Simon Little

Adaptive Deep Brain Stimulation In Advanced Parkinson Disease

Brain–computer interfaces (BCIs) could potentially be used to interact with pathological brain signals to intervene and ameliorate their effects in disease states. Here, we provide proof‐of‐principle of this approach by using a BCI to interpret pathological brain activity in patients with advanced Parkinson disease (PD) and to use this feedback to control when therapeutic deep brain stimulation (DBS) is delivered. Our goal was to demonstrate that by personalizing and optimizing stimulation in real time, we could improve on both the efficacy and efficiency of conventional continuous DBS.

What brain signals are suitable for feedback control of deep brain stimulation in Parkinson's disease?

Feedback control of deep brain stimulation (DBS) in Parkinsons disease has great potential to improve efficacy, reduce side effects, and decrease the cost of treatment. In this, the timing and intensity of stimulation are titrated according to biomarkers that capture current clinical state. Stimulation may be at standard high frequency or intelligently patterned to directly modify specific pathological rhythms. The search for and validation of appropriate feedback signals are therefore crucial. Signals recorded from the DBS electrode currently appear to be the most promising source of feedback. In particular, beta-frequency band oscillations in the local field potential recorded at the stimulation target may capture variation in bradykinesia and rigidity across patients, but this remains to be confirmed within patients. Biomarkers that reliably reflect other impairments, such as tremor, also need to be established. Finally, whether brain signals are causally important needs to be established before stimulation can be specifically patterned rather than delivered at empirically defined high frequency.Feedback control of deep brain stimulation (DBS) in Parkinsons disease has great potential to improve efficacy, reduce side effects, and decrease the cost of treatment. In this, the timing and intensity of stimulation are titrated according to biomarkers that capture current clinical state. Stimulation may be at standard high frequency or intelligently patterned to directly modify specific pathological rhythms. The search for and validation of appropriate feedback signals are therefore crucial. Signals recorded from the DBS electrode currently appear to be the most promising source of feedback. In particular, beta‐frequency band oscillations in the local field potential recorded at the stimulation target may capture variation in bradykinesia and rigidity across patients, but this remains to be confirmed within patients. Biomarkers that reliably reflect other impairments, such as tremor, also need to be established. Finally, whether brain signals are causally important needs to be established before stimulation can be specifically patterned rather than delivered at empirically defined high frequency.

Beta band stability over time correlates with Parkinsonian rigidity and bradykinesia

Abnormal oscillatory activity in the basal ganglia is increasingly implicated in the pathophysiology of Parkinsons disease. Such activity is recorded in patients in the form of oscillations in the local field potential (LFP) picked up in the subthalamic nucleus. Previous studies have focused on correlations between features of the time averaged power or amplitude spectrum of the LFP and the clinical state, either off medication or in response to levodopa. However, average spectral densities do not take account of time variant spectral properties and we hypothesised that these dynamic properties of the spectrum of the LFP would contain additional information about clinical state. Here we assess the variability in LFP amplitude over time using the coefficient of variation (CV), evaluating this with regard to clinical state off medication and in response to levodopa in two datasets. The CV of activity in the high beta frequency band was found to be correlated with clinical state off levodopa (rho = − 0.59, p < 0.001) and this was shown to be complementary, rather than redundant, to spectral amplitude in a multiple regression analysis, selective for rigidity–bradykinesia and highly focal. Similarly, a strong correlation was found between change in clinical scores and change in high beta CV following levodopa (rho = − 0.66, p = 0.004). This too was selective for rigidity–bradykinesia and non-redundant to spectral power in a multiple regression model. Our results indicate that temporal stability in the beta band is correlated with rigidity–bradykinesia. It is suggested that loss of beta reactivity is deleterious to basal ganglia function over and above any concomitant change in absolute level of beta synchrony. The CV of LFP beta band amplitude may potentially provide an additional index of clinical state suitable for feedback control in closed loop stimulation therapy.

The functional role of beta oscillations in Parkinson's disease.

Modulations of beta oscillations (13-30 Hz) during normal motor control suggest that they may act to promote current motor set at the expense of new movements. These oscillations are greatly enhanced in Parkinsons disease (PD) and there is strong correlative evidence linking beta activity at rest and beta changes in response to treatment with bradykinesia and rigidity. Some evidence that this link may be mechanistically important or causal comes from studies in which either cortical or subcortical sites have been stimulated in the beta frequency range causing modest but significant slowing of movements. However, recent trials in which high frequency deep brain stimulation (DBS) has only been delivered during periods of elevated beta activity have demonstrated major clinical effects that even exceed those of standard continuous high frequency DBS. These studies suggest that beta activity may be both causally and quantitatively important in the motor impairment of PD, and demonstrate how improvements in the understanding of the pathophysiology of PD can lead to enhanced therapeutic interventions in this condition.

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.

