To date, invasive brain-computer interface (BCI) research has largely focused on replacing lost limb functions using signals from hand/arm areas of motor cortex. However, the oculomotor system may be better suited to BCI applications involving rapid serial selection from spatial targets, such as choosing from a set of possible words displayed on a computer screen in an augmentative and alternative communication application. First, we develop an intracortical oculomotor BCI based on the delayed saccade paradigm and demonstrate its feasibility to decode intended saccadic eye movement direction in primates. Using activity from three frontal cortical areas implicated in oculomotor production – dorsolateral prefrontal cortex, supplementary eye field, and frontal eye field – we could decode intended saccade direction in real time with high accuracy, particularly at contralateral locations. In a number of analyses in the decoding context, we investigated the amount of saccade-related information contained in different implant regions and in different neural measures. A novel neural measure using power in the 80-500 Hz band is proposed as the optimal signal for this BCI purpose. In the second part of this thesis, we characterize the interactions between the neural signals recorded from electrodes in these three implant areas. We employ a number of techniques to quantify the spectrotemporal dynamics in this complex network, and we describe the resulting functional connectivity patterns between the three implant regions in the context of eye-movement production. In addition, we compare and contrast the amount of saccade-related information present in the coupling strengths in the network, on both an electrode-to-electrode scale and an area-to-area scale. Different frequency bands stand out during different epochs of the task, and their information contents are distinct between implant regions. For example, the 13-30 Hz band stands out during the delay epoch, and the 8-12 Hz band is relevant during target and response epochs. This work extends the boundary of BCI research into the oculomotor domain, and invites potential applications by showing its feasibility. Furthermore, it elucidates the complex dynamics of the functional coupling underlying oculomotor production across multiple areas of frontal cortex.

Older bilingual adults typically perform better than monolinguals in tasks of executive control, and are diagnosed later with dementia. Studies have also shown structural and functional brain differences between bilinguals and monolinguals. However, it remains poorly understood how language history influences the functional organization of the aging brain. The current study investigated; 1) differences in resting-state functional connectivity between monolinguals and bilinguals in the Default Mode Network (DMN), Frontoparietal Network (FPN), Executive Control Network (ECN), Language Network (LANG), and a network consisting of structures associated with tasks of executive control coined the Bilingual Control Network (BCN); 2) the relationship of cognitive performance with functional connectivity of the BCN; and 3) whether proficiency, age of second language acquisition, degree of second language exposure, and frequency of language use predicts the network’s functional connectivity. Healthy older bilinguals (N=10) were matched pairwise for age, sex and education to healthy older monolinguals (N=10). All participants completed a battery of cognitive tests, a language history questionnaire, and a 6-minute functional scan during rest. Results showed that groups did not differ in cognitive performance, or in the functional connectivity of the FPN, ECN, LANG, or BCN. However, monolinguals had significantly stronger functional connectivity in the DMN compared to bilinguals. Later age of second language acquisition and lower proficiency were also associated with greater DMN functional connectivity. None of these variables predicted BCN’s functional connectivity. However, bilinguals showed stronger functional connectivity with other structures outside of the canonical networks compared to monolinguals. Finally, vocabulary scores, local switch cost accuracy and reaction time were negatively correlated with BCN’s functional connectivity. Overall, these findings illustrate differences in functional brain organization associated with language experience in the DMN, while challenging the “bilingual advantage” hypothesis. The results also suggest a possible neural mechanism by which bilingualism might mediate cognitive reserve.

Stream flowline delineation from high-resolution digital elevation models (HRDEMs) can be problematic due to the fine representation of terrain features as well as anthropogenic drainage structures (e.g., bridges, culverts) within the grid surface. The anthropogenic drainage structures (ADS) may create digital dams while delineating stream flowlines from HRDEMs. The study assessed the effects of ADS locations, spatial resolution (ranged from 1m to 10m), depression processing methods, and flow direction algorithms (D8, D-Infinity, and MFD-md) on hydrologic connectivity through digital dams using HRDEMs in Nebraska. The assessment was conducted based on the offset distances between modeled stream flowlines and original ADS locations using kernel density estimation (KDE) and calculated frequency of ADS samples within offset distances. Three major depression processing techniques (i.e., depression filling, stream breaching, and stream burning) were considered for this study. Finally, an automated method, constrained burning was proposed for HRDEMs which utilizes ancillary datasets to create underneath stream crossings at possible ADS locations and perform DEM reconditioning. The results suggest that coarser resolution DEMs with depression filling and breaching can produce better hydrologic connectivity through ADS compared with finer resolution DEMs with different flow direction algorithms. It was also found that stream burning with known stream crossings at ADS locations outperformed depression filling and breaching techniques for HRDEMs in terms of hydrologic connectivity. The flow direction algorithms combining with depression filling and breaching techniques do not have significant effects on the hydrologic connectivity of modeled stream flowlines. However, for stream burning methods, D8 was found as the best performing flow direction algorithm in HRDEMs with statistical significance. The stream flowlines delineated using the proposed constrained burning method from the HRDEM was found better than depression filling and breaching techniques. This method has an overall accuracy of 78.82% in detecting possible ADS locations within the study area.

