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The synaptic organization of the brain is constantly modified by activity-dependent synaptic plasticity. In several neurological disorders, abnormal neuronal activity and pathological synaptic connectivity may significantly impair normal brain function. Reorganization of neuronal circuits by therapeutic stimulation has the potential to restore normal brain dynamics. Increasing evidence suggests that the temporal stimulation pattern crucially determines the long-lasting therapeutic effects of stimulation. Here, we tested whether a specific pattern of brain stimulation can enable the suppression of pathologically strong inter-population synaptic connectivity through spike-timing-dependent plasticity (STDP). More specifically, we tested how introducing a time shift between stimuli delivered to two interacting populations of neurons can effectively decouple them. To that end, we first used a tractable model, i.e., two bidirectionally coupled leaky integrate-and-fire (LIF) neurons, to theoretically analyze the optimal range of stimulation frequency and time shift for decoupling. We then extended our results to two reciprocally connected neuronal populations (modules) where inter-population delayed connections were modified by STDP. As predicted by the theoretical results, appropriately time-shifted stimulation causes a decoupling of the two-module system through STDP, i.e., by unlearning pathologically strong synaptic interactions between the two populations. Based on the overall topology of the connections, the decoupling of the two modules, in turn, causes a desynchronization of the populations that outlasts the cessation of stimulation. Decoupling effects of the time-shifted stimulation can be realized by time-shifted burst stimulation as well as time-shifted continuous simulation. Our results provide insight into the further optimization of a variety of multichannel stimulation protocols aiming at a therapeutic reshaping of diseased brain networks. Author summary: To clinically advance different types of brain stimulation, e.g., deep brain stimulation or epicortical stimulation, in numerous clinical studies, typically only a few types of stimulus patterns have been delivered to different target areas in the midbrain or cortex. To further leverage the power of these clinical trials we here present a theoretical and numerical study demonstrating that the effects of brain stimulation may massively depend on variations of supposedly minor parameters. To this end, we introduce a time shift between stimulus trains delivered to two anatomically separate neuronal populations interacting through plastic synapses. Depending on the specific time shift, stimulation may be ineffective or induce pronounced changes of the connections between and, in turn, within the neuronal populations, ultimately causing a long-lasting unlearning of abnormal neuronal synchrony. To thoroughly understand the time shift-induced decoupling mechanism, we first consider a simple two-neuron motif of two leaky integrate-and-fire neurons. Intriguingly, our results obtained in the two-neuron motif are in excellent agreement with the two-population scenario, illustrating the predictive power of comparably simple models. Our results are important in the context of the control of plastic neuronal networks and provide testable hypotheses for the improvement of clinically used stimulation techniques. [ABSTRACT FROM AUTHOR]

