Selection Of Stimulation Parameters Research Articles

Local neuroanatomical and tract-based proxies of optimal subcallosal cingulate deep brain stimulation

BackgroundDeep brain stimulation of the subcallosal cingulate area (SCC-DBS) is a promising neuromodulatory therapy for treatment-resistant depression (TRD). Biomarkers of optimal target engagement are needed to guide surgical targeting and stimulation parameter selection and to reduce variance in clinical outcome. Objective/HypothesisWe aimed to characterize the relationship between stimulation location, white matter tract engagement, and clinical outcome in a large (n = 60) TRD cohort treated with SCC-DBS. A smaller cohort (n = 22) of SCC-DBS patients with differing primary indications (bipolar disorder/anorexia nervosa) was utilized as an out-of-sample validation cohort. MethodsVolumes of tissue activated (VTAs) were constructed in standard space using high-resolution structural MRI and individual stimulation parameters. VTA-based probabilistic stimulation maps (PSMs) were generated to elucidate voxelwise spatial patterns of efficacious stimulation. A whole-brain tractogram derived from Human Connectome Project diffusion-weighted MRI data was seeded with VTA pairs, and white matter streamlines whose overlap with VTAs related to outcome (‘discriminative’ streamlines; Puncorrected < 0.05) were identified using t-tests. Linear modelling was used to interrogate the potential clinical relevance of VTA overlap with specific structures. ResultsPSMs varied by hemisphere: high-value left-sided voxels were located more anterosuperiorly and squarely in the lateral white matter, while the equivalent right-sided voxels fell more posteroinferiorly and involved a greater proportion of grey matter. Positive discriminative streamlines localized to the bilateral (but primarily left) cingulum bundle, forceps minor/rostrum of corpus callosum, and bilateral uncinate fasciculus. Conversely, negative discriminative streamlines mostly belonged to the right cingulum bundle and bilateral uncinate fasciculus. The best performing linear model, which utilized information about VTA volume overlap with each of the positive discriminative streamline bundles as well as the negative discriminative elements of the right cingulum bundle, explained significant variance in clinical improvement in the primary TRD cohort (R = 0.46, P < 0.001) and survived repeated 10-fold cross-validation (R = 0.50, P = 0.040). This model was also able to predict outcome in the out-of-sample validation cohort (R = 0.43, P = 0.047). Conclusion(s)These findings reinforce prior indications of the importance of white matter engagement to SCC-DBS treatment success while providing new insights that could inform surgical targeting and stimulation parameter selection decisions.

Targeted Selection of Stimulation Parameters for Restoration of Motor and Autonomic Function in Individuals With Spinal Cord Injury

Study DesignThis is a report of methods and tools for selection of task and individual configurations targeted for voluntary movement, standing, stepping, blood pressure stabilization, and facilitation of bladder storage and emptying using tonic-interleaved excitation of the lumbosacral spinal cord. ObjectivesThis study aimed to present strategies used for selection of stimulation parameters for various motor and autonomic functions. ConclusionsTonic-interleaved functionally focused neuromodulation targets a myriad of consequences from spinal cord injury with surgical implantation of the epidural electrode at a single location. This approach indicates the sophistication of the human spinal cord circuitry and its important role in the regulation of motor and autonomic functions in humans.

Image-Guided Programming Tool for DBS Programming Used with a Multiple-Source, Constant-Current System Reduces Initial Programming Time (P4-11.012)

Image-Guided Programming Tool for DBS Programming Used with a Multiple-Source, Constant-Current System Reduces Initial Programming Time (P4-11.012)

Microneurography as a minimally invasive method to assess target engagement during neuromodulation

