Subthalamic deep brain stimulation at individualized frequencies for Parkinson disease

Personalized and Circuit-Based Transcranial Magnetic Stimulation: Evidence, Controversies, and Opportunities

The development of neuroimaging methodologies to map brain connectivity has transformed our understanding of psychiatric disorders, the distributed effects of brain stimulation, and how transcranial magnetic stimulation can be best employed to target and ameliorate psychiatric symptoms. In parallel, neuroimaging research has revealed that higher-order brain regions such as the prefrontal cortex, which represent the most common therapeutic brain stimulation targets for psychiatric disorders, show some of the highest levels of interindividual variation in brain connectivity. These findings provide the rationale for personalized target site selection based on person-specific brain network architecture. Recent advances have made it possible to determine reproducible personalized targets with millimeter precision in clinically tractable acquisition times. These advances enable the potential advantages of spatially personalized transcranial magnetic stimulation targeting to be evaluated and translated to basic and clinical applications. In this review, we outline the motivation for target site personalization, preliminary support (mostly in depression), convergent evidence from other brain stimulation modalities, and generalizability beyond depression and the prefrontal cortex. We end by detailing methodological recommendations, controversies, and notable alternatives. Overall, while this research area appears highly promising, the value of personalized targeting remains unclear, and dedicated large prospective randomized clinical trials using validated methodology are critical.

Towards an optimised deep brain stimulation using a large-scale computational network and realistic volume conductor model

Objective. Constructing a theoretical framework to improve deep brain stimulation (DBS) based on the neuronal spatiotemporal patterns of the stimulation-affected areas constitutes a primary target.Approach. We develop a large-scale biophysical network, paired with a realistic volume conductor model, to estimate theoretically efficacious stimulation protocols. Based on previously published anatomically defined structural connectivity, a biophysical basal ganglia-thalamo-cortical neuronal network is constructed using Hodgkin-Huxley dynamics. We define a new biomarker describing the thalamic spatiotemporal activity as a ratio of spiking vs. burst firing. The per cent activation of the different pathways is adapted in the simulation to minimise the differences of the biomarker with respect to its value under healthy conditions.Main results.This neuronal network reproduces spatiotemporal patterns that emerge in Parkinson's disease. Simulations of the fibre per cent activation for the defined biomarker propose desensitisation of pallido-thalamic synaptic efficacy, induced by high-frequency signals, as one possible crucial mechanism for DBS action. Based on this activation, we define both an optimal electrode position and stimulation protocol using pathway activation modelling.Significance. A key advantage of this research is that it combines different approaches, i.e. the spatiotemporal pattern with the electric field and axonal response modelling, to compute the optimal DBS protocol. By correlating the inherent network dynamics with the activation of white matter fibres, we obtain new insights into the DBS therapeutic action.

Pallidal Beta Activity Is Linked to Stimulation-Induced Slowness in Dystonia

BACKGROUND

Pallidal deep brain stimulation (DBS) effectively alleviates symptoms in dystonia patients, but may induce movement slowness as a side-effect. In Parkinson's disease, hypokinetic symptoms have been associated with increased beta oscillations (13-30 Hz). We hypothesize that this pattern is symptom-specific, thus accompanying DBS-induced slowness in dystonia.

METHODS

In 6 dystonia patients, pallidal rest recordings with a sensing-enabled DBS device were performed and tapping speed was assessed using marker-less pose estimation over 5 time points following cessation of DBS.

RESULTS

After cessation of pallidal stimulation, movement speed increased over time (P < 0.01). A linear mixed-effects model revealed that pallidal beta activity explained 77% of the variance in movement speed across patients (P = 0.01).

CONCLUSIONS

The association between beta oscillations and slowness across disease entities provides further evidence for symptom-specific oscillatory patterns in the motor circuit. Our findings might help DBS therapy improvements, as DBS-devices able to adapt to beta oscillations are already commercially available. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Deep brain stimulation creates informational lesion through membrane depolarization in mouse hippocampus

Deep brain stimulation (DBS) is a promising neuromodulation therapy, but the neurophysiological mechanisms of DBS remain unclear. In awake mice, we performed high-speed membrane voltage fluorescence imaging of individual hippocampal CA1 neurons during DBS delivered at 40 Hz or 140 Hz, free of electrical interference. DBS powerfully depolarized somatic membrane potentials without suppressing spike rate, especially at 140 Hz. Further, DBS paced membrane voltage and spike timing at the stimulation frequency and reduced timed spiking output in response to hippocampal network theta-rhythmic (3-12 Hz) activity patterns. To determine whether DBS directly impacts cellular processing of inputs, we optogenetically evoked theta-rhythmic membrane depolarization at the soma. We found that DBS-evoked membrane depolarization was correlated with DBS-mediated suppression of neuronal responses to optogenetic inputs. These results demonstrate that DBS produces powerful membrane depolarization that interferes with the ability of individual neurons to respond to inputs, creating an informational lesion.

Clinical neurophysiology of Parkinson's disease and parkinsonism

•

This review is part of the series on the clinical neurophysiology of movement disorders and focuses on Parkinson’s disease and parkinsonism.

•

The pathophysiology of cardinal parkinsonian motor symptoms and myoclonus are reviewed.

