Impact of anesthesia on micromagnetic stimulation (µMS) of the vagus nerve.

To treat diseases associated with vagal nerve control of peripheral organs, it is necessary to selectively activate efferent and afferent fibers in the vagus. As a result of the nerve's complex anatomy, fiber-specific activation proves challenging. Spatially selective neuromodulation using micromagnetic stimulation(µMS) is showing incredible promise. This neuromodulation technique uses microcoils(µcoils) to generate magnetic fields by powering them with a time-varying current. Following the principles of Faraday's law of induction, a highly directional electric field is induced in the nerve from the magnetic field. In this study on rodent cervical vagus, a solenoidalµcoil was oriented at an angle to left and right branches of the nerve. The aim of this study was to measure changes in the mean arterial pressure (MAP) and heart rate (HR) followingµMS of the vagus. Theµcoils were powered by a single-cycle sinusoidal current varying in pulse widths(PW = 100, 500, and 1000µsec) at a frequency of 20 Hz. Under the influence of isoflurane,µMS of the left vagus at 1000µsec PW led to an average drop in MAP of 16.75 mmHg(n = 7). In contrast,µMS of the right vagus under isoflurane resulted in an average drop of 11.93 mmHg in the MAP(n = 7). Surprisingly, there were no changes in HR to either right or left vagalµMS suggesting the drop in MAP associated with vagusµMS was the result of stimulation of afferent, but not efferent fibers. In urethane anesthetized rats, no changes in either MAP or HR were observed uponµMS of the right or left vagus(n = 3). These findings suggest the choice of anesthesia plays a key role in determining the efficacy ofµMS on the vagal nerve. Absence of HR modulation uponµMS could offer alternative treatment options using VNS with fewer heart-related side-effects.

Neural signal data collection and analysis of Percept™ PC BrainSense recordings for thalamic stimulation in epilepsy.

Deep brain stimulation (DBS) using Medtronic's Percept™ PC implantable pulse generator is FDA-approved for treating Parkinson's disease (PD), essential tremor, dystonia, obsessive compulsive disorder, and epilepsy. Percept™ PC enables simultaneous recording of neural signals from the same lead used for stimulation. Many Percept™ PC sensing features were built with PD patients in mind, but these features are potentially useful to refine therapies for many different disease processes. When starting our ongoing epilepsy research study, we found it difficult to find detailed descriptions about these features and have compiled information from multiple sources to understand it as a tool, particularly for use in patients other than those with PD. Here we provide a tutorial for scientists and physicians interested in using Percept™ PC's features and provide examples of how neural time series data is often represented and saved. We address characteristics of the recorded signals and discuss Percept™ PC hardware and software capabilities in data pre-processing, signal filtering, and DBS lead performance. We explain the power spectrum of the data and how it is shaped by the filter response of Percept™ PC as well as the aliasing of the stimulation due to digitally sampling the data. We present Percept™ PC's ability to extract biomarkers that may be used to optimize stimulation therapy. We show how differences in lead type affects noise characteristics of the implanted leads from seven epilepsy patients enrolled in our clinical trial. Percept™ PC has sufficient signal-to-noise ratio, sampling capabilities, and stimulus artifact rejection for neural activity recording. Limitations in sampling rate, potential artifacts during stimulation, and shortening of battery life when monitoring neural activity at home were observed. Despite these limitations, Percept™ PC demonstrates potential as a useful tool for recording neural activity in order to optimize stimulation therapies to personalize treatment.

Micromagnetic Stimulation (µMS) Controls Dopamine Release: An in vivo Study Using WINCS Harmoni.