Objective. Peripheral neural signals recorded during neuromodulation therapies provide insights into local neural target engagement and serve as a sensitive biomarker of physiological effect. Although these applications make peripheral recordings important for furthering neuromodulation therapies, the invasive nature of conventional nerve cuffs and longitudinal intrafascicular electrodes (LIFEs) limit their clinical utility. Furthermore, cuff electrodes typically record clear asynchronous neural activity in small animal models but not in large animal models. Microneurography, a minimally invasive technique, is already used routinely in humans to record asynchronous neural activity in the periphery. However, the relative performance of microneurography microelectrodes compared to cuff and LIFE electrodes in measuring neural signals relevant to neuromodulation therapies is not well understood. Approach. To address this gap, we recorded cervical vagus nerve electrically evoked compound action potentials (ECAPs) and spontaneous activity in a human-scaled large animal model—the pig. Additionally, we recorded sensory evoked activity and both invasively and non-invasively evoked CAPs from the great auricular nerve. In aggregate, this study assesses the potential of microneurography electrodes to measure neural activity during neuromodulation therapies with statistically powered and pre-registered outcomes (https://osf.io/y9k6j). Main results. The cuff recorded the largest ECAP signal (p < 0.01) and had the lowest noise floor amongst the evaluated electrodes. Despite the lower signal to noise ratio, microneurography electrodes were able to detect the threshold for neural activation with similar sensitivity to cuff and LIFE electrodes once a dose-response curve was constructed. Furthermore, the microneurography electrodes recorded distinct sensory evoked neural activity. Significance. The results show that microneurography electrodes can measure neural signals relevant to neuromodulation therapies. Microneurography could further neuromodulation therapies by providing a real-time biomarker to guide electrode placement and stimulation parameter selection to optimize local neural fiber engagement and study mechanisms of action.

Development of a muscle electrical stimulation parameter selection method with an intelligent system

In this study, we propose a methodology for the selection of electrical stimulation parameters for muscle rehabilitation. This methodology uses a particle swarm optimizer to find a set of parameters that maximizes the muscle contraction force during the stimulation session. The optimization makes use of a previously validated mathematical muscle contraction model. To adjust the model to this application, we propose a series of adaptations to the model, such as the inclusion of a muscle fatigue function and different levels of muscle atrophy representations thru parametric variation. We based our model adaptations on the results of parametric sensitivity analysis and the qualitative changes in muscle properties during atrophy and fatigue described in the current literature. With the fatigue function, we successfully recreated the qualitative behavior reported in the literature for muscle fatigue caused by electrical stimulation. The parametric variations proposed following the sensitivity analysis are consistent with the physiological changes occurring during muscle atrophy, and the simulations with the model supported our hypothesis. Finally, we showed that with the model and the particle swarm optimizer, it is possible to find a set of electrical stimulation parameters that maximize the muscle contraction force during the stimulation session.

Real-time monitoring of manual acupuncture stimulation parameters based on domain adaptive 3D hand pose estimation

Manual acupuncture (MA) is a widely used type of therapy method in the world, its treatment result and clinical safety are highly related to the selection of stimulation parameters (needling amplitude and frequency) of acupuncturists. However, to date, there is no stimulation parameter measurement solution that can be conveniently used in the clinic. Thus, there is an urgent need to develop a single camera-based real-time monitoring system for MA operation. This monitoring system is expected to give the result of both the amplitude and frequency of MA. Considering that constructing the labeled MA monitoring dataset is laborious and time-consuming and that there is a large amount of unlabeled data, we propose an adaptive orientation-based domain adaptation framework to alleviate the domain shift and achieve better performance. Moreover, we contribute a benchmark that contains 20 videos of on-body MA operation and 30 videos of on-simulator MA operation with 3D coordinates to facilitate the future development of real-time MA monitoring. Extensive experiments on the proposed benchmark demonstrate the superiority of the proposed methods on both movement estimation and frequency estimation of hand acupuncture. The application prospects of this framework for the clinical work of MA included the investigation of dose–effect relationship of MA, enhancement of its operation safety, etc. Our data is publicly available at https://github.com/SHUTCM-tcme/SUTCM-AM.

Globus pallidus internus deep brain stimulation evokes resonant neural activity in Parkinson's disease.