•

The recordings from microelectrode and deep brain stimulation electrodes are reported in detail.

This review is part of the series on the clinical neurophysiology of movement disorders. It focuses on Parkinson’s disease and parkinsonism. The topics covered include the pathophysiology of tremor, rigidity and bradykinesia, balance and gait disturbance and myoclonus in Parkinson’s disease. The use of electroencephalography, electromyography, long latency reflexes, cutaneous silent period, studies of cortical excitability with single and paired transcranial magnetic stimulation, studies of plasticity, intraoperative microelectrode recordings and recording of local field potentials from deep brain stimulation, and electrocorticography are also reviewed. In addition to advancing knowledge of pathophysiology, neurophysiological studies can be useful in refining the diagnosis, localization of surgical targets, and help to develop novel therapies for Parkinson’s disease.

Deep brain stimulation in the subthalamic nucleus for Parkinson's disease can restore dynamics of striatal networks

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is highly effective in alleviating movement disability in patients with Parkinson’s disease (PD). However, its therapeutic mechanism of action is unknown. The healthy striatum exhibits rich dynamics resulting from an interaction of beta, gamma, and theta oscillations. These rhythms are essential to selection and execution of motor programs, and their loss or exaggeration due to dopamine (DA) depletion in PD is a major source of behavioral deficits. Restoring the natural rhythms may then be instrumental in the therapeutic action of DBS. We develop a biophysical networked model of a BG pathway to study how abnormal beta oscillations can emerge throughout the BG in PD and how DBS can restore normal beta, gamma, and theta striatal rhythms. Our model incorporates STN projections to the striatum, long known but understudied, found to preferentially target fast-spiking interneurons (FSI). We find that DBS in STN can normalize striatal medium spiny neuron activity by recruiting FSI dynamics and restoring the inhibitory potency of FSIs observed in normal conditions. We also find that DBS allows the reexpression of gamma and theta rhythms, thought to be dependent on high DA levels and thus lost in PD, through cortical noise control. Our study highlights that DBS effects can go beyond regularizing BG output dynamics to restoring normal internal BG dynamics and the ability to regulate them. It also suggests how gamma and theta oscillations can be leveraged to supplement DBS treatment and enhance its effectiveness.

Gamma Oscillations and Coherence Are Weaker in the Dorsomedial Subregion of STN in Parkinson's Disease

Background: Deep-brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for motor symptoms of advanced Parkinson's disease (PD). Due to a lack of detailed somatotopic organization in STN, the clinically most effective part of the STN for stimulation has already become one of the hot research focuses. At present, there are some reports about topographic distribution for different depths within the STN, but few about a mediolateral topography in this area.

Objective: The objective was to investigate the local field potential (LFP) distribution patterns in dorsomedial and dorsolateral subparts of STN.

Methods: In total, 18 PD patients eventually enrolled in this study. The DBS electrodes were initially located on the lateral portion of dorsolateral STN. Because of internal capsule side effects presented at low threshold (below 1.5 mA), the electrode was reimplanted more medially to the dorsomedial STN. In this process, intraoperative LFPs from dorsomedial and dorsolateral STN were recorded from the inserted electrode. Both beta power and gamma power of the LFPs were calculated using the power spectral density (PSD) for each DBS contact pair. Furthermore, coherence between any two pairs of contacts was computed in the dorsomedial and dorsolateral parts of STN, respectively. Meanwhile, the Unified Parkinson's Disease Rating Scale part III (UPDRS-III) was monitored prior to surgery and at the 6-month follow-up.

Results: Compared to the dorsolateral part of STN, gamma oscillations (p < 0.01) and coherence (p < 0.05) were all weaker in the dorsomedial part. However, no obvious differences in beta oscillations and coherence were observed between the two groups (p > 0.05). Moreover, it should be noted that DBS of the dorsomedial STN resulted in significant improvement in the UPDRS-III in PD patients. There was a 61.50 ± 21.30% improvement in UPDRS-III scores in Med-off/Stim-on state relative to the Med-off state at baseline (from 15.44 ± 6.84 to 43.94 ± 15.79, p < 0.01).

Conclusions: The specific features of gamma activity may be used to differentiate STN subregions. Moreover, the dorsomedial part of STN might be a potential target for DBS in PD.

Neurophysiological biomarkers to optimize deep brain stimulation in movement disorders

Intraoperative neurophysiological information could increase accuracy of surgical deep brain stimulation (DBS) lead placement. Subsequently, DBS therapy could be optimized by specifically targeting pathological activity. In Parkinson’s disease, local field potentials (LFPs) excessively synchronized in the beta band (13–35 Hz) correlate with akinetic-rigid symptoms and their response to DBS therapy, particularly low beta band suppression (13–20 Hz) and high frequency gamma facilitation (35–250 Hz). In dystonia, LFPs abnormally synchronize in the theta/alpha (4–13 Hz), beta and gamma (60–90 Hz) bands. Phasic dystonic symptoms and their response to DBS correlate with changes in theta/alpha synchronization. In essential tremor, LFPs excessively synchronize in the theta/alpha and beta bands. Adaptive DBS systems will individualize pathological characteristics of neurophysiological signals to automatically deliver therapeutic DBS pulses of specific spatial and temporal parameters.

