Bilateral adaptive deep brain stimulation is effective in Parkinson's disease

INTRODUCTION & OBJECTIVES

Adaptive deep brain stimulation (aDBS) uses feedback from brain signals to guide stimulation. A recent acute trial of unilateral aDBS showed that aDBS can lead to substantial improvements in contralateral hemibody Unified Parkinson's Disease Rating Scale (UPDRS) motor scores and may be superior to conventional continuous DBS in Parkinson's disease (PD). We test whether potential benefits are retained with bilateral aDBS and in the face of concurrent medication.

METHODS

We applied bilateral aDBS in 4 patients with PD undergoing DBS of the subthalamic nucleus. aDBS was delivered bilaterally with independent triggering of stimulation according to the amplitude of β activity at the corresponding electrode. Mean stimulation voltage was 3.0±0.1 volts. Motor assessments consisted of double-blinded video-taped motor UPDRS scores that included both limb and axial features.

RESULTS

UPDRS scores were 43% (p=0.04; Cohen's d=1.62) better with aDBS than without stimulation. Motor improvement with aDBS occurred despite an average time on stimulation (ToS) of only 45%. Levodopa was well tolerated during aDBS and led to further reductions in ToS.

CONCLUSION

Bilateral aDBS can improve both axial and limb symptoms and can track the need for stimulation across drug states.

Deep brain stimulation modulates synchrony within spatially and spectrally distinct resting state networks in Parkinson's disease

Chronic dopamine depletion in Parkinson's disease leads to progressive motor and cognitive impairment, which is associated with the emergence of characteristic patterns of synchronous oscillatory activity within cortico-basal-ganglia circuits. Deep brain stimulation of the subthalamic nucleus is an effective treatment for Parkinson's disease, but its influence on synchronous activity in cortico-basal-ganglia loops remains to be fully characterized. Here, we demonstrate that deep brain stimulation selectively suppresses certain spatially and spectrally segregated resting state subthalamic nucleus-cortical networks. To this end we used a validated and novel approach for performing simultaneous recordings of the subthalamic nucleus and cortex using magnetoencephalography (during concurrent subthalamic nucleus deep brain stimulation). Our results highlight that clinically effective subthalamic nucleus deep brain stimulation suppresses synchrony locally within the subthalamic nucleus in the low beta oscillatory range and furthermore that the degree of this suppression correlates with clinical motor improvement. Moreover, deep brain stimulation relatively selectively suppressed synchronization of activity between the subthalamic nucleus and mesial premotor regions, including the supplementary motor areas. These mesial premotor regions were predominantly coupled to the subthalamic nucleus in the high beta frequency range, but the degree of deep brain stimulation-associated suppression in their coupling to the subthalamic nucleus was not found to correlate with motor improvement. Beta band coupling between the subthalamic nucleus and lateral motor areas was not influenced by deep brain stimulation. Motor cortical coupling with subthalamic nucleus predominantly involved driving of the subthalamic nucleus, with those drives in the higher beta frequency band having much shorter net delays to subthalamic nucleus than those in the lower beta band. These observations raise the possibility that cortical connectivity with the subthalamic nucleus in the high and low beta bands may reflect coupling mediated predominantly by the hyperdirect and indirect pathways to subthalamic nucleus, respectively, and that subthalamic nucleus deep brain stimulation predominantly suppresses the former. Yet only the change in strength of local subthalamic nucleus oscillations correlates with the degree of improvement during deep brain stimulation, compatible with the current view that a strengthened hyperdirect pathway is a prerequisite for locally generated beta activity but that it is the severity of the latter that may determine or index motor impairment.

Adaptive deep brain stimulation in Parkinson's disease

Although Deep Brain Stimulation (DBS) is an established treatment for Parkinson's disease (PD), there are still limitations in terms of effectivity, side-effects and battery consumption. One of the reasons for this may be that not only pathological but also physiological neural activity can be suppressed whilst stimulating. For this reason, adaptive DBS (aDBS), where stimulation is applied according to the level of pathological activity, might be advantageous. Initial studies of aDBS demonstrate effectiveness in PD, but there are still many questions to be answered before aDBS can be applied clinically. Here we discuss the feedback signals and stimulation algorithms involved in adaptive stimulation in PD and sketch a potential road-map towards clinical application.

Tremor Reduction by Deep Brain Stimulation Is Associated With Gamma Power Suppression in Parkinson's Disease

Objectives

Rest tremor is a cardinal symptom of Parkinson's disease (PD), and is readily suppressed by deep brain stimulation (DBS) of the subthalamic nucleus (STN). The therapeutic effect of the latter on bradykinesia and rigidity has been associated with the suppression of exaggerated beta (13–30 Hz) band synchronization in the vicinity of the stimulating electrode, but there is no correlation between beta suppression and tremor amplitude. In the present study, we investigate whether tremor suppression is related to suppression of activities at other frequencies.

Materials and Methods

We recorded hand tremor and contralateral local field potential (LFP) activity from DBS electrodes during stimulation of the STN in 15 hemispheres in 11 patients with PD. DBS was applied with increasing voltages starting at 0.5 V until tremor suppression was achieved or until 4.5 V was reached.