Globus pallidus internus deep brain stimulation is an established therapy for patients with medication-refractory Parkinson's disease. Clinical outcomes are highly dependent on applying stimulation to precise locations in the brain. However, robust neurophysiological markers are needed to determine the optimal electrode location and to guide postoperative stimulation parameter selection. In this study, we evaluated evoked resonant neural activity in the pallidum as a potential intraoperative marker to optimize targeting and stimulation parameter selection to improve outcomes of deep brain stimulation for Parkinson's disease. Intraoperative local field potential recordings were acquired in 22 patients with Parkinson's disease undergoing globus pallidus internus deep brain stimulation implantation (N = 27 hemispheres). A control group of patients undergoing implantation in the subthalamic nucleus (N = 4 hemispheres) for Parkinson's disease or the thalamus for essential tremor (N = 9 patients) were included for comparison. High-frequency (135 Hz) stimulation was delivered from each electrode contact sequentially while recording the evoked response from the other contacts. Low-frequency stimulation (10 Hz) was also applied as a comparison. Evoked resonant neural activity features, including amplitude, frequency and localization were measured and analysed for correlation with empirically derived postoperative therapeutic stimulation parameters. Pallidal evoked resonant neural activity elicited by stimulation in the globus pallidus internus or externus was detected in 26 of 27 hemispheres and varied across hemispheres and across stimulating contacts within individual hemispheres. Bursts of high-frequency stimulation elicited evoked resonant neural activity with similar amplitudes (P = 0.9) but a higher frequency (P = 0.009) and a higher number of peaks (P = 0.004) than low-frequency stimulation. We identified a 'hotspot' in the postero-dorsal pallidum where stimulation elicited higher evoked resonant neural activity amplitudes (P < 0.001). In 69.6% of hemispheres, the contact that elicited the maximum amplitude intraoperatively matched the contact empirically selected for chronic therapeutic stimulation by an expert clinician after 4 months of programming sessions. Pallidal and subthalamic nucleus evoked resonant neural activity were similar except for lower pallidal amplitudes. No evoked resonant neural activity was detected in the essential tremor control group. Given its spatial topography and correlation with postoperative stimulation parameters empirically selected by expert clinicians, pallidal evoked resonant neural activity shows promise as a potential marker to guide intraoperative targeting and to assist the clinician with postoperative stimulation programming. Importantly, evoked resonant neural activity may also have the potential to guide directional and closed-loop deep brain stimulation programming for Parkinson's disease.

Parasympathetic control of gastrointestinal motility and cross-branch actions of parasympathetic neuromodulation.

Parasympathetic control of gastrointestinal motility and cross-branch actions of parasympathetic neuromodulation.

Research on Electroacupuncture Parameters for Cancer Pain Based on Data Mining.

Cancer pain, a common complication of this disease, has been widely treated by electroacupuncture in recent years. However, there are numerous treatment parameters that are not conducive to clinical translation applications. This study aims to summarize the stimulation parameters commonly used in electroacupuncture treating cancer pain by data mining and visualization techniques to provide a basis for the future acupuncture technology transformation and selection of optimal stimulation parameters. Nine databases, including Pubmed, Cochrane Library, Embase, Web of Science, OVID, China National Knowledge Infrastructure Database, China Biology Medicine disk, China Science and Technology Journal Database, and Wanfang Database, were searched for clinical studies on electroacupuncture treatment cancer pain published between January 2012 and September 2022. A database was established using Microsoft Excel 2020 and analyzed with SPSS Modeler 18.1 software and SPSS statistics 26.0 software. Twenty-four articles were included according to the established criteria. The most used electroacupuncture stimulation parameters were a dilatational wave, the current frequency of 2/100 Hz, stimulation duration of 30 minutes per treatment, and frequency of treatment once a day. Fifty-eight acupoints were mentioned, and the total frequency of acupoints involved was 156 times. The most used ones include Zusanli (ST36), Sanyinjiao (SP06), Hegu (LI04), Neiguan (PC06), Quchi (LI11), Taichong (LR03), Ashi point, Jiaji point, and those most generally used acupoints that are closely arranged on the Stomach Channel of Foot Yangming and the Spleen Channel of Foot Taiyin. The association analysis of acupoints revealed that the most supported acupoint pair was Sanyinjiao (SP06) and Zusanli (ST36). Cluster analysis demonstrated 3 groups, 1 for obligatory acupoints, 1 for Ashi point, and the third for Jiaji point. A dilatational wave, the current frequency of 2/100 Hz, 30-minute stimulation, and acupoints of the Stomach Channel of Foot Yangming and the Spleen Channel of Foot Taiyin selection are frequently used in electroacupuncture for treating cancer pain. Due to the limitations of this study, further research and more standardized, multi-center, large-sample clinical trials can be carried out to guide optimizing acupuncture treatment schemes and promote the formation of TCM-characteristic technologies for cancer pain.

