Biomedical Commons^™

Closed-Loop Brain-Computer Interfaces For Memory Restoration Using Deep Brain Stimulation, David Xiaoliang Wang

Electrical Engineering Theses and Dissertations

The past two decades have witnessed the rapid growth of therapeutic brain-computer interfaces (BCI) targeting a diversity of brain dysfunctions. Among many neurosurgical procedures, deep brain stimulation (DBS) with neuromodulation technique has emerged as a fruitful treatment for neurodegenerative disorders such as epilepsy, Parkinson's disease, post-traumatic amnesia, and Alzheimer's disease, as well as neuropsychiatric disorders such as depression, obsessive-compulsive disorder, and schizophrenia. In parallel to the open-loop neuromodulation strategies for neuromotor disorders, recent investigations have demonstrated the superior performance of closed-loop neuromodulation systems for memory-relevant disorders due to the more sophisticated underlying brain circuitry during cognitive processes. Our efforts are …

Microglia Induced Neuroinflammation Through The Nlrp3 Inflammasome Following Blast Traumatic Brain Injury, Daniel Younger

Dissertations

The incidence of traumatic brain injury (TBI) among military personnel have been steadily increasing with modern conflicts. A recent RAND report estimated 320,000 service members, totaling 20% of deployed forces, suffer from TBI. However, of this population roughly 60% have not seen a medical professional specifically for TBI. Unlike the civilian population, the primary cause of TBI for active-duty military personnel is blast exposure. Blasts now account for over 70% of all US military casualties in operation Iraqi Freedom (OIF) and Operation enduring freedom (OEF) and are the major cause of TBI. Among many pathological mechanisms associated with blast TBI, …

Wearable Assistive Technologies For Autism: Opportunities And Challenges, Emma Mansouri Benssassi, Juan-Carlos Gomez, Louanne E. Boyd, Gillian R. Hayes, Juan Ye

Engineering Faculty Articles and Research

Autism is a lifelong developmental condition that affects how people perceive the world and interact with others. Challenges with typical social engagement, common in the autism experience, can have a significant negative impact on the quality of life of individuals and families living with autism. Recent advances in sensing, intelligent, and interactive technologies can enable new forms of assistive and augmentative technologies to support social interactions. However, researchers have not yet demonstrated effectiveness of these technologies in long-term real-world use. This article presents an overview of the social and sensory challenges of autism, which offer great opportunities and challenges for …

Longitudinal Tracking Of Physiological State With Electromyographic Signals., Robert Warren Stallard

Electronic Theses and Dissertations

Electrophysiological measurements have been used in recent history to classify instantaneous physiological configurations, e.g., hand gestures. This work investigates the feasibility of working with changes in physiological configurations over time (i.e., longitudinally) using a variety of algorithms from the machine learning domain. We demonstrate a high degree of classification accuracy for a binary classification problem derived from electromyography measurements before and after a 35-day bedrest. The problem difficulty is increased with a more dynamic experiment testing for changes in astronaut sensorimotor performance by taking electromyography and force plate measurements before, during, and after a jump from a small platform. A …

Synchronization Of Coupled Neurons Via Robust Feedback, Hector Puebla, Ricardo Aguilar-Lopez, Priti Kumar Roy

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Mechanical Reliability Of Implantable Polyimide-Based Magnetic Microactuators For Biofouling Removal, Christian G. Figueroa-Espada, Qi Yang, Hyowon Lee

The Summer Undergraduate Research Fellowship (SURF) Symposium

Hydrocephalus is a neurological disorder that typically requires a long-term implantation of a shunt system to manage its symptoms. These shunt systems are notorious for their extremely high failure rate. More than 40% of all implanted shunt systems fail within the first year of implantation. On average, 85% of all hydrocephalus patients with shunt systems undergo at least two shunt-revision surgeries within 10 years of implantation. A large portion of this high failure rate can be attributed to biofouling-related obstructions and infections. Previously, we developed flexible polyimide-based magnetic microactuators to remove obstructions formed on hydrocephalus shunts. To test the long-term …

Development And Investigation Of Sparse Co-Adaptive Algorithms In Ecog Based Closed-Loop Brain Computer Interface, Piyush Karande

McKelvey School of Engineering Theses & Dissertations

Electrocorticography (ECoG) has gained a lot of momentum and has become a serious contender as a recording modality for the implementation of Brain-Computer Interface (BCI) systems in the last few years. ECoG signals provide the right balance between minimal invasiveness and robust spectral information to accomplish a BCI task. However, all the BCI studies until now have used signals recorded from a large number of implanted electrodes and a larger number of spectral features. The recording and processing of these signals uses a lot of electrical power and thus hinders its use outside the research setting. To translate this research …

Experimental And Computational Studies Of Cortical Neural Network Properties Through Signal Processing, Wesley Patrick Clawson

Graduate Theses and Dissertations

Previous studies, both theoretical and experimental, of network level dynamics in the cerebral cortex show evidence for a statistical phenomenon called criticality; a phenomenon originally studied in the context of phase transitions in physical systems and that is associated with favorable information processing in the context of the brain. The focus of this thesis is to expand upon past results with new experimentation and modeling to show a relationship between criticality and the ability to detect and discriminate sensory input. A line of theoretical work predicts maximal sensory discrimination as a functional benefit of criticality, which can then be characterized …

The Connectivity Domain: Analyzing Resting State Fmri Data Using Feature-Based Data-Driven And Model-Based Methods, Armin Iraji, Vince D. Calhoun, Natalie M. Wiseman, Esmaeil Davoodi-Bojd, Mohammad R. N. Avanaki, Zhifeng Kou

