation while we measured their motor behavior. Our results show that closed-loop stimulation can alter motor performance at distinct movement intervals. Of particular relevance, closed-loop DBS compromised behavior during the returning period by increasing the amount of submovements executed, and in turn delayed movement termination. Following these findings, we hypothesize that the use of machine learning decoding different movement intervals to fully switch off the stimulator may be beneficial, and present here an exemplary approach decoding the initiation of the movement returning interval above chance level. These findings highlight the importance of evaluating these systems during functional tasks, and the need of extracting more robust biomarkers encoding ongoing symptoms or tasks execution intervals. Abbreviations: DBS: deep brain stimulation LFP: local field potentials PD: Parkinson's disease STN: subthalamic nucleus LMM: linear mixed model UPDRS: Unified Parkinson's Disease rating scale CLDBS: closed-loop deep brain stimulation AUC: area under the receiver-operating characteristic curve

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Dual threshold neural closed loop deep brain stimulation in Parkinson disease patients

Cited by 187 publications

References 24 publications

Acute effects of Adaptive Deep Brain Stimulation in Parkinson’s disease

Acute effects of Adaptive Deep Brain Stimulation in Parkinson’s disease

A Novel Method for Calculating Beta Band Burst Durations in Parkinson’s Disease Using a Physiological Baseline

Beta-driven closed-loop deep brain stimulation can compromise human motor behavior in Parkinson’s Disease

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