Early sensory experiences play a critical role in the activity-dependent development of the sensorimotor system. The sources of sensory input to the neonatal nervous system involve external stimulation (exafference) and sensory feedback arising from self-generated movements (reafference). In the perinatal period, reafference from twitches of the limbs and facial muscles during active (REM) sleep is a powerful driver of neural activity across the entire neuraxis. Thus, sleep-related twitches are thought to contribute to the activity-dependent development of sensorimotor networks. In this dissertation, we first aimed to identify a motor pathway for the generation of twitching. Using newborn rats at postnatal day (P) 8, we provide evidence that the red nucleus (RN; source of the rubrospinal tract) is involved in the production of twitching. In addition, we show that reafference from twitches drives neural activity in the RN, therefore suggesting that the RN is an important site for sensorimotor integration. Also, in the RN of P8 rats, twitch-related reafference triggers theta (4–7 Hz) oscillations. By P12, theta oscillations are expressed continuously and exclusively across bouts of active sleep. Synchronized neuronal oscillations comprise a fundamental mechanism by which distant neural structures establish and express functional connectivity. Thus, we next hypothesized that sleep-dependent theta oscillatory activity enables the expression of network connectivity between the RN and associated neural networks, such as the hippocampus. Simultaneous recordings from the hippocampus and RN at P12 show that theta oscillations in both structures are synchronized, co-modulated, and mutually interactive exclusively during active sleep. Lastly, we test the hypothesis that twitches drive synchronized oscillatory activity across functionally related sensory structures at early ages when the occurrence of oscillations largely depends on sensory input. Focusing on the cortico-hippocampal network at P8, we demonstrate that, unlike periods of wake-related movements or behavioral quiescence, twitching promotes coupled oscillatory activity at Beta2 frequency (~20-30 Hz). Altogether, the findings in this dissertation suggest that one of the functions of active sleep in early infancy is to provide a context for sensorimotor processing and for synchronizing activity within and between forebrain and brainstem structures. Consequently, any condition or manipulation that restricts active sleep can deprive the infant animal of substantial sensory experience, potentially resulting in atypical developmental trajectories.

Complex cognitive functions require interactions within and between different brain regions by direct anatomical connections or synchronous activation. As such, damage to any region involved in a cognitive process has the potential to affect its function. Impulsivity is a multifaceted construct that, when dysfunctional, contributes to many psychiatric conditions. The striatum has been implicated as an integral part of the neural circuitry of impulsivity. The current work aims to contribute to the understanding of neural dysfunction underlying disorders of impulsivity by examining how striatal damage affects impulsive behavior. It also aims to improve our understanding of whether neural processes involved in impulsivity are also involved in maintaining awareness of one's thoughts and actions. No studies have systematically examined the extent to which damage to the striatum correlates with both changes in impulsive behavior and changes in self-awareness of impulsive personality. In the first experiment, I examined the effects of focal unilateral striatal damage on self-awareness of impulsivity and other personality traits. I predicted that participants with striatal damage (SD) would have less self-awareness of changes in impulsivity and other personality traits after brain damage, as compared to brain damage comparisons (BDC), due to indirect disruption of neural networks responsible for self-referential processing. I tested this prediction using self and collateral versions of the Barratt Impulsiveness scale (BIS) and the Iowa Scales of Personality Change. In partial support of my hypothesis, there were mean differences in self- and collateral-reported impulsivity on the BIS, with self ratings higher than collateral ratings in the SD group. There were no significant differences in the correlations between self- and collateral-reports for current impulsivity, change in impulsivity, or change in other personality traits. In the second experiment, I examined the effects of focal unilateral striatal damage on laboratory measures of impulsivity. I predicted that participants with striatal damage would exhibit lower levels impulsivity than brain damaged comparisons due to structural loss of regions involved in reward/motivation and motor activity. I tested this using impulsive action tasks (Go/NoGo and Stop Signal Tasks) and impulsive choice tasks (Delay and Probability Discounting). In contrast to my hypothesis, SD participants did not exhibit less impulsive action or impulsive choice than BDC participants. In the third experiment, I examined the effects of focal unilateral striatal damage on the integrity of frontostriatal resting state functional connectivity. I predicted that participants with striatal damage would exhibit alterations in functional connectivity between the remaining regions of the frontostriatal network. I tested this by comparing the strength of functional connectivity of the caudate head and ventromedial prefrontal cortex. While my hypothesis was not directly supported, the data showed interesting trends that warrant further exploration. These included stronger caudate-vmPFC resting state functional connectivity on the lesion side, and weaker functional connectivity on the non-lesioned side in striatal participants compared to brain damaged comparisons. Together, these experiments suggest that although unilateral striatal damage does not appear to affect subjective reports or laboratory measures of impulsivity, it may affect the underlying neural networks utilized by the striatum, as evidenced by changes in frontostriatal resting state functional connectivity. This work extends our understanding of the neurobiology of impulsive behavior and self-awareness, at systems level, and may help pave the way for treatments of those with brain injury, such as traumatic brain injury and stroke patients, or psychiatric disorders involving impulsivity.

