Adaptive Brain Stimulation for Movement Disorders

Deep brain stimulation (DBS) has markedly changed how we treat movement disorders including Parkinson's disease (PD), dystonia, and essential tremor (ET). However, despite its demonstrable clinical benefit, DBS is often limited by side effects and partial efficacy. These limitations may be due in part to the fact that DBS interferes with both pathological and physiological neural activities. DBS could, therefore, be potentially improved were it applied selectively and only at times of enhanced pathological activity. This form of stimulation is known as closed-loop or adaptive DBS (aDBS). An aDBS approach has been shown to be superior to conventional DBS in PD in primates using cortical neuronal spike triggering and in humans employing local field potential biomarkers. Likewise, aDBS studies for essential and Parkinsonian tremor are advancing and show great promise, using both peripheral or central sensing and stimulation. aDBS has not yet been trialed in dystonia and yet exciting and promising biomarkers suggest it could be beneficial here too. In this chapter, we will review the existing literature on aDBS in movement disorders and explore potential biomarkers and stimulation algorithms for applying aDBS in PD, ET, and dystonia

A Clinical Applicable Smartwatch Application for Measuring Hyperkinetic Movement Disorder Severity

Measuring the severity of hyperkinetic movement disorders like tremor and myoclonus is challenging. Although many accelerometers are available to quantify movements, the vast majority lacks real-time analysis and an interface that makes it possible to real-time adjust therapy like deep brain stimulation (DBS). Here, we developed a smartwatch / smartphone application that is capable of real-time analysing movement disorder severity. Movement analysis was realised by integrating acceleration values, to velocity and subsequently to distance. Measured distances were compared with a validated accelerometer already applied for quantifying movement disorders. Further validation was done by quantitative assessment of simulated movement disorders in 10 healthy volunteers. Finally, the approach was tested in two patients treated with DBS to quantify the effect of different DBS settings on myoclonus and tremor severity, respectively. The distance measured with the application had a 96% accuracy. This was non-inferior (p = 0.76) compared to accelerometers already clinically applied. Furthermore, (simulated) movement disorder severity could be classified correctly in 93% of the cases. Finally, the method was capable of distinguishing effective from non-effective DBS parameters in two patients. In summary, with our approach we realised an instantaneous and reliable estimation of the severity of movement disorders which can assist in real time titrating therapy like DBS.</p

Treatment of Parkinson’s Disease:Early, Late, and Combined

Medical therapy in de novo Parkinson’s disease typically starts with a dopamine agonist or levodopa in combination with a decarboxylase inhibitor or if symptoms are still very mild with a MAO-B inhibitor. When patients do not (or no longer) respond satisfactorily to these initial therapies, different drugs can be initiated or combined (i.e., “add-on” treatments). These add-on therapies not only comprise oral agents but also intra-jejunal and intra-cutaneous treatments and functional neurosurgical procedures. This chapter starts with the treatment of de novo Parkinson’s disease whereafter indications and expected effects of the different “add-on” therapies will be described. The “add-on” therapies will be described in a hierarchical way and treatment algorithms will be provided based on prevailing symptoms including non-motor symptoms. The symptoms that will be discussed are: (1) bradykinesia and “wearing-OFF, " (2) tremor at rest, (3) dyskinesia, (4) gait and postural symptoms including freezing of gait, and (5) important non-motor symptoms. Finally, a comprehensive add-on treatment algorithm will be provided that takes into account non-motor symptoms that may limit the efficacy and tolerability of the different add-on therapies.</p

Interruption of visually perceived forward motion in depth evokes a cortical activation shift from spatial to intentional motor regions

Forward locomotion generates a radially expanding flow of visual motion which supports goal-directed walking. In stationary mode, wide-field visual presentation of optic flow stimuli evokes the illusion of forward self-motion. These effects illustrate an intimate relation between visual and motor processing. In the present fMRI study, we applied optic flow to identify distinct interfaces between circuitries implicated in vision and movement. The dorsal premotor cortex (PMd) was expected to contribute to wide-field forward motion flow (FFw), reflecting a pathway for externally triggered motor control. Medial prefrontal activation was expected to follow interrupted optic flow urging internally generated action. Data of 15 healthy subjects were analyzed with Statistical Parametric Mapping and confirmed this hypothesis. Right PMd activation was seen in FFw, together with activations of posterior parietal cortex, ventral V5, and the right fusiform gyms. Conjunction analysis of the transition from wide to narrow forward flow and reversed wide-field flow revealed selective dorsal medial prefrontal activation. These findings point at equivalent visuomotor transformations in locomotion and goal-directed hand movement, in which parietal-premotor circuitry is crucially implicated. Possible implications of an activation shift from spatial to intentional motor regions for understanding freezing of gait in Parkinson's disease are discussed: impaired medial prefrontal function in Parkinson's disease may reflect an insufficient internal motor drive when visual support from optic flow is reduced at the entrance of a narrow corridor. (C) 2010 Elsevier B.V. All rights reserved