Synaptic dysfunction is associated with several brain disorders, including Alzheimer's disease, Parkinson's disease (PD) and obsessive compulsive disorder (OCD). Utilizing synaptic plasticity, brain stimulation is capable of reshaping synaptic connectivity. This may pave the way for novel therapies that specifically counteract pathological synaptic connectivity. For instance, in PD, novel multichannel coordinated reset stimulation (CRS) was designed to counteract neuronal synchrony and down-regulate pathological synaptic connectivity. CRS was shown to entail long-lasting therapeutic aftereffects in PD patients and related animal models. This is in marked contrast to conventional deep brain stimulation (DBS) therapy, where PD symptoms return shortly after stimulation ceases. In the present paper, we study synaptic reshaping by periodic multichannel stimulation (PMCS) in networks of leaky integrate-and-fire (LIF) neurons with spike-timing-dependent plasticity (STDP). During PMCS, phase-shifted periodic stimulus trains are delivered to segregated neuronal subpopulations. Harnessing STDP, PMCS leads to changes of the synaptic network structure. We found that the PMCS-induced changes of the network structure depend on both the phase lags between stimuli and the shape of individual stimuli. Single-pulse stimuli and burst stimuli with low intraburst frequency down-regulate synapses between neurons receiving stimuli simultaneously. In contrast, burst stimuli with high intraburst frequency up-regulate these synapses. We derive theoretical approximations of the stimulation-induced network structure. This enables us to formulate stimulation strategies for inducing a variety of network structures. Our results provide testable hypotheses for future pre-clinical and clinical studies and suggest that periodic multichannel stimulation may be suitable for reshaping plastic neuronal networks to counteract pathological synaptic connectivity. Furthermore, we provide novel insight on how the stimulus type may affect the long-lasting outcome of conventional DBS. This may strongly impact parameter adjustment procedures for clinical DBS, which, so far, primarily focused on acute effects of stimulation. Author summary: Synaptic dysfunction accompanies several brain disorders, such as Alzheimer's, Parkinson's disease and obsessive compulsive disorder. For therapeutic purposes, stimulation is delivered to disease-related brain areas. Brain stimulation therapies that manipulate synaptic connections in disease-related brain areas may provide long-lasting symptom relief. In this computational and theoretical study, we study periodic multichannel stimulation, a stimulation technique that allows for manipulating selected synaptic populations. Stimulus trains are delivered to multiple neuronal subpopulations in order to trigger neuronal responses. Using a model network of leaky integrate-and-fire neurons with spike-timing-dependent plasticity and theoretical analysis, we show how the relative timings between and the shape of delivered stimuli can be tuned to down-regulate certain synaptic connections while up-regulating others. Single-pulse stimuli triggered precise neuronal responses and were suitable for inducing a variety of synaptic network structures. When burst stimuli were employed, tuning the intraburst frequency allowed for distinguishing between down- and up-regulation of synaptic connections within individual neuronal subpopulations. Our work provides a theoretical basis for selecting suitable stimulation parameters for inducing long-lasting therapeutic effects in patients suffering from neurological disorders. [ABSTRACT FROM AUTHOR]

Excessive neuronal synchrony is a hallmark of several neurological disorders, e.g., Parkinson's disease. An established treatment for medically refractory Parkinson's disease is high-frequency deep brain stimulation. However, it provides only acute relief, and symptoms return shortly after cessation of stimulation. A theory-based approach called coordinated reset (CR) has shown great promise in achieving long-lasting effects. During CR stimulation, phase-shifted stimuli are delivered to multiple stimulation sites to counteract neuronal synchrony. Computational studies in plastic neuronal networks reported that synaptic weights reduce during stimulation, which may cause sustained structural changes leading to stabilized desynchronized activity even after stimulation ceases. Corresponding long-lasting effects were found in recent preclinical and clinical studies. We study long-lasting desynchronization by CR stimulation in excitatory recurrent neuronal networks of integrate-and-fire neurons with spike-timing-dependent plasticity (STDP). We focus on the impact of the stimulation frequency and the number of stimulation sites on long-lasting effects. We compare theoretical predictions to simulations of plastic neuronal networks. Our results are important regarding CR calibration for two reasons. We reveal that long-lasting effects become most pronounced when stimulation parameters are adjusted to the characteristics of STDP—rather than to neuronal frequency characteristics. This is in contrast to previous studies where the CR frequency was adjusted to the dominant neuronal rhythm. In addition, we reveal a nonlinear dependence of long-lasting effects on the number of stimulation sites and the CR frequency. Intriguingly, optimal long-lasting desynchronization does not require larger numbers of stimulation sites. [ABSTRACT FROM AUTHOR]