My dissertation focused on understanding how different areas of the brain coordinate in networks to drive higher cognitive functions, and how damage, changes the brain’s synchronized activity (or functional connectivity) in the short and long term. In this dissertation, I studied the functional connectivity of brain networks that are thought to underlie emotion and decision-making, and how these networks change in the face of neurological injury. In my first set of experiments, I studied participants with chronic focal brain damage to determine how damage to brain areas which have been identified as important in emotion and decision-making behaviors (amygdala, ventromedial prefrontal cortex, & insula), affected connectivity of brain networks, and how changes in connectivity following damage to these areas related to emotion and decision-making behavior. Supporting my predictions, I found evidence that damage to the amygdala, ventromedial prefrontal cortex, and insula all result in significantly weaker connections between a network of areas important for assigning value to stimuli. Additionally, I found that stronger connectivity in this valuation network was significantly positively associated with performance on ratings of disgusted faces, while stronger connectivity in a network important for processing emotional salience was significantly positively correlated with decision-making performance. In the second set of studies in this dissertation, I utilized a population of epilepsy patients who were undergoing brain surgery to treat their seizures to investigate how a brain network related to emotional salience changed from before to after surgery. This approach allowed me to study how the connectivity and associated behavior of this network changed from preoperative baseline, to the weeks and months after part of this network was removed. While I expected a decline in this network in the weeks following surgery, instead I found a significant positive correlation between preoperative and acute postoperative connectivity in a subset of this network. However, my hypothesis that there would be a significant increase in the connectivity of this network between acute and chronic postoperative epochs was supported. I only have partial evidence for a significant correlation between the change in salience network connectivity between preoperative and acute postoperative assessments and the associated change in decision-making behavior. This correlation was in the opposite direction of my hypothesis, with increased change in connectivity being positively associated with change in risk-taking behavior. I did not observe a significant correlation between the change in network connectivity and change in behavior across acute and chronic measurements. These findings provide important insight on how measures of network connectivity can inform theories of neuroplasticity and reorganization following brain damage. Understanding how these networks change over time, and how changes in these networks relate to behavioral outcomes, are critical for the development and effective deployment of therapeutic interventions. Together, these studies provide a foundation for further study, demonstrating that these networks change over time with damage, and the residual network strength is associated with performance on measures of emotion and decision-making.

Mobile technology is becoming more and more pervasive within the consumer industry. Devices such as Smartphones and Tablets are able to relay information effectively and affordably either with or without an accompanying cellular connectivity plan. The effect of this technology is slowly making its way through the corporate world. Recognizing that this technology has the potential to affect workflow practices within a Department of Transportation, this thesis first presents two mobile applications to address specific areas of concern identified within the Utah Department of Transportation maintenance division. The first application creates a living directory that provides specific information regarding employees, equipment, and location within maintenance shed locations throughout the state of Utah. The second application provides a seamless method of information transfer as it relates to traffic signs from the field directly to central servers in an effort to reduce data loss and corruption.