Automated deep brain stimulation programming based on electrode location: a randomised, crossover trial using a data-driven algorithm

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is highly effective in controlling motor symptoms in patients with Parkinson's disease. However, correct selection of stimulation parameters is pivotal to treatment success and currently follows a time-consuming and demanding trial-and-error process. We aimed to assess treatment effects of stimulation parameters suggested by a recently published algorithm (StimFit) based on neuroimaging data. This double-blind, randomised, crossover, non-inferiority trial was carried out at Charité - Universitätsmedizin, Berlin, Germany, and enrolled patients with Parkinson's disease treated with directional octopolar electrodes targeted at the STN. All patients had undergone DBS programming according to our centre's standard of care (SoC) treatment before study recruitment. Based on perioperative imaging data, DBS electrodes were reconstructed and StimFit was applied to suggest optimal stimulation settings. Patients underwent motor assessments using the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS-III) during OFF-medication and in OFF-stimulation and ON-stimulation states under both conditions, StimFit and SoC parameter settings. Patients were randomly assigned (1:1) to receive either StimFit-programmed DBS first and SoC-programmed DBS second, or SoC-programmed DBS first and StimFit-programmed DBS second. The allocation schedule was generated using a computerised random number generator. Both the rater and patients were masked to the sequence of SoC and StimFit stimulation conditions. All patients who participated in the study were included in the analysis. The primary endpoint of this study was the absolute mean difference between MDS-UPDRS-III scores under StimFit and SoC stimulation, with a non-inferiority margin of 5 points. The study was registered at the German Register for Clinical Trials (DRKS00023115), and is complete. Between July 10, 2020, and Oct 28, 2021, 35 patients were enrolled in the study; 18 received StimFit followed by SoC stimulation, and 17 received SoC followed by StimFit stimulation. Mean MDS-UPDRS-III scores improved from 47·3 (SD 17·1) at OFF-stimulation baseline to 24·7 (SD 12·4) and 26·3 (SD 12·4) under SoC and StimFit stimulation, respectively. Mean difference between motor scores was -1·6 (SD 7·1; 95% CI -4·0 to 0·9; superiority test psuperiority=0·20; n=35), establishing non-inferiority of StimFit stimulation at a margin of -5 points (non-inferiority test pnon-inferiority=0·0038). In six patients (17%), initial programming of StimFit settings resulted in acute side-effects and amplitudes were reduced until side-effects disappeared. Automated data-driven algorithms can predict stimulation parameters that lead to motor symptom control comparable to SoC treatment. This approach could significantly decrease the time necessary to obtain optimal treatment parameters. Deutsche Forschungsgemeinschaft through NeuroCure Clinical Research Center and TRR 295.

PO035 / #735 PATIENT-SPECIFIC MODELLING FOR PRECISION NEUROMODULATION: E-POSTER VIEWING

The selection of electrode geometry, electrode positioning and stimulation parameters has a significant impact on the efficacy of electrical neuromodulation. The changes in the electric field that these factors produce can be unpredictable and influence the effect of stimulation on the target. Further, individual variations in anatomy affect the electric field, making generalization across individuals challenging. This individual variation can be partially overcome using post-intervention programming.

Effect of stimulation parameters on sequential current-steered stimuli in cochlear implants.