Several brain disorders are characterized by abnormally strong neuronal synchrony. Coordinated Reset (CR) stimulation was developed to selectively counteract abnormal neuronal synchrony by desynchronization. For this, phase resetting stimuli are delivered to different subpopulations in a timely coordinated way. In neural networks with spike timing-dependent plasticity CR stimulation may eventually lead to an anti-kindling, i.e., an unlearning of abnormal synaptic connectivity and abnormal synchrony. The spatiotemporal sequence by which all stimulation sites are stimulated exactly once is called the stimulation site sequence, or briefly sequence. So far, in simulations, pre-clinical and clinical applications CR was applied either with fixed sequences or rapidly varying sequences (RVS). In this computational study we show that appropriate repetition of the sequence with occasional random switching to the next sequence may significantly improve the anti-kindling effect of CR. To this end, a sequence is applied many times before randomly switching to the next sequence. This new method is called SVS CR stimulation, i.e., CR with slowly varying sequences. In a neuronal network with strong short-range excitatory and weak long-range inhibitory dynamic couplings SVS CR stimulation turns out to be superior to CR stimulation with fixed sequences or RVS. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The brain operates through complex interactions in the flow of information and signal processing within neural networks. The 'wiring' of such networks, being neuronal or glial, can physically and/or functionally go rogue in various pathological states. Neuromodulation, as a multidisciplinary venture, attempts to correct such faulty nets. In this review, selected approaches and challenges in neuromodulation are discussed. The use of water-dispersible carbon nanotubes has been proven effective in the modulation of neurite outgrowth in culture and in aiding regeneration after spinal cord injury in vivo. Studying neural circuits using computational biology and analytical engineering approaches brings to light geometrical mapping of dynamics within neural networks, much needed information for stimulation interventions in medical practice. Indeed, sophisticated desynchronization approaches used for brain stimulation have been successful in coaxing 'misfiring' neuronal circuits to resume productive firing patterns in various human disorders. Devices have been developed for the real-time measurement of various neurotransmitters as well as electrical activity in the human brain during electrical deep brain stimulation. Such devices can establish the dynamics of electrochemical changes in the brain during stimulation. With increasing application of nanomaterials in devices for electrical and chemical recording and stimulating in the brain, the era of cellular, and even intracellular, precision neuromodulation will soon be upon us. [ABSTRACT FROM AUTHOR]

Tinnitus is a deafferentation-induced phantom phenomenon characterized by abnormal cerebral synchrony and connectivity. Computationally, we show that desynchronizing acoustic coordinated reset (CR) stimulation can effectively counteract both up-regulated synchrony and connectivity. CR stimulation has initially been developed for the application to electrical deep brain stimulation. We here adapt this approach to non-invasive, acoustic CR stimulation. For this, we use the tonotopic organization of the central auditory system and replace electrical stimulation bursts applied to different brain sites by acoustically delivered tones of different pitch. Based on our simulations, we propose non-invasive acoustic CR stimulation as a possible novel therapy for tinnitus. [ABSTRACT FROM AUTHOR]

Abstract: Large-amplitude oscillations of macroscopic neuronal signals, such as local field potentials and electroencephalography or magnetoencephalography signals, are commonly considered as being generated by a population of mutually synchronized neurons. In a computational study in generic networks of phase oscillators and bursting neurons, however, we show that this common belief may be wrong if the neuronal population receives an external rhythmic input. The latter may stem from another neuronal population or an external, e.g., sensory or electrical, source. In that case the population field potential may be entrained by the rhythmic input, whereas the individual neurons are phase desynchronized both mutually and with their field potential. Intriguingly, the corresponding large-amplitude oscillations of the population mean field are generated by pairwise desynchronized neurons oscillating at frequencies shifted far away from the frequency of the macroscopic field potential. [Copyright &y& Elsevier]

We show that synchronization processes can effectively be controlled with nonlinear delayed feedback. We demonstrate that nonlinear delayed feedback can have a twofold impact on the collective dynamics of large ensembles of coupled oscillators: synchronizing and, mostly, desynchronizing effects. By means of a model equation for the mean field, we explore the existence and stability of the feedback-induced desynchronized states, their multistability and dynamical properties. We propose nonlinear delayed feedback stimulation for the therapy of neurological diseases characterized by abnormal synchrony. [ABSTRACT FROM AUTHOR]

