Toward adaptive deep brain stimulation for dystonia

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The presence of abnormal neural oscillations within the cortico-basal ganglia-thalamo-cortical (CBGTC) network has emerged as one of the current principal theories to explain the pathophysiology of movement disorders. In theory, these oscillations can be used as biomarkers and thereby serve as a feedback signal to control the delivery of deep brain stimulation (DBS). This new form of DBS, dependent on different characteristics of pathological oscillations, is called adaptive DBS (aDBS), and it has already been applied in patients with Parkinson’s disease. In this review, the authors summarize the scientific research to date on pathological oscillations in dystonia and address potential biomarkers that might be used as a feedback signal for controlling aDBS in patients with dystonia.

ABBREVIATIONS AA = agonist-antagonist; aDBS = adaptive deep brain stimulation; CBGTC = cortico-basal ganglia-thalamo-cortical; cDBS = continuous DBS; ECoG = electrocorticography; EEG = electroencephalography; EMG = electromyography; GPi = internal globus pallidus; LFP = local field potential; PD = Parkinson’s disease.

Abstract

The presence of abnormal neural oscillations within the cortico-basal ganglia-thalamo-cortical (CBGTC) network has emerged as one of the current principal theories to explain the pathophysiology of movement disorders. In theory, these oscillations can be used as biomarkers and thereby serve as a feedback signal to control the delivery of deep brain stimulation (DBS). This new form of DBS, dependent on different characteristics of pathological oscillations, is called adaptive DBS (aDBS), and it has already been applied in patients with Parkinson’s disease. In this review, the authors summarize the scientific research to date on pathological oscillations in dystonia and address potential biomarkers that might be used as a feedback signal for controlling aDBS in patients with dystonia.

According to the latest expert consensus, dystonia is clinically defined as “a movement disorder characterized by sustained or intermittent muscle contractions causing abnormal, often repetitive, movements, postures, or both.”2 Dystonia can be caused by numerous etiologies, including acquired and different biochemical, cellular, or genetic substrates. The similarity of the clinical dystonia phenotype, however, suggests a unifying common pathophysiological pathway at a functional or network level.4 A currently leading hypothesis on its neurophysiological basis is that dystonia is the result of abnormal activity in cortico-basal ganglia-thalamo-cortical (CBGTC) and cerebellar networks.52 The treatment for the majority of dystonia subtypes only provides symptomatic relief, without addressing the underlying cause of the disease. Options currently available include oral medication (e.g., anticholinergic and antidopaminergic drugs, benzodiazepines, and baclofen), botulinum toxin (treatment of choice in focal dystonias), and deep brain stimulation (DBS).4

DBS in Dystonia

Given the limited efficacy and high prevalence of adverse effects associated with oral medication in generalized dystonia, DBS of the internal globus pallidus (GPi) has become the preferred therapy in this patient group.4 Several randomized controlled trials have demonstrated a sustained improvement in patients with (isolated) generalized dystonia following DBS, as shown by lower motor and functional scores on the Burke-Fahn-Marsden dystonia rating scale.29 After 5 years of DBS, generalized dystonia is reported to show a reduction in the Burke-Fahn-Marsden dystonia rating scale score of 42%–61%.8 Furthermore, the health-related quality of life after DBS for dystonia improves significantly, by about 24%–51%, among several independent trials.27 DBS therapy has also been utilized in other types of dystonia when an adequate response to botulinum toxin therapy could not be achieved.24 A large, randomized clinical trial demonstrated that DBS is useful in medication-refractory cervical dystonia compared to sham stimulation, with a significant improvement of the Toronto Western Spasmodic Torticollis Rating Scale severity score (26% vs 6%, respectively), 3 months after implantation.73

Despite its good effect, the exact mechanism of DBS in dystonia remains unclear,10 and clinical outcomes can differ from patient to patient, as well as among different subtypes of dystonia.8 Patients at an early stage of the disease and with less disability usually respond better to DBS. This is especially the case in patients with DYT1 mutations and tardive dystonia. In contrast, the response in other types of dystonia is less predictable, which makes the selection of appropriate candidates for DBS challenging.3

Drawbacks of Current (Continuous) DBS

More than 15 years of experience with DBS in dystonia has demonstrated the efficacy of the current model of continuous DBS (cDBS) once the optimal stimulation parameters have been achieved.41 Nevertheless, there are still limitations in terms of efficacy and side effects related to cDBS. Due to limited knowledge of CBGTC and cerebellar networks in dystonia, the modification of electrical stimulation parameters in DBS is essentially heuristic, and DBS programming is based on clinical records and examination. In this process, the clinician starts with the conventional initial settings of the DBS system, delivering a constant current or voltage through the selected electrode(s). The settings are then adjusted in a trial-and-error process, based on the clinical response and the absence of adverse effects.50 However, an immediate response is often not possible to achieve, since it generally takes weeks to months to notice a perceptible change, especially in tonic dystonic components.53 For this reason, it can take up to several weeks to modify the initial parameters.30 In general, significant improvement can be expected approximately 3 months after the surgery, but it usually takes up to a year to achieve the maximum clinical effect.41 Another technical problem is the voltage required for stimulation in dystonia. While a mean of 3.0 V is usually effective to obtain an adequate clinical response in Parkinson’s disease (PD) patients, with electrodes implanted either in the GPi or the subthalamic nucleus,47 the effective voltage in dystonia is more variable. It depends, among other things, on the type of dystonia, the area of the body affected, and the patient’s tolerance of high voltages (due to the subsequent emergence of stimulation-related side effects), ranging from 2.2 up to 7.0 V.28 Therefore, non-rechargeable batteries need to be replaced more often, with a mean longevity of 28.1 months for dystonia compared with 47.2 months for PD.53 This not only increases the treatment costs, but it also exposes the patient to more surgical procedures, as well as their attendant risks.