Objective: Research into the role of neurotransmitters in regulating normal and pathologic brain functions has made significant progress. Yet, clinical trials that aim to improve therapeutic interventions do not take advantage of the in vivo changes in the neurochemistry that occur in real time during disease progression, drug interactions or response to pharmacological, cognitive, behavioral, and neuromodulation therapies. In this work, we used the WINCS Harmoni tool to study the real time in vivo changes in dopamine release in rodent brains for the micromagnetic neuromodulation therapy. Approach: Although still in its infancy, micromagnetic stimulation (µMS) using micro-meter sized coils or microcoils (µcoils) has shown incredible promise in spatially selective, galvanic contact free and highly focal neuromodulation. These µcoils are powered by a time-varying current which generates a magnetic field. As per Faraday's Laws of Electromagnetic Induction, this magnetic field induces an electric field in a conducting medium (here, the brain tissues). We used a solenoidal-shaped µcoil to stimulate the medial forebrain bundle (MFB) of the rodent brain in vivo. The evoked in vivo dopamine releases in the striatum were tracked in real time by carbon fiber microelectrodes (CFM) using fast scan cyclic voltammetry (FSCV). Results: Our experiments report that µcoils can successfully activate the MFB in rodent brains, triggering dopamine release in vivo. We further show that the successful release of dopamine upon micromagnetic stimulation is dependent on the orientation of the µcoil. Furthermore, varied intensities of µMS can control the concentration of dopamine releases in the striatum. Significance: This work helps us better understand the brain and its conditions arising from a new therapeutic intervention, like µMS, at the level of neurotransmitter release. Despite its early stage, this study potentially paves the path for µMS to enter the clinical world as a precisely controlled and optimized neuromodulation therapy.

Micromagnetic stimulation (µMS) dose-response of the rat sciatic nerve.

Objective.The objective of this study was to investigate the effects of micromagnetic stimuli strength and frequency from theMagneticPen(MagPen) on the rat right sciatic nerve. The nerve's response was measured by recording muscle activity and movement of the right hind limb.Approach.The MagPen was custom-built to be stably held over the sciatic nerve. Rat leg muscle twitches were captured on video, and movements were extracted using image processing algorithms. EMG recordings were also used to measure muscle activity.Main results.The MagPen prototype, when driven by an alternating current, generates a time-varying magnetic field, which, according to Faraday's law of electromagnetic induction, induces an electric field for neuromodulation. The orientation-dependent spatial contour maps of the induced electric field from the MagPen prototype have been numerically simulated. Furthermore, in thisin vivowork onµMS, a dose-response relationship has been reported by experimentally studying how varying the amplitude (Range: 25 mVp-pthrough 6Vp-p) and frequency (range: 100 Hz through 5 kHz) of the MagPen stimuli alters hind limb movement. The primary highlight of this dose-response relationship (repeated overnrats, wheren= 7) is that for aµMS stimuli of higher frequency, significantly smaller amplitudes can trigger hind limb muscle twitch. This frequency-dependent activation can be justified by Faraday's Law, which states that the magnitude of the induced electric field is directly proportional to the frequency.Significance.This work reports thatµMS can successfully activate the sciatic nerve in a dose-dependent manner. The impact of this dose-response curve addresses the controversy in this research community about whether the stimulation from theseµcoils arise from a thermal effect or micromagnetic stimulation. MagPen probes do not have a direct electrochemical interface with tissue and therefore do not experience electrode degradation, biofouling, and irreversible redox reactions like traditional direct contact electrodes. Magnetic fields from theµcoils create more precise activation than electrodes because they apply more focused and localized stimulation. Finally, unique features ofµMS, such as the orientation dependence, directionality, and spatial specificity, have been discussed.

Epidural stimulation restores muscle synergies by modulating neural drives in participants with sensorimotor complete spinal cord injuries.