The Relationship Between Electrical Energy Delivered by Deep Brain Stimulation and Levodopa-Induced Dyskinesias in Parkinson's Disease: A Retrospective Preliminary Analysis

Background: Adaptive Deep Brain Stimulation (aDBS) is now considered as a new feasible and effective paradigm to deliver DBS to patients with Parkinson's disease (PD) in such a way that not only stimulation is personalized and finely tuned to the instantaneous patient's state, but also motor improvement is obtained with a lower amount of energy transferred to the tissue. Amplitude-controlled aDBS was shown to significantly decrease the amplitude-driven total electrical energy delivered to the tissue (aTEED), an objective measure of the amount of energy transferred by DBS amplitude to the patient's brain. However, there is no direct evidence of a relationship between aTEED and the occurrence of DBS-related adverse events in humans.

Objective: In this work, we investigated the correlation of aTEED with the occurrence of levodopa-induced dyskinesias pooling all the data available from our previous experiments using aDBS and cDBS.

Methods: We retrospectively analyzed data coming from 19 patients with PD undergoing surgery for STN-DBS electrode positioning and participating to experiments involving cDBS and aDBS delivery. Patients were all studied some days after the surgery (acute setting). The aTEED and dyskinesia assessments (Rush Dyskinesia Rating Scale, RDRS) considered in the Med ON-Stim ON condition.

Results: We confirmed both that aTEED values and RDRS were significantly lower in the aDBS than in cDBS sessions (aTEED mean value, cDBS: 0.0278 ± 0.0011 j, vs. aDBS: 0.0071 ± 0.0003 j, p < 0.0001 Wilcoxon's rank sum; normalized RDRS mean score, cDBS: 0.66 ± 0.017 vs. aDBS: 0.45 ± 0.01, p = 0.025, Wilcoxon's rank sum test). In addition, we found a direct significant correlation between aTEED and RDRS (ρ = 0.44, p = 0.0032, Spearman's correlation).

Conclusions: Our results provide a first piece of evidence that aTEED is correlated to the amount of levodopa-induced dyskinesias in patients with PD undergoing STN-DBS, thus supporting the role of aDBS as feasible and safe alternative to cDBS.

Subthalamic deep brain stimulation induces finely-tuned gamma oscillations in the absence of levodopa

Finely-tuned gamma (FTG) oscillations can be recorded from cortex or the subthalamic nucleus (STN) in patients with Parkinson's disease (PD) on dopaminergic medication, and have been associated with dyskinesias. When recorded during deep brain stimulation (DBS) on medication the FTG is entrained to half the stimulation frequency. We investigated whether these characteristics are shared off medication by recording local field potentials (LFP) from the STN from externalised DBS leads in 14 PD patients after overnight withdrawal of medication. FTG was induced de-novo by DBS in the absence of dyskinesias in a third of our cohort. The FTG could outlast stimulation or arise only after DBS ceased. FTG frequencies decreased during and across consecutive DBS blocks, but did not shift with changing stimulation frequency off medication. Together with the sustained after-effects this argues against simple entrainment by DBS in the off medication state. We also found significant coherence between STN-LFP and electroencephalogram (EEG) signals at FTG frequencies. We conclude that FTG is a network phenomenon that behaves differently in the off medication state, when it is neither associated with dyskinesias nor susceptible to entrainment.

Cross-frequency coupling between gamma oscillations and deep brain stimulation frequency in Parkinson's disease

The disruption of pathologically enhanced beta oscillations is considered one of the key mechanisms mediating the clinical effects of deep brain stimulation on motor symptoms in Parkinson's disease. However, a specific modulation of other distinct physiological or pathological oscillatory activities could also play an important role in symptom control and motor function recovery during deep brain stimulation. Finely tuned gamma oscillations have been suggested to be prokinetic in nature, facilitating the preferential processing of physiological neural activity. In this study, we postulate that clinically effective high-frequency stimulation of the subthalamic nucleus imposes cross-frequency interactions with gamma oscillations in a cortico-subcortical network of interconnected regions and normalizes the balance between beta and gamma oscillations. To this end we acquired resting state high-density (256 channels) EEG from 31 patients with Parkinson's disease who underwent deep brain stimulation to compare spectral power and power-to-power cross-frequency coupling using a beamformer algorithm for coherent sources. To show that modulations exclusively relate to stimulation frequencies that alleviate motor symptoms, two clinically ineffective frequencies were tested as control conditions. We observed a robust reduction of beta and increase of gamma power, attested in the regions of a cortical (motor cortex, supplementary motor area, premotor cortex) and subcortical network (subthalamic nucleus and cerebellum). Additionally, we found a clear cross-frequency coupling of narrowband gamma frequencies to the stimulation frequency in all of these nodes, which negatively correlated with motor impairment. No such dynamics were revealed within the control posterior parietal cortex region. Furthermore, deep brain stimulation at clinically ineffective frequencies did not alter the source power spectra or cross-frequency coupling in any region. These findings demonstrate that clinically effective deep brain stimulation of the subthalamic nucleus differentially modifies different oscillatory activities in a widespread network of cortical and subcortical regions. Particularly the cross-frequency interactions between finely tuned gamma oscillations and the stimulation frequency may suggest an entrainment mechanism that could promote dynamic neural processing underlying motor symptom alleviation.

