Matthew P. Ward

Toward a comparison of microelectrodes for acute and chronic recordings.

Several variations of microelectrode arrays are used to record and stimulate intracortical neuronal activity. Bypassing the immune response to maintain a stable recording interface remains a challenge. Companies and researchers are continuously altering the material compositions and geometries of the arrays in order to discover a combination that allows for a chronic and stable electrode-tissue interface. From this interface, they wish to obtain consistent quality recordings and a stable, low impedance pathway for charge injection over extended periods of time. Despite numerous efforts, no microelectrode array design has managed to evade the host immune response and remain fully functional. This study is an initial effort comparing several microelectrode arrays with fundamentally different configurations for use in an implantable epilepsy prosthesis. Specifically, NeuroNexus (Michigan) probes, Cyberkinetics (Utah) Silicon and Iridium Oxide arrays, ceramic-based thin-film microelectrode arrays (Drexel), and Tucker-Davis Technologies (TDT) microwire arrays are evaluated over a 31-day period in an animal model. Microelectrodes are compared in implanted rats through impedance, charge capacity, signal-to-noise ratio, recording stability, and elicited immune response. Results suggest significant variability within and between microelectrode types with no clear superior array. Some applications for the microelectrode arrays are suggested based on data collected throughout the longitudinal study. Additionally, specific limitations of assaying biological phenomena and comparing fundamentally different microelectrode arrays in a highly variable system are discussed with suggestions on how to improve the reliability of observed results and steps needed to develop a more standardized microelectrode design.

The design and hardware implementation of a low-power real-time seizure detection algorithm

Epilepsy affects more than 1% of the worlds population. Responsive neurostimulation is emerging as an alternative therapy for the 30% of the epileptic patient population that does not benefit from pharmacological treatment. Efficient seizure detection algorithms will enable closed-loop epilepsy prostheses by stimulating the epileptogenic focus within an early onset window. Critically, this is expected to reduce neuronal desensitization over time and lead to longer-term device efficacy. This work presents a novel event-based seizure detection algorithm along with a low-power digital circuit implementation. Hippocampal depth-electrode recordings from six kainate-treated rats are used to validate the algorithm and hardware performance in this preliminary study. The design process illustrates crucial trade-offs in translating mathematical models into hardware implementations and validates statistical optimizations made with empirical data analyses on results obtained using a real-time functioning hardware prototype. Using quantitatively predicted thresholds from the depth-electrode recordings, the auto-updating algorithm performs with an average sensitivity and selectivity of 95.3 +/- 0.02% and 88.9 +/- 0.01% (mean +/- SE(alpha = 0.05)), respectively, on untrained data with a detection delay of 8.5 s [5.97, 11.04] from electrographic onset. The hardware implementation is shown feasible using CMOS circuits consuming under 350 nW of power from a 250 mV supply voltage from simulations on the MIT 180 nm SOI process.

EFFECT OF STIMULUS PARAMETERS IN THE TREATMENT OF SEIZURES BY ELECTRICAL STIMULATION IN THE KAINATE ANIMAL MODEL

Preliminary results from animal and clinical studies demonstrate that electrical stimulation of brain structures can reduce seizure frequency in patients with refractory epilepsy. Since most researchers derive stimulation parameters by trial and error, it is unclear what stimulation frequency, amplitude and duration constitutes a set of optimal stimulation parameters for aborting seizure activity in a given patient. In this investigation, we begin to quantify the independent effects of stimulation parameters on electrographic seizures, such that they could be used to develop an efficient closed-loop prosthesis that intervenes before the clinical onset of a seizure and seizure generalization. Biphasic stimulation is manually delivered to the hippocampus in response to a visually detected electrographic seizure. Such focal, responsive stimulation allows for anti-seizure treatment delivery with improved temporal and spatial specificity over conventional open-loop stimulation paradigms, with the possibility of avoiding tissue damage stemming from excessive exposure to electrical stimulation. We retrospectively examine the effects of stimulation frequency (low, medium and high), pulse-width (low and high) and amplitude (low and high) in seizures recorded from 23 kainic acid treated rats. We also consider the effects of total charge delivered and the rate of charge delivery, and identify stimulation parameter sets that induce after-discharges or more seizures. Among the stimulation parameters evaluated, we note 2 major findings. First, stimulation frequency is a key parameter for inhibiting seizure activity; the anti-seizure effect cannot be attributed to only the charge delivered per phase. Second, an after-discharge curve shows that as the frequency and pulse-width of stimulation increases, smaller pulse amplitudes are capable of eliciting an after-discharge. It is expected that stimulation parameter optimization will lead to devices with enhanced treatment efficacies and reduced side-effect profiles, especially when used in conjunction with seizure prediction or detection algorithms in a closed-loop control application.

