Closed-loop stimulation of hypoglossal nerve in a dog model of upper airway obstruction

Sleep Apnea Research in Animals. Past, Present, and Future

Obstructive sleep apnea (OSA) is a common disorder that describes recurrent collapse of the upper airway during sleep. Animal models have been pivotal to the understanding of OSA pathogenesis, consequences, and treatment. In this review, we highlight the history of OSA research in animals and include the discovery of animals with spontaneous OSA, the induction of OSA in animals, and the emulation of OSA using exposures to intermittent hypoxia and sleep fragmentation.

Implantable neurotechnologies: a review of integrated circuit neural amplifiers

Neural signal recording is critical in modern day neuroscience research and emerging neural prosthesis programs. Neural recording requires the use of precise, low-noise amplifier systems to acquire and condition the weak neural signals that are transduced through electrode interfaces. Neural amplifiers and amplifier-based systems are available commercially or can be designed in-house and fabricated using integrated circuit (IC) technologies, resulting in very large-scale integration or application-specific integrated circuit solutions. IC-based neural amplifiers are now used to acquire untethered/portable neural recordings, as they meet the requirements of a miniaturized form factor, light weight and low power consumption. Furthermore, such miniaturized and low-power IC neural amplifiers are now being used in emerging implantable neural prosthesis technologies. This review focuses on neural amplifier-based devices and is presented in two interrelated parts. First, neural signal recording is reviewed, and practical challenges are highlighted. Current amplifier designs with increased functionality and performance and without penalties in chip size and power are featured. Second, applications of IC-based neural amplifiers in basic science experiments (e.g., cortical studies using animal models), neural prostheses (e.g., brain/nerve machine interfaces) and treatment of neuronal diseases (e.g., DBS for treatment of epilepsy) are highlighted. The review concludes with future outlooks of this technology and important challenges with regard to neural signal amplification.

A Multichannel Recording System with Optical Stimulation for Closed-Loop Optogenetic Experiments

Selective perturbation of the activity of specific cell types in the brain tissue is essential in understanding the function of neuronal circuits involved in cognition and behavior and might also provide therapeutic neuromodulation strategies. Such selective neuronal addressing can be achieved through the optical activation of light-sensitive proteins called opsins that are expressed in specific cell populations through genetic methods-hence the name "optogenetics." In optogenetic experiments, the electrical activity of the targeted cell populations is optically triggered and monitored using arrays of microelectrodes. In closed-loop studies, the optical stimulation parameters are adjusted based on the recorded activity, ideally in real time. Here we describe the basic tools and the protocols allowing closed-loop optogenic experiments in vivo.

Closed-loop optical neural stimulation based on a 32-channel low-noise recording system with online spike sorting

OBJECTIVE

Closed-loop operation of neuro-electronic systems is desirable for both scientific and clinical (neuroprosthesis) applications. Integrating optical stimulation with recording capability further enhances the selectivity of neural stimulation. We have developed a system enabling the local delivery of optical stimuli and the simultaneous electrical measuring of the neural activities in a closed-loop approach.

APPROACH

The signal analysis is performed online through the implementation of a template matching algorithm. The system performance is demonstrated with the recorded data and in awake rats.

MAIN RESULTS

Specifically, the neural activities are simultaneously recorded, detected, classified online (through spike sorting) from 32 channels, and used to trigger a light emitting diode light source using generated TTL signals.

SIGNIFICANCE

A total processing time of 8 ms is achieved, suitable for optogenetic studies of brain mechanisms online.

High-resolution measurement of electrically-evoked vagus nerve activity in the anesthetized dog

OBJECTIVE

Not fully understanding the type of axons activated during vagus nerve stimulation (VNS) is one of several factors that limit the clinical efficacy of VNS therapies. The main goal of this study was to characterize the electrical recruitment of both myelinated and unmyelinated fibers within the cervical vagus nerve.

APPROACH

In anesthetized dogs, recording nerve cuff electrodes were implanted on the vagus nerve following surgical excision of the epineurium. Both the vagal electroneurogram (ENG) and laryngeal muscle activity were recorded in response to stimulation of the right vagus nerve.

MAIN RESULTS

Desheathing the nerve significantly increased the signal-to-noise ratio of the ENG by 1.2 to 9.9 dB, depending on the nerve fiber type. Repeated VNS following nerve transection or neuromuscular block (1) enabled the characterization of A-fibers, two sub-types of B-fibers, and unmyelinated C-fibers, (2) confirmed the absence of stimulation-evoked reflex compound nerve action potentials in both the ipsilateral and contralateral vagus nerves, and (3) provided evidence of stimulus spillover into muscle tissue surrounding the stimulating electrode.

