Matching Items (122)
Description
An accurate sense of upper limb position is crucial to reaching movements where sensory information about upper limb position and target location is combined to specify critical features of the movement plan. This dissertation was dedicated to studying the mechanisms of how the brain estimates the limb position in space and the consequences of misestimation of limb position on movements. Two independent but related studies were performed. The first involved characterizing the neural mechanisms of limb position estimation in the non-human primate brain. Single unit recordings were obtained in area 5 of the posterior parietal cortex in order to examine the role of this area in estimating limb position based on visual and somatic signals (proprioceptive, efference copy). When examined individually, many area 5 neurons were tuned to the position of the limb in the workspace but very few neurons were modulated by visual feedback. At the population level however decoding of limb position was somewhat more accurate when visual feedback was provided. These findings support a role for area 5 in limb position estimation but also suggest that visual signals regarding limb position are only weakly represented in this area, and only at the population level. The second part of this dissertation focused on the consequences of misestimation of limb position for movement production. It is well known that limb movements are inherently variable. This variability could be the result of noise arising at one or more stages of movement production. Here we used biomechanical modeling and simulation techniques to characterize movement variability resulting from noise in estimating limb position ('sensing noise') and in planning required movement vectors ('planning noise'), and compared that to the variability expected due to noise in movement execution. We found that the effects of sensing and planning related noise on movement variability were dependent upon both the planned movement direction and the initial configuration of the arm and were different in many respects from the effects of execution noise.
ContributorsShi, Ying (Author) / Buneo, Christopher A (Thesis advisor) / Helms Tillery, Stephen (Committee member) / Santello, Marco (Committee member) / He, Jiping (Committee member) / Santos, Veronica (Committee member) / Arizona State University (Publisher)
Created2011
Description
The oceans play an essential role in global biogeochemical cycles and in regulating climate. The biological carbon pump, the photosynthetic fixation of carbon dioxide by phytoplankton and subsequent sequestration of organic carbon into deep water, combined with the physical carbon pump, make the oceans the only long-term net sink for anthropogenic carbon dioxide. A full understanding of the workings of the biological carbon pump requires a knowledge of the role of different taxonomic groups of phytoplankton (protists and cyanobacteria) to organic carbon export. However, this has been difficult due to the degraded nature of particles sinking into particle traps, the main tools employed by oceanographers to collect sinking particulate matter in the ocean. In this study DNA-based molecular methods, including denaturing gradient gel electrophoresis, cloning and sequencing, and taxon-specific quantitative PCR, allowed for the first time for the identification of which protists and cyanobacteria contributed to the material collected by the traps in relation to their presence in the euphotic zone. I conducted this study at two time-series stations in the subtropical North Atlantic Ocean, one north of the Canary Islands, and one located south of Bermuda. The Bermuda study allowed me to investigate seasonal and interannual changes in the contribution of the plankton community to particle flux. I could also show that small unarmored taxa, including representatives of prasinophytes and cyanobacteria, constituted a significant fraction of sequences recovered from sediment trap material. Prasinophyte sequences alone could account for up to 13% of the clone library sequences of trap material during bloom periods. These observations contradict a long-standing paradigm in biological oceanography that only large taxa with mineral shells are capable of sinking while smaller, unarmored cells are recycled in the euphotic zone through the microbial loop. Climate change and a subsequent warming of the surface ocean may lead to a shift in the protist community toward smaller cell size in the future, but in light of these findings these changes may not necessarily lead to a reduction in the strength of the biological carbon pump.
ContributorsAmacher, Jessica (Author) / Neuer, Susanne (Thesis advisor) / Garcia-Pichel, Ferran (Committee member) / Lomas, Michael (Committee member) / Wojciechowski, Martin (Committee member) / Stout, Valerie (Committee member) / Arizona State University (Publisher)
Created2011
Description
In this thesis I introduce a new direction to computing using nonlinear chaotic dynamics. The main idea is rich dynamics of a chaotic system enables us to (1) build better computers that have a flexible instruction set, and (2) carry out computation that conventional computers are not good at it. Here I start from the theory, explaining how one can build a computing logic block using a chaotic system, and then I introduce a new theoretical analysis for chaos computing. Specifically, I demonstrate how unstable periodic orbits and a model based on them explains and predicts how and how well a chaotic system can do computation. Furthermore, since unstable periodic orbits and their stability measures in terms of eigenvalues are extractable from experimental times series, I develop a time series technique for modeling and predicting chaos computing from a given time series of a chaotic system. After building a theoretical framework for chaos computing I proceed to architecture of these chaos-computing blocks to build a sophisticated computing system out of them. I describe how one can arrange and organize these chaos-based blocks to build a computer. I propose a brand new computer architecture using chaos computing, which shifts the limits of conventional computers by introducing flexible instruction set. Our new chaos based computer has a flexible instruction set, meaning that the user can load its desired instruction set to the computer to reconfigure the computer to be an implementation for the desired instruction set. Apart from direct application of chaos theory in generic computation, the application of chaos theory to speech processing is explained and a novel application for chaos theory in speech coding and synthesizing is introduced. More specifically it is demonstrated how a chaotic system can model the natural turbulent flow of the air in the human speech production system and how chaotic orbits can be used to excite a vocal tract model. Also as another approach to build computing system based on nonlinear system, the idea of Logical Stochastic Resonance is studied and adapted to an autoregulatory gene network in the bacteriophage λ.