Evolving Refractory Major Depressive Disorder Diagnostic and Treatment Paradigms: Toward Closed-Loop Therapeutics

Current antidepressant therapies do not effectively control or cure depressive symptoms. Pharmaceutical therapies altogether fail to address an estimated 4 million Americans who suffer from a recurrent and severe treatment-resistant form of depression known as refractory major depressive disorder. Subjective diagnostic schemes, differing manifestations of the disorder, and antidepressant treatments with limited theoretical bases each contribute to the general lack of therapeutic efficacy and differing levels of treatment resistance in the refractory population. Stimulation-based therapies, such as vagus nerve stimulation, transcranial magnetic stimulation, and deep brain stimulation, are promising treatment alternatives for this treatment-resistant subset of patients, but are plagued with inconsistent reports of efficacy and variable side effects. Many of these problems stem from the unknown mechanisms of depressive disorder pathogenesis, which prevents the development of treatments that target the specific underlying causes of the disorder. Other problems likely arise due to the non-specific stimulation of various limbic and paralimbic structures in an open-loop configuration. This review critically assesses current literature on depressive disorder diagnostic methodologies, treatment schemes, and pathogenesis in order to emphasize the need for more stringent depressive disorder classifications, quantifiable biological markers that are suitable for objective diagnoses, and alternative closed-loop treatment options tailored to well-defined forms of the disorder. A closed-loop neurostimulation device design framework is proposed, utilizing symptom-linked biomarker abnormalities as control points for initiating and terminating a corrective electrical stimulus which is autonomously optimized for correcting the magnitude and direction of observed biomarker abnormality.

Real-time seizure prediction from local field potentials using an adaptive Wiener algorithm

Approximately 30% of individuals with epilepsy have refractory seizures that cannot be controlled by current pharmacological treatment measures. For such patients, responsive neurostimulation prior to a seizure may lead to greater efficacy when compared with current treatments. In this paper, we present a real-time adaptive Wiener prediction algorithm implemented on a digital signal processor to be used with local field potential (LFP) recordings. The hardware implementation of the algorithm enables it to be a miniaturized portable system that could be used in a hand-held device. The adaptive nature of the algorithm allows the seizure data to be compared with baseline data occurring in the recent past rather than a preset value. This enhances the sensitivity of the algorithm by accounting for the time-varying dynamics of baseline, inter-ictal and ictal activity. The Wiener algorithm was compared to two statistical-based naïve prediction algorithms. ROC curves, area over ROC curves, predictive power, and time under false positives are computed to characterize the algorithm. Testing of the algorithm via offline Matlab analysis on kainate-treated rats results in prediction of seizures about 27 s before clinical onset, with 94% sensitivity and a false positive rate of 0.009 min(-1). When implemented on a real-time TI C6713 signal processor, the algorithm predicts seizures about 6.7s before their clinical onset, with 92% sensitivity and a false positive rate of 0.08 min(-1). These results compare favorably with those obtained in similar studies in terms of sensitivity and false positive rate.

Vagus nerve modulation using focused pulsed ultrasound: Potential applications and preliminary observations in a rat

The use of focused ultrasonic waves to modulate neural structures has gained recent interest due to its potential in treating neurological disorders noninvasively. While several articles have focused on the use of ultrasound neuromodulation on peripheral nerves, none of these studies have been performed on the vagus nerve. We present preliminary observations on the effects of focused pulsed ultrasound (FPUS) on the conduction of the left cervical vagus nerve of a Long Evans rat. Ultrasound energy was applied at a frequency of 1.1 MHz, and at spatial‐peak, temporal average intensities that ranged from 13.6 to 93.4 W/cm2. Vagus nerve inhibition was observed in most cases. Results of this preliminary study suggested that there is a proportional relationship between acoustic intensity and the level of nerve inhibition.

