Optimal Deep Brain Stimulation Parameters Research Articles

Utilising activity patterns of a complex biophysical network model to optimise intra-striatal deep brain stimulation

A large-scale biophysical network model for the isolated striatal body is developed to optimise potential intrastriatal deep brain stimulation applied to, e.g. obsessive-compulsive disorder. The model is based on modified Hodgkin–Huxley equations with small-world connectivity, while the spatial information about the positions of the neurons is taken from a detailed human atlas. The model produces neuronal spatiotemporal activity patterns segregating healthy from pathological conditions. Three biomarkers were used for the optimisation of stimulation protocols regarding stimulation frequency, amplitude and localisation: the mean activity of the entire network, the frequency spectrum of the entire network (rhythmicity) and a combination of the above two. By minimising the deviation of the aforementioned biomarkers from the normal state, we compute the optimal deep brain stimulation parameters, regarding position, amplitude and frequency. Our results suggest that in the DBS optimisation process, there is a clear trade-off between frequency synchronisation and overall network activity, which has also been observed during in vivo studies.

SAFE-OPT: a Bayesian optimization algorithm for learning optimal deep brain stimulation parameters with safety constraints

Objective.To treat neurological and psychiatric diseases with deep brain stimulation (DBS), a trained clinician must select parameters for each patient by monitoring their symptoms and side-effects in a months-long trial-and-error process, delaying optimal clinical outcomes. Bayesian optimization has been proposed as an efficient method to quickly and automatically search for optimal parameters. However, conventional Bayesian optimization does not account for patient safety and could trigger unwanted or dangerous side-effects.Approach.In this study we develop SAFE-OPT, a Bayesian optimization algorithm designed to learn subject-specific safety constraints to avoid potentially harmful stimulation settings during optimization. We prototype and validate SAFE-OPT using a rodent multielectrode stimulation paradigm which causes subject-specific performance deficits in a spatial memory task. We first use data from an initial cohort of subjects to build a simulation where we design the best SAFE-OPT configuration for safe and accurate searchingin silico. Main results.We then deploy both SAFE-OPT and conventional Bayesian optimization without safety constraints in new subjectsin vivo, showing that SAFE-OPT can find an optimally high stimulation amplitude that does not harm task performance with comparable sample efficiency to Bayesian optimization and without selecting amplitude values that exceed the subject's safety threshold.Significance.The incorporation of safety constraints will provide a key step for adopting Bayesian optimization in real-world applications of DBS.

DBS-evoked cortical responses index optimal contact orientations and motor outcomes in Parkinson’s disease

Although subthalamic deep brain stimulation (DBS) is a highly-effective treatment for alleviating motor dysfunction in patients with Parkinson’s disease (PD), clinicians currently lack reliable neurophysiological correlates of clinical outcomes for optimizing DBS parameter settings, which may contribute to treatment inefficacies. One parameter that could aid DBS efficacy is the orientation of current administered, albeit the precise mechanisms underlying optimal contact orientations and associated clinical benefits are not well understood. Herein, 24 PD patients received monopolar stimulation of the left STN during magnetoencephalography and standardized movement protocols to interrogate the directional specificity of STN-DBS current administration on accelerometer metrics of fine hand movements. Our findings demonstrate that optimal contact orientations elicit larger DBS-evoked cortical responses in the ipsilateral sensorimotor cortex, and importantly, are differentially predictive of smoother movement profiles in a contact-dependent manner. Moreover, we summarize traditional evaluations of clinical efficacy (e.g., therapeutic windows, side effects) for a comprehensive review of optimal/non-optimal STN-DBS contact settings. Together, these data suggest that DBS-evoked cortical responses and quantitative movement outcomes may provide clinical insight for characterizing the optimal DBS parameters necessary for alleviating motor symptoms in patients with PD in the future.

Short-term changes in cortical physiological arousal measured by electroencephalography during thalamic centromedian deep brain stimulation.