Finally, there are significant side effects induced by cDBS in dystonia patients, such as dysarthria (in up to 12%)29 and parkinsonism (13%).70 Among patients with cranial-cervical dystonia treated with GPi DBS, 90% reported at least one motor symptom associated with parkinsonism, such as handwriting problems, difficulty with standing up from a chair, and gait disturbances.7 In line with this, a correlation has been described between the increase in GPi stimulation frequency and the development of bradykinesia.26

The appearance of these side effects after stimulation suggests that DBS interferes with both pathological activity in the CBGTC circuits39 and physiological activity that helps to control voluntary movements.9,29

To improve efficacy and limit side effects, much effort has been put into developing DBS systems that only stimulate when pathological activity and clinical symptoms are present.39 Future DBS devices might be able to deliver electrical stimulation in response to pathological oscillations by increasing electrical current on demand—that is, only when, for example, the oscillatory power exceeds a threshold.46 This adaptive form of DBS (aDBS) has already been successfully applied in nonhuman primate models of PD56 by using the occurrence of cortical spikes as a biomarker. In patients with PD, there is also evidence of the effectiveness of aDBS.32,34,51,55 In these studies, the power of subcortical beta (13–30 Hz) oscillations, which correlate with bradykinesia and rigidity in PD,54 was used as a biomarker. The most important positive effects of human aDBS studies in PD were increased efficacy, energy-saving properties, and potentially fewer side effects. This line of evidence strongly suggests that pathological oscillations can successfully be used as a biomarker for controlling DBS.

Preparing the Way for aDBS in Dystonia

Neural Oscillations as Biomarker

Neural oscillations are part of the physiological components present in the regulatory pathways of voluntary movements and are potentially a means by which neuronal structures communicate among one another and with muscular units.61 The relationship of oscillations between two different sources can be addressed by means of coherence analysis, which indicates the degree of mutual dependence.12 Experiments carried out in healthy subjects have shown an increased coherence between cortical beta activity (13–30 Hz) and contralateral muscle discharges, respectively recorded with electroencephalography (EEG) and electromyography (EMG), suggesting that voluntary contractions are coupled with the physiological oscillatory activity of cortical neurons.12,60

In certain movement disorders, this physiological oscillatory activity is thought to be altered, since abnormal (pathological) oscillatory profiles have been detected.5,18,43 The use of subcortical beta oscillations as a biomarker for aDBS in PD was motivated by recordings of synchronized activity of large populations of neurons in the basal ganglia, known as local field potentials (LFPs). These LFPs can be recorded from the same DBS electrode contacts that deliver electrical stimulation. During a recording, LFPs are rapidly processed, and changes in power on a selected frequency band (e.g., beta range) are detected through spectral analysis. The increase in frequency power triggers DBS in PD, which is continued until the power drops below a selected threshold.25

One of the lessons learned from aDBS in PD patients is that the feedback signal of a biomarker needs to be both sensitive and specific. This means that the biomarker should correlate well in time with the severity of clinical symptoms (specificity)33 and that the signal detected should be powerful enough to be differentiated from artifacts—e.g., the noise caused by the stimulation itself (sensitivity).57

Neural Oscillations in Isolated (Primary) Dystonia

As discussed above, increased beta oscillations have been found in patients with PD and used as a biomarker for aDBS. To answer the question of whether it is possible to transfer aDBS from PD to dystonia, it is necessary to identify biomarkers for the latter (Fig. 1, Table 1). Several studies have addressed the presence of (pathological) oscillations in patients with isolated dystonia. LFP recordings have shown increased power in low frequencies (4–12 Hz) in dystonia patients.64 Chen et al. demonstrated a positive correlation between pallidal low-frequency oscillations and muscle (EMG) activity in dystonia patients that was consistent among all contact pairs of the tested DBS-electrodes.9 In the same experiment, an additional correlation was found in the beta range (13–30 Hz), but this was not consistent among different contact pairs. Abnormal low-frequency oscillations have not only been found between GPi and EMG, but also in LFPs recorded in the subthalamic nucleus of dystonia patients17,45 and between different EMG signals.69 Directed transfer analyses suggest that this excessive oscillatory GPi activity is mostly driven from the GPi to the affected muscles.62

Fig. 1.
Fig. 1.