Manipulation of cochlear implant (CI) place pitch was carried out with current steering by stimulating two CI electrodes sequentially. The objective was to investigate whether shifts in activated neural populations could be achieved to produce salient pitch differences and to determine which stimulation parameters would be more effective in steering of current. These were the pulse rate and pulse width of electrical stimuli and the distance between the two current-steering electrodes. Nine CI users participated, and ten ears were tested. The pattern of pitch changes was not consistent across listeners, but the data suggest that individualized selection of stimulation parameters may be used to effect place pitch changes with sequential current steering. Individual analyses showed that pulse width generally had little influence on the effectiveness of current steering with sequential stimuli, while more salient place pitch shifts were often achieved at wider electrode spacing or when the stimulation pulse rate was the same as that indicated on the clinical MAP (the set of stimulation parameters) of the listener. Results imply that current steering may be used in CIs that allow only sequential stimulation to achieve place pitch manipulation.

Stereotactic EEG Helps Define Networks and Optimize Stimulation Parameter Selection in DBS for Treatment-Resistant Depression (TRD).

Deep brain stimulation for TRD faces critical unknowns, including defining the modulated brain network, and characterizing response patterns to optimize stimulation parameter selection. In a novel experimental setting – patients undergoing DBS for TRD with temporary stereotactic EEG (sEEG) electrodes implanted across the fronto-temporal networks – we study network structure using a single-pulse evoked potential paradigm, and then undertake a new approach to stimulation parameter selection guided by electrophysiology.

Brain Imaging and Visualization Technologies to Identify Stimulation Targets

Invasive brain stimulation therapies for neuropsychiatric disorders have long relied upon MRI data to identify anatomical targets for stimulation. However, recent developments in connectomic data analyses have introduced a wide range of new approaches to overlaying model-based results associated with the brain networks of interest onto the MRI. These new methods are playing an important role in directing electrode placement and stimulation parameter selection in DBS research subjects.

Identifying the neural network for neuromodulation in epilepsy through connectomics and graphs.

Deep brain stimulation is a treatment option for patients with drug-resistant epilepsy. The precise mechanism of neuromodulation in epilepsy is unknown, and biomarkers are needed for optimizing treatment. The aim of this study was to describe the neural network associated with deep brain stimulation targets for epilepsy and to explore its potential application as a novel biomarker for neuromodulation. Using seed-to-voxel functional connectivity maps, weighted by seizure outcomes, brain areas associated with stimulation were identified in normative resting state functional scans of 1000 individuals. To pinpoint specific regions in the normative epilepsy deep brain stimulation network, we examined overlapping areas of functional connectivity between the anterior thalamic nucleus, centromedian thalamic nucleus, hippocampus and less studied epilepsy deep brain stimulation targets. Graph network analysis was used to describe the relationship between regions in the identified network. Furthermore, we examined the associations of the epilepsy deep brain stimulation network with disease pathophysiology, canonical resting state networks and findings from a systematic review of resting state functional MRI studies in epilepsy deep brain stimulation patients. Cortical nodes identified in the normative epilepsy deep brain stimulation network were in the anterior and posterior cingulate, medial frontal and sensorimotor cortices, frontal operculum and bilateral insulae. Subcortical nodes of the network were in the basal ganglia, mesencephalon, basal forebrain and cerebellum. Anterior thalamic nucleus was identified as a central hub in the network with the highest betweenness and closeness values, while centromedian thalamic nucleus and hippocampus showed average centrality values. The caudate nucleus and mammillothalamic tract also displayed high centrality values. The anterior cingulate cortex was identified as an important cortical hub associated with the effect of deep brain stimulation in epilepsy. The neural network of deep brain stimulation targets shared hubs with known epileptic networks and brain regions involved in seizure propagation and generalization. Two cortical clusters identified in the epilepsy deep brain stimulation network included regions corresponding to resting state networks, mainly the default mode and salience networks. Our results were concordant with findings from a systematic review of resting state functional MRI studies in patients with deep brain stimulation for epilepsy. Our findings suggest that the various epilepsy deep brain stimulation targets share a common cortico-subcortical network, which might in part underpin the antiseizure effects of stimulation. Interindividual differences in this network functional connectivity could potentially be used as biomarkers in selection of patients, stimulation parameters and neuromodulation targets.