Multiple studies have corroborated the restoration of volitional motor control after motor-complete spinal cord injury (SCI) through the use of epidural spinal cord stimulation (eSCS), but rigorous quantitative descriptions of muscle coordination have been lacking. Six participants with chronic, motor and sensory complete SCI underwent a brain motor control assessment (BMCA) consisting of a set of structured motor tasks with and without eSCS. We investigated how muscle activity complexity and muscle synergies changed with and without stimulation. We performed this analysis to better characterize the impact of stimulation on neuromuscular control. We also recorded data from nine healthy participants as controls. Competition exists between the task origin and neural origin hypotheses underlying muscle synergies. The ability to restore motor control with eSCS in participants with motor and sensory complete SCI allows us to test whether changes in muscle synergies reflect a neural basis in the same task. Muscle activity complexity was computed with Higuchi Fractal Dimensional (HFD) analysis, and muscle synergies were estimated using non-negative matrix factorization (NNMF) in six participants with American Spinal Injury Association (ASIA) Impairment Score (AIS) A. We found that the complexity of muscle activity was immediately reduced by eSCS in the SCI participants. We also found that over the follow-up sessions, the muscle synergy structure of the SCI participants became more defined, and the number of synergies decreased over time, indicating improved coordination between muscle groups. Lastly, we found that the muscle synergies were restored with eSCS, supporting the neural hypothesis of muscle synergies. We conclude that eSCS restores muscle movements and muscle synergies that are distinct from those of healthy, able-bodied controls.

In silicodevelopment and validation of Bayesian methods for optimizing deep brain stimulation to enhance cognitive control.

Objective.deep brain stimulation (DBS) of the ventral internal capsule/striatum (VCVS) is a potentially effective treatment for several mental health disorders when conventional therapeutics fail. Its effectiveness, however, depends on correct programming to engage VCVS sub-circuits. VCVS programming is currently an iterative, time-consuming process, with weeks between setting changes and reliance on noisy, subjective self-reports. An objective measure of circuit engagement might allow individual settings to be tested in seconds to minutes, reducing the time to response and increasing patient and clinician confidence in the chosen settings. Here, we present an approach to measuring and optimizing that circuit engagement.Approach.we leverage prior results showing that effective VCVS DBS engages cognitive control circuitry and improves performance on the multi-source interference task, that this engagement depends primarily on which contact(s) are activated, and that circuit engagement can be tracked through a state space modeling framework. We develop a simulation framework based on those empirical results, then combine this framework with an adaptive optimizer to simulate a principled exploration of electrode contacts and identify the contacts that maximally improve cognitive control. We explore multiple optimization options (algorithms, number of inputs, speed of stimulation parameter changes) and compare them on problems of varying difficulty.Main results.we show that an upper confidence bound algorithm outperforms other optimizers, with roughly 80% probability of convergence to a global optimum when used in a majority-vote ensemble.Significance.we show that the optimization can converge even with lag between stimulation and effect, and that a complete optimization can be done in a clinically feasible timespan (a few hours). Further, the approach requires no specialized recording or imaging hardware, and thus could be a scalable path to expand the use of DBS in psychiatric and other non-motor applications.

Methods and system for recording human physiological signals from implantable leads during spinal cord stimulation.

Objectives: This article presents a method-including hardware configuration, sampling rate, filtering settings, and other data analysis techniques-to measure evoked compound action potentials (ECAPs) during spinal cord stimulation (SCS) in humans with externalized percutaneous electrodes. The goal is to provide a robust and standardized protocol for measuring ECAPs on the non-stimulation contacts and to demonstrate how measured signals depend on hardware and processing decisions. Methods: Two participants were implanted with percutaneous leads for the treatment of chronic pain with externalized leads during a trial period for stimulation and recording. The leads were connected to a Neuralynx ATLAS system allowing us to simultaneously stimulate and record through selected electrodes. We examined different hardware settings, such as online filters and sampling rate, as well as processing techniques, such as stimulation artifact removal and offline filters, and measured the effects on the ECAPs metrics: the first negative peak (N1) time and peak-valley amplitude. Results: For accurate measurements of ECAPs, the hardware sampling rate should be least at 8 kHz and should use a high pass filter with a low cutoff frequency, such as 0.1 Hz, to eliminate baseline drift and saturation (railing). Stimulation artifact removal can use a double exponential or a second-order polynomial. The polynomial fit is 6.4 times faster on average in computation time than the double exponential, while the resulting ECAPs' N1 time and peak-valley amplitude are similar between the two. If the baseline raw measurement drifts with stimulation, a median filter with a 100-ms window or a high pass filter with an 80-Hz cutoff frequency preserves the ECAPs. Conclusions: This work is the first comprehensive analysis of hardware and processing variations on the observed ECAPs from SCS leads. It sets recommendations to properly record and process ECAPs from the non-stimulation contacts on the implantable leads.