Magnetic insertion system for flexible electrode implantation

Chronic recording electrodes are a vital tool for brain research and neural prostheses. Despite decades of advances in recording technology, probe structures and implantation methods have changed little over time. Then as now, compressive insertion methods require probes to be constructed from hard, stiff materials, such as silicon, and contain a large diameter shank to penetrate the brain, particularly for deeper structures. The chronic presence of these probes results in an electrically isolating glial scar, degrading signal quality over time. This work demonstrates a new magnetic tension-based insertion mechanism that allows for the use of soft, flexible, and thinner probe materials, overcoming the materials limitations of modern electrodes. Probes are constructed from a sharp magnetic tip attached to a flexible tether. A pulsed magnetic field is generated in a coil surrounding a glass pipette containing the electrode. The applied field pulls the electrode tip forward, accelerating the probe into the neural tissue with a penetration depth that is calibrated against the charge voltage. Mathematical modeling and agar gel insertion testing demonstrate that the electrode can be implanted to a predictable depth given system specific parameters. Trial rodent implantations resulted in discernible single-unit activity on one of the probes. The current prototype demonstrates the feasibility of a tension based, magnetically driven implantation system and opens the door to a wide variety of new minimally invasive probe materials and configurations.

A low-power implantable event-based seizure detection algorithm

Closed-loop neurostimulation has shown great promise as an alternate therapy for over 30% of the epileptic patient population that remain non-responsive to other forms of treatment. We present an event-based seizure detection algorithm that can be implemented in real-time using low power digital CMOS circuits to form an implantable epilepsy prosthesis. Seizures are detected by classifying and marking out ‘events’ in the recorded local field potential data and measuring the inter-event-intervals (IEI). The circuit implementation can be programmed post-implantation to custom fit the thresholds for detection. Hippocampal depth electrode recordings are used to validate the efficacy of a designed hardware prototype and thresholds are tuned to produce less than 5% false positives from recorded data.

Magnetically Inserted Neural Electrodes: Tissue Response and Functional Lifetime

Neural recording and stimulation have great clinical potential. Long-term neural recording remains a challenge, however, as implantable electrodes eventually fail due to the adverse effects of the host tissue response to the indwelling implant. Astrocytes and microglia attempt to engulf the electrode, increasing the electrical impedance between the electrode and neurons, and possibly pushing neurons away from the recording site. Faster insertion speed, finer tip geometry, smaller size, and lower material stiffness all seem to decrease damage caused by insertion and reduce the intensity of the tissue response. However, electrodes that are too small result in buckling, making insertion impossible. In this paper, we assess the viability of high-speed (27.8 m/s) deployment of 25 μm, ferromagnetic microelectrodes into rat brain. To characterize functionality of magnetically inserted electrodes, 4 Long-Evans rats were implanted for 31 days with impedance measurements and neural recordings taken daily. Performance was compared to 150 μm diameter PlasticsOne electrodes since 25 μm electrodes buckled during “slow speed” insertion. Platinum-iron magnetically inserted electrodes resolved single unit activity throughout the duration of the study in one rat, and saw no significant change (p=0.970) in impedance (4.54% increase) from day 0 (Z0 ≈ 144 kΩ,Z31 ≈ 150 kΩ). These findings provide a proof-of-concept for magnetic insertion as a viable insertion method that enables nonbuckling implantation of small (25 μm) microelectrodes, with potential for neural recording applications.

A Flexible Platform for Biofeedback-Driven Control and Personalization of Electrical Nerve Stimulation Therapy

Electrical vagus nerve stimulation is a treatment alternative for many epileptic and depressed patients whose symptoms are not well managed with pharmaceutical therapy. However, the fixed stimulus, open loop dosing mechanism limits its efficacy and precludes major advances in the quality of therapy. A real-time, responsive form of vagus nerve stimulation is needed to control nerve activation according to therapeutic need. This personalized approach to therapy will improve efficacy and reduce the number and severity of side effects. We present autonomous neural control, a responsive, biofeedback-driven approach that uses the degree of measured nerve activation to control stimulus delivery. We demonstrate autonomous neural control in rats, showing that it rapidly learns how to most efficiently activate any desired proportion of vagal A, B, and/or C fibers over time. This system will maximize efficacy by minimizing patient response variability and by minimizing therapeutic failures resulting from longitudinal decreases in nerve activation with increasing durations of treatment. The value of autonomous neural control equally applies to other applications of electrical nerve stimulation.