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Cravings that precede loss of control (LOC) over food consumption present an opportunity for intervention in patients with the binge eating disorder (BED). In this pilot study, we used responsive deep brain stimulation (DBS) to record nucleus accumbens (NAc) electrophysiology during food cravings preceding LOC eating in two patients with BED and severe obesity (trial registration no. NCT03868670). Increased NAc low-frequency oscillations, prominent during food cravings, were used to guide DBS delivery. Over 6 months, we observed improved self-control of food intake and weight loss. These findings provide early support for restoring inhibitory control with electrophysiologically-guided NAc DBS. Further work with increased sample sizes is required to determine the scalability of this approach., (© 2022. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

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.

Background: Loss of control (LOC) is a pervasive feature of binge eating, which contributes significantly to the growing epidemic of obesity; approximately 80 million US adults are obese. Brain-responsive neurostimulation guided by the delta band was previously found to block binge-eating behavior in mice. Following novel preclinical work and a human case study demonstrating an association between the delta band and reward anticipation, the US Food and Drug Administration approved an Investigational Device Exemption for a first-in-human study., Objective: To assess feasibility, safety, and nonfutility of brain-responsive neurostimulation for LOC eating in treatment-refractory obesity., Methods: This is a single-site, early feasibility study with a randomized, single-blinded, staggered-onset design. Six subjects will undergo bilateral brain-responsive neurostimulation of the nucleus accumbens for LOC eating using the RNS® System (NeuroPace Inc). Eligible participants must have treatment-refractory obesity with body mass index ≥ 45 kg/m2. Electrophysiological signals of LOC will be characterized using real-time recording capabilities coupled with synchronized video monitoring. Effects on other eating disorder pathology, mood, neuropsychological profile, metabolic syndrome, and nutrition will also be assessed., Expected Outcomes: Safety/feasibility of brain-responsive neurostimulation of the nucleus accumbens will be examined. The primary success criterion is a decrease of ≥1 LOC eating episode/week based on a 28-d average in ≥50% of subjects after 6 mo of responsive neurostimulation., Discussion: This study is the first to use brain-responsive neurostimulation for obesity; this approach represents a paradigm shift for intractable mental health disorders., (Copyright © 2020 by the Congress of Neurological Surgeons.)

Adaptive deep brain stimulation (aDBS) is a closed-loop method, where high-frequency DBS is turned on and off according to a feedback signal, whereas conventional high-frequency DBS (cDBS) is delivered permanently. Using a computational model of subthalamic nucleus and external globus pallidus, we extend the concept of adaptive stimulation by adaptively controlling not only continuous, but also demand-controlled stimulation. Apart from aDBS and cDBS, we consider continuous pulsatile linear delayed feedback stimulation (cpLDF), specifically designed to induce desynchronization. Additionally, we combine adaptive on-off delivery with continuous delayed feedback modulation by introducing adaptive pulsatile linear delayed feedback stimulation (apLDF), where cpLDF is turned on and off using pre-defined amplitude thresholds. By varying the stimulation parameters of cDBS, aDBS, cpLDF, and apLDF we obtain optimal parameter ranges. We reveal a simple relation between the thresholds of the local field potential (LFP) for aDBS and apLDF, the extent of the stimulation-induced desynchronization, and the integral stimulation time required. We find that aDBS and apLDF can be more efficient in suppressing abnormal synchronization than continuous simulation. However, apLDF still remains more efficient and also causes a stronger reduction of the LFP beta burst length. Hence, adaptive on-off delivery may further improve the intrinsically demand-controlled pLDF.