Neuromodulation Through Spinal Cord Stimulation Restores Ability to Voluntarily Cycle After Motor Complete Paraplegia.

Abstract Epidural spinal cord stimulation (eSCS) of the lower thoracic spinal cord has been shown to partially restore volitional movement in patients with complete chronic spinal cord injury (cSCI). Combining eSCS with intensive locomotor training improves motor function, including standing and stepping, but many patients with cSCI suffer from long-standing muscle atrophy and loss of bone mineral density, which may prohibit safe implementation. Safe, accessible, and effective avenues for pairing neuromodulation with activity-based therapy remain unexplored. Cycling is one such option that can be utilized as an eSCS therapy given its low-risk and low-weight-bearing requirement. We investigated the feasibility and kinematics of motor-assisted and passive cycle-based therapy for cSCI patients with epidural spinal cord stimulation. Seven participants who underwent spinal cord stimulation surgery in the Epidural Stimulation After Neurologic Damage (E-STAND) trial (NCT03026816) participated in a cycling task using the motor assist MOTOmed Muvi 300. A factorial design was used such that participants were asked to cycle with and without conscious effort with and without stimulation. We used mixed effects models assessing maximum power output and time pedaling unassisted to evaluate the interaction between stimulation and conscious effort. Cycling was well-tolerated and we observed no adverse events, including in participants up to 17 years post-initial injury and up to 58 years old. All participants were found to be able to pedal without motor assist, which primarily occurred when stimulation and effort were applied together (p = 0.001). Additionally, the combination of stimulation and intention was significantly associated with higher maximum power production (p < 0.0001) and distance pedaled (p = 0.0001). No association was found between volitional movement and participant factors: age, time since injury, and spinal cord atrophy. With stimulation and conscious effort, all participants were able to achieve active cycling without motor assistance. Thus, our stationary cycling factorial study design demonstrated volitional movement restoration with eSCS in a diverse study population of cSCI participants. Further, motor-assist cycling was well-tolerated without any adverse events. Cycling has the potential to be a safe research assessment and physical therapy modality for cSCI patients utilizing eSCS who have a high risk of injury with weight bearing exercise. The cycling modality in this study was demonstrated to be a straightforward assessment of motor function and safe for all participants regardless of age or time since initial injury.

Feasibility testing of a novel prosthetic socket sensor system.

PURPOSE: Poorly fitting prosthetic sockets contribute to decreased quality of life, health, and well-being for persons with amputations. Therefore, improved socket fit is a high clinical priority. METHODS: In this study, we describe the design and testing of a novel sensor system that can be incorporated into a prosthetic socket to measure distal end weight bearing in the socket and can alert a prosthesis user if poor socket fit is suspected. We present the results of testing this device with three Veterans who were new prosthesis users and three Veterans who were experienced prosthesis users. RESULTS AND CONCLUSIONS: We collected sensor data during walking trials while participants wore varying numbers of sock plies and qualitative feedback on the design of the socket fit sensor system. For analysis, peak sensor measurements during walking cycles were identified and combined with socket fit data (i.e., a clinician-determined level of "good," "too tight," or "too loose" and the number of sock ply worn each trial). We found consistent relationships between peak sensor measurements and socket fit in our sample. Also, all users expressed an interest in the device, highlighting its potential benefits during early prosthesis training.Implications for RehabilitationEnsuring socket fit is challenging for many prosthesis users.A novel wearable sensor system can be used to identify socket fit issues for some prosthesis users.This type of system could be most helpful for new prosthesis users and those with sensory and cognitive challenges.

Optimization of closed-loop electrical stimulation enables robust cerebellar-directed seizure control.