Optimal open-loop desynchronization of neural oscillator populations

Deep brain stimulation (DBS) is an increasingly used medical treatment for various neurological disorders. While its mechanisms are not fully understood, experimental evidence suggests that through application of periodic electrical stimulation DBS may act to desynchronize pathologically synchronized populations of neurons resulting desirable changes to a larger brain circuit. However, the underlying mathematical mechanisms by which periodic stimulation can engender desynchronization in a coupled population of neurons is not well understood. In this work, a reduced phase-amplitude reduction framework is used to characterize the desynchronizing influence of periodic stimulation on a population of coupled oscillators. Subsequently, optimal control theory allows for the design of periodic, open-loop stimuli with the capacity to destabilize completely synchronized solutions while simultaneously stabilizing rotating block solutions. This framework exploits system nonlinearities in order to strategically modify unstable Floquet exponents. In the limit of weak neural coupling, it is shown that this method only requires information about the phase response curves of the individual neurons. The effects of noise and heterogeneity are also considered and numerical results are presented. This framework could ultimately be used to inform the design of more efficient deep brain stimulation waveforms for the treatment of neurological disease.

Dysphonia and Dysarthria in People With Parkinson's Disease After Subthalamic Nucleus Deep Brain Stimulation: Effect of Frequency Modulation

PURPOSE

Subthalamic nucleus deep brain stimulation (STN-DBS) parameters, for example the frequency of stimulation, seem to affect speech and voice aspects. However, this influence is not well understood. This study aimed to investigate the impact of low- and high-frequency STN-DBS on voice and speech for people with Parkinson's disease.

METHODS

Nineteen individuals with Parkinson's disease who received bilateral STN-DBS were assessed for motor performance (Unified Parkinson's Disease Rating Scale-III), perceptual evaluation of voice (grade, roughness, breathiness, asthenia, strain, and instability [GRBASI]), dysarthria assessment, and computerized acoustic analysis of voice upon receiving low-frequency (60 Hz) and high-frequency (130 Hz) STN-DBS.

RESULTS

In the GRBASI protocol, asthenia, and instability were significantly better at 130 Hz of stimulation. In the dysarthria evaluation, the phonation aspect, articulation, and grade of dysarthria showed deterioration at the same high-frequency condition. There was no significant difference for any vocal acoustic measures.

CONCLUSION

The high-frequency of STN-DBS may affect speech and voice differently, leading to an amelioration of the vocal production, but with adverse effects in the speech control.

Alternate Subthalamic Nucleus Deep Brain Stimulation Parameters to Manage Motor Symptoms of Parkinson's Disease: Systematic Review and Meta-analysis

Background

The use of alternate frequencies, amplitudes, and pulse widths to manage motor symptoms in Parkinson's disease (PD) patients with subthalamic nucleus deep brain stimulation (STN-DBS) is of clinical interest, but currently lacks systematic evidence.

Objective/Hypothesis

Systematically review whether alternate STN-DBS settings influence the therapy's efficacy for managing PD motor symptoms.

Methods

Systematic searches identified studies that; involved bilateral STN-DBS PD patients; manipulated ≥ 1 STN-DBS parameter (e.g., amplitude); assessed ≥ 1 motor symptom (e.g., tremor); and contrasted the experimental and chronic stimulation settings. A Mantel-Haenszel random-effects meta-analysis compared the UPDRS-III sub-scores at low (60-Hz) and high frequencies ( ≥ 130 Hz). Inter-study heterogeneity was assessed with the Cohen's χ² and I² index, while the standard GRADE evidence assessment examined strength of evidence.

Results

Of the 21 included studies, 17 investigated the effect of alternate stimulation frequencies, five examined alternate stimulation amplitudes, and two studied changes in pulse width. Given the available data, meta-analyses were only possible for alternate stimulation frequencies. Analysis of the heterogeneity amongst the included studies indicated significant variability between studies and, on the basis of the GRADE framework, the pooled evidence from the meta-analysis studies was of very low quality due to the significant risks of bias.

Conclusions

The meta-analysis reported a very low quality of evidence for the efficacy of low-frequency STN-DBS for managing PD motor symptoms. Furthermore, it highlighted that lower amplitudes lead to the re-emergence of motor symptoms and further research is needed to understand the potential benefits of alternate STN-DBS parameters for PD patients.

Future perspectives on neural mechanisms underlying rhythm and music based neurorehabilitation in Parkinson's disease

Parkinson's disease (PD) is characterized primarily by a dysfunctional basal ganglia (BG) system, producing motor and non-motor symptoms. A significant number of studies have demonstrated that rhythmic auditory stimulation can improve gait and other motor behaviors in PD that are not well managed by the conventional therapy. As music, being highly complex stimulus, can modulate brain activity/function in distributed areas of brain, the therapeutic properties of music potentially extend to alleviate non-motor symptoms of PD. Despite the clinical, behavioral evidence and promises of rhythm and music based interventions, the neural substrates underlying the effectiveness are poorly understood. The goal of this review is to appraise the current state of knowledge in order to direct further neuroimaging studies that help to determine the therapeutic effects of rhythm and music based interventions for motor and non-motor symptoms of PD.

Beneficial effects of bilateral subthalamic stimulation on alexithymia in Parkinson's disease

BACKGROUND AND PURPOSE

Subthalamic nucleus (STN) deep brain stimulation (DBS) improves quality of life (QoL) and motor and non-motor symptoms in advanced Parkinson's disease (PD). However, its effect on alexithymia and its relationship to other neuropsychiatric symptoms and QoL in PD is unclear.

METHODS

In this prospective, observational study of 39 patients with PD undergoing STN-DBS, we examined the Parkinson's Disease Questionnaire-8 (PDQ-8), 20-item Toronto Alexithymia Scale (TAS-20), Hospital Anxiety and Depression Scale (HADS), Self-Report Manic Inventory (SRMI), Apathy Evaluation Scale (AES), Unified Parkinson's Disease Rating Scale (UPDRS) activities of daily living, UPDRS motor examination and UPDRS complications (UPDRS-II/-III/-IV) and levodopa-equivalent daily dose (LEDD) pre-operatively and at 5-month follow-up. Outcome changes were tested with Wilcoxon signed-rank or paired t-test when parametric tests were applicable and corrected for multiple comparisons. The relationship between outcome changes was explored with bivariate correlations. Additionally, partial correlations between PDQ-8 and TAS-20 were computed controlling for HADS, SRMI and AES change scores. Predictor analyses for PDQ-8 improvement were calculated for all baseline parameters.

RESULTS

The baseline prevalence of alexithymia was 17.9%. We observed significant beneficial effects of STN-DBS on PDQ-8, TAS-20, HADS, UPDRS-II, -III and -IV scores and significant LEDD reduction. The correlation between TAS-20 and PDQ-8 improvements remained significant after controlling for all other aforementioned outcomes. Predictor analyses for PDQ-8 improvement were significant for PDQ-8 and TAS-20.

CONCLUSIONS

This is the first report of beneficial effects of STN-DBS on alexithymia. Alexithymia was significantly associated with QoL outcome independent of anxiety, depression, mania and apathy. Our study highlights the importance of alexithymia for holistic assessments of DBS outcomes.

Automated Deep Brain Stimulation Programming for Tremor

Deep brain stimulation (DBS) programming, the systematic selection of fixed electrical stimulation parameters that deliver maximal therapeutic benefit while limiting side effects, poses several challenges in the treatment of movement disorders. DBS programming requires the expertise of trained neurologists or nurses who assess patient symptoms according to standardized clinical rating scales and use patient reports of DBS-related side effects to adjust stimulation parameters and optimize therapy. In this paper, we describe and validate an automated software platform for DBS programming for tremor associated with Parkinson's disease and essential tremor. DBS parameters are changed automatically through a direct computer interface with implanted neurostimulators. Each tested DBS setting is ranked according to its effect on tremor, which is assessed using smartwatch inertial measurement unit data, and side effects, which are reported through a user interface. Blinded neurologist assessments showed the automated programming method performed at least as well as clinician mediated programming in selecting the optimal settings for tremor therapy. This proof of concept study describes a novel DBS programming paradigm that may improve programming efficiency and outcomes, increase access to programming outside specialty clinics, and aid in the development of adaptive and closed-loop DBS strategies.

Toward adaptive deep brain stimulation in Parkinson's disease: a review

Clinical deep brain stimulation (DBS) is now regarded as the therapeutic intervention of choice at the advanced stages of Parkinson's disease. However, some major challenges of DBS are stimulation induced side effects and limited pacemaker battery life. Side effects and shortening of pacemaker battery life are mainly as a result of continuous stimulation and poor stimulation focus. These drawbacks can be mitigated using adaptive DBS (aDBS) schemes. Side effects resulting from continuous stimulation can be reduced through adaptive control using closed-loop feedback, while those due to poor stimulation focus can be mitigated through spatial adaptation. Other advantages of aDBS include automatic, rather than manual, initial adjustment and programming, and long-term adjustments to maintain stimulation parameters with changes in patient's condition. Both result in improved efficacy. This review focuses on the major areas that are essential in driving technological advances for the various aDBS schemes. Their challenges, prospects and progress so far are analyzed. In addition, important advances and milestones in state-of-the-art aDBS schemes are highlighted – both for closed-loop adaption and spatial adaption. With perspectives and future potentials of DBS provided at the end.

Dopamine-dependent scaling of subthalamic gamma bursts with movement velocity in patients with Parkinson's disease

Gamma synchronization increases during movement and scales with kinematic parameters. Here, disease-specific characteristics of this synchronization and the dopamine-dependence of its scaling in Parkinson's disease are investigated. In 16 patients undergoing deep brain stimulation surgery, movements of different velocities revealed that subthalamic gamma power peaked in the sensorimotor part of the subthalamic nucleus, correlated positively with maximal velocity and negatively with symptom severity. These effects relied on movement-related bursts of transient synchrony in the gamma band. The gamma burst rate highly correlated with averaged power, increased gradually with larger movements and correlated with symptom severity. In the dopamine-depleted state, gamma power and burst rate significantly decreased, particularly when peak velocity was slower than ON medication. Burst amplitude and duration were unaffected by the medication state. We propose that insufficient recruitment of fast gamma bursts during movement may underlie bradykinesia as one of the cardinal symptoms in Parkinson's disease.

Algorithmic design of a noise-resistant and efficient closed-loop deep brain stimulation system: A computational approach

Advances in the field of closed-loop neuromodulation call for analysis and modeling approaches capable of confronting challenges related to the complex neuronal response to stimulation and the presence of strong internal and measurement noise in neural recordings. Here we elaborate on the algorithmic aspects of a noise-resistant closed-loop subthalamic nucleus deep brain stimulation system for advanced Parkinson’s disease and treatment-refractory obsessive-compulsive disorder, ensuring remarkable performance in terms of both efficiency and selectivity of stimulation, as well as in terms of computational speed. First, we propose an efficient method drawn from dynamical systems theory, for the reliable assessment of significant nonlinear coupling between beta and high-frequency subthalamic neuronal activity, as a biomarker for feedback control. Further, we present a model-based strategy through which optimal parameters of stimulation for minimum energy desynchronizing control of neuronal activity are being identified. The strategy integrates stochastic modeling and derivative-free optimization of neural dynamics based on quadratic modeling. On the basis of numerical simulations, we demonstrate the potential of the presented modeling approach to identify, at a relatively low computational cost, stimulation settings potentially associated with a significantly higher degree of efficiency and selectivity compared with stimulation settings determined post-operatively. Our data reinforce the hypothesis that model-based control strategies are crucial for the design of novel stimulation protocols at the backstage of clinical applications.

Optimized temporal pattern of brain stimulation designed by computational evolution

Brain stimulation is a promising therapy for several neurological disorders, including Parkinson's disease. Stimulation parameters are selected empirically and are limited to the frequency and intensity of stimulation. We varied the temporal pattern of deep brain stimulation to ameliorate symptoms in a parkinsonian animal model and in humans with Parkinson's disease. We used model-based computational evolution to optimize the stimulation pattern. The optimized pattern produced symptom relief comparable to that from standard high-frequency stimulation (a constant rate of 130 or 185 Hz) and outperformed frequency-matched standard stimulation in a parkinsonian rat model and in patients. Both optimized and standard high-frequency stimulation suppressed abnormal oscillatory activity in the basal ganglia of rats and humans. The results illustrate the utility of model-based computational evolution of temporal patterns to increase the efficiency of brain stimulation in treating Parkinson's disease and thereby reduce the energy required for successful treatment below that of current brain stimulation paradigms.

Proceedings of the Fourth Annual Deep Brain Stimulation Think Tank: A Review of Emerging Issues and Technologies

This paper provides an overview of current progress in the technological advances and the use of deep brain stimulation (DBS) to treat neurological and neuropsychiatric disorders, as presented by participants of the Fourth Annual DBS Think Tank, which was convened in March 2016 in conjunction with the Center for Movement Disorders and Neurorestoration at the University of Florida, Gainesveille FL, USA. The Think Tank discussions first focused on policy and advocacy in DBS research and clinical practice, formation of registries, and issues involving the use of DBS in the treatment of Tourette Syndrome. Next, advances in the use of neuroimaging and electrochemical markers to enhance DBS specificity were addressed. Updates on ongoing use and developments of DBS for the treatment of Parkinson's disease, essential tremor, Alzheimer's disease, depression, post-traumatic stress disorder, obesity, addiction were presented, and progress toward innovation(s) in closed-loop applications were discussed. Each section of these proceedings provides updates and highlights of new information as presented at this year's international Think Tank, with a view toward current and near future advancement of the field.

State of the Art for Deep Brain Stimulation Therapy in Movement Disorders: A Clinical and Technological Perspective

Deep brain stimulation (DBS) therapy is a widely used brain surgery that can be applied for many neurological and psychiatric disorders. DBS is American Food and Drug Administration approved for medication refractory Parkinson's disease, essential tremor and dystonia. Although DBS has shown consistent success in many clinical trials, the therapy has limitations and there are well-recognized complications. Thus, only carefully selected patients are ideal candidates for this surgery. Over the last two decades, there have been significant advances in clinical knowledge on DBS. In addition, the surgical techniques and technology related to DBS has been rapidly evolving. The goal of this review is to describe the current status of DBS in the context of movement disorders, outline the mechanisms of action for DBS in brief, discuss the standard surgical and imaging techniques, discuss the patient selection and clinical outcomes in each of the movement disorders, and finally, introduce the recent advancements from a clinical and technological perspective.

Low-frequency deep brain stimulation for Parkinson's disease: Great expectation or false hope?

The long-term efficacy of subthalamic deep brain stimulation for Parkinson's disease is not always retained, and many patients lose the improvement achieved during the "second honeymoon" following surgery. Deep brain stimulation is a versatile tool, as stimulation parameters may undergo a fine-tuning depending on clinical needs. Among them, frequency is the parameter that leads to more complex scenarios because there is no generalizable relationship between its modulation and the overall clinical response, which also depends on the specific considered sign. High-frequency stimulation (>100 Hz) has shown to be effective in improving most parkinsonian signs, particularly the levodopa-responsive ones. However, its effect on axial signs (such as balance, gait, speech, or swallowing) may not be sustained, minimal, or even detrimental. For these reasons, several studies have explored the effectiveness of low-frequency stimulation (generally 60 or 80 Hz). Methods, results, and especially interpretations of these studies are quite variable. Although the use of low-frequency stimulation certainly opens new avenues in the field of deep brain stimulation, after having gathered all the available evidence in patients with subthalamic implants, our conclusion is that it might be clinically useful mainly when it lessens the detrimental effects of high-frequency stimulation. © 2016 International Parkinson and Movement Disorder Society.

Deep brain stimulation for obesity: past, present, and future targets

The authors review the history of deep brain stimulation (DBS) in patients for treating obesity, describe current DBS targets in the brain, and discuss potential DBS targets and nontraditional stimulation parameters that may improve the effectiveness of DBS for ameliorating obesity. Deep brain stimulation for treating obesity has been performed both in animals and in humans with intriguing preliminary results. The brain is an attractive target for addressing obesity because modulating brain activity may permit influencing both sides of the energy equation--caloric intake and energy expenditure.

Mechanisms of deep brain stimulation

Deep brain stimulation (DBS) is widely used for the treatment of movement disorders including Parkinson's disease, essential tremor, and dystonia and, to a lesser extent, certain treatment-resistant neuropsychiatric disorders including obsessive-compulsive disorder. Rather than a single unifying mechanism, DBS likely acts via several, nonexclusive mechanisms including local and network-wide electrical and neurochemical effects of stimulation, modulation of oscillatory activity, synaptic plasticity, and, potentially, neuroprotection and neurogenesis. These different mechanisms vary in importance depending on the condition being treated and the target being stimulated. Here we review each of these in turn and illustrate how an understanding of these mechanisms is inspiring next-generation approaches to DBS.

Origins and suppression of oscillations in a computational model of Parkinson's disease

Efficacy of deep brain stimulation (DBS) for motor signs of Parkinson's disease (PD) depends in part on post-operative programming of stimulus parameters. There is a need for a systematic approach to tuning parameters based on patient physiology. We used a physiologically realistic computational model of the basal ganglia network to investigate the emergence of a 34 Hz oscillation in the PD state and its optimal suppression with DBS. Discrete time transfer functions were fit to post-stimulus time histograms (PSTHs) collected in open-loop, by simulating the pharmacological block of synaptic connections, to describe the behavior of the basal ganglia nuclei. These functions were then connected to create a mean-field model of the closed-loop system, which was analyzed to determine the origin of the emergent 34 Hz pathological oscillation. This analysis determined that the oscillation could emerge from the coupling between the globus pallidus external (GPe) and subthalamic nucleus (STN). When coupled, the two resonate with each other in the PD state but not in the healthy state. By characterizing how this oscillation is affected by subthreshold DBS pulses, we hypothesize that it is possible to predict stimulus frequencies capable of suppressing this oscillation. To characterize the response to the stimulus, we developed a new method for estimating phase response curves (PRCs) from population data. Using the population PRC we were able to predict frequencies that enhance and suppress the 34 Hz pathological oscillation. This provides a systematic approach to tuning DBS frequencies and could enable closed-loop tuning of stimulation parameters.

A neurochemical closed-loop controller for deep brain stimulation: toward individualized smart neuromodulation therapies

Current strategies for optimizing deep brain stimulation (DBS) therapy involve multiple postoperative visits. During each visit, stimulation parameters are adjusted until desired therapeutic effects are achieved and adverse effects are minimized. However, the efficacy of these therapeutic parameters may decline with time due at least in part to disease progression, interactions between the host environment and the electrode, and lead migration. As such, development of closed-loop control systems that can respond to changing neurochemical environments, tailoring DBS therapy to individual patients, is paramount for improving the therapeutic efficacy of DBS. Evidence obtained using electrophysiology and imaging techniques in both animals and humans suggests that DBS works by modulating neural network activity. Recently, animal studies have shown that stimulation-evoked changes in neurotransmitter release that mirror normal physiology are associated with the therapeutic benefits of DBS. Therefore, to fully understand the neurophysiology of DBS and optimize its efficacy, it may be necessary to look beyond conventional electrophysiological analyses and characterize the neurochemical effects of therapeutic and non-therapeutic stimulation. By combining electrochemical monitoring and mathematical modeling techniques, we can potentially replace the trial-and-error process used in clinical programming with deterministic approaches that help attain optimal and stable neurochemical profiles. In this manuscript, we summarize the current understanding of electrophysiological and electrochemical processing for control of neuromodulation therapies. Additionally, we describe a proof-of-principle closed-loop controller that characterizes DBS-evoked dopamine changes to adjust stimulation parameters in a rodent model of DBS. The work described herein represents the initial steps toward achieving a “smart” neuroprosthetic system for treatment of neurologic and psychiatric disorders.

The role of frontostriatal impairment in freezing of gait in Parkinson's disease

Freezing of gait (FOG) is a disabling symptom of advanced Parkinson's disease (PD) that leads to an increased risk of falls and nursing home placement. Interestingly, multiple lines of evidence suggest that the manifestation of FOG is related to specific deficits in cognition, such as set shifting and the ability to process conflict-related signals. These findings are consistent with the specific patterns of abnormal cortical processing seen during functional neuroimaging experiments of FOG, implicating increased neural activation within cortical structures underlying cognition, such as the Cognitive Control Network. In addition, these studies show that freezing episodes are associated with abnormalities in the BOLD response within key structures of the basal ganglia, such as the striatum and the subthalamic nucleus. In this article, we discuss the implications of these findings on current models of freezing behavior and propose an updated model of basal ganglia impairment during FOG episodes that integrates the neural substrates of freezing from the cortex and the basal ganglia to the cognitive dysfunctions inherent in the condition.

MEG studies of motor cortex gamma oscillations: evidence for a gamma "fingerprint" in the brain?

The human motor cortex exhibits transient bursts of high frequency gamma oscillations in the 60–90 Hz range during movement. It has been proposed that gamma oscillations generally reflect local intracortical activity. However, movement-evoked gamma is observed simultaneously in both cortical and subcortical (basal ganglia) structures and thus appears to reflect long-range cortical-subcortical interactions. Recent evidence suggests that gamma oscillations do not simply reflect sensory reafference, but have a facilitative role in movement initiation. Here we summarize contributions of MEG to our understanding of movement-evoked gamma oscillations, including evidence that transient gamma bursts during the performance of specific movements constitutes a stereotyped spectral and temporal pattern within individuals—a gamma “fingerprint”—that is highly stable over time. Although their functional significance remains to be fully understood, movement-evoked gamma oscillations may represent frequency specific tuning within cortical-subcortical networks that can be monitored non-invasively using MEG during a variety of motor tasks, and may provide important information regarding cortical dynamics of ongoing motor control.

Movement related dynamics of subthalmo-cortical alpha connectivity in Parkinson's disease

Functional neurosurgical techniques provide a unique opportunity to explore patterns of interaction between the cerebral cortex and basal ganglia in patients with Parkinson's disease (PD). Previous work using simultaneous magnetoencephalographic (MEG) and local field potential (LFP) recordings from the region of the subthalamic nucleus (STNr) has characterised resting patterns of connectivity in the alpha and beta frequency bands and their modulation by dopaminergic medication. Recently we have also characterised the effect of movement on patterns of gamma band coherence between the STNr and cortical sites. Here we specifically investigate how the prominent coherence between the STNr and temporal cortex in the alpha band is modulated by movement both on and off dopaminergic medication in patients following the insertion of Deep Brain Stimulation (DBS) electrodes. We show that movement is associated with a suppression of local alpha power in the temporal cortex and STNr that begins about 2 s prior to a self-paced movement and is independent of dopaminergic status. In contrast, the peak reduction in coherence between these sites occurs after movement onset and is more marked in the on than in the off dopaminergic medication state. The difference in alpha band coherence on and off medication was found to correlate with the drug related improvement in clinical parameters. Overall, the movement-related behaviour of activities in the alpha band in patients with PD serves to highlight the role of dopamine in modulating large-scale, interregional synchronisation.

Reduced dynamics for delayed systems with harmonic or stochastic forcing

The analysis of nonlinear delay-differential equations (DDEs) subjected to external forcing is difficult due to the infinite dimensionality of the space in which they evolve. To simplify the analysis of such systems, the present work develops a non-homogeneous center manifold (CM) reduction scheme, which allows the derivation of a time-dependent order parameter equation in finite dimension. This differential equation captures the major dynamical features of the delayed system. The forcing is assumed to be small compared to the amplitude of the autonomous system, in order to cause only small variations of the fixed points and of the autonomous CM. The time-dependent CM is shown to satisfy a non-homogeneous partial differential equation. We first briefly review CM theory for DDEs. Then we show, for the general scalar case, how an ansatz that separates the CM into one for the autonomous problem plus an additional time-dependent order-two correction leads to satisfying results. The paper then details the application to a transcritical bifurcation subjected to single or multiple periodic forcings. The validity limits of the reduction scheme are also highlighted. Finally, we characterize the specific case of additive stochastic driving of the transcritical bifurcation, where additive white noise shifts the mode of the probability density function of the state variable to larger amplitudes.

The epistemology of Deep Brain Stimulation and neuronal pathophysiology

Deep Brain Stimulation (DBS) is a remarkable therapy succeeding where all manner of pharmacological manipulations and brain transplants fail. The success of DBS has resurrected the relevance of electrophysiology and dynamics on the order of milliseconds. Despite the remarkable effects of DBS, its mechanisms of action are largely unknown. There has been an expanding catalogue of various neuronal and neural responses to DBS or DBS-like stimulation but no clear conceptual encompassing explanatory scheme has emerged despite the technological prowess and intellectual sophistication of the scientists involved. Something is amiss. If the scientific observations are sound, then why has there not been more progress? The alternative is that it may be the hypotheses that frame the questions are at fault as well as the methods of inference (logic) used to validate the hypotheses. An analysis of the past and current notions of the DBS mechanisms of action is the subject in order to identify the presuppositions (premises) and logical fallacies that may be at fault. The hope is that these problems will be avoided in the future so the DBS can realize its full potential quickly. In this regard, the discussion of the methods of inference and presuppositions that underlie many current notions is no different then a critique of experimental methods common in scientific discussions and consequently, examinations of the epistemology and logic are appropriate. This analysis is in keeping with the growing appreciation among scientists and philosophers of science, the scientific observations (data) to not “speak for themselves” nor is the scientific method self-evidently true and that consideration of the underlying inferential methods is necessary.