A model of desynchronizing deep brain stimulation with a demand-controlled coordinated reset of neural subpopulations

The coordinated reset of neural subpopulations is introduced as an effectively desynchronizing stimulation technique. For this, short sequences of high-frequency pulse trains are administered at different sites in a coordinated way. Desynchronization is easily maintained by performing a coordinated reset with demand-controlled timing or by periodically administering resetting high-frequency pulse trains of demand-controlled length. Unlike previously developed methods, this novel approach is robust against variations of model parameters and does not require time-consuming calibration. The novel technique is suggested to be used for demand-controlled deep brain stimulation in patients suffering from Parkinson's disease or essential tremor. It might even be applicable to diseases with intermittently emerging synchronized neural oscillations like epilepsy.     

Long-term anti-kindling effects of desynchronizing brain stimulation: a theoretical study

In a modeling study we show that desynchronization stimulation may have powerful anti-kindling effects. For this, we incorporate spike-timing-dependent plasticity into a generic network of coupled phase oscillators, which serves as a model network of synaptically interacting neurons. Two states may coexist under spontaneous conditions: a state of uncorrelated firing and a state of pathological synchrony. Appropriate stimulation protocols make the network learn or unlearn the pathological synaptic interactions, respectively. Low-frequency periodic pulse train stimulation causes a kindling. Permanent high-frequency stimulation, used as golden standard for deep brain stimulation in medically refractory movement disorders, basically freezes the synaptic weights. In contrast, desynchronization stimulation, e.g., by means of a multi-site coordinated reset, has powerful long-term anti-kindling effects and enables the network to unlearn pathologically strong synaptic interactions. We propose desynchronization stimulation for the therapy of movement disorders and epilepsies.     

Control of Neuronal Synchrony by Nonlinear Delayed Feedback

We present nonlinear delayed feedback stimulation as a technique for effective desynchronization. This method is intriguingly robust with respect to system and stimulation parameter variations. We demonstrate its broad applicability by applying it to different generic oscillator networks as well as to a population of bursting neurons. Nonlinear delayed feedback specifically counteracts abnormal interactions and, thus, restores the natural frequencies of the individual oscillatory units. Nevertheless, nonlinear delayed feedback enables to strongly detune the macroscopic frequency of the collective oscillation. We propose nonlinear delayed feedback stimulation for the therapy of neurological diseases characterized by abnormal synchrony.     

Washout filter aided mean field feedback desynchronization in an ensemble of globally coupled neural oscillators

We propose an approach for desynchronization in an ensemble of globally coupled neural oscillators. The impact of washout filter aided mean field feedback on population synchronization process is investigated. By blocking the Hopf bifurcation of the mean field, the controller desynchronizes the ensemble. The technique is generally demand-controlled. It is robust and can be easily implemented practically. We suggest it for effective deep brain stimulation in neurological diseases characterized by pathological synchronization.     

Desynchronization in Networks of Globally Coupled Neurons with Dendritic Dynamics

Effective desynchronization can be exploited as a tool for probing the functional significance of synchronized neural activity underlying perceptual and cognitive processes or as a mild treatment for neurological disorders like Parkinson’s disease. In this article we show that pulse-based desynchronization techniques, originally developed for networks of globally coupled oscillators (Kuramoto model), can be adapted to networks of coupled neurons with dendritic dynamics. Compared to the Kuramoto model, the dendritic dynamics significantly alters the response of the neuron to the stimulation. Under medium stimulation amplitude a bistability of the re- sponse of a single neuron is observed. When stimulated at some initial phases, the neuron displays only modulations of its firing, whereas at other initial phases it stops oscillating entirely. Significant alterations in the duration of stimulation-induced transients are also observed. These transients endure after the end of the stimulation and cause maximal desynchronization to occur not during the stimulation, but with some delay after the stimulation has been turned off. To account for this delayed desynchronization effect, we have designed a new calibration procedure for finding the stimulation parameters that result in optimal desynchronization. We have also developed a new desynchronization technique by low frequency entrainment. The stimulation techniques originally developed for the Kuramoto model, when using the new calibration procedure, can also be applied to networks with dendritic dynamics. However, the mechanism by which desynchronization is achieved is substantially different than for the network of Kuramoto oscillators. In particular, the addition of dendritic dynamics significantly changes the timing of the stimulation required to obtain desynchronization. We propose desynchronization stimulation for experimental analysis of synchronized neural processes and for the therapy of movement disorders.     