Biomedical Engineering Faculty Research Publications

Spontaneous fluctuations of resting state functional MRI (rsfMRI) have been widely used to understand the macro-connectome of the human brain. However, these fluctuations are not synchronized among subjects, which leads to limitations and makes utilization of first-level model-based methods challenging. Considering this limitation of rsfMRI data in the time domain, we propose to transfer the spatiotemporal information of the rsfMRI data to another domain, the connectivity domain, in which each value represents the same effect across subjects. Using a set of seed networks and a connectivity index to calculate the functional connectivity for each seed network, we transform data into …

The Viability Of High-Frequency Oscillation Analysis In Eeg Signals For Seizure Prediction, Bryan David Kern

Open Access Theses & Dissertations

Seizure prediction is a decades-old research problem that has yet to reach any satisfying conclusions. Many studies have tackled the problem with varying results, but there has yet to be any major breakthroughs that define the direction of all future research. However, a promising, new predictor may have presented itself in recent years in the form of high frequency oscillations (HFOs). With the discovery of HFOs (80 - 800 Hz) as a biomarker for epilepsy, new interest has been placed in studying the high frequency content of EEGs to find a possible link between epilepsy and HFOs. In this paper, …

Intracranial Volume Estimation And Graph Theoretical Analysis Of Brain Functional Connectivity Networks, Saman Sargolzaei

FIU Electronic Theses and Dissertations

Understanding pathways of neurological disorders requires extensive research on both functional and structural characteristics of the brain. This dissertation introduced two interrelated research endeavors, describing (1) a novel integrated approach for constructing functional connectivity networks (FCNs) of brain using non-invasive scalp EEG recordings; and (2) a decision aid for estimating intracranial volume (ICV). The approach in (1) was developed to study the alterations of networks in patients with pediatric epilepsy. Results demonstrated the existence of statistically significant (p

A Novel Signal Processing Method For Intraoperative Neurophysiological Monitoring In Spinal Surgeries, Krishnatej Vedala

FIU Electronic Theses and Dissertations

Intraoperative neurophysiologic monitoring is an integral part of spinal surgeries and involves the recording of somatosensory evoked potentials (SSEP). However, clinical application of IONM still requires anywhere between 200 to 2000 trials to obtain an SSEP signal, which is excessive and introduces a significant delay during surgery to detect a possible neurological damage. The aim of this study is to develop a means to obtain the SSEP using a much less, twelve number of recordings. The preliminary step involved was to distinguish the SSEP with the ongoing brain activity. We first establish that the brain activity is indeed quasi-stationary whereas …

Effects Of Hearing Aid Amplification On Robust Neural Coding Of Speech, Jonathan Daniel Boley

Open Access Dissertations

Hearing aids are able to restore some hearing abilities for people with auditory impairments, but background noise remains a significant problem. Unfortunately, we know very little about how speech is encoded in the auditory system, particularly in impaired systems with prosthetic amplifiers. There is growing evidence that relative timing in the neural signals (known as spatiotemporal coding) is important for speech perception, but there is little research that relates spatiotemporal coding and hearing aid amplification.

This research uses a combination of computational modeling and physiological experiments to characterize how hearing aids affect vowel coding in noise at the level of …

Effects Of Dip-Coated Films On The Properties Of Implantable Intracortical Microelectrodes, Salah Sommakia

Open Access Dissertations

The successful clinical use of implantable intracortical microelectrodes (ICMs) to treat certain types of deafness, blindness, and paralysis is limited by a reactive tissue response (RTR) of the brain. This RTR culminates in the formation of a tight glial scar and a loss of neuronal density around implanted ICMs, and is accompanied by a decrease in signal to noise ratio and an increase in impedance. While no comprehensive mechanistic understanding of the underlying biology is currently agreed upon in the field, a general consensus exists around a highly volatile acute RTR phase. During this acute phase, the electrical properties of …

Manufacturing Nerve Guidance Conduits By Stereolithography For Use In Peripheral Nerve Regeneration, Mireya Aidee Perez

Open Access Theses & Dissertations

Nerve regeneration techniques have been studied in great depth in recent years. Peripheral nerve injuries, in particular, can be caused by accidents, falls, athletic injuries, etc. Current methods of repair include direct suturing of the 2 injured nerve ends or the use of autografts, when a nerve section is taken from another area of the body. Both methods have a series of limitations which have led researchers to study alternative methods of repair. Nerve guidance conduits may provide a viable solution because they can be modified and adapted to the patient's needs. Some conduits already exist on the market and …

Brain-Computer Interfaces In Medicine, Jerry J. Shih, Dean J. Krusienski, Johnathan R. Wolpaw

Electrical & Computer Engineering Faculty Publications

Brain-computer interfaces (BCIs) acquire brain signals, analyze them, and translate them into commands that are relayed to output devices that carry out desired actions. BCIs do not use normal neuromuscular output pathways. The main goal of BCI is to replace or restore useful function to people disabled by neuromuscular disorders such as amyotrophic lateral sclerosis, cerebral palsy, stroke, or spinal cord injury. From initial demonstrations of electroenceph-alography-based spelling and single-neuron-based device control, researchers have gone on to use electroenceph-alographic, intracortical, electrocorticographic, and other brain signals for increasingly complex control of cursors, robotic arms, prostheses, wheelchairs, and other devices. Brain-computer interfaces …