Potential interface for aDBS using low-frequency oscillations. In this figure, the presence of low-frequency oscillations on an LFP is visualized and used for an adaptive stimulation algorithm. Raw signals (LFP L and R) are dynamically recorded and filtered around the low-frequency peak registered (FILT LFP L and R). Afterwards, the filtered signal would be rectified, and an amplitude threshold would be set, in order to trigger the stimulation (STIM L and R) every time that an increment in low-frequency activity is detected. A brief delay in the activation of the stimulation would ensure that the stimulation is triggered only by actual increments of low-frequency activity and not by short-lived artifacts. AMP ENV = amplitude envelope of the rectified filtered signal; FILT LFP = LFP filtered around the low-frequency peak detected in order to visualize low-frequency oscillations embedded in the signal; L = left; R = right; STIM = channels representing stimulation amplitude.

TABLE 1.

Potential biomarkers for aDBS in dystonia with their advantages, disadvantages, and challenges

BiomarkerAdvantagesDisadvantagesFurther Questions
I. GPI LFPs of 4- to 12-Hz magnitude/spectral powerMost-studied oscillations. Correlated w/ phasic dystonia. Direct measurement of pathological network activityNot correlated w/ tonic dystonia. Noise generated by stimulation might interfereEvaluate the adequacy of the biomarker
II. Muscle activity (EMG) 4- to 12-Hz magnitude/spectral powerCoherent w/ LFPs. Direct measurement of dystonic activityAdditional device required for EMGInvestigate applicability of subcutaneous EMG in aDBS
III. Dystonic tremor (EMG) 4- to 12-Hz magnitude/spectral powerPotentially useful if tremor is the predominant symptom. Direct measurement of a clinical symptomNonspecific biomarkerDevelop algorithms capable of increased specificity in detection of dystonic tremor
IV. ECoG 4- to 12-Hz spectral powerPotential alternative for aDBS use. High signal amplitude & less stimulation interferenceSubdural electrodes needed to be placed. Still at an early phaseElucidate which ECoG biomarkers could be used as a feedback for aDBS
V. Coherence between biomarkers (e.g., LFP-EMG)Correlates two different sources of pathological oscillationsAt least two different devices are required. Lower temporal resolutionExamine whether coherence estimation is sufficiently fast for adaptive stimulation
VI. EMG AA ratio/sumIdentifies when dystonic activity is present. Good time resolutionAt least two different devices are required. Nonspecific. Not predictive (rather reactive)Explore possibilities of using this statistic to increase the specificity & time resolution of aDBS biomarkers

Common to all biomarkers is the need to establish their robustness across time and their reliability during brain states like sleep.

Furthermore, a sensorimotor modulation of GPi LFPs has been observed in response to active and passive movements, with a decreased LFP synchronization at 8–20 Hz and in dystonic involuntary muscle spasms with an increased activity in the range of 3–18 Hz.35 This modulation of LFPs has also been observed in patients with an effective sensory trick (directing actions or movements to a specific part of their bodies where dystonia is present in order to alleviate their symptoms2).67 In these patients, a suppression of the abnormally synchronized activity in the range of 6–8 Hz and beta bands was observed during the performance of the sensory trick, indicating a peripheral regulation of the CBGCT oscillations. In summary, information from peripheral stimuli also influences the behavior of neural oscillations, at least to a certain degree.

A major finding that directly supports the use of low-frequency (4- to 12-Hz) oscillations as a biomarker for dystonia was described by Barow et al.5 In this study, increased low-frequency oscillations recorded from DBS electrodes of dystonia patients were significantly suppressed at the moment DBS was switched on, and they reemerged after stimulation was switched off. Additionally, increased coherence from EEG LFPs and EMG LFPs within the 4- to 12-Hz range was reduced after DBS stimulation. Another study showed that increased low-frequency activity in the cortex is normalized after applying DBS.40 These findings indicate that the application of high-frequency GPi DBS modulates the abnormally increased low-frequency activity. For these reasons, a paradigm for aDBS in dystonia based on the level of low-frequency oscillations seems plausible (Fig. 2).

Fig. 2.
Fig. 2.

Potential biomarkers and recording sites. Dystonic brain activity (A) (e.g., increased low-frequency oscillations) can be recorded either in the form of local field potentials—from the electrodes used for stimulation or from electrodes placed on the cortical surface of the brain (electrocorticography) (1). Dystonic muscle activity (B) can be recorded either from subcutaneous EMG (2) or through wearable devices (3), which could also detect dystonic tremor (C), thanks to integrated accelerometers. Signals can be instantaneously processed in the battery (4), to modulate stimulation according to the biomarker selected (to visualize a stimulation algorithm [see Fig. 1]). Copyright Dan Piña-Fuentes. Published with permission.

The studies mentioned so far in this section included a varying degree of patients with different types of local, segmental, and generalized forms of isolated dystonia (both sporadic and genetic/familial) in their cohorts. For that reason, the specific roles of low-frequency oscillations in each form of isolated dystonia are currently unclear. Recently, a study that only included patients with cervical dystonia showed that the power of low-frequency oscillations in the dystonic GPi positively correlates with Toronto Western Spasmodic Torticollis Rating Scale scores, and an increased coherence is present between dystonic GPi and EMG signals in the low-frequency band.44 This gives a rationale for the employment of low-frequency oscillations as a biomarker for aDBS in this particular group.

