This paper outlines a surgical procedure for exposing and stimulating the sciatic nerve of an anesthetized rodent for purposes of obtaining conduction velocity readings. The ability to accurately quantify nerve conduction velocity has potential for use in the field of diagnostic medicine and disease characterization. An accurate reading depends on both the surgical method used to expose the desired nerve without imposing onto it any physical trauma as well as the stimulation protocol used to initiate action potentials. This paper contains the specific steps required to set up the necessary hardware and software for electrical stimulation as well as a detailed surgical and stimulation protocol. The animal model chosen to perform this experiment is the rat because it is the smallest animal model available with large enough nerve size to perform histology as a step toward validating the nerve size estimates obtained from this procedure. Based on repeated experimental runs, these methods are are expected to yield the most usable results while inflicting the least amount of physical trauma to the nerve. Upon isolating the sciatic nerve, the surgeon is to place an electrode cuff around the nerve and then initiate the stimulation protocol. The stimulation software is designed to slowly increment the current passing through the nerve to recruit increasing numbers of neurons one-at-a-time. The resulting data would theoretically offer researchers the actual threshold values for each individual neuron, uncovering information about the conduction characteristics of each one. The steps outlined in this thesis have been optimized to implement the theoretical model of group delay. Using the decomposition model introduced by Szlavik et al., the signal obtained from the entire nerve is broken down into individual action potentials associated with individual neurons.

The characterization of postsynaptic potentials, in terms of neurotransmitter receptor activation, is of clinical significance because information associated with receptor activation can be used in the diagnosis and study of neurological disorders. Single-unit recordings provide a method of measuring postsynaptic potentials in neurons using a microelectrode system, but yield no detailed information regarding the neurotransmitter receptors that contribute to the potential. To determine the types of neurotransmitter receptors that result in a compound postsynaptic potential from a microelectrode reading, decomposition of the potential is necessary. In this work, a perturbation-based decomposition method developed by R. Szlavik is evaluated for this application, and compared to a generalized Fourier series approach. The resultant estimator is valid for decomposition of multiple-receptor compound postsynaptic potentials as well as single-receptor compound postsynaptic potentials. The estimator also yields a satisfactory decomposition of experimental postsynaptic potential data found in the literature.

In some instances neuropathies can be diagnosed through a conduction velocity test. However, not all neuropathies can be classified using this method. Gaining an understanding of how the stimulus level varies for different fiber sizes at different fiber depths within a conductive medium will provide useful information for simulation studies. Following a two-step approach using COMSOL and MATLAB, a simulation was implemented to investigate the stimulus necessary to activate different sized fibers at different depths. In this two-step approach, COMSOL was used to describe the voltage profile that would be present within a conductive medium after a stimulus was applied. This voltage profile could then be analyzed using a program written in MATLAB to determine if the applied stimulus was sufficient to activate a given fiber. The analysis was performed using a stimulus method using a constant DC source. Two finite element models were also used, one using a homogeneous medium and the other inhomogeneous. A three dimensional plot was created to describe the effect of both the depth and diameter of a fiber on the required stimulus for fiber activation. From this plot, an equation was fit to the data to represent the activation function of a nerve fiber at various diameters and depths.

Characterizing postsynaptic current signals in the retina by neuroreceptor activation frequency is important for studying the mechanism of action behind phototransduction of varied visual stimuli. A better understanding could in turn lead to the creation of methods for early detection and prevention of debilitating optical neuropathies, such as glaucoma, age-related macular degeneration, and retinitis pigmentosa. More recent in-vitro and in-vivo studies have aimed to differentiate the effects of various neurotransmitters, such as acetylcholine, GABA, and glutamate, on receiving and processing different types of visual stimuli from the retina into the visual cortex. The focus of this work will be to evaluate a computational analysis method as a way to determine the activation frequency of different neuroreceptors in the retina, specifically in direction specific ganglion cells. The perturbation-based decomposition method developed by R. Szlavik was utilized in this application using a simulated compound postsynaptic current, comprised of nicotinic acetylcholine receptor, GABA receptor, and AMPA receptor current components and experimental data. The resulting application of Szlavik’s method produced a more satisfactory output compared to the results using a generalized Fourier series method.