Pathological synchronization in the basal ganglia network has been considered an important component of Parkinson's disease pathophysiology. An established treatment for some patients with Parkinson's disease is deep brain stimulation, in which a tonic high-frequency pulse train is delivered to target regions of the brain. In recent years, a novel neuromodulation paradigm called coordinated reset stimulation has been proposed, which aims to reverse the pathological synchrony by sequentially delivering short high-frequency bursts to distinct sub-regions of the pathologically synchronized network, with an average intra-burst interval for each sub-region corresponding to period of the pathological oscillation. It has further been proposed that the resultant desynchronization can be enhanced when stimulation is interrupted periodically, and that it is particularly beneficial to precisely tune the stimulation ON and OFF time-windows to the underlying pathological frequency. Pre-clinical and clinical studies of coordinated reset stimulation have relied on these proposals for their stimulation protocols. In this study, we present a modified ON-OFF coordinated reset stimulation paradigm called periodic flashing and study its behavior through computational modeling using the Kuramoto coupled phase oscillator model. We demonstrate that in contrast to conventional coordinated reset stimulation, the periodic flashing variation does not exhibit a need for precise turning of the ON-OFF periods to the pathological frequency, and demonstrates desynchronization for a wide range of ON and OFF periods. We provide a mechanistic explanation for the previously observed sensitivities and demonstrate that they are an artifact of the specific ON-OFF cycling paradigm used. As a practical consequence, the periodic flashing paradigm simplifies the tuning of optimal stimulation parameters by decreasing the dimension of the search space. It also suggests new, more flexible ways of delivering coordinated reset stimulation., Competing Interests: DT was employed by Boston Scientific Corporation when this work was performed. PAT’s contribution was part of consultancy work for Boston Scientific Corporation. HB is employed by and owns stock in Boston Scientific Corporation. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Computationally it was shown that desynchronizing delayed feedback stimulation methods are effective closed-loop techniques for the control of synchronization in ensembles of interacting oscillators. We here computationally design stimulation signals for electrical stimulation of neuronal tissue that preserve the desynchronizing delayed feedback characteristics and comply with mandatory charge deposit-related safety requirements. For this, the amplitude of the high-frequency (HF) train of biphasic charge-balanced pulses used by the standard HF deep brain stimulation (DBS) is modulated by the smooth feedback signals. In this way we combine the desynchronizing delayed feedback approach with the HF DBS technique. We show that such a pulsatile delayed feedback stimulation can effectively and robustly desynchronize a network of model neurons comprising subthalamic nucleus and globus pallidus external and suggest this approach for desynchronizing closed-loop DBS. Intriguingly, an interphase gap introduced between the recharging phases of the charge-balanced biphasic pulses can significantly improve the stimulation-induced desynchronization and reduce the amount of the administered stimulation. In view of the recent experimental and clinical studies indicating a superiority of the closed-loop DBS to open-loop HF DBS, our results may contribute to a further development of effective stimulation methods for the treatment of neurological disorders characterized by abnormal neuronal synchronization.

High-frequency (HF) deep brain stimulation (DBS) is the gold standard for the treatment of medically refractory movement disorders like Parkinson's disease, essential tremor, and dystonia, with a significant potential for application to other neurological diseases. The standard setup of HF DBS utilizes an open-loop stimulation protocol, where a permanent HF electrical pulse train is administered to the brain target areas irrespectively of the ongoing neuronal dynamics. Recent experimental and clinical studies demonstrate that a closed-loop, adaptive DBS might be superior to the open-loop setup. We here combine the notion of the adaptive high-frequency stimulation approach, that aims at delivering stimulation adapted to the extent of appropriately detected biomarkers, with specifically desynchronizing stimulation protocols. To this end, we extend the delayed feedback stimulation methods, which are intrinsically closed-loop techniques and specifically designed to desynchronize abnormal neuronal synchronization, to pulsatile electrical brain stimulation. We show that permanent pulsatile high-frequency stimulation subjected to an amplitude modulation by linear or nonlinear delayed feedback methods can effectively and robustly desynchronize a STN-GPe network of model neurons and suggest this approach for desynchronizing closed-loop DBS.

