International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering最新文献

The development of models and approaches for controlling the spreading dynamics of epileptic seizures is an essential step towards new therapies for people with pharmacologically resistant epilepsy. Beyond resective neurosurgery, in which epileptogenic zones (EZs) are the target of surgery, closed-loop control based on intracranial electrical stimulation, applied at the very early stage of seizure evolution, has been the main alternative, e.g. the RNS system from NeuroPace (Mountain View, CA). In this approach the electrical stimulation is delivered to target brain areas after detection of seizure initiation in the EZ. Here, we examined, on model simulations, some of the closed-loop control aspects of the problem. Seizure dynamics and spread are typically modeled with highly nonlinear dynamics on complex brain networks. Despite the nonlinearity and complexity, currently available optimal feedback control approaches are mostly based on linear approximations. Alternative machine learning control approaches might require amounts of data beyond what is commonly available in the intended application. We thus examined how standard linear feedback control approaches perform when applied to nonlinear models of neural dynamics of seizure generation and spread. In particular, we considered patient-specific epileptor network models for seizure onset and spread. The models incorporate network connectivity derived from (diffusion MRI) white-matter tractography, have been shown to capture the qualitative dynamics of epileptic seizures and can be fit to patient data. For control, we considered simple linear quadratic Gaussian (LQG) regulators. The LQG control was based on a discrete-time state-space model derived from the linearization of the patient-specific epileptor network model around a stable fixed point in the regime of preictal dynamics. We show in simulations that LQG regulators acting on the EZ node during the initial seizure period tend to be unstable. The LQG solution for the control law in this case leads to global feedback to the EZ-node actuator. However, if the LQG solution is constrained to depend on only local feedback originating from the EZ node itself, the controller is stable. In this case, we demonstrate that localized LQG can easily terminate the seizure at the early stage and prevent spread. In the context of optimal feedback control based on linear approximations, our results point to the need for investigating in more detail feedback localization and additional relevant control targets beyond epileptogenic zones.

Current leakage between channels in microelectrode arrays is a sign of device failure and can lead to shorting of neural signals. The purpose of this project is to detect crosstalk between 32 channels of electrodes. We designed an embedded crosstalk detection system that can stimulate each electrode individually with a constant-current pulse and record voltage transients of the stimulated and adjacent electrodes to generate a matrix of crosstalk values. Charge injection in a phosphate buffered saline solution was used to check the condition of each electrode. A semi-wet condition was then used to determine the percent crosstalk between the channels. The analysis showed that there was minimal crosstalk between the electrodes, except for a known physical defect on the probe. The measurement technique enabled by the electronics circuit has the potential to be used in functional testing and screening of implantable devices.

Although vagus nerve stimulation (VNS) can be used to reduce heartrate by enhancing parasympathetic activity, a fully controllable intervention would also require a method for downregulating parasympathetic activity. A direct current (DC) block can be applied to a nerve to block its action potential conduction. This nerve block can be used to downregulate parasympathetic activity by blocking afferent reflexes. The damaging effects of reactions that occur at the electrode-nerve interface using conventional platinum electrodes can be avoided by separating the electrode from the nerve. Using a biocompatible, ionically conducting medium, the electrode and the damaging reactions can be isolated in a vessel away from the nerve. This type of electrode has been called the Separated Interface Nerve Electrode (SINE). Fuzzy logic control (FLC) is a controller approach that is well suited to physiological systems. The SINE, controlled by an FLC, was utilized to block a stimulated vagus nerve and regulate heart rate. The FLC was able to maintain the heartrate at a pre-determined setpoint while still achieving instant recovery when the block was removed.

Musculoskeletal modeling is a new computational tool to reverse engineer human control systems, which require efficient algorithms running in real-time. Human hand pronation-supination movement is accomplished by movement of the radius and ulna bones relative to each other via the complex proximal and distal radioulnar joints, each with multiple degrees of freedom (DOFs). Here, we report two simplified models of this complex kinematic transformation implemented as a part of a 20 DOF model of the hand and forearm. The pronation/supination DOF was implemented as a single rotation joint either within the forearm segment or separating proximal and distal parts of the forearm segment. Torques produced by the inverse dynamic simulations with anatomical architecture of the forearm (OpenSim model) were used as the "gold standard" in the comparison of two simple models. Joint placement was iteratively optimized to achieve the closest representation of torques during realistic hand movements. The model with a split forearm segment performed better than the model with a solid forearm segment in simulating pronation/supination torques. We conclude that simplifying pronation/supination DOF as a single-axis rotation between arm segments is a viable strategy to reduce the complexity of multi-DOF dynamic simulations.

Efficacious stimulation of neural tissues requires high charge injection capacity while minimizing electrode polarization. Applying anodic bias on certain electrode materials is a way to enhance charge injection both in vitro and in vivo. We developed an embedded neurostimulator system that enabled a digital control of user-defined bias levels, without requiring a potentiometer or external voltage source. Comparison of charge injection with and without anodic-bias, as well as at different bias potentials were conducted in phosphate-buffered saline with Blackrock iridium oxide microelectrodes. Results showed that a nine-fold increase in current intensity and charge injection capacity, was achieved with a 0.7 V anodic bias and within electrochemically safe limits.