Midline Frontal Cortex Low-Frequency Activity Drives Subthalamic Nucleus Oscillations during Conflict

Making the right decision from conflicting information takes time. Recent computational, electrophysiological, and clinical studies have implicated two brain areas as being crucial in assuring sufficient time is taken for decision-making under conditions of conflict: the medial prefrontal cortex and the subthalamic nucleus (STN). Both structures exhibit an elevation of activity at low frequencies (<10 Hz) during conflict that correlates with the amount of time taken to respond. This suggests that the two sites could become functionally coupled during conflict. To establish the nature of this interaction we recorded from deep-brain stimulation electrodes implanted bilaterally in the STN of 13 Parkinsons disease patients while they performed a sensory integration task involving randomly moving dots. By gradually increasing the number of dots moving coherently in one direction, we were able to determine changes in the STN associated with response execution. Furthermore, by occasionally having 10% of the dots move in the opposite direction as the majority, we were able to identify an independent increase in STN theta-delta activity triggered by conflict. Crucially, simultaneous midline frontal electroencephalographic recordings revealed an increase in the theta-delta band coherence between the two structures that was specific to high-conflict trials. Activity over the midline frontal cortex was Granger causal to that in STN. These results establish the cortico-subcortical circuit enabling successful choices to be made under conditions of conflict and provide support for the hypothesis that the brain uses frequency-specific channels of communication to convey behaviorally relevant information.

Phase dependent modulation of tremor amplitude in essential tremor through thalamic stimulation.

High frequency deep brain stimulation of the thalamus can help ameliorate severe essential tremor. Here we explore how the efficacy, efficiency and selectivity of thalamic deep brain stimulation might be improved in this condition. We started from the hypothesis that the effects of electrical stimulation on essential tremor may be phase dependent, and that, in particular, there are tremor phases at which stimuli preferentially lead to a reduction in the amplitude of tremor. The latter could be exploited to improve deep brain stimulation, particularly if tremor suppression could be reinforced by cumulative effects. Accordingly, we stimulated 10 patients with essential tremor and thalamic electrodes, while recording tremor amplitude and phase. Stimulation near the postural tremor frequency entrained tremor. Tremor amplitude was also modulated depending on the phase at which stimulation pulses were delivered in the tremor cycle. Stimuli in one half of the tremor cycle reduced median tremor amplitude by ∼10%, while those in the opposite half of the tremor cycle increased tremor amplitude by a similar amount. At optimal phase alignment tremor suppression reached 27%. Moreover, tremor amplitude showed a non-linear increase in the degree of suppression with successive stimuli; tremor suppression was increased threefold if a stimulus was preceded by four stimuli with a similar phase relationship with respect to the tremor, suggesting cumulative, possibly plastic, effects. The present results pave the way for a stimulation system that tracks tremor phase to control when deep brain stimulation pulses are delivered to treat essential tremor. This would allow treatment effects to be maximized by focussing stimulation on the optimal phase for suppression and by ensuring that this is repeated over many cycles so as to harness cumulative effects. Such a system might potentially achieve tremor control with far less power demand and greater specificity than current high frequency stimulation approaches, and may lower the risk for tolerance and rebound.

The nature of tremor circuits in parkinsonian and essential tremor

See Arkadir et al. (doi:10.1093/brain/awu285) for a scientific commentary on this article. The mechanisms underlying tremor generation remain unclear. Cagnan et al. use deep brain stimulation of the thalamus or subthalamic nucleus at/near a patients own tremor frequency to investigate the networks responsible for parkinsonian and essential tremor. The results reveal differences in the circuitry underlying these two tremor types.

The modulatory effect of adaptive deep brain stimulation on beta bursts in Parkinson's disease

Pilot studies suggest that adaptive deep brain stimulation (DBS) may be more effective than conventional DBS for the treatment of Parkinsons disease. Tinkhauser et al. show that adaptive DBS regulates pathological beta synchronisation in the subthalamic nucleus by selectively limiting long duration beta bursts, which are related to clinical impairment.

Bilateral functional connectivity of the basal ganglia in patients with Parkinson's disease and its modulation by dopaminergic treatment.

Parkinson’s disease is characterised by excessive subcortical beta oscillations. However, little is known about the functional connectivity of the two basal ganglia across hemispheres and specifically the role beta plays in this. We recorded local field potentials from the subthalamic nucleus bilaterally in 23 subjects with Parkinson’s disease at rest, on and off medication. We found suppression of low beta power in response to levodopa (t22 = −4.4, p<0.001). There was significant coherence between the two sides in the beta range in 19 of the subjects. Coherence was selectively attenuated in the low beta range following levodopa (t22 = −2.7; p = 0.01). We also separately analysed amplitude co-modulation and phase synchronisation in the beta band and found significant amplitude co-modulation and phase locking values in 17 and 16 subjects respectively, off medication. There was a dissociable effect of levodopa on these measures, with a significant suppression only in low beta phase locking value (t22 = −2.8, p = 0.01) and not amplitude co-modulation. The absolute mean values of amplitude co-modulation (0.40±0.03) and phase synchronisation (0.29±0.02) off medication were, however, relatively low, suggesting that the two basal ganglia networks may have to be approached separately with independent sensing and stimulation during adaptive deep brain stimulation. In addition, our findings highlight the functional distinction between the lower and upper beta frequency ranges and between amplitude co-modulation and phase synchronization across subthalamic nuclei.