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.
In this paper, we present a novel Bayesian adaptive dual controller (ADC) for autonomously programming deep brain stimulation devices. We evaluated the Bayesian ADC's performance in the context of ...reducing beta power in a computational model of Parkinson's disease, in which it was tasked with finding the set of stimulation parameters which optimally reduced beta power as fast as possible. Here, the Bayesian ADC has dual goals: (a) to minimize beta power by exploiting the best parameters found so far, and (b) to explore the space to find better parameters, thus allowing for better control in the future. The Bayesian ADC is composed of two parts: an inner parameterized feedback stimulator and an outer parameter adjustment loop. The inner loop operates on a short time scale, delivering stimulus based upon the phase and power of the beta oscillation. The outer loop operates on a long time scale, observing the effects of the stimulation parameters and using Bayesian optimization to intelligently select new parameters to minimize the beta power. We show that the Bayesian ADC can efficiently optimize stimulation parameters, and is superior to other optimization algorithms. The Bayesian ADC provides a robust and general framework for tuning stimulation parameters, can be adapted to use any feedback signal, and is applicable across diseases and stimulator designs.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
We propose a novel, closed-loop approach to tuning deep brain stimulation (DBS) for Parkinson's disease (PD). The approach, termed Phasic Burst Stimulation (PhaBS), applies a burst of stimulus pulses ...over a range of phases predicted to disrupt pathological oscillations seen in PD. Stimulation parameters are optimized based on phase response curves (PRCs), which would be measured from each patient. This approach is tested in a computational model of PD with an emergent population oscillation. We show that the stimulus phase can be optimized using the PRC, and that PhaBS is more effective at suppressing the pathological oscillation than a single phasic stimulus pulse. PhaBS provides a closed-loop approach to DBS that can be optimized for each patient.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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.
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.
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.
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.
Schizophrenia is a complex disorder that is diagnosed mainly with clinical observation and evaluation. Recent studies suggest that many people with schizophrenia have abnormalities in the function of ...the N-methyl-d-aspartate receptor (NMDAR). The retina is part of the central nervous system and expresses the NMDAR, raising the possibility of the early detection of NMDAR-related schizophrenia by detecting differences in retinal function. As a first-step, we used two non-invasive outpatient tests of retinal function, the photopic negative response (PhNR) of the light-adapted flash-electroretinogram (PhNR-fERG) and the pattern ERG (PERG), to test individuals with schizophrenia and controls to determine if there were measurable differences between the two populations. The PhNR-fERG showed that males with schizophrenia had a significant increase in the variability of the overall response, which was not seen in the females with schizophrenia. Additionally at the brightest flash strength, there were significant increases in the PhNR amplitude in people with schizophrenia that were maximal in controls. Our results show measurable dysfunction of retinal ganglion cells (RGCs) in schizophrenia using the PhNR-fERG, with a good deal of variability in the retinal responses of people with schizophrenia. The PhNR-fERG holds promise as a method to identify individuals more at risk for developing schizophrenia, and may help understand heterogeneity in etiology and response to treatment.
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.
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.
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 Rehabilitation
Ensuring 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.
Computational modeling can be a powerful tool for an experimentalist, providing a rigorous mathematical model of the system you are studying. This can be valuable in testing your hypotheses and ...developing experimental protocols prior to experimenting. This paper reviews models of seizures and epilepsy at different scales, including cellular, network, cortical region, and brain scales by looking at how they have been used in conjunction with experimental data. At each scale, models with different levels of abstraction, the extraction of physiological detail, are presented. Varying levels of detail are necessary in different situations. Physiologically realistic models are valuable surrogates for experimental systems because, unlike in an experiment, every parameter can be changed and every variable can be observed. Abstract models are useful in determining essential parameters of a system, allowing the experimentalist to extract principles that explain the relationship between mechanisms and the behavior of the system. Modeling is becoming easier with the emergence of platforms dedicated to neuronal modeling and databases of models that can be downloaded. Modeling will never be a replacement for animal and clinical experiments, but it should be a starting point in designing experiments and understanding their results.
Transcranial focused ultrasound (tFUS) at low intensities has been reported to directly evoke responses and reversibly inhibit function in the central nervous system. While some doubt has been cast ...on the ability of ultrasound to directly evoke neuronal responses, spatially-restricted transcranial ultrasound has demonstrated consistent, inhibitory effects, but the underlying mechanism of reversible suppression in the central nervous system is not well understood.
In this study, we sought to characterize the effect of transcranial, low-intensity, focused ultrasound on the thalamus during somatosensory evoked potentials (SSEP) and investigate the mechanism by modulating the parameters of ultrasound.
TFUS was applied to the ventral posterolateral nucleus of the thalamus of a rodent while electrically stimulating the tibial nerve to induce an SSEP. Thermal changes were also induced through an optical fiber that was image-guided to the same target.
Focused ultrasound reversibly suppressed SSEPs in a spatially and intensity-dependent manner while remaining independent of duty cycle, peak pressure, or modulation frequency. Suppression was highly correlated and temporally consistent with in vivo temperature changes while producing no pathological changes on histology. Furthermore, stereotactically-guided delivery of thermal energy through an optical fiber produced similar thermal effects and suppression.
We confirm that tFUS predominantly causes neuroinhibition and conclude that the most primary biophysical mechanism is the thermal effect of focused ultrasound.
•Transcranial low-intensity focused ultrasound reversibly inhibits neural activity.•tFUS robustly suppresses SSEPs when the thalamus (VPL) is targeted.•Evoked responses or startle were not observed with dual-mode ultrasound arrays.•Suppression varies with ultrasound intensity with multi-second time constants.•A thermal effect underlies the primary mechanism of tFUS.
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 (
= 0.001). Additionally, the combination of stimulation and intention was significantly associated with higher maximum power production (
< 0.0001) and distance pedaled (
= 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.
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