abstract: Intracranial pressure is an important parameter to monitor, and elevated intracranial pressure can be life threatening. Elevated intracranial pressure is indicative of distress in the brain attributed by conditions such as aneurysm, traumatic brain injury, brain tumor, hydrocephalus, stroke, or meningitis. Electrocorticography (ECoG) recordings are invaluable in understanding epilepsy and detecting seizure zones. However, ECoG electrodes cause a foreign body mass effect, swelling, and pneumocephaly, which results in elevation of intracranial pressure (ICP). Thus, the aim of this work is to design an intracranial pressure monitoring system that could augment ECoG electrodes. A minimally invasive, low-cost epidural intracranial pressure monitoring system is developed for this purpose, using a commercial pressure transducer available for biomedical applications. The system is composed of a pressure transducer, sensing cup, electronics, and data acquisition system. The pressure transducer is a microelectromechanical system (MEMS)-based die that works on piezoresistive phenomenon with dielectric isolation for direct contact with fluids. The developed system was bench tested and verified in an animal model to confirm the efficacy of the system for intracranial pressure monitoring. The system has a 0.1 mmHg accuracy and a 2% error for the 0-10 mmHg range, with resolution of 0.01 mmHg. This system serves as a minimally invasive (2 mm burr hole) epidural ICP monitor, which could augment existing ECoG electrode arrays, to simultaneously measure intracranial pressure along with the neural signals. This device could also be employed with brain implants that causes elevation in ICP due to tissue - implant interaction often leading to edema. This research explores the concept and feasibility for integrating the sensing component directly on to the ECoG electrode arrays. / Dissertation/Thesis / Masters Thesis Bioengineering 2015

abstract: Robust and stable decoding of neural signals is imperative for implementing a useful neuroprosthesis capable of carrying out dexterous tasks. A nonhuman primate (NHP) was trained to perform combined flexions of the thumb, index and middle fingers in addition to individual flexions and extensions of the same digits. An array of microelectrodes was implanted in the hand area of the motor cortex of the NHP and used to record action potentials during finger movements. A Support Vector Machine (SVM) was used to classify which finger movement the NHP was making based upon action potential firing rates. The effect of four feature selection techniques, Wilcoxon signed-rank test, Relative Importance, Principal Component Analysis, and Mutual Information Maximization was compared based on SVM classification performance. SVM classification was used to examine the functional parameters of (i) efficacy (ii) endurance to simulated failure and (iii) longevity of classification. The effect of using isolated-neuron and multi-unit firing rates was compared as the feature vector supplied to the SVM. The best classification performance was on post-implantation day 36, when using multi-unit firing rates the worst classification accuracy resulted from features selected with Wilcoxon signed-rank test (51.12 ± 0.65%) and the best classification accuracy resulted from Mutual Information Maximization (93.74 ± 0.32%). On this day when using single-unit firing rates, the classification accuracy from the Wilcoxon signed-rank test was 88.85 ± 0.61 % and Mutual Information Maximization was 95.60 ± 0.52% (degrees of freedom =10, level of chance =10%) / Dissertation/Thesis / Masters Thesis Bioengineering 2015

abstract: Optical Fibers coupled to laser light sources, and Light Emitting Diodes are the two classes of technologies used for optogenetic experiments. Arizona State University's Flexible Display Center fabricates novel flexible Organic Light Emitting Diodes(OLEDs). These OLEDs have the capability of being monolithically fabricated over flexible, transparent plastic substrates and having power efficient ways of addressing high density arrays of LEDs. This thesis critically evaluates the technology by identifying the key advantages, current limitations and experimentally assessing the technology in in-vivo and in-vitro animal models. For in-vivo testing, the emitted light from a flat OLED panel was directly used to stimulate the neo-cortex in the M1 region of transgenic mice expressing ChR2 (B6.Cg-Tg (Thy1-ChR2/EYFP) 9Gfng/J). An alternative stimulation paradigm using a collimating optical system coupled with an optical fiber was used for stimulating neurons in layer 5 of the motor cortex in the same transgenic mice. EMG activity was recorded from the contralateral vastus lateralis muscles. In vitro testing of the OLEDs was done in primary cortical neurons in culture transfected with blue light sensitive ChR2. The neurons were cultured on a microelectrode array for taking neuronal recordings. / Dissertation/Thesis / ICMS response in front and hind limb / Optogenetic response using iLEDs and OLEDs / iLED vs iLED coupled to optical fiber response / Masters Thesis Bioengineering 2015

<p> The nervous system exists as our interface to the world, both integrating and interpreting sensory information and coordinating voluntary and involuntary movements. Given its importance, it has become a target for neuromodulatory therapies. The research to develop these therapies cannot be done purely on living tissues - animals, manpower, and equipment make that cost prohibitive and, given the cost of life required, it would be unethical to not search for alternatives. Computation modeling, the use of mathematics and modern computational power to simulate phenomena, has sought to provide such an alternative since the work of Hodgkin and Huxley in 1952. These models, though they cannot yet replace in-vivo and in-vitro experiments, can ease the burden on living tissues and provide details difficult or impossible to ascertain from them. This thesis iterates on previous frameworks for performing in-silico experiments for the purposes of mechanistic exploration and threshold prediction. To do so, an existing volume conductor model and validated nerve-fiber model were joined and a series of programs were developed around them to perform a set of in-silico experiments. The experiments are designed to predict changes in thresholds of behaviors elicited by bioelectric neuromodulation to parametric changes in experimental setup and to explore the mechanisms behind bioelectric neuromodulation, particularly surrounding the recently discovered Low Frequency Alternating Current (LFAC) waveform. This framework improved upon its predecessors through efficiency-oriented design and modularity, allowing for rapid simulation on consumer-grade computers. Results show a high degree of convergence with in-vivo experimental results, such as mechanistic alignment with LFAC and being within an order of magnitude of in-vivo pulse-stimulation threshold results for equivalent in-vivo and in-silico experimental designs. </p>