Desynchronizing double-pulse phase resetting and application to deep brain stimulation

 Based on a stochastic phase-resetting approach, three different double-pulse stimulation techniques are presented here which make it possible to effectively desynchronize a population of phase oscillators in the presence of noise. In the three sorts of double pulses the first, stronger pulse restarts the cluster independent of its initial dynamic state. The three methods differ with respect to the mechanism through which the second, weaker pulse desynchronizes the cluster. Both first and second pulses are delivered to the same site. Because of the oscillators' global couplings in the model under consideration, the incoherent state is unstable, so that after the desynchronization the cluster tends to resynchronize. However, resynchronization is effectively blocked by repeated administration of a double pulse. The experimental application of double-pulse stimulation is explained in detail. In particular, demand-controlled deep brain double-pulse stimulation is suggested for the therapy of patients suffering from Parkinson's disease or essential tremor. Received: 22 November 2000 / Accepted in revised form: 26 April 2001     

Locally optimal extracellular stimulation for chaotic desynchronization of neural populations

We use optimal control theory to design a methodology to find locally optimal stimuli for desynchronization of a model of neurons with extracellular stimulation. This methodology yields stimuli which lead to positive Lyapunov exponents, and hence desynchronizes a neural population. We analyze this methodology in the presence of interneuron coupling to make predictions about the strength of stimulation required to overcome synchronizing effects of coupling. This methodology suggests a powerful alternative to pulsatile stimuli for deep brain stimulation as it uses less energy than pulsatile stimuli, and could eliminate the time consuming tuning process.     

Combined (thalamotomy and stimulation) stereotactic surgery of the VIM thalamic nucleus for bilateral Parkinson disease

Stereotactic thalamotomy of the thalamic nucleus ventralis intermedius (VIM) is routinely used for movement disorders. During this procedure, it has been observed that high-frequency (100 Hz) stimulation of VIM was able to stop the extrapyramidal tremor. In patients with bilateral tremor of extrapyramidal origin, who were resistant to drug therapy, the therapeutic protocol associated (1) a radiofrequency VIM thalamotomy for the most disabled side, and (2) a continuous VIM stimulation for the other side using stereotactically implanted electrodes, connected to subcutaneous stimulators. VIM thalamotomy relieved the tremor in all operated cases. Side effects were mild and regressive. VIM stimulation strongly decreased the tremor but failed to suppress it as completely as thalamotomy did. This was due in part to the fact that programmable stimulator frequency rate is limited to 130 Hz, while it appeared that the optimal stimulation frequency was 200 Hz. This therapeutic protocol appears to be of interest for patients with bilateral extrapyramidal movement disorders.     

Deep brain stimulation for Parkinson's disease

Deep brain stimulation at high frequency was first used in 1997 to replace thalamotomy in treating the characteristic tremor of Parkinson's disease, and has subsequently been applied to the pallidum and the subthalamic nucleus. The subthalamic nucleus is a key node in the functional control of motor activity in the basal ganglia. Its inhibition suppresses symptoms in animal models of Parkinson's disease, and high frequency chronic stimulation does the same in human patients. Acute and long-term results after deep brain stimulation show a dramatic and stable improvement of a patient's clinical condition, which mimics the effects of levodopa treatment. The mechanism of action may involve a functional disruption of the abnormal neural messages associated with the disease. Long-term changes, neural plasticity and neural protection might be induced in the network. Similar effects of stimulation and lesioning have led to the extension of this technique for other targets and diseases.     

Modeling and Automatic Feedback Control of Tremor: Adaptive Estimation of Deep Brain Stimulation

This paper discusses modeling and automatic feedback control of (postural and rest) tremor for adaptive-control-methodology-based estimation of deep brain stimulation (DBS) parameters. The simplest linear oscillator-based tremor model, between stimulation amplitude and tremor, is investigated by utilizing input-output knowledge. Further, a nonlinear generalization of the oscillator-based tremor model, useful for derivation of a control strategy involving incorporation of parametric-bound knowledge, is provided. Using the Lyapunov method, a robust adaptive output feedback control law, based on measurement of the tremor signal from the fingers of a patient, is formulated to estimate the stimulation amplitude required to control the tremor. By means of the proposed control strategy, an algorithm is developed for estimation of DBS parameters such as amplitude, frequency and pulse width, which provides a framework for development of an automatic clinical device for control of motor symptoms. The DBS parameter estimation results for the proposed control scheme are verified through numerical simulations.     

Controlled sinus arrhythmia during burst stimulation of the vagus nerve

In experiments on anesthesized cats and rats the desynchronization of the heart rate and burst stimulation of the vagus brought about severe sinus arrhythmia. Analysis of the functional dependence between the P--S interval (atrial wave of the ECG--moment of vagus stimulation) and the P--P interval showed periodical alterations in pacemaker sensitivity to the effect of the vagus during each cardiac cycle. It is supposed that natural vagus arrhythmia is the result of discoordination between heart automacy and efferent vagus bursts of central origin.     