Processes that influence the early life stages of fishes can significantly impact population dynamics, yet they continue to be poorly understood. This dissertation examined relationships between the environment, early life history traits (ELHTs), behavior, and post-settlement survival for a coral reef fish, Stegastes partitus, in the upper Florida Keys, to elucidate how they influence juvenile demography. Otolith analysis of settlers and recruits coupled with environmental data revealed that S. partitus surviving the early juvenile period settled at larger sizes and grew slower post-settlement. Water temperature also influenced the ranges of these and other ELHTs as well as the intensity and direction of selective mortality processes acting on some of these traits (i.e., pelagic larval duration, mean larval growth). Otolith analysis was paired with behavioral observations of newly settled juvenile S. partitus in the field to reveal that the relationship between size-at-settlement, early juvenile growth and survival is behaviorally-mediated. Individuals that were larger at settlement were more active (i.e., spent less time sheltered, swam farther from shelters) and grew more slowly post-settlement. Likewise, slower juvenile growth was associated with greater activity, more conspecific aggression, and faster escape swimming speeds. A six-year time series of recruitment densities revealed substantial temporal (interannual, seasonal, lunar) and spatial (by microhabitat, conspecific density) variability in recruitment which influenced the composition of recruits. For instance, larvae settling during the darkest phases of the moon were larger at settlement, but selective mortality processes during brighter periods removed more of the smallest settlers, resulting in juveniles with similar sizes-at-settlement regardless of when they arrived to the reef. Because recruitment strength and composition varied temporally, genetic markers (6 microsatellite and 1 mitochondrial loci) were used to determine if the genetic composition of monthly cohorts of settling larvae and juveniles also varies interannually, monthly, or across life stages. A lack of genetic structure suggested that S. partitus has a large effective population size and variation in ELHTs is not likely the result of successful spawning of a disproportionately small group of adults. As a whole, these results reveal processes associated with larval supply and post-settlement life that collectively shape juvenile demography.

Recent efforts to optimize oil recovery from Green River reservoirs, Uinta Basin, have stimulated the need for better understanding of the reservoir connectivity at the scale of the operational unit. This study focuses on Green River reservoirs in the Wells Draw study area where oil production response to implemented waterflood is poor and a better understanding of the reservoir connectivity is required to enhance future secondary oil recovery. Correlating the sand bodies between well locations in the area remains difficult at 40-acre well spacing. Thus, interwell connectivity of the reservoirs is uncertain. Understanding the reservoir connectivity in the Wells Draw study area requires integration of all static and dynamic data for generation of probabilistic models of the reservoir at the interwell locations. The objective of this study is two-fold. The first objective was to determine reservoir connectivity at the interwell scale in the Wells Draw study area. To achieve this goal, I used well log and perforation data in the Wells Draw study area to produce probabilistic models of net-porosity for four producing intervals: (1) Castle Peak, (2) Lower Douglas Creek, (3) Upper Douglas Creek, and (4) Garden Gulch. The second objective was to find readily applicable methods for determining interwell connectivity. To achieve this goal, I used sandstone net thickness and perforation data to evaluate interwell connectivity in the Wells Draw study area. This evaluation was done to: (1) assess and visualize connectivity, (2) provide an assessment of connectivity for validating / calibrating percolation and capacitance based methods, and (3) determine flow barriers for simulation. The probabilistic models encompass the four producing intervals with a gross thickness of 1,900 ft and enable simulation assessments of different development strategies for optimization of oil recovery in the Wells Draw study area. The method developed for determining interwell connectivity in Wells Draw study area is reliable and suited to the four producing intervals. Also, this study shows that the percolation based method is reliable for determining interwell connectivity in the four producing intervals.

With a   growing human population, cities keep growing worldwide altering ecosystem   and thereby affecting the species living in these areas. Most studies of   urbanization and its effect on ecosystem have been conducted in the western   world and little is known about its effect in the neotropical part of the   world. I examined effects of fragment size, vegetation structure and   connectivity of urban green areas on bird species richness, mean abundance,   diversity and biomass in La Paz, Bolivia. Additionally, the effects of   different disturbance variables on bird community were evaluated. In total,   36 bird species were found in 24 fragment of varying size, connectivity and   level of disturbance. Bird species richness decreased with increasing   disturbance while connectivity and fragment size did not contribute   significantly to explain the variation in species richness at count point scale (p>0.005, multiple linear regression). At fragment   scale, however, species richness increased with fragment sizes,   which has been shown in other studies from neotrophical regions. Variation in   abundance, diversity or biomass could not be explained by connectivity,   fragment size or disturbance.     Furthermore, coverage of construction had a negative effect on species   richness while coverage of bushes and coverage of herbs were negatively   related to biomass and diversity, respectively. The composition of bird   species differed with size and disturbance of the fragments, so that more   omnivorous and granivorous species such as Zonotrichia capensis, Turdus chiguanco and Zenaida auriculata, were present in areas highly affected by human activities. Larger fragments,   less affected by human presence held a larger proportion of insectivorous   species.