Although several comparative studies have found increased subcortical low-frequency activity to be a characteristic of dystonia when compared to PD,17,64,75 this has not always been replicated.65,68,74 The co-occurrence of dystonia and PD might, at least partially, explain this phenomenon.71 However, the exact role of (pathological) low-frequency oscillations in dystonia is yet to be clarified.

Neural Oscillations in Other Types of Dystonia

Although virtually all neurophysiological studies described above have been carried out in patients with diverse forms of isolated dystonia, some studies have shown similar results for increased low-frequency oscillations in other subtypes of dystonia, indicating at least a partially shared common pathophysiology for all of them. Prominent 5- to 18-Hz oscillations from the GPi and thalamus were recorded in a patient with acquired dystonia secondary to a cryptogenic stroke.72 Furthermore, studies based on LFP EMG and EMG-EMG coherence analysis have found an increased abnormal coherence in the low-frequency range in patients with myoclonus-dystonia.15,16 These findings suggest that another potential biomarker to modulate the intensity of aDBS could include the low-frequency common drive to motor units detected through EMG; detection of this could be technically possible thanks to the development of subcutaneous EMG registers that can transmit the information wirelessly to the DBS generator.38,59

Phasic and Tonic Components of Dystonia

While dystonia is usually composed of tonic (sustained) and phasic (rhythmic) abnormal movements,2 increased low-frequency oscillations have only, thus far, been correlated with the phasic components of dystonia,36,44 including the reduction of such abnormal oscillations after cDBS.5 With conventional cDBS, the clinical improvement of phasic and tonic components differs in time; phasic components improve faster (sometimes even immediately) following the application of DBS, whereas improvement in tonic components can take weeks to months.11 In contrast, when discontinuing stimulation, phasic components can recur rapidly, while tonic components recur in a more gradual manner.19 This temporal dissociation leads to the hypothesis that different pathophysiological mechanisms are involved.1 The rapid improvement seen in the phasic components is thought to be due to a direct DBS effect, whereas changes in tonic components are attributed to stimulation effects on neuronal plasticity.22 It has been observed that the benefits of DBS may remain after stimulation is discontinued, even after the 1-year follow-up period.20,58,66 This could imply that DBS produces a series of readjustments in CBGTC and cerebellar networks that persist after stimulation has ceased. It remains to be elucidated how aDBS might influence the tonic components of dystonia.

Dystonic Tremor

A specific component of phasic dystonia in which aDBS might be considered is the presence of dystonic tremor. The prevalence of tremor in patients with dystonia varies from 11% to 87% among studies.14 Lee et al. contrasted data of patients with task-specific primary bowing tremor (a task-specific tremor especially occurring in string musicians) with data obtained in matched healthy controls, revealing coherence between the coactivation of wrist antagonist muscles (measured with EMG) and tremor fluctuation (measured with accelerometers on the metacarpal-phalangeal joint of the index finger) in the low-frequency range only in the patient group.31 Whereas this might indicate an influence of the dystonic oscillatory activity in dystonic tremor, more studies are required to elucidate this relationship. At present, when the tremor is the most disabling symptom,21 the ventral intermediate/lateral thalamus is used as a primary target in dystonia patients.42

In a recent study, patients had an improvement of 77% on clinical tremor scales after DBS of the ventrolateral thalamus.49 However, significant side effects also occurred, which raises the question of whether aDBS based on tremor amplitude/phase could be an alternative. However, at this moment, the assessment of tremor using current accelerometers is still nonspecific, owing to the difficulties in distinguishing accelerometer signals resultant from voluntary movements. Advanced tremor-specific accelerometer computation paradigms to treat patients with PD are currently being explored,37 so in theory similar devices to assess dystonic tremor might be applied in the future.63

Electrocorticography

Electrocorticography (ECoG) recording is another neurophysiological tool that might be considered for aDBS. It uses electrodes implanted in the subdural space, giving a powerful spatial resolution of local cortical activity. One of the first ECoG studies on movement disorders used this technique to measure cortical LFPs in patients with PD, essential tremor, and (cranio-)cervical dystonia.13 In the resting state, the authors found a peak in motor cortex LFPs that occurred in the high-beta band for PD and in the low-beta band for dystonia and essential tremor. They also found an impaired cortical beta desynchronization related to movement, present in both motor and somatosensory areas. Low-frequency oscillations (4–12 Hz) were not analyzed in this study due to roll-off interference of the high-pass filter in the recordings. Recently, the utility of ECoG to measure neural oscillations in the CBGCT network was addressed in a series of 189 patients (200 recordings) with movement disorders undergoing DBS surgery.48 Some of the advantages of ECoG mentioned included higher-amplitude signaling, less DBS noise interference, and potentially a safe clinical profile (no significant adverse events added to the DBS procedure were reported in this study). These findings give rise to the potential use of ECoG to further investigate oscillations within the CBGTC network and, ultimately, find a potential biomarker for aDBS.