Linking profiles of pathway activation with clinical motor improvements – A retrospective computational study

Background: Deep brain stimulation (DBS) is an established therapy for patients with Parkinson’s disease. In silico computer models for DBS hold the potential to inform a selection of stimulation parameters. In recent years, the focus has shifted towards DBS-induced firing in myelinated axons, deemed particularly relevant for the external modulation of neural activity.Objective: The aim of this project was to investigate correlations between patient-specific pathway activation profiles and clinical motor improvement.Methods: We used the concept of pathway activation modeling, which incorporates advanced volume conductor models and anatomically authentic fiber trajectories to estimate DBS-induced action potential initiation in anatomically plausible pathways that traverse in close proximity to targeted nuclei. We applied the method on two retrospective datasets of DBS patients, whose clinical improvement had been evaluated according to the motor part of the Unified Parkinson’s Disease Rating Scale. Based on differences in outcome and activation levels for intrapatient DBS protocols in a training cohort, we derived a pathway activation profile that theoretically induces a complete alleviation of symptoms described by UPDRS-III. The profile was further enhanced by analyzing the importance of matching activation levels for individual pathways.Results: The obtained profile emphasized the importance of activation in pathways descending from the motor-relevant cortical regions as well as the pallidothalamic pathways. The degree of similarity of patient-specific profiles to the optimal profile significantly correlated with clinical motor improvement in a test cohort.Conclusion: Pathway activation modeling has a translational utility in the context of motor symptom alleviation in Parkinson’s patients treated with DBS.

Effects of parameters selection with transcranial direct current stimulation based on real head model

Transcranial direct current stimulation (tDCS) is a brain stimulation intervention technique, which has the problem of different criteria for the selection of stimulation parameters. In this study, a four-layer real head model was constructed. Based on this model, the changes of the electric field distribution in the brain with the current intensity, electrode shape, electrode area and electrode spacing were analyzed by using finite element simulation technology, and then the optimal scheme of electrical stimulation parameters was discussed. The results showed that the effective stimulation region decreased and the focusing ability increased with the increase of current intensity. The normal current density of the quadrilateral electrode was obviously larger than that of the circular electrode, which indicated that the quadrilateral electrode was more conducive to current stimulation of neurons. Moreover, the effective stimulation region of the quadrilateral electrode was more concentrated and the focusing ability was stronger. The focusing ability decreased with the increase of electrode area. Specifically, the focusing tended to increase first and then decrease with the increase of electrode spacing and the optimal electrode spacing was 64.0-67.2 mm. These results could provide some basis for the selection of electrical stimulation parameters.

Effects of anterior thalamic nuclei stimulation on hippocampal activity: Chronic recording in a patient with drug-resistant focal epilepsy.

Implanted neurostimulation devices are gaining traction as palliative treatment options for certain forms of drug-resistant epilepsy, but clinical utility of these devices is hindered by incomplete mechanistic understanding of their therapeutic effects. Approved devices for anterior thalamic nuclei deep brain stimulation (ANT DBS) are thought to work at a network level, but limited sensing capability precludes characterization of neurophysiological effects outside the thalamus. Here, we describe a patient with drug-resistant temporal lobe epilepsy who was implanted with a responsive neurostimulation device (RNS System), involving hippocampal and ipsilateral temporal neocortical leads, and subsequently received ANT DBS. Over 1.5years, RNS System electrocorticography enabled multiscale characterization of neurophysiological effects of thalamic stimulation. In brain regions sampled by the RNS System, ANT DBS produced acute, phasic, frequency-dependent responses, including suppression of hippocampal low frequency local field potentials. ANT DBS modulated functional connectivity between hippocampus and neocortex. Finally, ANT DBS progressively suppressed hippocampal epileptiform activity in relation to the extent of hippocampal theta suppression, which informs stimulation parameter selection for ANT DBS. Taken together, this unique clinical scenario, involving hippocampal recordings of unprecedented chronicity alongside ANT DBS, sheds light on the therapeutic mechanism of thalamic stimulation and highlights capabilities needed in next-generation devices.

Structural connectivity predicts clinical outcomes of deep brain stimulation for Tourette syndrome.