Deep brain stimulation (DBS) has been applied in more than 70000 patients worldwide during the last two decades. The main target is the subthalamic nucleus (STN) for the treatment of motor complications in late stage Parkinson's disease (PD). Positive results in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated non-human primates have set the grounds for its successful translation to PD patients. Since then, this model has allowed gaining significant insights in the underlying mechanisms of action of DBS and is currently being used for the development of new stimulation techniques. Altogether, this underpins the high potential of this preclinical model for future translation of DBS research in PD.

The loss of segregation of neuronal signal processing pathways is an important hypothesis for explaining the origin of functional deficits as associated with Parkinson's disease. Here we use a modeling approach which is utilized to study the influence of deep brain stimulation on the restoration of segregated activity in the target structures. Besides the spontaneous activity of the target network, the model considers a weak sensory input mimicking signal processing tasks, electrical deep brain stimulation delivered through a standard DBS electrode and synaptic plasticity. We demonstrate that the sensory input is capable of inducing a modification of the network structure which results in segregated microcircuits if the network is initialized in the healthy, desynchronized state. Depending on the strength and coverage, the sensory input is capable of restoring the functional sub-circuits even if the network is initialized in the synchronized, pathological state. Weak coordinated reset stimulation, applied to a network featuring a loss of segregation caused by global synchronization, is able to restore the segregated activity and to truncate the pathological, synchronized activity.

High-frequency test stimulation for tremor suppression is a standard procedure for functional target localization during deep brain stimulation. This method does not work in cases where tremor vanishes intraoperatively, for example, due to general anaesthesia or due to an insertional effect. To overcome this difficulty, we developed a stimulation technique that effectively evokes tremor in a well-defined and quantifiable manner. For this, we used patterned low-frequency stimulation (PLFS), i.e. brief high-frequency pulse trains administered at pulse rates similar to neurons' preferred burst frequency. Unlike periodic single-pulse stimulation, PLFS enables one to convey effective and considerably greater integral charge densities without violation of safety requirements. In a computational investigation of an oscillatory neuronal network temporarily rendered inactive, we found that PLFS evokes synchronized activity, phase locked to the stimulus. While a stronger increase in the amount of synchrony in the neuronal population requires higher stimulus intensities, the portion of synchronously active neurons nevertheless becomes strongly phase locked to PLFS already at weak stimulus intensities. The phase entrainment effect of PLFS turned out to be robust against variations in the stimulation frequency, whereas enhancement of synchrony required precisely tuned stimulation frequencies. We applied PLFS to a patient with spinocerebellar ataxia type 2 (SCA2) with pronounced tremor that disappeared intraoperatively under general anaesthesia. In accordance with our computational results, PLFS evoked tremor, phase locked to the stimulus. In particular, weak PLFS caused low-amplitude, but strongly phase-locked tremor. PLFS test stimulations provided the only functional information about target localization. Optimal target point selection was confirmed by excellent post-operative tremor suppression.

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.

We study possible anti-kindling effects of the standard high-frequency deep brain stimulation (HFDBS) and of a desynchronizing multisite coordinated reset stimulation (MCRS) theoretically in a mathematical model of the subthalamic nucleus (STN). The latter is an effective target for deep brain stimulation (DBS) in patients suffering from Parkinson's disease (PD). Depending on the structures being activated, electrical pulses may have excitatory and/or inhibitory impact. According to our simulation results MCRS may achieve robust long-term anti-kindling (i.e., curative) effects, irrespectively, of the ratio between excitatory and inhibitory impact. This means, that during MCRS the STN unlearns its pathologic synaptic connections and reestablishes a physiological level of connectivity. In contrast, HFDBS has anti-kindling effects only if its impact is predominantly excitatory. Our results are relevant for selecting appropriate locations for DBS electrodes. In fact, even with HFDBS we may expect anti-kindling effects, provided the target is properly chosen.