Temporal Dynamics of Prospective Biomarkers

One of the main questions that need to be answered before implementing aDBS in dystonia is what the temporal characteristics of the selected biomarker are. The latency and duration of the biomarkers mentioned (e.g., GPi-LFPs), and how fast they react to electrical stimulation, should be investigated to determine how the aDBS system must be programmed and how well it can anticipate rather than react to the appearance of symptoms.

Combining Neurophysiological Techniques

In addition to single signals, the relation between oscillatory activity at two different sources, by means of coherence and/or other statistics might be used for aDBS. For example, LFP-EMG coherence or the EMG agonist-antagonist (AA) ratio might provide a more informative biomarker than a single-site recording. As mentioned before, increased coherence between LFP-EMG and EMG-EMG has been correlated with the severity of dystonic contractions.15,16 In relation to this, aDBS might be programmed based on the volatility in coherence. Nevertheless, to perform a “real-time” coherence analysis, the original signal has to be estimated over a finite period of time, limiting temporal resolution.

Besides coherence, other indicators of dystonic muscle activity can be obtained from EMG. This is based on the evidence that the co-contraction and overflow of AA muscles have been found on EMG measurements of dystonic patients.6 However, at present, an AA sum or AA ratio is not yet specific enough to differentiate signals of pathological contractions from voluntary contractions.23 In the future, evaluation of the predictive value of combined signals through machine learning may lead to greater specificity.

Conclusions

After years of successful application in dystonia, the potential of cDBS is still limited in terms of efficacy, side effects, and efficiency. Next to this, the current lack of neurophysiological parameters that can predict the individual clinical response of dystonia to DBS makes programming difficult. For these reasons, improvements in knowledge about the neurophysiological alterations underpinning dystonia and the emergence of DBS devices capable of simultaneously recording neural activity and providing stimulation should allow aDBS to be developed for the treatment of dystonia in the future. At present, 4- to 12-Hz LFP oscillations appear to be the most promising candidate, but other neurophysiological signals (e.g., those from EMG and ECoG) and their interactions might also be suitable. However, many questions remain, such as the effects of microlesion effects, sleep, and medication on DBS recordings. Regardless of the source of the biomarker or biomarkers selected for aDBS, their volatility and robustness over time will have to be established. Critical too, most of the potential biomarkers described here relate to phasic aspects of dystonia, and therefore the more delayed response of more tonic dystonic elements to aDBS remains to be established.

Acknowledgments

We would like to thank Prof. Peter Brown for his advice.

This review was carried out thanks to public funds received from the Dutch Brain Foundation (Hersenstichting Nederland), the National Mexican Council of Science and Technology (CONACYT), and the University of Groningen/University Medical Center Groningen (RuG/UMCG).

S.L. is personally supported by the Wellcome Trust (105804/Z/14/Z).

Disclosures

The authors report no conflict of interest concerning the materials or methods used in this study or the findings specified in this paper.

Author Contributions

Conception and design: Piña-Fuentes, Beudel. Drafting the article: Piña-Fuentes, Beudel. Critically revising the article: Piña-Fuentes, Beudel, Little, van Dijk, Tijssen. Reviewed submitted version of manuscript: all authors. Approved the final version of the manuscript on behalf of all authors: Piña-Fuentes. Administrative/technical/material support: Piña-Fuentes. Study supervision: Beudel.

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    Miocinovic SSomayajula SChitnis SVitek JL: History, applications, and mechanisms of deep brain stimulation. JAMA Neurol 70:1631712013

  • 42

    Morishita TFoote KDHaq IUZeilman PJacobson CEOkun MS: Should we consider Vim thalamic deep brain stimulation for select cases of severe refractory dystonic tremor. Stereotact Funct Neurosurg 88:981042010

  • 43

    Neumann WJDegen KSchneider GHBrücke CHuebl JBrown P: Subthalamic synchronized oscillatory activity correlates with motor impairment in patients with Parkinson’s disease. Mov Disord 31:174817512016

  • 44

    Neumann WJHorn AEwert SHuebl JBrücke CSlentz C: A localized pallidal physiomarker in cervical dystonia. Ann Neurol 82:9129242017

  • 45

    Neumann WJHuebl JBrücke CRuiz MHKupsch ASchneider GH: Enhanced low-frequency oscillatory activity of the subthalamic nucleus in a patient with dystonia. Mov Disord 27:106310662012

  • 46

    Neumann WJStaub FHorn ASchanda JMueller JSchneider GH: Deep brain recordings using an implanted pulse generator in Parkinson’s disease. Neuromodulation 19:20242016

  • 47

    Odekerken VJJvan Laar TStaal MJMosch AHoffmann CFENijssen PCG: Subthalamic nucleus versus globus pallidus bilateral deep brain stimulation for advanced Parkinson’s disease (NSTAPS study): a randomised controlled trial. Lancet Neurol 12:37442013

  • 48

    Panov FLevin Ede Hemptinne CSwann NCQasim SMiocinovic S: Intraoperative electrocorticography for physiological research in movement disorders: principles and experience in 200 cases. J Neurosurg 126:1221312017

  • 49

    Pauls KAMHammesfahr SMoro EMoore APBinder EEl Majdoub F: Deep brain stimulation in the ventrolateral thalamus/subthalamic area in dystonia with head tremor. Mov Disord 29:9539592014