Peripheral neuropathies are disorders that involve the damage of peripheral nerve fibers, affecting the ability of different parts of the body to communicate. A differentiating factor in diagnosis between various clinical conditions can be which size class of nerve fibers are affected. A nerve conduction velocity test can be used to assess the viability of the nerve but is a single-parameter test and gives no information about the population characteristics of the remaining active fibers. A method developed and previously reported by Szlavik (2016) utilizes a mathematical perturbed decomposition to determine the normalized frequency of each size class of fiber contributing to a compound action potential. In this study, the effects of focused ultrasound and anesthetics on the profile of active fiber diameters are analyzed using the Szlavik method and compared against another method used to estimate the sizes in the fiber population. The sciatic nerves of rats were subjected to focused ultrasound, focused ultrasound and bupivacaine, or focused ultrasound and ropivacaine and stimulated. The resulting compound action potential was recorded and decomposed, using the perturbation method and the action potential amplitude to assess fiber size involved in each potential. The range and variability of results confound the ability to draw decisive conclusions about application of this model this data and the effect of focused ultrasound. This study did show that a perturbative decomposition method for analyzing compound evoked potentials is feasible for vast amounts of data and identified sources of variability to be accounted for and the mathematical functions necessary in further trials.

More than one billion people worldwide suffer from neurological and neuropsychiatric disorders. Neuromodulation systems that use closed-loop brain stimulation to control brain states can provide new therapies. Current closed-loop brain stimulation has largely used linear time-invariant (LTI) controllers. However, nonlinear brain network dynamics and noise can appear during real-time stimulation, collectively leading to real-time model uncertainty, which degrades the performance or even causes instability of LTI controllers. Three problems need to be resolved to enable accurate and stable control under model uncertainty. First, an adaptive controller is needed to track the model uncertainty. Second, the adaptive controller additionally needs to be robust to noise. Third, theoretical analyses of stability and robustness are needed as prerequisites for applications. We develop a robust adaptive neuromodulation algorithm that solves the above three problems. First, we develop a state-space brain network model that explicitly includes nonlinear terms of real-time model uncertainty and designs an adaptive controller to track and cancel the model uncertainty. Second, to improve the robustness of the adaptive controller, we design linear filters to reduce sensitivity to high-frequency noise. Third, we conduct theoretical analyses to prove the stability of the neuromodulation algorithm. We test the algorithm using comprehensive Monte Carlo simulations spanning a broad range of model nonlinearity, uncertainty, and complexity. We further test the proposed algorithm using nonlinear cortex-basal ganglia-thalamus network models in Parkinson's disease and nonlinear neural mass models in Major depressive disorder. Our results showed that the proposed algorithm accurately tracks various types of target brain state trajectories, enables stable and robust control, and significantly outperforms current neuromodulation algorithms. Our algorithm has implications for future designs of precise and stable closed-loop neuromodulation systems to treat neurological and neuropsychiatric disorders.

An estimated 0.5% of world’s population has been diagnosed with epilepsy. Of these patients 20-30% will be unable to achieve seizure control with anti-epileptic drugs. Vagus nerve stimulation (VNS) may be an appropriate treatment option for some patients with pharmaceutically refractory, partial-onset seizures. VNS therapy uses a helical electrode to interface between the implantable pulse generator and the vagus nerve. While there have been several studies related to the mechanical and electrical safety of such electrodes, little work has been done toward understanding the effectiveness of the helical electrode in nerve stimulation. A better understanding of the voltage field and nerve fiber activation patterns produced by a helical electrode is necessary in order to evaluate its effectiveness and suggest design improvements. This thesis is primarily focused on investigating the effect on nerve fiber activation of changing the circumferential coverage of the platinum conductor. Finite Element Analysis and a nerve fiber model were used to evaluate several electrode designs. The circumferential coverage caused significant changes to nerve fiber activation. Coverage greater than 330°-360° was found to be inversely related to fiber activation. It was also noted that neurons located near the electrode ends, or near where the ends cross when coverage is greater than 360° were more difficult to activate. The phenomenon is discussed at length and several electrode design improvements were suggested based on these findings