Deep brain stimulation may be an effective therapy for select cases of severe, treatment-refractory Tourette syndrome; however, patient responses are variable, and there are no reliable methods to predict clinical outcomes. The objectives of this retrospective study were to identify the stimulation-dependent structural networks associated with improvements in tics and comorbid obsessive-compulsive behaviour, compare the networks across surgical targets, and determine if connectivity could be used to predict clinical outcomes. Volumes of tissue activated for a large multisite cohort of patients (n = 66) implanted bilaterally in globus pallidus internus (n = 34) or centromedial thalamus (n = 32) were used to generate probabilistic tractography to form a normative structural connectome. The tractography maps were used to identify networks that were correlated with improvement in tics or comorbid obsessive-compulsive behaviour and to predict clinical outcomes across the cohort. The correlated networks were then used to generate 'reverse' tractography to parcellate the total volume of stimulation across all patients to identify local regions to target or avoid. The results showed that for globus pallidus internus, connectivity to limbic networks, associative networks, caudate, thalamus, and cerebellum was positively correlated with improvement in tics; the model predicted clinical improvement scores (P = 0.003) and was robust to cross-validation. Regions near the anteromedial pallidum exhibited higher connectivity to the positively correlated networks than posteroventral pallidum, and volume of tissue activated overlap with this map was significantly correlated with tic improvement (P < 0.017). For centromedial thalamus, connectivity to sensorimotor networks, parietal-temporal-occipital networks, putamen, and cerebellum was positively correlated with tic improvement; the model predicted clinical improvement scores (P = 0.012) and was robust to cross-validation. Regions in the anterior/lateral centromedial thalamus exhibited higher connectivity to the positively correlated networks, but volume of tissue activated overlap with this map did not predict improvement (P > 0.23). For obsessive-compulsive behaviour, both targets showed that connectivity to the prefrontal cortex, orbitofrontal cortex, and cingulate cortex was positively correlated with improvement; however, only the centromedial thalamus maps predicted clinical outcomes across the cohort (P = 0.034), but the model was not robust to cross-validation. Collectively, the results demonstrate that the structural connectivity of the site of stimulation are likely important for mediating symptom improvement, and the networks involved in tic improvement may differ across surgical targets. These networks provide important insight on potential mechanisms and could be used to guide lead placement and stimulation parameter selection, as well as refine targets for neuromodulation therapies for Tourette syndrome.

Specific vagus nerve stimulation parameters alter serum cytokine levels in the absence of inflammation

BackgroundElectrical stimulation of peripheral nerves is a widely used technique to treat a variety of conditions including chronic pain, motor impairment, headaches, and epilepsy. Nerve stimulation to achieve efficacious symptomatic relief depends on the proper selection of electrical stimulation parameters to recruit the appropriate fibers within a nerve. Recently, electrical stimulation of the vagus nerve has shown promise for controlling inflammation and clinical trials have demonstrated efficacy for the treatment of inflammatory disorders. This application of vagus nerve stimulation activates the inflammatory reflex, reducing levels of inflammatory cytokines during inflammation.MethodsHere, we wanted to test whether altering the parameters of electrical vagus nerve stimulation would change circulating cytokine levels of normal healthy animals in the absence of increased inflammation. To examine this, we systematically tested a set of electrical stimulation parameters and measured serum cytokine levels in healthy mice.ResultsSurprisingly, we found that specific combinations of pulse width, pulse amplitude, and frequency produced significant increases of the pro-inflammatory cytokine tumor necrosis factor (TNF), while other parameters selectively lowered serum TNF levels, as compared to sham-stimulated mice. In addition, serum levels of the anti-inflammatory cytokine interleukin-10 (IL-10) were significantly increased by select parameters of electrical stimulation but remained unchanged with others.ConclusionsThese results indicate that electrical stimulation parameter selection is critically important for the modulation of cytokines via the cervical vagus nerve and that specific cytokines can be increased by electrical stimulation in the absence of inflammation. As the next generation of bioelectronic therapies and devices are developed to capitalize on the neural regulation of inflammation, the selection of nerve stimulation parameters will be a critically important variable for achieving cytokine-specific changes.