  • 50

    Picillo MLozano AMKou NMunhoz RPFasano A: Programming deep brain stimulation for tremor and dystonia: the Toronto Western Hospital algorithms. Brain Stimul 9:4384522016

  • 51

    Piña-Fuentes DLittle SOterdoom MNeal SPogosyan ATijssen MAJ: Adaptive DBS in a Parkinson’s patient with chronically implanted DBS: A proof of principle. Mov Disord 32:125312542017

  • 52

    Prudente CNHess EJJinnah HA: Dystonia as a network disorder: what is the role of the cerebellum? Neuroscience 260:23352014

  • 53

    Rawal PVAlmeida LSmelser LBHuang HGuthrie BLWalker HC: Shorter pulse generator longevity and more frequent stimulator adjustments with pallidal DBS for dystonia versus other movement disorders. Brain Stimul 7:3453492014

  • 54

    Ray NJJenkinson NWang SHolland PBrittain JSJoint C: Local field potential beta activity in the subthalamic nucleus of patients with Parkinson’s disease is associated with improvements in bradykinesia after dopamine and deep brain stimulation. Exp Neurol 213:1081132008

  • 55

    Rosa MArlotti MArdolino GCogiamanian FMarceglia SDi Fonzo A: Adaptive deep brain stimulation in a freely moving Parkinsonian patient. Mov Disord 30:100310052015

  • 56

    Rosin BSlovik MMitelman RRivlin-Etzion MHaber SNIsrael Z: Closed-loop deep brain stimulation is superior in ameliorating parkinsonism. Neuron 72:3703842011

  • 57

    Rossi LFoffani GMarceglia SBracchi FBarbieri SPriori A: An electronic device for artefact suppression in human local field potential recordings during deep brain stimulation. J Neural Eng 4:961062007

  • 58

    Ruge DCif LLimousin PGonzalez VVasques XCoubes P: Longterm deep brain stimulation withdrawal: clinical stability despite electrophysiological instability. J Neurol Sci 342:1971992014

  • 59

    Ryapolova-Webb EAfshar PStanslaski SDenison Tde Hemptinne CBankiewicz K: Chronic cortical and electromyographic recordings from a fully implantable device: preclinical experience in a nonhuman primate. J Neural Eng 11:0160092014

  • 60

    Salenius SPortin KKajola MSalmelin RHari R: Cortical control of human motoneuron firing during isometric contraction. J Neurophysiol 77:340134051997

  • 61

    Schoffelen JMOostenveld RFries P: Neuronal coherence as a mechanism of effective corticospinal interaction. Science 308:1111132005

  • 62

    Sharott AGrosse PKühn AASalih FEngel AKKupsch A: Is the synchronization between pallidal and muscle activity in primary dystonia due to peripheral afferance or a motor drive? Brain 131:4734842008

  • 63

    Shukla PBasu ITuninetti D: Towards closed-loop deep brain stimulation: decision tree-based essential tremor patient’s state classifier and tremor reappearance predictor. Conf Proc IEEE Eng Med Biol Soc 2014:260526082014

  • 64

    Silberstein PKühn AAKupsch ATrottenberg TKrauss JKWöhrle JC: Patterning of globus pallidus local field potentials differs between Parkinson’s disease and dystonia. Brain 126:259726082003

  • 65

    Starr PARau GMDavis VMarks WJJ JrOstrem JLSimmons D: Spontaneous pallidal neuronal activity in human dystonia: comparison with Parkinson’s disease and normal macaque. J Neurophysiol 93:316531762005

  • 66

    Stavrinou LCBoviatsis EJStathis PLeonardos APanourias IGSakas DE: Sustained relief after discontinuation of DBS for dystonia: implications for the possible role of synaptic plasticity and cortical reorganization. J Neurol Surg A Cent Eur Neurosurg 73:1751782012

  • 67

    Tang JKHMahant NCunic DChen RMoro ELang AE: Changes in cortical and pallidal oscillatory activity during the execution of a sensory trick in patients with cervical dystonia. Exp Neurol 204:8458482007

  • 68

    Tang JKHMoro EMahant NHutchison WDLang AELozano AM: Neuronal firing rates and patterns in the globus pallidus internus of patients with cervical dystonia differ from those with Parkinson’s disease. J Neurophysiol 98:7207292007

  • 69

    Tijssen MAMarsden JFBrown P: Frequency analysis of EMG activity in patients with idiopathic torticollis. Brain 123:6776862000

  • 70

    Tisch SZrinzo LLimousin PBhatia KPQuinn NAshkan K: Effect of electrode contact location on clinical efficacy of pallidal deep brain stimulation in primary generalised dystonia. J Neurol Neurosurg Psychiatry 78:131413192007

  • 71

    Tolosa ECompta Y: Dystonia in Parkinson’s disease. J Neurol 253 (Suppl 7):VII7VII132006

  • 72

    Tsang EWHamani CMoro EMazzella FLozano AMYeh IJ: Prominent 5–18 Hz oscillations in the pallidal-thalamic circuit in secondary dystonia. Neurology 78:3613632012