There are forty registered organophosphates in the United States and they range from pesticides and insecticides to nerve agents or neurotoxins such as sarin. Organophosphates (OP’s) have been used in chemical warfare for years and tend to lead to death due to an attack on the nervous system. Chemical assays and mass microscopy have been used to assess the concentration of OP’s in the environment, but both methods require the body to metabolize the OP first, which can be detrimental to the victim. It is crucial to come up with a method to investigate and detect these neurotoxins without causing harm first. There have been several studies presented in the literature that use medicinal leeches and sharp electrode electrophysiology to study the function of the motor end plate. Kuffler, Potter and Stuart have all conducted studies using the medicinal leeches to do so. They mapped out the cells within the leech ganglion as well as created an atlas of the entire leech anatomy, and demonstrated the electrical connection between the motor neuron and longitudinal muscle fibers. Using the knowledge they have provided, a medicinal leech and sharp electrode electrophysiology can be used to investigate the effects of organophosphates on the nervous system. Before this can be achieved a dissection preparation must be implemented that can be utilized in electrophysiological experiments and that demonstrates the electrical connection between the motor neuron and muscle fibers. This thesis outlines the implementation of the medicinal leech dissection preparation described above. The preparation removes one ganglion from the leech, leaving the roots attached to the portion of the muscle wall it innervates. To demonstrate the preparations validity, sharp electrode electrophysiology is performed using a current clamp and discontinuous single electrode voltage clamp (dSEVC). A current pulse stimulates the motor neuron and a voltage recording is obtained from the ganglion as well a current recording from the muscle wall. The electrical connection is therefore demonstrated. This dissection preparation and electrophysiology experiment are written up in a procedural manner so that another individual could repeat the experiment. The next logical step would be to use these procedures to perform OP nerve agent experiments to investigate the effect of OP’s on the neuromuscular junction.

Much work has been done to study the external stimulation of nervous tissue as well as the transmission of neural signals to electronics. Peter Fromherz was one of the pioneers in this area of electrophysiology, with a series of experiments in the 1990s that aimed to characterize and optimize the interface between neural tissue and transistors. In this thesis, Kurt Sjoberg and I interfaced a Retzius cell isolated from a Hirudo medicinalis ganglion with the insulated gate of a MOSFET. The goal was to see change in membrane potential that could be related Fromherz’s original 1991 work. Our experimental setup utilized a classic electrophysiology technique, the current clamp. After varying the amplitude of the stimulating current pulses injected via microelectrode and ensuring the tight seal of the neuronal membrane with the insulated transistor gate, we found evidence of transistor voltage change that was temporally consistent with the elicited action potential of the neuron.

Similar to how electrocardiographic waves are the pace making signals of the heart, slow waves are the pace making signals of the intestines. Slow waves are electrical signals in the intestines that determine the speed at which food can move through the intestine ensuring proper digestion and uptake of nutrients. It has been shown that slow waves can be measured in adults using non-invasive, surface electrodes. However, no study has investigated the measurements of slow waves in neonates, specifically pre-term neonates. Around 7% of pre-term neonates suffer from necrotizing enterocolitis (NEC) which is a condition that causes damage to the intestinal tract and often death of intestinal tissue. NEC affects around 9,000 neonates each year with a survival rate estimated to be between 60%-80%. Currently, there are no non-invasive, early-stage indicators of NEC. This pilot study aims to create a non-invasive measurement setup to measure and characterize slow wave activity in neonates.