SIGNIFICANCE

Given the anatomical similarities between the canine and human vagus nerves, the results of this study provide a template for better understanding the nerve fiber recruitment patterns associated with VNS therapies.

Integrated electronics for peripheral nerve recording and signal processing

This paper describes the integrated circuit implementation of an electronic system for peripheral nerve recording and signal processing. Specifically, the system aims to record and condition neural activity from the phrenic nerve as a good indicator for breathing, and generate a stimulus trigger signal for a laryngeal pacemaker device to reanimate a paralyzed muscle with electrical stimulation paced with respiration. The 2.2 x 2.2-mm(2) integrated circuit is fabricated using the AMI 1.5 microm 2P/2M n-well CMOS process, and consumes 1 mW from +/-1.5 V. System architecture, circuit design, simulation results, and measurement data in benchtop experiments are presented.

The recording properties of a multi-contact nerve electrode as predicted by a finite element model of the canine hypoglossal nerve

Most functional electrical stimulation (FES) systems rely only on unidirectional (i.e., efferent) activation of the target organ to yield therapeutic outcomes. For applications involving multi-fasciculated nerves, however, artificial sensors have exhibited limited results. As such, the flat-interface-nerve-electrode (FINE) is presented as a means of obtaining an effective closed-loop control system. To investigate the ability of this electrode to achieve selective recordings at physiological signal-to-noise ratio (SNR), a finite element model (JFEM) of a beagle hypoglossal nerve with an implanted FINE was constructed. Action potentials (AP) were generated at various SNR levels and the performance of the electrode was assessed with a selectivity index (0 < or = SI < or = 1; ability of the electrode to distinguish two active sources). Computer simulations yielded a selective range (0.05 < or = SI < or = 0.76) that was (1) related to the inter-fiber distance and (2) used to predict the minimum inter-fiber distance (0.23 mm < or = d < or = 1.42 mm) required for selective recording. The results of this study suggest that the FINE can record neural activity from a multi-fasciculated nerve and, more importantly, distinguish neural activity from pairs of fascicles at physiologic SNR.

A low-noise preamplifier for nerve cuff electrodes

A single-stage, low-noise preamplifier is designed using the concept of noise matching for recordings of neural signal with cuff electrodes. The signal-to-noise ratio is approximately 1.6 times higher than that of a low-noise integrated amplifier (AMP-01) for a cuff impedance of 1.5 komega. The bandwidth is 230 Hz-8.25 kHz (Rs=2 komega), and the common-mode-rejection-ratio is 91.2 dB at 1 kHz.

Selective recording of the canine hypoglossal nerve using a multicontact flat interface nerve electrode

A flat-interface nerve electrode (FINE) is presented as a potential solution for using multifascicle nerve recordings as part of a closed-loop control system. To investigate the ability of this electrode to achieve selective recordings at physiological signal-to-noise ratio (SNR), a finite-element model (FEM) of a beagle hypoglossal nerve with an implanted FINE was constructed. Action potentials (AP) were generated at various SNR levels and the performance of the electrode was assessed with a selectivity index (0 < or = SI < or = 1; ability of the electrode to distinguish two active sources). Computer simulations yielded a selective range (0.05 < or = SI < or = 0.76) that was 1) related to the interfiber distance and 2) used to predict the minimum interfiber distance (0.23 mm < or = d < or = 1.42 mm) for selective recording at each SNR. The SI was further evaluated using recorded compound APs elicited from electrically activating the branches of the beagle hypoglossal nerve. For all experiments (n = 7), the selectivity (SI = 0.45 +/- 0.16) was within the range predicted by the FEM. This study suggests that the FINE can record the activity from a multifasciculated nerve and, more importantly, distinguish neural signals from pairs of fascicles at physiologic SNR.

Estimation of peroneal and tibial afferent activity from a multichannel cuff placed on the sciatic nerve

The afferent signals recorded with a multi-electrode cuff on the sciatic nerve were employed to investigate the possibility of extracting components ascending from the peroneal and tibial nerves. Two methods, an inverse regression model and principal component method, were studied. The parameters of inverse regression model, determined by data collected in semistatic conditions, were validated by data collected in dynamic conditions. The results showed that the regression model, which used only two channels of the sciatic recordings, was sufficient to separate the distal afferent components. The model, at the expense of requiring distal branch recordings for estimating model parameters, yielded better separation than the principal component method. In conclusion, peroneal and tibial afferent activity can be estimated from the sciatic nerve: the principal component method is suitable for applications focused on acquiring afferent information, whereas the inverse regression model is better for applications in which stimulations will be applied to the branches. The estimation technique provides a powerful tool for in vivo investigation of sensory information transmitted in a peripheral nerve and facilitates implementation of advanced functional neuromuscular stimulation systems.