  • 73

    Volkmann JMueller JDeuschl GKühn AAKrauss JKPoewe W: Pallidal neurostimulation in patients with medication-refractory cervical dystonia: a randomised, sham-controlled trial. Lancet Neurol 13:8758842014

  • 74

    Wang DDde Hemptinne CMiocinovic SQasim SEMiller AMOstrem JL: Subthalamic local field potentials in Parkinson’s disease and isolated dystonia: an evaluation of potential biomarkers. Neurobiol Dis 89:2132222016

  • 75

    Weinberger MHutchison WDAlavi MHodaie MLozano AMMoro E: Oscillatory activity in the globus pallidus internus: comparison between Parkinson’s disease and dystonia. Clin Neurophysiol 123:3583682012

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Article Information

Correspondence Dan Piña-Fuentes: University Medical Center Groningen, Groningen, The Netherlands. d.a.i.pina.fuentes@umcg.nl.

INCLUDE WHEN CITING DOI: 10.3171/2018.5.FOCUS18155.

Disclosures The authors report no conflict of interest concerning the materials or methods used in this study or the findings specified in this paper.

© AANS, except where prohibited by US copyright law.

Headings

Figures

  • View in gallery

    Potential interface for aDBS using low-frequency oscillations. In this figure, the presence of low-frequency oscillations on an LFP is visualized and used for an adaptive stimulation algorithm. Raw signals (LFP L and R) are dynamically recorded and filtered around the low-frequency peak registered (FILT LFP L and R). Afterwards, the filtered signal would be rectified, and an amplitude threshold would be set, in order to trigger the stimulation (STIM L and R) every time that an increment in low-frequency activity is detected. A brief delay in the activation of the stimulation would ensure that the stimulation is triggered only by actual increments of low-frequency activity and not by short-lived artifacts. AMP ENV = amplitude envelope of the rectified filtered signal; FILT LFP = LFP filtered around the low-frequency peak detected in order to visualize low-frequency oscillations embedded in the signal; L = left; R = right; STIM = channels representing stimulation amplitude.

  • View in gallery

    Potential biomarkers and recording sites. Dystonic brain activity (A) (e.g., increased low-frequency oscillations) can be recorded either in the form of local field potentials—from the electrodes used for stimulation or from electrodes placed on the cortical surface of the brain (electrocorticography) (1). Dystonic muscle activity (B) can be recorded either from subcutaneous EMG (2) or through wearable devices (3), which could also detect dystonic tremor (C), thanks to integrated accelerometers. Signals can be instantaneously processed in the battery (4), to modulate stimulation according to the biomarker selected (to visualize a stimulation algorithm [see Fig. 1]). Copyright Dan Piña-Fuentes. Published with permission.

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Miocinovic SMiller ASwann NCOstrem JLStarr PA: Chronic deep brain stimulation normalizes scalp EEG activity in isolated dystonia. Clin Neurophysiol 129:3683762017

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Miocinovic SSomayajula SChitnis SVitek JL: History, applications, and mechanisms of deep brain stimulation. JAMA Neurol 70:1631712013

42

Morishita TFoote KDHaq IUZeilman PJacobson CEOkun MS: Should we consider Vim thalamic deep brain stimulation for select cases of severe refractory dystonic tremor. Stereotact Funct Neurosurg 88:981042010

43

Neumann WJDegen KSchneider GHBrücke CHuebl JBrown P: Subthalamic synchronized oscillatory activity correlates with motor impairment in patients with Parkinson’s disease. Mov Disord 31:174817512016

44

Neumann WJHorn AEwert SHuebl JBrücke CSlentz C: A localized pallidal physiomarker in cervical dystonia. Ann Neurol 82:9129242017

45

Neumann WJHuebl JBrücke CRuiz MHKupsch ASchneider GH: Enhanced low-frequency oscillatory activity of the subthalamic nucleus in a patient with dystonia. Mov Disord 27:106310662012

46

Neumann WJStaub FHorn ASchanda JMueller JSchneider GH: Deep brain recordings using an implanted pulse generator in Parkinson’s disease. Neuromodulation 19:20242016

47

Odekerken VJJvan Laar TStaal MJMosch AHoffmann CFENijssen PCG: Subthalamic nucleus versus globus pallidus bilateral deep brain stimulation for advanced Parkinson’s disease (NSTAPS study): a randomised controlled trial. Lancet Neurol 12:37442013

48

Panov FLevin Ede Hemptinne CSwann NCQasim SMiocinovic S: Intraoperative electrocorticography for physiological research in movement disorders: principles and experience in 200 cases. J Neurosurg 126:1221312017

49

Pauls KAMHammesfahr SMoro EMoore APBinder EEl Majdoub F: Deep brain stimulation in the ventrolateral thalamus/subthalamic area in dystonia with head tremor. Mov Disord 29:9539592014

50

Picillo MLozano AMKou NMunhoz RPFasano A: Programming deep brain stimulation for tremor and dystonia: the Toronto Western Hospital algorithms. Brain Stimul 9:4384522016

51

Piña-Fuentes DLittle SOterdoom MNeal SPogosyan ATijssen MAJ: Adaptive DBS in a Parkinson’s patient with chronically implanted DBS: A proof of principle. Mov Disord 32:125312542017