Results

Tremor was reduced to 48.9% ± 10.9% of that without DBS once stimulation reached 2.5–3 V (t14 = −4.667, p < 0.001). There was a parallel suppression of low gamma (31–45 Hz) power to 92.5% ± 3% (t14 = −2.348, p = 0.034). This was not seen over a band containing tremor frequencies and their harmonic (4–12 Hz), or over the beta band. Moreover, low gamma power correlated with tremor severity (mean r = 0.43 ± 0.14, p = 0.008) within subjects. This was not the case for LFP power in the other two bands.

Conclusions

Our findings support a relationship between low gamma oscillations and PD tremor, and reinforce the principle that the subthalamic LFP is a rich signal that may contain information about the severity of multiple different Parkinsonian features.

Electroencephalographic Findings in Posthypoxic Myoclonus

The physical examination findings of early posthypoxic myoclonus (PHM) are associated with poor prognosis. Recent findings indicate that patients with multifocal PHM, assumed to have a cortical origin, have a comparable outcome to resuscitated patients without PHM. Generalized PHM, assumed to have a subcortical myoclonus origin, is still associated with a bad clinical outcome. It is not known whether the electroencephalographic (EEG) findings differ between the multifocal and generalized myoclonus groups nor is the clinical significance clearly defined. Forty-three patients with PHM were retrospectively derived from an EEG database. Patients were categorized as having multifocal (i), generalized (ii), or undetermined (iii) PHM. Outcome was expressed in cerebral performance category scores. The EEG background was categorized into isoelectric (I), low voltage (II), burst suppression (III), status epilepticus (SE; IV), diffuse slowing (V), and mild encephalopathic or normal (VI). 17 patients had generalized PHM and 23 had multifocal PHM (3 undetermined). The EEG showed more SE in generalized compared to multifocal PHM (64% vs 13%, P< .001). Diffuse slowing was more often present in multifocal PHM (52% vs 17%, P < .05). Early-onset myoclonus occurred significantly more often in generalized PHM, and early generalized PHM was invariantly associated with poor outcome. In conclusion, patients with generalized PHM showed more SE. These EEG findings might be either subcortical corollaries or primarily cortical phenomena. Our retrospective results conflict with currently used clinical criteria for myoclonus classification, and we suggest that more refined difference may be needed for accurate assessment of PHM. To better understand PHM, prospective research with standardized clinical assessment and quantitative EEG analysis is needed.

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 25 Hz 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 6 months. 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.

Secondary sensory area SII is crucially involved in the preparation of familiar movements compared to movements never made before

Secondary sensorimotor regions are involved in sensorimotor integration and movement preparation. These regions take part in parietal-premotor circuitry that is not only active during motor execution but also during movement observation and imagery. This activation particularly occurs when observed movements belong to one's own motor repertoire, consistent with the finding that motor imagery only improves performance when one can actually make such movement. We aimed to investigate whether imagery or observation of a movement that was never made before causes parietal-premotor activation or that the ability to perform this movement is indeed a precondition. Nine subjects [group Already Knowing It (AKI)] could abduct their hallux (moving big toe outward). Seven subjects initially failed to make such movement (Absolute Zero A0 group). They had to imagine, observe, or execute this movement, whereas fMRI data were obtained both before and after training. Contrasting abduction observation between the AKI-group and A0-group showed increased left SII and supplementary motor area activation. Comparing the observation of hallux flexion with abduction showed increased bilateral SII activation in the A0 and not in the AKI group. Prolonged training resulted in equal performance and similar cerebral activation patterns in the two groups. Thereby, conjunction analysis of the correlations on subject's range of abduction during execution, imagery, and observation of hallux abduction showed exclusive bilateral SII activation. The reduced SII involvement in A0 may imply that effective interplay between sensory predictions and feedback does not take place without actual movement experience. However, this can be acquired by training.

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 gyrus. 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.

Cerebral representations of space and time

A link between perception of time and spatial change is particularly revealed in dynamic conditions. By fMRI, we identified regional segregation as well as overlap in activations related to spatial and temporal processing. Using spatial and temporal anticipation concerning movements of a ball provided a balanced paradigm for contrasting spatial and temporal conditions. In addition, momentary judgments were assessed. Subjects watched a monitor-display with a moving ball that repeatedly disappeared. Ordered in 4 conditions, they indicated either where or when the ball would hit the screen bottom, where it actually disappeared or what its speed was. Analysis with SPM showed posterior parietal activations related to both spatial- and temporal predictions. After directly contrasting these two conditions, parietal activations remained robust in spatial prediction but virtually disappeared in temporal prediction, while additional left cerebellar-right prefrontal and pre-SMA activations in temporal prediction remained unchanged. Speed contrasted to the location of disappearance showed similar parietal decrease with maintained cerebellar-prefrontal activations, but also increased caudate activation. From these results we inferred that parietal-based spatial information was a prerequisite for temporal processing, while prefrontal-cerebellar activations subsequently reflected working memory and feedforward processing for the assessment of differences between past and future spatial states. We propose that a temporal component was extracted from speed, i.e. approximated momentary time, which demarcated minimal intervals of spatial change (defined by neuronal processing time). The caudate association with such interval demarcation provided an argument to integrate concepts of space-referenced time processing and a clock-like processing model.