Additional treatment options for temporal lobe epilepsy are needed, and potential interventions targeting the cerebellum are of interest. Previous animal work has shown strong inhibition of hippocampal seizures through on-demand optogenetic manipulation of the cerebellum. However, decades of work examining electrical stimulation-a more immediately translatable approach-targeting the cerebellum has produced very mixed results. We were therefore interested in exploring the impact that stimulation parameters may have on seizure outcomes. Using a mouse model of temporal lobe epilepsy, we conducted on-demand electrical stimulation of the cerebellar cortex, and varied stimulation charge, frequency and pulse width, resulting in over 1000 different potential combinations of settings. To explore this parameter space in an efficient, data-driven, manner, we utilized Bayesian optimization with Gaussian process regression, implemented in MATLAB with an Expected Improvement Plus acquisition function. We examined three different fitting conditions and two different electrode orientations. Following the optimization process, we conducted additional on-demand experiments to test the effectiveness of selected settings. Regardless of experimental setup, we found that Bayesian optimization allowed identification of effective intervention settings. Additionally, generally similar optimal settings were identified across animals, suggesting that personalized optimization may not always be necessary. While optimal settings were effective, stimulation with settings predicted from the Gaussian process regression to be ineffective failed to provide seizure control. Taken together, our results provide a blueprint for exploration of a large parameter space for seizure control and illustrate that robust inhibition of seizures can be achieved with electrical stimulation of the cerebellum, but only if the correct stimulation parameters are used.

Mapping Spinal Cord Stimulation-Evoked Muscle Responses in Patients With Chronic Spinal Cord Injury.

OBJECTIVES: Epidural spinal cord stimulation (eSCS) has shown promise for restoring some volitional motor control after spinal cord injury (SCI). Maximizing therapeutic response requires effective spatial stimulation generated through careful configuration of anodes and cathodes on the eSCS lead. By exploring the way the spatial distribution of low frequency stimulation affects muscle activation patterns, we investigated the spatial specificity of stimulation-evoked responses for targeted muscle groups for restoration after chronic SCI (cSCI) in participants in the Epidural Stimulation After Neurologic Damage (E-STAND) trial. MATERIALS AND METHODS: Fifteen participants with Abbreviated Injury Scale A cSCI from the E-STAND study were evaluated with a wide range of bipolar spatial patterns. Surface electromyography captured stimulation-evoked responses from the rectus abdominis (RA), intercostal, paraspinal, iliopsoas, rectus femoris (RF), tibialis anterior (TA), extensor hallucis longus (EHL), and gastrocnemius muscle groups bilaterally. Peak-to-peak amplitudes were analyzed for each pulse across muscles. Stimulation patterns with dipoles parallel (vertical configurations), perpendicular (horizontal configurations), and oblique (diagonal configurations) relative to the rostral-caudal axis were evaluated. RESULTS: Cathodic stimulation in the transverse plane indicated ipsilaterally biased activation in RA, intercostal, paraspinal, iliopsoas, RF, TA, EHL, and gastrocnemius muscles (p < 0.05). We found that caudal cathodic stimulation was significantly more activating only in the RF and EHL muscle groups than in the rostral (p < 0.037 and p < 0.006, respectively). Oblique stimulation was found to be more activating in the RA, intercostal, paraspinal, iliopsoas, and TA muscle groups than in the transverse (p < 0.05). CONCLUSIONS: Cathodic stimulation provides uniform specificity for targeting laterality. Few muscle groups responded specifically to variation in rostral/caudal stimulation, and oblique stimulation improved stimulation responses when compared with horizontal configurations. These relations may enable tailored targeting of muscle groups, but the surprising amount of variation observed suggests that monitoring these evoked muscle responses will play a key role in this tailoring process. CLINICAL TRIAL REGISTRATION: The Clinicaltrials.gov registration number for the study is NCT03026816.

Reliability of visual review of intracranial electroencephalogram in identifying the seizure onset zone: A systematic review and implications for the accuracy of automated methods.