A mathematical model of a target area for deep brain stimulation was used to investigate the effects of electrical stimulation on pathologically synchronized clusters of neurons. In total, three newly developed stimulation techniques based on multisite coordinated reset and delayed feedback were tested and compared with a high-frequency stimulation method that is currently used as a standard stimulation protocol for deep brain stimulation. By modeling both excitatory and inhibitory actions of the electrical stimulation, we revealed the desynchronization impacts of the novel stimulation techniques. This contrasts with standard high-frequency stimulation, which failed to desynchronize the target population and whose inhibitory effects blocked all neuronal activity. We also explored the demand-controlled character of the proposed methods, and demonstrated that the amount of stimulation current required was considerably smaller than that for high-frequency stimulation. These novel stimulation methods appear to be superior to standard high-frequency stimulation techniques, and we propose the methods now be used for deep brain stimulation. [ABSTRACT FROM AUTHOR]

Abstract: In a modeling study, we show that synaptic connectivity can effectively be reshaped by an appropriate modulation of neuronal dynamics. To this end, we incorporate synaptic plasticity with symmetric spike-timing characteristics into a population of bursting neurons, which are interacting via chemical synapses. Under spontaneous conditions, qualitatively different stable dynamical states may coexist. We observe states characterized either by pathological synchrony or by uncorrelated activity. Suitably designed stimulation protocols enable to shift the neuronal population from one dynamical state to another. Due to low-frequency periodic pulse train stimulation, the population learns pathologically strong interactions, as known from the kindling phenomenon. In contrast, desynchronizing stimulation, e.g., multi-site coordinated reset stimulation, enables the network to unlearn pathologically strong synaptic interactions, so that a powerful long-term anti-kindling is achieved. We demonstrate that anti-kindling can be achieved even with weak and/or short desynchronizing stimuli, which are not able to cause a complete desynchronization in the course of the stimulation. Our results show that desynchronizing stimulation may serve as a novel curative approach for the therapy of neurological diseases connected with pathological cerebral synchrony. [Copyright &y& Elsevier]

Synchronization processes may severely impair brain function, for instance, in Parkinson's disease, essential tremor or epilepsies. We present three different effectively desynchronizing stimulation techniques which have been developed with methods from nonlinear dynamics and statistical physics. These techniques exploit either stochastic phase resetting principles or complex delayed feedback mechanisms. We explain how these methods work and how they can be applied to therapeutic brain stimulation. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

A novel control method for desynchronization of strongly synchronized populations of interacting oscillators is described. We show that an ensemble's mean field, nonlinearly processed and fed back into the ensemble, causes an effective desynchronization. The method is mild, demand controlled, and robust against system and stimulation parameter variations. The desynchronization and decoupling effects of the method are illustrated by examples of one and two interacting populations of limit-cycle oscillators. We suggest our method for mild and effective deep brain stimulation in neurological diseases characterized by pathological cerebral synchronization. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Synchronization of neuronal firing is a hallmark of several neurological diseases. Recently, stimulation techniques have been developed which make it possible to desynchronize oscillatory neuronal activity in a mild and effective way, without suppressing the neurons' firing. As yet, these techniques are being used to establish demand-controlled deep brain stimulation (DBS) techniques for the therapy of movement disorders like severe Parkinson's disease or essential tremor. We here present a first conceptualization suggesting that the nucleus accumbens is a promising target for the standard, that is, permanent high-frequency, DBS in patients with severe and chronic obsessive-compulsive disorder (OCD). In addition, we explain how demand-controlled DBS techniques may be applied to the therapy of OCD in those cases that are refractory to behavioral therapies and pharmacological treatment. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In a mathematical model we show that the dynamical multi-stability of a network of bursting subthalamic neurons, caused by synaptic plasticity, has strong impact on the stimulus-response properties when exposed to desynchronizing coordinated reset (CR) stimulation. Such stimuli can reliably shift the network from a stable state with pathological synchrony and connectivity to a stable desynchronized state with down-regulated connectivity. Finally, the desynchronizing stimulation protocol is tested in two experimental setups: first, we studied long-lasting effects of CR stimulation in rat hippocampal slice rendered epileptic by magnesium withdrawal. We show that the CR stimulation causes a long-lasting desynchronization between hippocampal neuronal populations together with a widespread decrease of the amplitude of the epileptiform activity. In contrast, periodic stimulation control stimulation induces a long-lasting increase of both synchronization and amplitude. Second, we developed appropriate hardware enabling a clinical pilot-study applying coordinated reset stimulation through externalized DBS electrodes to patients suffering from Parkinson's disease. CR stimulation resulted in a long-lasting reduction of the symptoms depicted by clinical motor scores. These theoretical and experimental findings support the idea that desynchronizing stimulation can induce long-lasting effects in neuronal networks featuring dynamical multi-stability. [ABSTRACT FROM AUTHOR]