For epiretinal prostheses, disc electrodes stimulate retinal ganglion cells (RGCs) with electric current to create visual percepts. Prior studies have determined that the sodium channel band (SOCB), located on the RGC axon (30-50 μm from the soma) is the most sensitive site to extracellular stimulation because of its high sodium channel density. Biophysical cable models used to study RGC activation in silico often rely on simplified axon trajectories, disregarding the non-uniform paths that axons follow to the optic disc. However, since axonal activation is a critical mechanism in epiretinal stimulation, it is important to investigate variable RGC axon trajectories. In this study, we use a computational model to perform a sensitivity analysis examining how the morphology of an RGC axon affects predictions of retinal activation. We determine that RGC cable models are sensitive to changes in the ascending axon trajectory between the soma and nerve fiber layer. On the other hand, RGC cable models are relatively robust to trajectory deviations in the plane parallel to the disc electrode's surface. Overall, our results suggest that incorporating natural variations of soma depth and nerve fiber layer entry angle could result in a more realistic model of the retina's response to epiretinal stimulation and a better understanding of elicited visual percepts.

Validation of neural probe performance often includes implantation in live animals, to assess ability to detect and distinguish signals generated by individual neurons. While this method is informative, an effective in vitro alternative would streamline device development and improve ethical considerations by reducing the use of animals in the validation of neural recording devices. Here, we describe a simple system using ball electrodes to apply multiple neural waveforms to phosphate buffered saline, which are simultaneously recorded by a microelectrode probe. Using this technique, our neural probe was able to detect and distinguish spikes from multiple units of roughly physiological amplitudes (~100 microvolts peak to peak), indicating promise as an in vitro alternative to animal testing for initial validation of neural recording devices.

Closed-loop deep brain stimulation is a novel form of therapy that has shown benefit in preliminary studies and may be clinically available in the near future. Initial closed-loop studies have primarily focused on responding to sensed biomarkers with adjustments to stimulation amplitude, which is often perceptible to study participants depending on the slew or "ramp" rate of the amplitude changes. These subjective responses to stimulation ramping can result in transient side effects, illustrating that ramp rate is a unique safety parameter for closed-loop neural systems. This presents a challenge to the future of closed-loop neuromodulation systems: depending on the goal of the control policy, clinicians will need to balance ramp rates to avoid side effects and keep the stimulation therapeutic by responding in time to affect neural dynamics. In this paper, we demonstrate the results of an initial investigation into methodology for finding safe and tolerable ramp rates in four people with Parkinson's disease (PD). Results suggest that optimal ramp rates were found more accurately during varying stimulation when compared to simply toggling between maximal and minimal intensity levels. Additionally, switching frequency instantaneously was tolerable at therapeutic levels of stimulation. Future work should focus on including optimization techniques to find ramp rates.

Proprioception provides information regarding the state of an individual's limb in terms of static position and kinesthesia (dynamic movement). When such feedback is lost or impaired, the performance of dexterous control of our biological limbs or assistive devices tends to deteriorate. In this study, we determined if external vibratory stimulation patterns could allow for the perception of a finger's static position and kinesthesia. Using four tactors and two stimulus levels, eight vibratory settings corresponded to eight discrete finger positions. The transition patterns between these eight settings corresponded to kinesthesia. Three experimental blocks assessed the perception of a finger's static position, speed, and movement (amplitude and direction). Our results demonstrated that both position and kinesthesia could be recognized with over 93% accuracy. The outcomes suggest that vibratory stimulus can inform subjects of static and dynamic aspects of finger proprioception. This sensory stimulation approach can be implemented to improve outcomes in clinical populations with sensory deficits, and to enhance user experience when users interact with assistive devices.

Chronic pain affects millions of people in the United States and pharmacological treatments have been ineffective. Dorsal root ganglion (DRG) stimulation is a neuromodulation method that delivers electrical stimulation to the DRG to relieve pain. DRG electrodes are rigid and cylindrical. The implantation of DRG electrodes requires a technically-challenging surgery that involves steering electrodes laterally towards the DRG. The Injectrode is an injectable conductive polymer that cures in place and is capable of delivering electrical current to stimulate neural tissue. We used the Injectrode to stimulate the L6 and L7 DRG in cats, measuring neural responses evoked in the sciatic, tibial, and common peroneal nerves to measure the thresholds for activating fibers. A cylindrical stainless-steel electrode was used for comparison. Thresholds were 38% higher with the Injectrode versus stainless-steel, likely owing to its larger contact surface area with the DRG. Both Aα and Aβ sensory fibers were activated using DRG stimulation. The Injectrode has the potential to offer a new and simple method for DRG stimulation that can potentially offer more complete coverage of the DRG.