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<p>  </p> <p>Traumatic Brain Injuries (TBI) are a major cause of disability and death in the United States. One of the greatest consequences of the disease is the resulting long-term damage, especially in milder injury cases where the damage is initially subclinical and thus lacking acutely observable manifestations that over time can compound significantly. Among these chronic issues, Alzheimer’s Disease (AD) is one of the most serious. While multiple studies demonstrate an increased likelihood of developing neurodegenerative diseases in response to TBI, the underlying mechanisms remain undefined and no current treatment options are available. Multiple hypotheses have been postulated based on various animal and clinical models, which have contributed a great deal to our current knowledge base and implicated several targets of interest in this pathway (i.g. oxidative stress, inflammation, disruptions in proteostasis). While extremely valuable, these <em>in vivo</em> procedures and analyses are physiologically and ethically complex: there is currently no model capable of separating and visualizing TBI-induced sub-cellular damage in the moments (seconds) immediately following injury, and the subsequent associated long-term changes (AD). In addition, no mechanistic study has been performed to link mechanical-trauma independently with neurodegeneration initiation via protein aggregation. It is clear that additional investigative tools are needed to rectify these intricate issues, and while <em>in vitro </em>methodologies generally offer the type of resolution required, no such model replicates these phenomena. Therefore, we introduce the “TBI-on-a-chip” <em>in vitro </em>concussive model, with a series of concomitant targeted-experiments to address this urgent, currently unmet need. This dissertation work describes the development of our cellular trauma model, featuring a multi-disciplinary approach that provides investigatory opportunities into cellular mechanics, molecular biology, functional alterations (electrophysiology), and morphology, in both primary and secondary injury. Utilizing this model, we directly observe evidence of impact-induced electrical/functional and biochemical consequences, in addition to isolating oxidative stress as a key, contributing component. Taken together, these collective efforts suggest that oxidative stress may be a viable target for both acute and chronic potential therapeutic interventions.</p>

<p dir="ltr">Blast-induced traumatic brain injury (bTBI) accounts for one-third of traumatic brain injuries (TBI) in soldiers, with chronic effects largely unknown. Electroencephalogram (EEG) signal changes may help predict outcomes like sleep disorders and post-traumatic epilepsy (PTE), which have been reported in rodent bTBI models. Modification of sleep spindles (SSPs), crucial thalamus-cortical signal for sleep transitions, have been linked to PTE and sleep disorders in non-blast TBI, but variability in detection methods affects findings. This study uses an improved SSPs detection algorithm to aim a more rigorous analysis of SSPs characteristics, necessary to understand the sleep disorders and seizure risk 1-month post-bTBI in mice. Following either bTBI or sham (non-blast) treatment, mice underwent a 1-week video-EEG recording, with pentylenetetrazol (PTZ) administered at the end to assess seizure susceptibility. Increased NREM sleep during dark period (hypersomnia) was observed on the first day of recording and a slight reduction in REM sleep was present over the week in both groups, anticipated in bTBI compared to sham. Seizure susceptibility showed no group difference. SSPs density did not differ, but bTBI showed a reduction of SSPs in higher amplitude and frequency range compared to sham. A specific SSP profile correlated with increased seizure susceptibility, though not with REM reduction nor bTBI itself, was identified. In conclusion, video-EEG recording may induce stress, shown by REM reduction in both groups. bTBI appears to increase fragility to stress, likely due to SSPs alterations, both under acute (e.g., first day in new housing) and chronic stress, manifesting as hypersomnia and earlier REM reduction respectively. EEG electrode implantation surgery might also contribute to increased seizure susceptibility. Although the SSP profile is more associated with seizure susceptibility than with bTBI itself, SSP distribution remains altered in bTBI compared to sham reflecting a possible modification of thalamo-cortical connectivity. Further research is needed to confirm SSPs alterations' origins in bTBI.</p>

<p dir="ltr">Sensory feedback is a critical component for controlling neuroprosthetic devices and brain-machine interfaces (BMIs). A lack of sensory pathways can result in slow, coarse movements when using either of these technologies and, in addition, the user is unable to fully interact with the environment around them. Spinal cord stimulation (SCS) has shown potential for restoring these pathways, but traditional stimulation patterns with constant parameters fail to reproduce the complex neural firing necessary for conveying sensory information. Recent studies have proposed various biomimetic stimulation patterns as a more effective means of evoking naturalistic neural activity and, in turn, communicating meaningful sensory information to the brain. Unlike conventional patterns, biomimetic waveforms vary in frequency, amplitude, or pulse-width over the duration of the stimulation. To better understand the role of these parameters in sensory perception, this thesis worked to investigate the effects of SCS patterns utilizing stochastic frequency modulation, linear frequency modulation, and linear amplitude modulation. By calculating sensory detection thresholds and just-noticeable differences, the null hypothesis for stochastically-varied frequency and linear amplitude modulation techniques was rejected.</p>

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