The intralaminar thalamus is well implicated in the processes of arousal and attention. Stimulation of the intralaminar thalamus has been used therapeutically to improve level of alertness in minimally conscious individuals and to reduce seizures in refractory epilepsy, both presumably through modulation of thalamocortical function. Little work exists that directly measures the effects of intralaminar thalamic stimulation on cortical physiological arousal in humans. Therefore, our goal was to quantify cortical physiological arousal in individuals with epilepsy receiving thalamic intralaminar deep brain stimulation. We recorded scalp electroencephalogram (EEG) during thalamic intralaminar centromedian (CM) nucleus stimulation in 11 patients with medically refractory epilepsy. Participants underwent stimulation at 130Hz and 300µs for periods of 5 min alternating with 5 min of rest while stimulus voltage was titrated upward from 1 to 5V. EEG signal power was analyzed in different frequency ranges in relation to stimulus strength and time. We found a progressive increase in broadband gamma (25-100Hz) cortical EEG power (F=7.64, p<.05) and decrease in alpha (8-13Hz) power (F=4.37, p<.05) with thalamic CM stimulation. Topographic maps showed these changes to be widely distributed across the cortical surface rather than localized to one region. Previous work has shown that broadband increases in gamma frequency power and decreases in alpha frequency power are generally associated with states of cortical activation and increased arousal/attention. Our observed changes therefore support the possible role of cortical activation and increased physiological arousal in therapeutic effects of intralaminar thalamic stimulation for improving both epilepsy and attention. Further investigations with this approach may lead to methods for determining optimal deep brain stimulation parameters to improve clinical outcome in these disorders.

Towards automated patient-specific optimization of deep brain stimulation for movement disorders.

In this paper we present a simulation framework for automated optimization of deep brain stimulation (DBS) parameters based on the hand kinematics signal as the feedback signal, in patients with essential tremor. We used Gaussian Process regression (GPR) models to develop patient-specific models for predicting the effect of DBS on the hand kinematics using the clinical data that was recorded during DBS programming. In this framework, we characterized the performance of a Bayesian Optimization method to identify the optimal DBS parameters that maximized the clinical efficacy. Our results demonstrate the feasibility of using black-box optimization methods for automated identification of optimal DBS parameters in clinical settings.

Is Euthanasia Psychiatric Treatment? The Struggle With Death on Request in the Netherlands.

A 42-year-old married woman with three children was referred to our department for treatment of treatment-resistant depression. Pharmacotherapy, psychotherapy, and ECT were unsuccessful. We applied deep brain stimulation, which was partially effective and reduced depressive symptoms by 30%, but the patient still suffered. During our struggle to find optimal deep brain stimulation parameters in the course of treatment, the patient requested that her general physician provide euthanasia. Following guidelines in the Netherlands, our team was consulted, but we disapproved because her suffering was not prospectless and there still were treatment options with deep brain stimulation. Although we had treated her intensively for 2 years, our advice was disregarded. Eight weeks later we received the obituary of the patient.

Test–retest reliability of a stimulation‐locked evoked response to deep brain stimulation in subcallosal cingulate for treatment resistant depression

Deep brain stimulation (DBS) to the subcallosal cingulate cortex (SCC) is an emerging therapy for treatment resistant depression. Precision targeting of specific white matter fibers is now central to the model of SCC DBS treatment efficacy. A method to confirm SCC DBS target engagement is needed to reduce procedural variance across treatment providers and to optimize DBS parameters for individual patients. We examined the reliability of a novel cortical evoked response that is time-locked to a 2 Hz DBS pulse and shows the propagation of signal from the DBS target. The evoked response was detected in four individuals as a stereotyped series of components within 150 ms of a 6 V DBS pulse, each showing coherent topography on the head surface. Test-retest reliability across four repeated measures over 14 months met or exceeded standards for valid test construction in three of four patients. Several observations in this pilot sample demonstrate the prospective utility of this method to confirm surgical target engagement and instruct parameter selection. The topography of an orbital frontal component on the head surface showed specificity for patterns of forceps minor activation, which may provide a means to confirm DBS location with respect to key white matter structures. A divergent cortical response to unilateral stimulation of left (vs. right) hemisphere underscores the need for feedback acuity on the level of a single electrode, despite bilateral presentation of therapeutic stimulation. Results demonstrate viability of this method to explore patient-specific cortical responsivity to DBS for brain-circuit pathologies.

Closed-Loop Control of Tremor-Predominant Parkinsonian State Based on Parameter Estimation.