Since the 1990s deep brain stimulation is a widely used treatment for neurological disorders like Parkinson's disease and dystonia. Stimulation electrodes are implanted stereotactically in the target areas within the human brain. The main target areas used for the therapy of Parkinson patients are the subthalamic nucleus (STN) and the globus pallidus externus (GPe). The electric field generated by the electrode activates nerve fibers in the vicinity of the electrode. Even though the different target nuclei offer considerable differences in their anatomical structure, only two types of electrodes are currently available. These consist of four cylindrical contacts with a height of 1.5 mm and a diameter of 1.27 mm. The distance between the contacts is either 0.5 mm or 1.5 mm. The contacts can be separately activated and the commonly used approaches are monopolar and bipolar stimulation. Monopolar stimulation causes a wider distribution of the current in all directions in contrast to bipolar stimulation where the current flows between the activated contacts and stimulates a more restricted area. It is desirable to adjust the electric field and in particular the volume of activated tissue around the electrode with respect to the corresponding target nucleus such that side effects can be reduced. Furthermore, a more selective and partly activation of the target structure is desirable with respect to novel stimulation strategies, e.g. the coordinated reset of neuronal sub-population. Hence we designed and analyzed a DBS electrode with a novel design, allowing more selective activation of the target structure. As the second derivative of the field potential generated by the implanted electrode is correlated to the response of the neural system, we have created a FEM model of the electrode and the surrounding tissue and analyzed the activating function and the volume of activated tissue for the newly developed electrode design. [ABSTRACT FROM AUTHOR]

Electrical stimulation of neural structures is the basis of spinal cord stimulation (for pain therapy) as well as deep brain stimulation (for the therapy of neurological and psychiatric disorders). In deep brain stimulation, an electrical stimulus pulse is applied permanently or in pulse trains via an implanted electrode to selective brain regions. Recent applications tend to excite the neural structures up to a level at which they will eventually fire an action potential. Thus the neuronal activity within a region can be influenced. In order to carry out safe stimulation and prevent tissue or electrode damage, the waveform generally consists of biphasic, charge-balanced pulses. Effective yet gentle stimulation is of prime importance to aid in the prevention of side effects and in conserving the battery life of implants. We have developed new pulse shapes and tested these with different parameters for their effectiveness based on numerical simulations using the Hodgkin-Huxley neuron model. Our results show a predominance of the new pulse shapes over the widely used standard pulse shape while key requirements to the waveform are maintained. [ABSTRACT FROM AUTHOR]

Deep brain stimulation (DBS) is a neurosurgical procedure that allows targeted circuit-based neuromodulation. DBS is a standard of care in Parkinson disease, essential tremor and dystonia, and is also under active investigation for other conditions linked to pathological circuitry, including major depressive disorder and Alzheimer disease. Modern DBS systems, borrowed from the cardiac field, consist of an intracranial electrode, an extension wire and a pulse generator, and have evolved slowly over the past two decades. Advances in engineering and imaging along with an improved understanding of brain disorders are poised to reshape how DBS is viewed and delivered to patients. Breakthroughs in electrode and battery designs, stimulation paradigms, closed-loop and on-demand stimulation, and sensing technologies are expected to enhance the efficacy and tolerability of DBS. In this Review, we provide a comprehensive overview of the technical development of DBS, from its origins to its future. Understanding the evolution of DBS technology helps put the currently available systems in perspective and allows us to predict the next major technological advances and hurdles in the field. [ABSTRACT FROM AUTHOR]