This is a single case report of a patient with spinocerebellar ataxia type 2 (SCA2) and severe tremor. Whereas disease progression with prevailing ataxia and dysmetria was slow over the first symptomatic 6 years, 6 months prior to operation were characterized by the development of a severe, debilitating postural tremor rendering the patient unable to independently sit, stand, speak, or swallow. Deep brain stimulation (DBS) at a subthalamic-thalamic electrode position almost completely arrested her tremor. The patient regained the functional state prior to her rapid disease progression allowing a restricted range of daily activities. Her condition has remained approximately stable over the two postoperative years to date. In addition to the efficacy of DBS on cerebellar tremor, the results illustrate a remarkable improvement of the patient's general condition and independence.

This document is an editorial titled "Neuromodulation using spatiotemporally complex patterns" published in the journal Frontiers in Neuroinformatics. It discusses the use of different stimulation patterns in deep brain stimulation (DBS) for the treatment of Parkinson's disease (PD). The editorial highlights the potential benefits of stimulation with spatiotemporal patterns compared to conventional single-frequency stimulation. It also mentions other stimulation approaches, such as coordinated reset stimulation and adaptive DBS, and their potential clinical applications. The document emphasizes the importance of neuroplasticity as a target for the development of novel stimulation techniques. [Extracted from the article]

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]

Abnormally strong synchronized activity is related to several neurological disorders, including essential tremor, epilepsy, and Parkinson's disease. Chronic high-frequency deep brain stimulation (HF DBS) is an established treatment for advanced Parkinson's disease. To reduce the delivered integral electrical current, novel theory-based stimulation techniques such as coordinated reset (CR) stimulation directly counteract the abnormal synchronous firing by delivering phase-shifted stimuli through multiple stimulation sites. In computational studies in neuronal networks with spike-timing-dependent plasticity (STDP), it was shown that CR stimulation down-regulates synaptic weights and drives the network into an attractor of a stable desynchronized state. This led to desynchronization effects that outlasted the stimulation. Corresponding long-lasting therapeutic effects were observed in preclinical and clinical studies. Computational studies suggest that long-lasting effects of CR stimulation depend on the adjustment of the stimulation frequency to the dominant synchronous rhythm. This may limit clinical applicability as different pathological rhythms may coexist. To increase the robustness of the long-lasting effects, we study randomized versions of CR stimulation in networks of leaky integrate-and-fire neurons with STDP. Randomization is obtained by adding random jitters to the stimulation times and by shuffling the sequence of stimulation site activations. We study the corresponding long-lasting effects using analytical calculations and computer simulations. We show that random jitters increase the robustness of long-lasting effects with respect to changes of the number of stimulation sites and the stimulation frequency. In contrast, shuffling does not increase parameter robustness of long-lasting effects. Studying the relation between acute, acute after-, and long-lasting effects of stimulation, we find that both acute after- and long-lasting effects are strongly determined by the stimulation-induced synaptic reshaping, whereas acute effects solely depend on the statistics of administered stimuli. We find that the stimulation duration is another important parameter, as effective stimulation only entails long-lasting effects after a sufficient stimulation duration. Our results show that long-lasting therapeutic effects of CR stimulation with random jitters are more robust than those of regular CR stimulation. This might reduce the parameter adjustment time in future clinical trials and make CR with random jitters more suitable for treating brain disorders with abnormal synchronization in multiple frequency bands. [ABSTRACT FROM AUTHOR]

Alcohol use disorder (AUD) affects nearly 5% of the world's adult population. Despite treatment, AUD often manifests with relapse to binge drinking, which has been associated with corticostriatal hypersynchrony involving the nucleus accumbens (NAc). A modified "Drinking in the Dark" protocol was used to provoke binge-like alcohol drinking. We implemented Coordinated Reset Stimulation (CRS), a computationally designed, spatio-temporal stimulation algorithm, to desynchronize abnormal neuronal activity via a deep brain stimulation (DBS) electrode in the NAc of mice exhibiting binge-like alcohol drinking. Integral CRS charge injected would be 2.5% of that of conventional high-frequency DBS. NAc CRS delivery during only the initial phase of exposure to alcohol and prior to the exposure (but not during) significantly reduced binge-like drinking without interfering with social behavior or locomotor activity. NAc CRS ameliorates binge-like alcohol drinking and preliminarily exhibits sustained aftereffects that are suggestive of an unlearning of hypersynchrony. [ABSTRACT FROM AUTHOR]