52

Prudente CNHess EJJinnah HA: Dystonia as a network disorder: what is the role of the cerebellum? Neuroscience 260:23352014

53

Rawal PVAlmeida LSmelser LBHuang HGuthrie BLWalker HC: Shorter pulse generator longevity and more frequent stimulator adjustments with pallidal DBS for dystonia versus other movement disorders. Brain Stimul 7:3453492014

54

Ray NJJenkinson NWang SHolland PBrittain JSJoint C: Local field potential beta activity in the subthalamic nucleus of patients with Parkinson’s disease is associated with improvements in bradykinesia after dopamine and deep brain stimulation. Exp Neurol 213:1081132008

55

Rosa MArlotti MArdolino GCogiamanian FMarceglia SDi Fonzo A: Adaptive deep brain stimulation in a freely moving Parkinsonian patient. Mov Disord 30:100310052015

56

Rosin BSlovik MMitelman RRivlin-Etzion MHaber SNIsrael Z: Closed-loop deep brain stimulation is superior in ameliorating parkinsonism. Neuron 72:3703842011

57

Rossi LFoffani GMarceglia SBracchi FBarbieri SPriori A: An electronic device for artefact suppression in human local field potential recordings during deep brain stimulation. J Neural Eng 4:961062007

58

Ruge DCif LLimousin PGonzalez VVasques XCoubes P: Longterm deep brain stimulation withdrawal: clinical stability despite electrophysiological instability. J Neurol Sci 342:1971992014

59

Ryapolova-Webb EAfshar PStanslaski SDenison Tde Hemptinne CBankiewicz K: Chronic cortical and electromyographic recordings from a fully implantable device: preclinical experience in a nonhuman primate. J Neural Eng 11:0160092014

60

Salenius SPortin KKajola MSalmelin RHari R: Cortical control of human motoneuron firing during isometric contraction. J Neurophysiol 77:340134051997

61

Schoffelen JMOostenveld RFries P: Neuronal coherence as a mechanism of effective corticospinal interaction. Science 308:1111132005

62

Sharott AGrosse PKühn AASalih FEngel AKKupsch A: Is the synchronization between pallidal and muscle activity in primary dystonia due to peripheral afferance or a motor drive? Brain 131:4734842008

63

Shukla PBasu ITuninetti D: Towards closed-loop deep brain stimulation: decision tree-based essential tremor patient’s state classifier and tremor reappearance predictor. Conf Proc IEEE Eng Med Biol Soc 2014:260526082014

64

Silberstein PKühn AAKupsch ATrottenberg TKrauss JKWöhrle JC: Patterning of globus pallidus local field potentials differs between Parkinson’s disease and dystonia. Brain 126:259726082003

65

Starr PARau GMDavis VMarks WJJ JrOstrem JLSimmons D: Spontaneous pallidal neuronal activity in human dystonia: comparison with Parkinson’s disease and normal macaque. J Neurophysiol 93:316531762005

66

Stavrinou LCBoviatsis EJStathis PLeonardos APanourias IGSakas DE: Sustained relief after discontinuation of DBS for dystonia: implications for the possible role of synaptic plasticity and cortical reorganization. J Neurol Surg A Cent Eur Neurosurg 73:1751782012

67

Tang JKHMahant NCunic DChen RMoro ELang AE: Changes in cortical and pallidal oscillatory activity during the execution of a sensory trick in patients with cervical dystonia. Exp Neurol 204:8458482007

68

Tang JKHMoro EMahant NHutchison WDLang AELozano AM: Neuronal firing rates and patterns in the globus pallidus internus of patients with cervical dystonia differ from those with Parkinson’s disease. J Neurophysiol 98:7207292007

69

Tijssen MAMarsden JFBrown P: Frequency analysis of EMG activity in patients with idiopathic torticollis. Brain 123:6776862000

70

Tisch SZrinzo LLimousin PBhatia KPQuinn NAshkan K: Effect of electrode contact location on clinical efficacy of pallidal deep brain stimulation in primary generalised dystonia. J Neurol Neurosurg Psychiatry 78:131413192007

71

Tolosa ECompta Y: Dystonia in Parkinson’s disease. J Neurol 253 (Suppl 7):VII7VII132006

72

Tsang EWHamani CMoro EMazzella FLozano AMYeh IJ: Prominent 5–18 Hz oscillations in the pallidal-thalamic circuit in secondary dystonia. Neurology 78:3613632012

73

Volkmann JMueller JDeuschl GKühn AAKrauss JKPoewe W: Pallidal neurostimulation in patients with medication-refractory cervical dystonia: a randomised, sham-controlled trial. Lancet Neurol 13:8758842014

74

Wang DDde Hemptinne CMiocinovic SQasim SEMiller AMOstrem JL: Subthalamic local field potentials in Parkinson’s disease and isolated dystonia: an evaluation of potential biomarkers. Neurobiol Dis 89:2132222016

75

Weinberger MHutchison WDAlavi MHodaie MLozano AMMoro E: Oscillatory activity in the globus pallidus internus: comparison between Parkinson’s disease and dystonia. Clin Neurophysiol 123:3583682012

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