Optimal closed-loop deep brain stimulation using multiple independently controlled contacts

Deep brain stimulation (DBS) is a well-established treatment option for a variety of neurological disorders, including Parkinson’s disease and essential tremor. The symptoms of these disorders are known to be associated with pathological synchronous neural activity in the basal ganglia and thalamus. It is hypothesised that DBS acts to desynchronise this activity, leading to an overall reduction in symptoms. Electrodes with multiple independently controllable contacts are a recent development in DBS technology which have the potential to target one or more pathological regions with greater precision, reducing side effects and potentially increasing both the efficacy and efficiency of the treatment. The increased complexity of these systems, however, motivates the need to understand the effects of DBS when applied to multiple regions or neural populations within the brain. On the basis of a theoretical model, our paper addresses the question of how to best apply DBS to multiple neural populations to maximally desynchronise brain activity. Central to this are analytical expressions, which we derive, that predict how the symptom severity should change when stimulation is applied. Using these expressions, we construct a closed-loop DBS strategy describing how stimulation should be delivered to individual contacts using the phases and amplitudes of feedback signals. We simulate our method and compare it against two others found in the literature: coordinated reset and phase-locked stimulation. We also investigate the conditions for which our strategy is expected to yield the most benefit.     

Therapeutic electrical stimulation of the central nervous system

The electrical effects on the nervous system have been known for long. The excitatory effect has been used for diagnostic purposes or even for therapeutic applications, like in pain using low-frequency stimulation of the spinal cord or of the thalamus. The discovery that High-Frequency Stimulation (HFS) mimics the effect of lesioning has opened a new field of therapeutic application of electrical stimulation in all places where lesion of neuronal structures, such as nuclei of the basal ganglia, had proven some therapeutic efficiency. This was first applied to the thalamus to mimic thalamotomy for the treatment of tremor, then to the subthalamic nucleus and the pallidum to treat some advanced forms of Parkinson's disease and control not only the tremor but also akinesia, rigidity and dyskinesias. The field of application is increasingly growing, currently encompassing dystonias, epilepsy, obsessive compulsive disease, cluster headaches, and experimental approaches are being made in the field of obesity and food intake control. Although the effects of stimulation are clear-cut and the therapeutic benefit is clearly recognized, the mechanism of action of HFS is not yet understood. The similarity between HFS and the effect of lesions in several places of the brain suggests that this might induce an inhibition-like process, which is difficult to explain with the classical concept of physiology where electrical stimulation means excitation of neural elements. The current data coming from either clinical or experimental observations are providing elements to shape a beginning of an understanding. Intra-cerebral recordings in human patients with artefact suppression tend to show the arrest of electrical firing in the recorded places. Animal experiments, either in vitro or in vivo, show complex patterns mixing inhibitory effects and frequency stimulation induced bursting activity, which would suggest that the mechanism is based upon the jamming of the neuronal message, which is by this way functionally suppressed. More recent data from in vitro biological studies show that HFS profoundly affects the cellular functioning and particularly the protein synthesis, suggesting that it could alter the synaptic transmission by reducing the production of neurotransmitters. It is now clear that this method has a larger field of application than currently known and that its therapeutical applications will benefit to several diseases of the nervous system. The understanding of the mechanism has opened a new field of research, which will call for reappraisal of the basic effects of electricity on the living tissues.     

Mechanism of suppression of sustained neuronal spiking under high-frequency stimulation

Using Hodgkin–Huxley and isolated subthalamic nucleus (STN) model neurons as examples, we show that electrical high-frequency stimulation (HFS) suppresses sustained neuronal spiking. The mechanism of suppression is explained on the basis of averaged equations derived from the original neuron equations in the limit of high frequencies. We show that for frequencies considerably greater than the reciprocal of the neuron’s characteristic time scale, the result of action of HFS is defined by the ratio between the amplitude and the frequency of the stimulating signal. The effect of suppression emerges due to a stabilization of the neuron’s resting state or due to a stabilization of a low-amplitude subthreshold oscillation of its membrane potential. Intriguingly, although we neglect synaptic dynamics, neural circuity as well as contribution of glial cells, the results obtained with the isolated high-frequency stimulated STN model neuron resemble the clinically observed relations between stimulation amplitude and stimulation frequency required to suppress Parkinsonian tremor.     

Spike amplitude modulation at high stimulation frequencies

Summary A technique of mathematical analysis has been developed for studying spike amplitude variations, during natural sinusoidal stimulation. This technique is suitable even when stimulation frequency is of the same order as, or higher than, the cell firing rate.We used this technique for the cat's retinal ganglion cells. The results agree with the previous ones (Gestri et al., 1967) at low stimulation frequencies and show that the spike amplitude modulation occur even at high frequencies, the phase shift between spike amplitude and firing probability being a function of the stimulation frequency.     