Excessive neuronal synchrony is a hallmark of neurological disorders such as epilepsy and Parkinson's disease. An established treatment for medically refractory Parkinson's disease is high-frequency (HF) deep brain stimulation (DBS). However, symptoms return shortly after cessation of HF-DBS. Recently developed decoupling stimulation approaches, such as Random Reset (RR) stimulation, specifically target pathological connections to achieve long-lasting desynchronization. During RR stimulation, a temporally and spatially randomized stimulus pattern is administered. However, spatial randomization, as presented so far, may be difficult to realize in a DBS-like setup due to insufficient spatial resolution. Motivated by recently developed segmented DBS electrodes with multiple stimulation sites, we present a RR stimulation protocol that copes with the limited spatial resolution of currently available depth electrodes for DBS. Specifically, spatial randomization is realized by delivering stimuli simultaneously to L randomly selected stimulation sites out of a total of M stimulation sites, which will be called L/M-RR stimulation. We study decoupling by L/M-RR stimulation in networks of excitatory integrate-and-fire neurons with spike-timing dependent plasticity by means of theoretical and computational analysis. We find that L/M-RR stimulation yields parameter-robust decoupling and long-lasting desynchronization. Furthermore, our theory reveals that strong high-frequency stimulation is not suitable for inducing long-lasting desynchronization effects. As a consequence, low and high frequency L/M-RR stimulation affect synaptic weights in qualitatively different ways. Our simulations confirm these predictions and show that qualitative differences between low and high frequency L/M-RR stimulation are present across a wide range of stimulation parameters, rendering stimulation with intermediate frequencies most efficient. Remarkably, we find that L/M-RR stimulation does not rely on a high spatial resolution, characterized by the density of stimulation sites in a target area, corresponding to a large M. In fact, L/M-RR stimulation with low resolution performs even better at low stimulation amplitudes. Our results provide computational evidence that L/M-RR stimulation may present a way to exploit modern segmented lead electrodes for long-lasting therapeutic effects. [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]

Demand-controlled deep brain stimulation (DBS) appears to be a promising approach for the treatment of Parkinson's disease (PD) as revealed by computational, pre-clinical and clinical studies. Stimulation delivery is adapted to brain activity, for example, to the amount of neuronal activity considered to be abnormal. Such a closed-loop stimulation setup might help to reduce the amount of stimulation current, thereby maintaining therapeutic efficacy. In the context of the development of stimulation techniques that aim to restore desynchronized neuronal activity on a long-term basis, specific closed-loop stimulation protocols were designed computationally. These feedback techniques, e.g., pulsatile linear delayed feedback (LDF) or pulsatile nonlinear delayed feedback (NDF), were computationally developed to counteract abnormal neuronal synchronization characteristic for PD and other neurological disorders. By design, these techniques are intrinsically demand-controlled methods, where the amplitude of the stimulation signal is reduced when the desired desynchronized regime is reached. We here introduce a novel demand-controlled stimulation method, pulsatile multisite linear delayed feedback (MLDF), by employing MLDF to modulate the pulse amplitude of high-frequency (HF) DBS, in this way aiming at a specific, MLDF-related desynchronizing impact, while maintaining safety requirements with the charge-balanced HF DBS. Previously, MLDF was computationally developed for the control of spatio-temporal synchronized patterns and cluster states in neuronal populations. Here, in a physiologically motivated model network comprising neurons from subthalamic nucleus (STN) and external globus pallidus (GPe), we compare pulsatile MLDF to pulsatile LDF for the case where the smooth feedback signals are used to modulate the amplitude of charge-balanced HF DBS and suggest a modification of pulsatile MLDF which enables a pronounced desynchronizing impact. Our results may contribute to further clinical development of closed-loop DBS techniques. [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]

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]