Visual review of intracranial electroencephalography (iEEG) is often an essential component for defining the zone of resection for epilepsy surgery. Unsupervised approaches using machine and deep learning are being employed to identify seizure onset zones (SOZs). This prompts a more comprehensive understanding of the reliability of visual review as a reference standard. We sought to summarize existing evidence on the reliability of visual review of iEEG in defining the SOZ for patients undergoing surgical workup and understand its implications for algorithm accuracy for SOZ prediction. We performed a systematic literature review on the reliability of determining the SOZ by visual inspection of iEEG in accordance with best practices. Searches included MEDLINE, Embase, Cochrane Library, and Web of Science on May 8, 2022. We included studies with a quantitative reliability assessment within or between observers. Risk of bias assessment was performed with QUADAS-2. A model was developed to estimate the effect of Cohen kappa on the maximum possible accuracy for any algorithm detecting the SOZ. Two thousand three hundred thirty-eight articles were identified and evaluated, of which one met inclusion criteria. This study assessed reliability between two reviewers for 10 patients with temporal lobe epilepsy and found a kappa of .80. These limited data were used to model the maximum accuracy of automated methods. For a hypothetical algorithm that is 100% accurate to the ground truth, the maximum accuracy modeled with a Cohen kappa of .8 ranged from .60 to .85 (F-2). The reliability of reviewing iEEG to localize the SOZ has been evaluated only in a small sample of patients with methodologic limitations. The ability of any algorithm to estimate the SOZ is notably limited by the reliability of iEEG interpretation. We acknowledge practical limitations of rigorous reliability analysis, and we propose design characteristics and study questions to further investigate reliability.

Evaluation of functional MRI-based human brain parcellation: a review.

Brain parcellations play a crucial role in the analysis of brain imaging data sets, as they can significantly affect the outcome of the analysis. In recent years, several novel approaches for constructing MRI-based brain parcellations have been developed with promising results. In the absence of ground truth, several evaluation approaches have been used to evaluate currently available brain parcellations. In this article, we review and critique methods used for evaluating functional brain parcellations constructed using fMRI data sets. We also describe how some of these evaluation methods have been used to estimate the optimal parcellation granularity. We provide a critical discussion of the current approach to the problem of identifying the optimal brain parcellation that is suited for a given neuroimaging study. We argue that the criteria for an optimal brain parcellation must depend on the application the parcellation is intended for. We describe a teleological approach to the evaluation of brain parcellations, where brain parcellations are evaluated in different contexts and optimal brain parcellations for each context are identified separately. We conclude by discussing several directions for further research that would result in improved evaluation strategies.

The safety of epidural spinal cord stimulation to restore function after spinal cord injury: post-surgical complications and incidence of cardiovascular events.

STUDY DESIGN: Cohort prospective study. OBJECTIVES: Epidural spinal cord stimulation (eSCS) improves volitional motor and autonomic function after spinal cord injury (SCI). While eSCS has an established history of safety for chronic pain, it remains unclear if eSCS in the SCI population presents the same risk profile. We aimed to assess safety and autonomic monitoring data for the first 14 participants in the E-STAND trial. SETTING: Hennepin County Medical Center, Minneapolis and Minneapolis Veterans Affairs Medical Center, Minnesota, USA. METHODS: Monthly follow-up visits assessed surgical and medical device-related safety outcomes as well as stimulation usage. Beat-by-beat blood pressure (BP) and continuous electrocardiogram data were collected during head-up tilt-table testing with and without eSCS. RESULTS: All participants had a motor-complete SCI. Mean (SD) age and time since injury were 38 (10) and 7 (5) years, respectively. There were no surgical complications but one device malfunction 4 months post implantation. Stimulation was applied for up to 23 h/day, across a broad range of parameters: frequency (18-700 Hz), pulse width (100-600 µs), and amplitude (0.4-17 mA), with no adverse events reported. Tilt-table testing with eSCS demonstrated no significant increases in the incidence of elevated systolic BP or a greater frequency of arrhythmias. CONCLUSIONS: eSCS to restore autonomic and volitional motor function following SCI has a similar safety profile as when used to treat chronic pain, despite the prevalence of significant comorbidities and the wide variety of stimulation parameters tested.

Strength-frequency curve for micromagnetic neurostimulation through excitatory postsynaptic potentials (EPSPs) on rat hippocampal neurons and numerical modeling of magnetic microcoil (µcoil).