A significant feature of Parkinson's disease (PD) is the inability of the thalamus to respond faithfully to sensorimotor information from the cerebral cortex. This may be the result of abnormal oscillations in the basal ganglia (BG). Deep brain stimulation (DBS) is regarded as an effective method to modulate these pathological brain rhythmic activities. However, the selection of DBS parameters is challenging because the mechanism is not well understood. This work proposes the design of a closed-loop control strategy to automatically adjust the parameters of a DBS waveform based on a computational model. By estimating the synaptic input from BG to the thalamic neuron model as feedback variable, we designed and compared various control algorithms to counteract the effects of pathological oscillatory inputs. We then obtained optimal DBS parameters to modulate the tremor-predominant Parkinsonian state. We showed that even a simple proportional controller provides higher fidelity of thalamic relay of sensorimotor information and lower energy expenditure, as compared with classical open-loop DBS. Integral action further enhances DBS performance. Additionally, a positive bias voltage further improves the relay ability of the thalamus with decreased stimulation energy expenditure. These findings were conducive to the development of a more effective DBS to further improve the treatment of the PD.

Deep brain stimulation in mental health: Review of evidence for clinical efficacy.

There is increasing interest in the use of deep brain stimulation as a treatment for psychiatric disorders. In this review, we consider the evidence for the effectiveness of deep brain stimulation for psychiatric indications, with a primary focus on obsessive compulsive disorder and major depressive disorder. Case reports, case series and clinical trials where deep brain stimulation was primarily utilised in the treatment of a psychiatric disorder, including obsessive compulsive disorder, major depressive disorder, anorexia nervosa or an addictive disorder were identified. The evidence for the effectiveness of deep brain stimulation in the treatment of obsessive compulsive disorder and major depressive disorder was reviewed with studies clustered by the site of implantation. The majority of identified manuscripts report small case series or single cases. A limited number of studies have reported some form of randomised or blinded stimulation comparison. All of these comparative reports have included small samples of subjects (less than 20 per study in total) compromising the feasibility of making statistical comparison between outcomes in the comparison phases. The two exceptions to this have been industry-sponsored studies conducted in the treatment of major depressive disorder. However, both were stopped prematurely due to concerns about poor efficacy. There is insufficient evidence at this point in time to support the use of deep brain stimulation as a clinical treatment for any psychiatric disorder outside of research and programmes where formal outcome data are being systematically collated. While some promising initial data exist to support its potential efficacy for a number of psychiatric conditions, further research is required to establish optimal implantation targets, patient characteristics associated with positive therapeutic outcomes and optimal deep brain stimulation parameters and parameter-programming methods.

In search of optimal DBS paradigms to treat epilepsy: bilateral versus unilateral hippocampal stimulation in a rat model for temporal lobe epilepsy.

In many temporal lobe epilepsy (TLE) patients both hippocampi are seizure onset zones. These patients are unsuitable candidates for epilepsy surgery but may be amenable to hippocampal deep brain stimulation (DBS). The optimal DBS parameters for these patients are unknown. Recent observations suggest that even in patients with a unilateral focus switching from unilateral hippocampal DBS to bilateral hippocampal DBS could improve seizure control. Compare the effect of unilateral with bilateral hippocampal DBS on seizures in a rat model for TLE. In the post status epilepticus (SE) kainic acid rat model for TLE continuous EEG monitoring was performed for 50 days during which rats were subjected to 10 days of unilateral and 10 days of bilateral Poisson-distributed high frequency hippocampal DBS in a cross-over trial. During bilateral DBS, each hippocampus was stimulated with a separate stimulator and its own generated Poisson distribution with a mean and variance of 1/130s. Electrographic seizure rate was 23% lower during bilateral compared to unilateral hippocampal DBS (P<0.05). No effect of unilateral nor bilateral hippocampal DBS was observed on seizure duration. When bilateral hippocampal DBS was applied, lower stimulation intensities were required to evoke after discharges (P<0.05), reflecting a higher potency of bilateral hippocampal DBS compared to unilateral hippocampal DBS to affect hippocampal networks. Superior outcome in seizure control with bilateral compared to unilateral hippocampal DBS indicates that targeting larger regions of the hippocampal formation with more than one stimulation electrode may be more successful in suppressing seizures in TLE.

Calculating total electrical energy delivered by deep brain stimulation systems

Moro and colleagues should be commended for their recent article in Annals of Neurology on deep brain stimulation (DBS) for Huntington’s disease, the latest contribution to their ongoing effort to use constant energy paradigms to optimize DBS parameters and to determine which parameters have the most impact on clinical outcomes. An important measure of optimization is that which the authors term total electrical energy delivered or TEED. TEED, the total energy delivered by an electrical system over an arbitrary period of time, is determined by the programmed parameters of stimulation and the measured system impedance. In theory, optimized DBS settings will generate maximal clinical benefit at the lowest possible TEED, resulting in fewer stimulationrelated complications and longer battery life. The authors report that they use the following equation to calculate TEED: