Closed-loop Deep Brain Stimulation Research Articles

Local vs. volume conductance activity of field potentials in the human subthalamic nucleus.

Subthalamic nucleus field potentials have attracted growing research and clinical interest over the last few decades. However, it is unclear whether subthalamic field potentials represent locally generated neuronal subthreshold activity or volume conductance of the organized neuronal activity generated in the cortex. This study aimed at understanding of the physiological origin of subthalamic field potentials and determining the most accurate method for recording them. We compared different methods of recordings in the human subthalamic nucleus: spikes (300-9,000 Hz) and field potentials (3-100 Hz) recorded by monopolar micro- and macroelectrodes, as well as by differential-bipolar macroelectrodes. The recordings were done outside and inside the subthalamic nucleus during electrophysiological navigation for deep brain stimulation procedures (150 electrode trajectories) in 41 Parkinson's disease patients. We modeled the signal and estimated the contribution of nearby/independent vs. remote/common activity in each recording configuration and area. Monopolar micro- and macroelectrode recordings detect field potentials that are considerably affected by common (probably cortical) activity. However, bipolar macroelectrode recordings inside the subthalamic nucleus can detect locally generated potentials. These results are confirmed by high correspondence between the model predictions and actual correlation of neuronal activity recorded by electrode pairs. Differential bipolar macroelectrode subthalamic field potentials can overcome volume conductance effects and reflect locally generated neuronal activity. Bipolar macroelectrode local field potential recordings might be used as a biological marker of normal and pathological brain functions for future electrophysiological studies and navigation systems as well as for closed-loop deep brain stimulation paradigms.NEW & NOTEWORTHY Our results integrate a new method for human subthalamic recordings with a development of an advanced mathematical model. We found that while monopolar microelectrode and macroelectrode recordings detect field potentials that are considerably affected by common (probably cortical) activity, bipolar macroelectrode recordings inside the subthalamic nucleus (STN) detect locally generated potentials that are significantly different than those recorded outside the STN. Differential bipolar subthalamic field potentials can be used in navigation and closed-loop deep brain stimulation paradigms.

A platform for long-term monitoring the deep brain rhythms

Deep brain stimulation (DBS) provides a valuable platform for recording local field potentials (LFP) during surgery for studying the mechanisms of brain diseases and DBS therapy. Long-term neural activity monitoring remains a necessity for research on some neurodegenerative disorders and closed-loop DBS systems. A neurostimulator with recording ability has been developed as a research tool and a medical device. This study investigates the feasibility of chronic electrophysiological studies using neurostimulator (model G102RS) for recording LFP. Recent studies have suggested that oscillatory beta band activity can be used as a biomarker of Parkinson’s disease (PD). Here, subthalamic LFP recordings were obtained from (i) a group of PD patients undergoing DBS therapy, (ii) the1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) lesioned monkey model of PD, and (iii) a PD patient with an implanted neurostimulator. A total of 55/60 LFP datasets measured from the PD patients at rest during the operation contained spectral peaks in beta band as pathophysiological oscillations. These oscillations were strongly suppressed during DBS. The long-term animal experiment and the clinical implant demonstrated that the G102RS can adequately record the long-term frequency band-specific amplitude fluctuations such as the beta band activity. The device could identify the suppression of the beta band activity during DBS. Together, these data demonstrate the use of this medical device for chronic electrophysiological studies.

Neurosurgery of the future: Deep brain stimulations and manipulations

Important advances are afoot in the field of neurosurgery—particularly in the realms of deep brain stimulation (DBS), deep brain manipulation (DBM), and the newly introduced refinement “closed-loop” deep brain stimulation (CLDBS). Use of closed-loop technology will make both DBS and DBM more precise as procedures and will broaden their indications. CLDBS utilizes as feedback a variety of sources of electrophysiological and neurochemical afferent information about the function of the brain structures to be treated or studied. The efferent actions will be either electric, i.e. the classic excitatory or inhibitory ones, or micro-injection of such things as neural proteins and transmitters, neural grafts, implants of pluripotent stem cells or mesenchymal stem cells, and some variants of gene therapy. The pathologies to be treated, beside Parkinson's disease and movement disorders, include repair of neural tissues, neurodegenerative pathologies, psychiatric and behavioral dysfunctions, i.e. schizophrenia in its various guises, bipolar disorders, obesity, anorexia, drug addiction, and alcoholism. The possibility of using these new modalities to treat a number of cognitive dysfunctions is also under consideration. Because the DBS-CLDBS technology brings about a cross-fertilization between scientific investigation and surgical practice, it will also contribute to an enhanced understanding of brain function.

Need for multiple biomarkers to adjust parameters of closed-loop deep brain stimulation for Parkinson's disease.

Need for multiple biomarkers to adjust parameters of closed-loop deep brain stimulation for Parkinson's disease.

Emerging strategies in the management of essential tremor.

Currently available therapies for essential tremor (ET) provide sufficient control only for less than a half of patients and many unmet needs exist. This is in part due to the empiric nature of existing treatment options and persisting uncertainties about the pathogenesis of ET. The emerging concept of ET as a possible neurodegenerative disorder, better understanding of associated biochemical changes, including alterations in the γ-aminobutyric acid (GABA)-ergic system and gap junctions, and the identification of the role of the leucine-rich repeat and immunoglobulin-like domain-containing 1 (LINGO-1) gene in ET pathogenesis suggest new avenues for more targeted therapies. Here we review the most promising new approaches to treating ET, including allosteric modulation of GABA receptors and modifications of the LINGO-1 pathway. Medically refractory tremor can be successfully treated by high-frequency deep brain stimulation (DBS) of the ventral intermediate nucleus, but surgical therapies are also fraught with limitations due to adverse effects of stimulation and the loss of therapeutic response. The selection of additional thalamic and extrathalamic targets for electrode placements and the development of a closed-loop DBS system enabling automatic adjustment of stimulation parameters in response to changes in electrophysiologic brain activity are also reviewed. Tremor cancellation methods using exoskeleton and external hand-held devices are also briefly discussed.

Sixty-hertz stimulation improves bradykinesia and amplifies subthalamic low-frequency oscillations.

The objective of this study was to investigate the hypothesis that attenuation of subthalamic nucleus (STN) alpha-/beta-band oscillations is causal to improvement in bradykinesia. STN local field potentials from a sensing neurostimulator (Activa® PC+S; Medtronic, Inc.) and kinematics from wearable sensors were recorded simultaneously during 60- and 140-Hz deep brain stimulation (DBS) in 9 freely moving PD subjects (15 STNs) performing repetitive wrist flexion-extension. Kinematics were recorded during 20-Hz DBS in a subgroup. Both 60- and 140-Hz DBS improved the angular velocity and frequency of movement (P=0.002 and P=0.029, respectively, for 60 Hz; P<0.001 and P<0.001, respectively, for 140 Hz), but 60-Hz DBS did not attenuate beta-band power (13-30 Hz). In fact, 60-Hz DBS amplified alpha/low-beta (11-15 Hz, P=0.007) and attenuated high-beta power (19-27 Hz, P<0.001), whereas 140-Hz DBS broadly attenuated beta power (15-30 Hz, P<0.001). Only 60-Hz DBS improved the regularity of angular range (P=0.046) and 20-Hz DBS did not worsen bradykinesia. There was no correlation between beta-power modulation and bradykinesia. These novel results obtained from freely moving PD subjects demonstrated that both 140- and 60-Hz DBS improved bradykinesia and attenuated high beta oscillations; however, 60-Hz DBS amplified a subband of alpha/low-beta oscillations, and DBS at a beta-band frequency did not worsen bradykinesia. Based on recent literature, we suggest that both 140- and 60-Hz DBS decouple the cortico-STN hyperdirect pathway, whereas 60-Hz DBS increases coupling within striato-STN circuitry. These results inform future algorithms for closed-loop DBS in PD. © 2016 International Parkinson and Movement Disorder Society.

Prediction and detection of seizures from simultaneous thalamic and scalp electroencephalography recordings.

OBJECTIVE The authors explored the feasibility of seizure detection and prediction using signals recorded from the anterior thalamic nucleus, a major target for deep brain stimulation (DBS) in the treatment of epilepsy. METHODS Using data from 5 patients (13 seizures in total), the authors performed a feasibility study and analyzed the performance of a seizure prediction and detection algorithm applied to simultaneously acquired scalp and thalamic electroencephalography (EEG). The thalamic signal was obtained from DBS electrodes. The applied algorithm used the similarity index as a nonlinear measure for seizure identification, with patient-specific channel and threshold selection. Receiver operating characteristic (ROC) curves were calculated using data from all patients and channels to compare the performance between DBS and EEG recordings. RESULTS Thalamic DBS recordings were associated with a mean prediction rate of 84%, detection rate of 97%, and false-alarm rate of 0.79/hr. In comparison, scalp EEG recordings were associated with a mean prediction rate of 71%, detection rate of 100%, and false-alarm rate of 1.01/hr. From the ROC curves, when considering all channels, DBS outperformed EEG for both detection and prediction of seizures. CONCLUSIONS This is the first study to compare automated seizure detection and prediction from simultaneous thalamic and scalp EEG recordings. The authors have demonstrated that signals recorded from DBS leads are more robust than EEG recordings and can be used to predict and detect seizures. These results indicate feasibility for future designs of closed-loop anterior nucleus DBS systems for the treatment of epilepsy.

EP 4. Long term recordings of deep brain activity from the subthalamic nucleus in PD patients using PC+S

Introduction Oscillatory activity in the beta frequency band has been consistently found in the basal ganglia of patients with Parkinson’s disease (PD) and was related to bradykinesia and rigidity. Therefore, it has been suggested as a potential biomarker for closed-loop deep brain stimulation in PD. However, so far deep brain recordings have been feasible only for a short time window during electrode implantation before the leads are connected to the pulse generator. More recently, local field potential (LFP) neuronal activity can be recorded by using a chronically implanted pulse generator (Activa PC+S; Medtronic). Objectives To investigate stability of oscillatory activity in the beta frequency band in PD patients over a period of 8 months post implantation of a pulse generator device, -a prerequisite for its usability as future biomarker for closed-loop stimulation. Patients & methods Recordings from two contact pairs (E1E2, E2E3) of 12 PD patients (4 female, 8 male patients; mean age at implantation: 63.2 years; range 56–72 years) who received the Activa PC+S device for deep brain stimulation (DBS) therapy were included in the study. Rest recordings were conducted using the chronically implanted pulse generator under ON and OFF medication condition at Baseline, 3 months and 8 months post implantation. Channels were not used for stimulation at the time of LFP recordings. UPDRS was obtained for all patients at each time point. Analysis was performed using fast Fourier transform based methods. Beta power was calculated as percentage relative spectral power separately for ON/OFF condition. For further visualization of beta peaks across all subjects we realigned the individual peak frequency in the range of −5 Hz to +10 Hz before averaging. Moreover peak power was correlated with UPDRS motor scores. Results Power spectra averaged across all contacts in all subjects showed distinct peaks in the beta band at 3 and 8 months follow up but not at baseline. This was partly due to a wide spread of peaks within the 13–35 Hz band. Following peak realignment the peak amplitude of the beta peak OFF medication was similar for all three time points (p > 0.3) and was significantly suppressed by levodopa medication (p Conclusion Our study shows that oscillatory activity in the beta frequency band can be recorded chronically via the implanted pulse generator and beta power remains stable over a time period of 8 months of DBS (albeit a partial initial suppression or frequency dispersion that might be due to the stun effect). Moreover, a significant suppression of beta activity by antiparkinsonian medication could also be shown months after electrode implantation.

A miniature closed-loop deep brain stimulation device.

This paper presents a miniature light-weight closed-loop deep brain stimulation (DBS) device that delivers on-demand stimulation current pulses by monitoring and analysing local field potentials. The device includes monitoring and DBS units, each designed and fabricated on a separate small round circuit board. The closed-loop DBS device has been successfully validated by injecting a pre-recorded neural signal into its input, and collecting and analysing its output. The monitoring unit has an amplification gain of 113 dB in frequency range of 0.7-50 Hz. The DBS unit gives on-demand stimulation current pulses of duration 90 μs, frequency 130 Hz, and amplitude 200 μA. The total weight of the device including a 3V coin battery is 1.41 g. The diameter of the device is 11.4 mm. This portable head-mountable device is suitable for use in pre-clinical trials with small laboratory animals.

Brain-computer interface-based control of closed-loop brain stimulation: attitudes and ethical considerations

Patients who have undergone deep brain stimulation (DBS) for emerging indications have unique perspectives on ethical challenges that may shape trial design and identify key design features for BCI-driven DBS systems. DBS research in cognitive and emotional disorders has generated significant ethical interest. Much of this work has focused on developing ethical guidelines and recommendations for open-loop DBS systems. While early trials of open-loop DBS for depression gave disappointing results, research is moving toward clinical trials with closed-loop or patient-controllable DBS systems that may modulate aspects of personality and emotion. Though user-centered design is an increasingly important principle in neurotechnology, the perspectives of implanted individuals on ethical issues raised by DBS are poorly understood. We solicited those perspectives through a focus group and set of qualitative interviews of participants in trials of DBS for depression and obsessive-compulsive disorder. We identified four major themes: control over device function, authentic self, relationship effects, and meaningful consent. Each has implications for the design of closed-loop systems for non-motor disorders.

Closed-Loop Deep Brain Stimulation Effects on Parkinsonian Motor Symptoms in a Non-Human Primate - Is Beta Enough?

Incorporating feedback controls based on real-time measures of pathological brain activity may improve deep brain stimulation (DBS) approaches for the treatment of Parkinson's disease (PD). Excessive beta oscillations in subthalamic nucleus (STN) local field potentials (LFP) have been proposed as a potential biomarker for closed-loop DBS (CL-DBS). In a non-human primate PD model we compared CL-DBS, which delivered stimulation only when STN LFP beta activity was elevated, to traditional continuous DBS (tDBS). Therapeutic effects of CL-DBS and tDBS relative to the Off-DBS condition were evaluated via a clinical rating scale and objective measures of movement speed during a cued reaching task. CL-DBS was comparable to tDBS at reducing rigidity, while reducing the amount of time DBS was on by ≈50%; however, only tDBS improved bradykinesia during the reaching behavior. This was likely due to reach-related reductions in beta amplitude that influence the timing and duration of stimulation in the CL-DBS condition. These results illustrate the potential utility of closed-loop DBS devices for PD based on STN beta LFP levels. They also point to possible consequences in behavioral tasks when restricting real-time sensing to a single LFP frequency that itself is modulated during performance of such tasks. The present study provides data that suggest alternate algorithms or more than one physiological biomarker may be required to optimize the performance of behavioral tasks and demonstrates the value of using multiple objective measures when evaluating the efficacy of closed-loop DBS systems.

Detecting a Cortical Fingerprint of Parkinson's Disease for Closed-Loop Neuromodulation.

Recent evidence suggests that deep brain stimulation (DBS) of the subthalamic nucleus (STN) in Parkinson's disease (PD) mediates its clinical effects by modulating cortical oscillatory activity, presumably via a direct cortico-subthalamic connection. This observation might pave the way for novel closed-loop approaches comprising a cortical sensor. Enhanced beta oscillations (13-35 Hz) have been linked to the pathophysiology of PD and may serve as such a candidate marker to localize a cortical area reliably modulated by DBS. However, beta-oscillations are widely distributed over the cortical surface, necessitating an additional signal source for spotting the cortical area linked to the pathologically synchronized cortico-subcortical motor network. In this context, both cortico-subthalamic coherence and cortico-muscular coherence (CMC) have been studied in PD patients. Whereas, the former requires invasive recordings, the latter allows for non-invasive detection, but displays a rather distributed cortical synchronization pattern in motor tasks. This distributed cortical representation may conflict with the goal of detecting a cortical localization with robust biomarker properties which is detectable on a single subject basis. We propose that this limitation could be overcome when recording CMC at rest. We hypothesized that—unlike healthy subjects—PD would show CMC at rest owing to the enhanced beta oscillations observed in PD. By performing source space analysis of beta CMC recorded during resting-state magnetoencephalography, we provide preliminary evidence in one patient for a cortical hot spot that is modulated most strongly by subthalamic DBS. Such a spot would provide a prominent target region either for direct neuromodulation or for placing a potential sensor in closed-loop DBS approaches, a proposal that requires investigation in a larger cohort of PD patients.

Nonlinear interactions in the thalamocortical loop in essential tremor: A model-based frequency domain analysis

There is increasing evidence to suggest that essential tremor has a central origin. Different structures appear to be part of the central tremorogenic network, including the motor cortex, the thalamus and the cerebellum. Some studies using electroencephalogram (EEG) and magnetoencephalography (MEG) show linear association in the tremor frequency between the motor cortex and the contralateral tremor electromyography (EMG). Additionally, high thalamomuscular coherence is found with the use of thalamic local field potential (LFP) recordings and tremulous EMG in patients undergoing surgery for deep brain stimulation (DBS). Despite a well-established reciprocal anatomical connection between the thalamus and cortex, the functional association between the two structures during “tremor-on” periods remains elusive. Thalamic (Vim) LFPs, ipsilateral scalp EEG from the sensorimotor cortex and contralateral tremor arm EMG recordings were obtained from two patients with essential tremor who had undergone successful surgery for DBS. Coherence analysis shows a strong linear association between thalamic LFPs and contralateral tremor EMG, but the relationship between the EEG and the thalamus is much less clear. These measurements were then analyzed by constructing a novel parametric nonlinear autoregressive with exogenous input (NARX) model. This new approach uncovered two distinct and not overlapping frequency “channels” of communication between Vim thalamus and the ipsilateral motor cortex, defining robustly “tremor-on” versus “tremor-off” states. The associated estimated nonlinear time lags also showed non-overlapping values between the two states, with longer corticothalamic lags (exceeding 50ms) in the tremor active state, suggesting involvement of an indirect multisynaptic loop. The results reveal the importance of the nonlinear interactions between cortical and subcortical areas in the central motor network of essential tremor. This work is important because it demonstrates for the first time that in essential tremor the functional interrelationships between the cortex and thalamus should not be sought exclusively within individual frequencies but more importantly between cross-frequency nonlinear interactions. Should our results be successfully reproduced on a bigger cohort of patients with essential tremor, our approach could be used to create an on-demand closed-loop DBS device, able to automatically activate when the tremor is on.

Factors influencing the outcome of deep brain stimulation: Placebo, nocebo, lessebo, and lesion effects.

Deep brain stimulation (DBS) is a well-established treatment option for movement disorders, especially for Parkinson's disease (PD). There is a need to determine the role of expectation of benefit and the use of placebo to better understand the effects of electrode placement including the (micro)lesion effect. These factors must be understood to better interpret and attribute the therapeutic value of DBS. In this review, we critically present currently available data on the placebo, nocebo, lessebo, and lesion effects in the context of DBS. We provide a discussion of strategies that have the potential for controlling these effects in the setting of future DBS trials. We conclude that there is a need to standardize definitions for nocebo and (micro)lesion effects and that there are intrinsic limitations in defining the effect of expectation of benefit in DBS. These issues will be challenging to overcome especially with current technology and available study designs. New stimulation paradigms, better study designs, and the use of adaptive closed-loop DBS devices may facilitate a more accurate assessment of the placebo, nocebo, and lessebo effects in future DBS trials.

Closed-loop DBS in the non-human primate model of Parkinsonism

High-frequency deep brain stimulation (DBS) is a widely used therapy for advanced Parkinson’s disease (PD) management. However, the mechanisms by which DBS exerts its alleviating effect remain to be described. Furthermore, due to its non-adaptive nature, standard DBS is not ideally suited for the treatment of this highly dynamic and progressive disorder. We have devised several closed-loop stimulation strategies for PD and tested them in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) primate model of PD. These included stimulation of the internal pallidal segment (GPi) according to a predefined trigger in the ongoing neuronal activity. Application of pallido-pallidal closed-loop stimulation leads to dissociation between changes in basal ganglia (BG) discharge rates and patterns, providing insights into PD pathophysiology. Notably, cortico-pallidal closed-loop stimulation has a significantly greater effect on akinesia and on cortical and pallidal discharge patterns than standard open-loop DBS and matched control stimulation paradigms. These results demonstrate that closed-loop DBS paradigms, by modulating pathological oscillatory activity rather than the discharge rate of the BG-cortical networks, may afford more effective management of advanced PD. Such strategies have the potential to be effective in additional brain disorders in which a pathological neuronal discharge pattern can be recognized.

Spatiotemporal dynamics of cortical perfusion in response to thalamic deep brain stimulation

Deep brain stimulation (DBS) has revolutionized the treatment of movement disorders. The parameters of electrical stimulation are important to its therapeutic effect and remain a source of clinical controversy. DBS exerts its actions not only locally at the site of stimulation but also remotely through afferent and efferent connections, which are vital to its clinical effects. Yet, only a few studies have examined how cortical activity changes in response to various electrical parameters. Here, we investigated how the parameters of thalamic DBS alter cortical perfusion in rats using intrinsic optical imaging. We hypothesized that thalamic DBS will increase perfusion in primary motor cortex (M1), proportional to amplitude, pulse width, or frequency of the stimulation applied. We applied 45 different combinations of amplitude, pulse width and frequency in the ventro-lateral (VL) nucleus of the thalamus in anesthetized rats while measuring perfusion in M1. VL thalamic DBS reduced cortical reflectance, which corresponds to an increase in cortical perfusion. We computed the maximum change in reflectance (MCR) as well as the spatial spread of MCR in each trial. Both MCR and spatial spread increased linearly with increases in current amplitude or pulse width of stimulation; however, the effect of frequency was non-linear. Stimulation at 20Hz was significantly different from that at higher frequencies while stimulation at higher frequencies did not differ significantly from each other. Moreover, the effect of pulse width on MCR was larger than the effect of amplitude. The proportional increase in M1 perfusion due to increase in amplitude or pulse width suggests that both activate more neural elements and increase the volume of tissue activated. These results should help clinicians set parameters of DBS. The use of optical imaging to monitor effects of DBS on M1 may not only help understand DBS mechanisms, but may also provide feedback for closed loop DBS devices.

A Fuzzy Inference System for Closed-Loop Deep Brain Stimulation in Parkinson’s Disease

Parkinsons disease is a complex neurodegenerative disorder for which patients present many symptoms, tremor being the main one. In advanced stages of the disease, Deep Brain Stimulation is a generalized therapy which can significantly improve the motor symptoms. However despite its beneficial effects on treating the symptomatology, the technique can be improved. One of its main limitations is that the parameters are fixed, and the stimulation is provided uninterruptedly, not taking into account any fluctuation in the patients state. A closed-loop system which provides stimulation by demand would adjust the stimulation to the variations in the state of the patient, stimulating only when it is necessary. It would not only perform a more intelligent stimulation, capable of adapting to the changes in real time, but also extending the devices battery life, thereby avoiding surgical interventions. In this work we design a tool that learns to recognize the principal symptom of Parkinsons disease and particularly the tremor. The goal of the designed system is to detect the moments the patient is suffering from a tremor episode and consequently to decide whether stimulation is needed or not. For that, local field potentials were recorded in the subthalamic nucleus of ten Parkinsonian patients, who were diagnosed with tremor-dominant Parkinsons disease and who underwent surgery for the implantation of a neurostimulator. Electromyographic activity in the forearm was simultaneously recorded, and the relation between both signals was evaluated using two different synchronization measures. The results of evaluating the synchronization indexes on each moment represent the inputs to the designed system. Finally, a fuzzy inference system was applied with the goal of identifying tremor episodes. Results are favourable, reaching accuracies of higher 98.7% in 70% of the patients.

Beta oscillations in freely moving Parkinson's subjects are attenuated during deep brain stimulation.

Investigations into the effect of deep brain stimulation (DBS) on subthalamic (STN) beta (13-30 Hz) oscillations have been performed in the perioperative period with the subject tethered to equipment. Using an embedded sensing neurostimulator, this study investigated whether beta power was similar in different resting postures and during forward walking in freely moving subjects with Parkinson's disease (PD) and whether STN DBS attenuated beta power in a voltage-dependent manner. Subthalamic local field potentials were recorded from the DBS lead, using a sensing neurostimulator (Activa(®) PC+S, Medtronic, Inc., Food and Drug Administration- Investigational Device Exemption (IDE)-, institutional review board-approved) from 15 PD subjects (30 STNs) off medication during lying, sitting, and standing, during forward walking, and during randomized periods of 140 Hz DBS at 0 V, 1 V, and 2.5/3 V. Continuous video, limb angular velocity, and forearm electromyography recordings were synchronized with neural recordings. Data were parsed to avoid any movement or electrical artifact during resting states. Beta power was similar during lying, sitting, and standing (P = 0.077, n = 28) and during forward walking compared with the averaged resting state (P = 0.466, n = 24), although akinetic rigid PD subjects tended to exhibit decreased beta power when walking. Deep brain stimulation at 3 V and at 1 V attenuated beta power compared with 0 V (P < 0.003, n = 14), and this was voltage dependent (P < 0.001). Beta power was conserved during resting and forward walking states and was attenuated in a voltage-dependent manner during 140-Hz DBS. Phenotype may be an important consideration if this is used for closed-loop DBS.

Long-term detection of Parkinsonian tremor activity from subthalamic nucleus local field potentials.

Current deep brain stimulation paradigms deliver continuous stimulation to deep brain structures to ameliorate the symptoms of Parkinson's disease. This continuous stimulation has undesirable side effects and decreases the lifespan of the unit's battery, necessitating earlier replacement. A closed-loop deep brain stimulator that uses brain signals to determine when to deliver stimulation based on the occurrence of symptoms could potentially address these drawbacks of current technology. Attempts to detect Parkinsonian tremor using brain signals recorded during the implantation procedure have been successful. However, the ability of these methods to accurately detect tremor over extended periods of time is unknown. Here we use local field potentials recorded during a deep brain stimulation clinical follow-up visit 1 month after initial programming to build a tremor detection algorithm and use this algorithm to detect tremor in subsequent visits up to 8 months later. Using this method, we detected the occurrence of tremor with accuracies between 68-93%. These results demonstrate the potential of tremor detection methods for efficacious closed-loop deep brain stimulation over extended periods of time.

Towards fully automated closed-loop Deep Brain Stimulation in Parkinson's disease patients: A LAMSTAR-based tremor predictor.

This paper describes the application of the LAMSTAR (LArge Memory STorage and Retrieval) neural network for prediction of onset of tremor in Parkinson's disease (PD) patients to allow for on-off adaptive control of Deep Brain Stimulation (DBS). Currently, the therapeutic treatment of PD by DBS is an open-loop system where continuous stimulation is applied to a target area in the brain. This work demonstrates a fully automated closed-loop DBS system so that stimulation can be applied on-demand only when needed to treat PD symptoms. The proposed LAMSTAR network uses spectral, entropy and recurrence rate parameters for prediction of the advent of tremor after the DBS stimulation is switched off. These parameters are extracted from non-invasively collected surface electromyography and accelerometry signals. The LAMSTAR network has useful characteristics, such as fast retrieval of patterns and ability to handle large amount of data of different types, which make it attractive for medical applications. Out of 21 trials blue from one subject, the average ratio of delay in prediction of tremor to the actual delay in observed tremor from the time stimulation was switched off achieved by the proposed LAMSTAR network is 0.77. Moreover, sensitivity of 100% and overall performance better than previously proposed Back Propagation neural networks is obtained.