Objective.The objective of this study was to measure the effect of micromagnetic stimulation (µMS) on hippocampal neurons, by using single microcoil (µcoil) prototype, magnetic pen (MagPen). MagPen will be used to stimulate the CA3 region magnetically and excitatory post synaptic potential (EPSP) response measurements will be made from the CA1 region. The threshold for micromagnetic neurostimulation as a function of stimulation frequency of the current driving theµcoil will be demonstrated. Finally, the optimal stimulation frequency of the current driving theµcoil to minimize power will be estimated.Approach.A biocompatible, watertight, non-corrosive prototype, MagPen was built, and customized such that it is easy to adjust the orientation of theµcoil and its distance over the hippocampal tissue in anin vitrorecording setting. Finite element modeling of theµcoil design was performed to estimate the spatial profiles of the magnetic flux density (in T) and the induced electric fields (in V m-1). The induced electric field profiles generated at different values of current applied to theµcoil can elicit a neuronal response, which was validated by numerical modeling. The modeling settings for theµcoil were replicated in experiments on rat hippocampal neurons.Main results.The preferred orientation of MagPen over the Schaffer Collateral fibers was demonstrated such that they elicit a neuron response. The recorded EPSPs from CA1 region due toµMS at CA3 region were validated by applying tetrodotoxin (TTX). Application of TTX to the hippocampal slice blocked the EPSPs fromµMS while after prolonged TTX washout, a partial recovery of the EPSP fromµMS was observed. Finally, it was interpreted through numerical analysis that increasing frequency of the current driving theµcoil, led to a decrease in the current amplitude threshold for micromagnetic neurostimulation.Significance.This work reports that micromagnetic neurostimulation can be used to evoke population EPSP responses in the CA1 region of the hippocampus. It demonstrates the strength-frequency curve forµMS and its unique features related to orientation dependence of theµcoils, spatial selectivity and stimulation threshold related to distance dependence. Finally, the challenges related toµMS experiments were studied including ways to overcome them.

Perspectives on Understanding Aberrant Brain Networks in Epilepsy.

Epilepsy is a neurological disorder affecting approximately 70 million people worldwide. It is characterized by seizures that are complex aberrant dynamical events typically treated with drugs and surgery. Unfortunately, not all patients become seizure-free, and there is an opportunity for novel approaches to treat epilepsy using a network view of the brain. The traditional seizure focus theory presumed that seizures originated within a discrete cortical area with subsequent recruitment of adjacent cortices with seizure progression. However, a more recent view challenges this concept, suggesting that epilepsy is a network disease, and both focal and generalized seizures arise from aberrant activity in a distributed network. Changes in the anatomical configuration or widespread neural activities spanning lobes and hemispheres could make the brain more susceptible to seizures. In this perspective paper, we summarize the current state of knowledge, address several important challenges that could further improve our understanding of the human brain in epilepsy, and invite novel studies addressing these challenges.

Disparate insults relevant to schizophrenia converge on impaired spike synchrony and weaker synaptic interactions in prefrontal local circuits.

Schizophrenia results from hundreds of known causes, including genetic, environmental, and developmental insults that cooperatively increase risk of developing the disease. In spite of the diversity of causal factors, schizophrenia presents with a core set of symptoms and brain abnormalities (both structural and functional) that particularly impact the prefrontal cortex. This suggests that many different causal factors leading to schizophrenia may cause prefrontal neurons and circuits to fail in fundamentally similar ways. The nature of convergent malfunctions in prefrontal circuits at the cell and synaptic levels leading to schizophrenia are not known. Here, we apply convergence-guided search to identify core pathological changes in the functional properties of prefrontal circuits that lie downstream of mechanistically distinct insults relevant to the disease. We compare the impacts of blocking NMDA receptors in monkeys and deleting a schizophrenia risk gene in mice on activity timing and effective communication in prefrontal local circuits. Although these manipulations operate through distinct molecular pathways and biological mechanisms, we found they produced convergent pathophysiological effects on prefrontal local circuits. Both manipulations reduced the frequency of synchronous (0-lag) spiking between prefrontal neurons and weakened functional interactions between prefrontal neurons at monosynaptic lags as measured by information transfer between the neurons. The two observations may be related, as reduction in synchronous spiking between prefrontal neurons would be expected to weaken synaptic connections between them via spike-timing-dependent synaptic plasticity. These data suggest that the link between spike timing and synaptic connectivity could comprise the functional vulnerability that multiple risk factors exploit to produce disease.