Small-world characteristics of EEG patterns in post-anoxic encephalopathy

Post-anoxic encephalopathy (PAE) has a heterogenous outcome which is difficult to predict. At present, it is possible to predict poor outcome using somatosensory evoked potentials in only a minority of the patients at an early stage. In addition, it remains difficult to predict good outcome at an early stage. Network architecture, as can be quantified with continuous electroencephalography (cEEG), may serve as a candidate measure for predicting neurological outcome. Here, we explore whether cEEG monitoring can be used to detect the integrity of neural network architecture in patients with PAE after cardiac arrest. From 56 patients with PAE treated with mild therapeutic hypothermia, 19-channel cEEG data were recorded starting as soon as possible after cardiac arrest. Adjacency matrices of shared frequencies between 1 and 25Hz of the EEG channels were obtained using Fourier transformations. Number of network nodes and connections, clustering coefficient (C), average path length (L), and small-world index (SWI) were derived. Outcome was quantified by the best cerebral performance category (CPC)-score within 6months. Compared to non-survivors, survivors showed significantly more nodes and connections. L was significantly higher and C and SWI were significantly lower in the survivor group than in the non-survivor group. The number of nodes, connections, and the L were negatively correlated with the CPC-score. C and SWI correlated positively with the CPC-score. The combination of number of nodes, connections, C, and L showed the most significant difference and correlation between survivors and non-survivors and CPC-score. Our data might implicate that non-survivors have insufficient distribution and differentiation of neural activity for regaining normal brain function. These network differences, already present during hypothermia, might be further developed as early prognostic markers. The predictive values are however still inferior to current practice parameters. Keywords: small-world network, continuous EEG, post-anoxic encephalopathy, prognosis, resuscitatio

Improving neurophysiological biomarkers for functional myoclonic movements.

INTRODUCTION: Differentiating between functional jerks (FJ) and organic myoclonus can be challenging. At present, the only advanced diagnostic biomarker to support FJ is the Bereitschaftspotential (BP). However, its sensitivity is limited and its evaluation subjective. Recently, event related desynchronisation in the broad beta range (13-45 Hz) prior to functional generalised axial (propriospinal) myoclonus was reported as a possible complementary diagnostic marker for FJ. Here we study the value of ERD together with a quantified BP in clinical practice. METHODS: Twenty-nine patients with FJ and 16 patients with cortical myoclonus (CM) were included. Jerk-locked back-averaging for determination of the 'classical' and quantified BP, and time-frequency decomposition for the event related desynchronisation (ERD) were performed. Diagnostic gain, sensitivity and specificity were obtained for individual and combined techniques. RESULTS: We detected a classical BP in 14/29, a quantitative BP in 15/29 and an ERD in 18/29 patients. At group level we demonstrate that ERD in the broad beta band preceding a jerk has significantly higher amplitude in FJ compared to CM (respectively -0.14 ± 0.13 and +0.04 ± 0.09 (p < 0.001)). Adding ERD to the classical BP achieved an additional diagnostic gain of 53%. Furthermore, when combining ERD with quantified and classical BP, an additional diagnostic gain of 71% was achieved without loss of specificity. CONCLUSION: Based on the current findings we propose to the use of combined beta ERD assessment and quantitative BP analyses in patients with a clinical suspicion for all types of FJ with a negative classical BP

Low-frequency oscillation suppression in dystonia:Implications for adaptive deep brain stimulation

Background: Low-frequency oscillations (LFO) detected in the internal globus pallidus of dystonia patients have been identified as a physiomarker for adaptive Deep Brain Stimulation (aDBS), since LFO correlate with dystonic symptoms and are rapidly suppressed by continuous DBS (cDBS). However, it is as yet unclear how LFO should be incorporated as feedback for aDBS. Objectives: to test the acute effects of aDBS, using the amplitude of short-lived LFO-bursts to titrate stimulation, to explore the immediate effects of cDBS on LFO-modulation and dystonic symptoms, and to investigate whether a difference in the resting-state LFO is present between DBS-naïve patients and patients with chronic DBS. Methods: seven patients were assessed during either DBS-implantation (n = 2) or battery replacement surgery (n = 5), and pseudorandomized in three conditions: no stimulation, cDBS, and aDBS. Additionally, resting-state LFP-recordings from patients undergoing battery replacement were compared to those obtained during DBS-implantation; LFP-recordings from a previous cohort of six dystonia patients undergoing DBS-implantation were incorporated into this analysis (total n = 8 newly implanted patients). Results: we corroborated that a mild LFO-suppression rapidly occurs during cDBS. However, no acute changes in clinical symptoms were observed after cDBS or aDBS. Remarkably, we observed that resting-state LFO were significantly lower in patients who had been effectively treated with chronic cDBS compared to those of newly implanted patients, even when stimulation was suspended. Conclusions: our results indicate that LFO-suppression in dystonia, similar to symptom response to cDBS, might be gradual, and remain after stimulation is suspended. Therefore, tracking gradual changes in LFO may be required for aDBS implementation

The Inter-rater Variability of Clinical Assessment in Post-anoxic Myoclonus.

Acute post-anoxic myoclonus (PAM) can be divided into an unfavorable (generalized/subcortical) and more favorable ((multi)focal/cortical) outcome group that could support prognostication in post-anoxic encephalopathy; however, the inter-rater variability of clinically assessing these PAM subtypes is unknown. We prospectively examined PAM patients using a standardized video protocol. Videos were rated by three neurologists who classified PAM phenotype (generalized/(multi)focal), stimulus sensitivity, localization (proximal/distal/both), and severity (Clinical Global Impression-Severity Scale (CGI-S) and Unified Myoclonus Rating Scale (UMRS)). Poor inter-rater agreement was found for phenotype and stimulus sensitivity (κ=-0.05), moderate agreement for localization (κ=0.46). Substantial agreement was obtained for the CGI-S (intraclass correlation coefficient (ICC)=0.64) and almost perfect agreement for the UMRS (ICC=0.82). Clinical assessment of PAM is not reproducible between physicians, and should therefore not be used for prognostication. PAM severity measured by the UMRS appears to be reliable; however, the relation between PAM severity and outcome is unknown