Time-frequency analysis of chemosensory event-related potentials to characterize the cortical representation of odors in humans

Background

The recording of olfactory and trigeminal chemosensory event-related potentials (ERPs) has been proposed as an objective and non-invasive technique to study the cortical processing of odors in humans. Until now, the responses have been characterized mainly using across-trial averaging in the time domain. Unfortunately, chemosensory ERPs, in particular, olfactory ERPs, exhibit a relatively low signal-to-noise ratio. Hence, although the technique is increasingly used in basic research as well as in clinical practice to evaluate people suffering from olfactory disorders, its current clinical relevance remains very limited. Here, we used a time-frequency analysis based on the wavelet transform to reveal EEG responses that are not strictly phase-locked to onset of the chemosensory stimulus. We hypothesized that this approach would significantly enhance the signal-to-noise ratio of the EEG responses to chemosensory stimulation because, as compared to conventional time-domain averaging, (1) it is less sensitive to temporal jitter and (2) it can reveal non phase-locked EEG responses such as event-related synchronization and desynchronization.

Methodology/Principal Findings

EEG responses to selective trigeminal and olfactory stimulation were recorded in 11 normosmic subjects. A Morlet wavelet was used to characterize the elicited responses in the time-frequency domain. We found that this approach markedly improved the signal-to-noise ratio of the obtained EEG responses, in particular, following olfactory stimulation. Furthermore, the approach allowed characterizing non phase-locked components that could not be identified using conventional time-domain averaging.

Conclusion/Significance

By providing a more robust and complete view of how odors are represented in the human brain, our approach could constitute the basis for a robust tool to study olfaction, both for basic research and clinicians.     

Analysis of the effect of increasing electrodermal stimulation on the somatovegetative reactions evoked by stimulation of the ventromedial hypothalamus

The influence of increasing electrodermal stimulation (EDS) on the dynamics of the somatovegetative reactions evoked by electrical stimulation of negative emotiogenic regions of the hypothalamus was studied. EDS produced a blocking effect on the somatovegetative reactions evoked by stimulation of the ventromedial hypothalamus (VMH). Pretreatment with naloxone prevented the effects of EDS. Injection of beta-endorphine in a dose of 10 micrograms to the lateral ventricules of the animal brain also blocked the somatovegetative reactions during VMH stimulation. Injection of beta-endorphine in doses of 50-100 micrograms enhanced and prolonged the somatovegetative reactions evoked by VMH stimulation. Elevated arterial blood pressure, pronounced bradycardia, extrasystoles, muscle tremor, and pathologic respiration were recorded. These disorders were completely reversed by EDS. It is assumed that both opiate peptides and their receptors are involved in the mechanism of the somatovegetative reactions evoked by VMH stimulation, experiencing the influence of EDS.     

Phase model-based neuron stabilization into arbitrary clusters

Deep brain stimulation (DBS) is a common method of combating pathological conditions associated with Parkinson’s disease, Tourette syndrome, essential tremor, and other disorders, but whose mechanisms are not fully understood. One hypothesis, supported experimentally, is that some symptoms of these disorders are associated with pathological synchronization of neurons in the basal ganglia and thalamus. For this reason, there has been interest in recent years in finding efficient ways to desynchronize neurons that are both fast-acting and low-power. Recent results on coordinated reset and periodically forced oscillators suggest that forming distinct clusters of neurons may prove to be more effective than achieving complete desynchronization, in particular by promoting plasticity effects that might persist after stimulation is turned off. Current proposed methods for achieving clustering frequently require either multiple input sources or precomputing the control signal. We propose here a control strategy for clustering, based on an analysis of the reduced phase model for a set of identical neurons, that allows for real-time, single-input control of a population of neurons with low-amplitude, low total energy signals. After demonstrating its effectiveness on phase models, we apply it to full state models to demonstrate its validity. We also discuss the effects of coupling on the efficacy of the strategy proposed and demonstrate that the clustering can still be accomplished in the presence of weak to moderate electrotonic coupling.     

Deep brain stimulation for neurologic and neuropsychiatric disorders

In the 1960s, ablative stereotactic surgery was employed for a variety of movement disorders and psychiatric conditions. Although largely abandoned in the 1970s because of highly effective drugs, such as levodopa for Parkinson's disease (PD), and a reaction against psychosurgery, the field has undergone a virtual renaissance, guided by a better understanding of brain circuitry and the circuit abnormalities underlying movement disorders such as PD and neuropsychiatric conditions, such as obsessive compulsive disorder. High-frequency electrical deep brain stimulation (DBS) of specific targets, introduced in the early 1990s for tremor, has gained widespread acceptance because of its less invasive, reversible, and adjustable features and is now utilized for an increasing number of brain disorders. This review summarizes the rationale behind DBS and the use of this technique for a variety of movement disorders and neuropsychiatric diseases.