Optimization of Spinal Cord Stimulation Using Bayesian Preference Learning and Its Validation.

Epidural spinal cord stimulation has been reported to partially restore volitional movement and autonomic functions after motor and sensory-complete spinal cord injury (SCI). Modern spinal cord stimulation platforms offer significant flexibility in spatial and temporal parameters of stimulation delivered. Heterogeneity in SCI and injury-related symptoms necessitate stimulation personalization to maximally restore functions. However, the large multi-dimensional stimulation space makes exhaustive tests impossible. In this paper, we present a Bayesian optimization strategy for identifying personalized optimal stimulation patterns based on the participant's expressed preference for stimulation settings. We present companion validation protocols for investigating the credibility of learned preference models. The results obtained for five participants in the E-STAND spinal cord stimulation clinical trial are reported. Personalized preference models produced by the proposed learning and optimization algorithm show that there is more similarity in optimal frequency than in pulse width across participants. Across five participants, the average model prediction accuracy is 71.5% in internal cross-validation and 65.6% in prospective validation. Statistical tests of both validation studies show that the ability of the preference models to correctly predict unseen preference data is significantly greater than chance. The personalized preference models are also shown to be significantly correlated with motor task performance across participants. We show that several aspects in participants' quality of life has been improved over the course of the trial. Overall, the results indicate that the Bayesian preference optimization algorithm could assist clinicians in the systematic programming of individualized therapeutic stimulation settings and improve the therapeutic outcomes.

Semi-automated approaches to optimize deep brain stimulation parameters in Parkinson's disease.

BACKGROUND: Deep brain stimulation (DBS) is a treatment option for Parkinson's disease patients when medication does not sufficiently manage their symptoms. DBS can be a highly effect therapy, but only after a time-consuming trial-and-error stimulation parameter adjustment process that is susceptible to clinician bias. This trial-and-error process will be further prolonged with the introduction of segmented electrodes that are now commercially available. New approaches to optimizing a patient's stimulation parameters, that can also handle the increasing complexity of new electrode and stimulator designs, is needed. METHODS: To improve DBS parameter programming, we explored two semi-automated optimization approaches: a Bayesian optimization (BayesOpt) algorithm to efficiently determine a patient's optimal stimulation parameter for minimizing rigidity, and a probit Gaussian process (pGP) to assess patient's preference. Quantified rigidity measurements were obtained using a robotic manipulandum in two participants over two visits. Rigidity was measured, in 5Hz increments, between 10-185Hz (total 30-36 frequencies) on the first visit and at eight BayesOpt algorithm-selected frequencies on the second visit. The participant was also asked their preference between the current and previous stimulation frequency. First, we compared the optimal frequency between visits with the participant's preferred frequency. Next, we evaluated the efficiency of the BayesOpt algorithm, comparing it to random and equal interval selection of frequency. RESULTS: The BayesOpt algorithm estimated the optimal frequency to be the highest tolerable frequency, matching the optimal frequency found during the first visit. However, the participants' pGP models indicate a preference at frequencies between 70-110 Hz. Here the stimulation frequency is lowest that achieves nearly maximal suppression of rigidity. BayesOpt was efficient, estimating the rigidity response curve to stimulation that was almost indistinguishable when compared to the longer brute force method. CONCLUSIONS: These results provide preliminary evidence of the feasibility to use BayesOpt for determining the optimal frequency, while pGP patient's preferences include more difficult to measure outcomes. Both novel approaches can shorten DBS programming and can be expanded to include multiple symptoms and parameters.