ContributorsKia, Behnam (Author) / Ditto, William (Thesis advisor) / Huang, Liang (Committee member) / Lai, Ying-Cheng (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2011
Description
Anticipatory planning of digit positions and forces is critical for successful dexterous object manipulation. Anticipatory (feedforward) planning bypasses the inherent delays in reflex responses and sensorimotor integration associated with reactive (feedback) control. It has been suggested that feedforward and feedback strategies can be distinguished based on the profile of grip and load force rates during the period between initial contact with the object and object lift. However, this has not been validated in tasks that do not constrain digit placement. The purposes of this thesis were (1) to validate the hypothesis that force rate profiles are indicative of the control strategy used for object manipulation and (2) to test this hypothesis by comparing manipulation tasks performed with and without digit placement constraints. The first objective comprised two studies. In the first study an additional light or heavy mass was added to the base of the object. In the second study a mass was added, altering the object's center of mass (CM) location. In each experiment digit force rates were calculated between the times of initial digit contact and object lift. Digit force rates were fit to a Gaussian bell curve and the goodness of fit was compared across predictable and unpredictable mass and CM conditions. For both experiments, a predictable object mass and CM elicited bell shaped force rate profiles, indicative of feedforward control. For the second objective, a comparison of performance between subjects who performed the grasp task with either constrained or unconstrained digit contact locations was conducted. When digit location was unconstrained and CM was predictable, force rates were well fit to a bell shaped curve. However, the goodness of fit of the force rate profiles to the bell shaped curve was weaker for the constrained than the unconstrained digit placement condition. These findings seem to indicate that brain can generate an appropriate feedforward control strategy even when digit placement is unconstrained and an infinite combination of digit placement and force solutions exists to lift the object successfully. Future work is needed that investigates the role digit positioning and tactile feedback has on anticipatory control of object manipulation.
ContributorsCooperhouse, Michael A (Author) / Santello, Marco (Thesis advisor) / Helms Tillery, Stephen (Committee member) / Buneo, Christopher (Committee member) / Arizona State University (Publisher)
Created2011
Description
Gene manipulation techniques, such as RNA interference (RNAi), offer a powerful method for elucidating gene function and discovery of novel therapeutic targets in a high-throughput fashion. In addition, RNAi is rapidly being adopted for treatment of neurological disorders, such as Alzheimer's disease (AD), Parkinson's disease, etc. However, a major challenge in both of the aforementioned applications is the efficient delivery of siRNA molecules, plasmids or transcription factors to primary cells such as neurons. A majority of the current non-viral techniques, including chemical transfection, bulk electroporation and sonoporation fail to deliver with adequate efficiencies and the required spatial and temporal control. In this study, a novel optically transparent biochip is presented that can (a) transfect populations of primary and secondary cells in 2D culture (b) readily scale to realize high-throughput transfections using microscale electroporation and (c) transfect targeted cells in culture with spatial and temporal control. In this study, delivery of genetic payloads of different sizes and molecular characteristics, such as GFP plasmids and siRNA molecules, to precisely targeted locations in primary hippocampal and HeLa cell cultures is demonstrated. In addition to spatio-temporally controlled transfection, the biochip also allowed simultaneous assessment of a) electrical activity of neurons, b) specific proteins using fluorescent immunohistochemistry, and c) sub-cellular structures. Functional silencing of GAPDH in HeLa cells using siRNA demonstrated a 52% reduction in the GAPDH levels. In situ assessment of actin filaments post electroporation indicated a sustained disruption in actin filaments in electroporated cells for up to two hours. Assessment of neural spike activity pre- and post-electroporation indicated a varying response to electroporation. The microarray based nature of the biochip enables multiple independent experiments on the same culture, thereby decreasing culture-to-culture variability, increasing experimental throughput and allowing cell-cell interaction studies. Further development of this technology will provide a cost-effective platform for performing high-throughput genetic screens.
ContributorsPatel, Chetan (Author) / Muthuswamy, Jitendran (Thesis advisor) / Helms Tillery, Stephen (Committee member) / Jain, Tilak (Committee member) / Caplan, Michael (Committee member) / Vernon, Brent (Committee member) / Arizona State University (Publisher)
Created2012
Description
Humans have an inherent capability of performing highly dexterous and skillful tasks with their arms, involving maintaining posture, movement and interacting with the environment. The latter requires for them to control the dynamic characteristics of the upper limb musculoskeletal system. Inertia, damping and stiffness, a measure of mechanical impedance, gives a strong representation of these characteristics. Many previous studies have shown that the arm posture is a dominant factor for determining the end point impedance in a horizontal plane (transverse plane). The objective of this thesis is to characterize end point impedance of the human arm in the three dimensional (3D) space. Moreover, it investigates and models the control of the arm impedance due to increasing levels of muscle co-contraction. The characterization is done through experimental trials where human subjects maintained arm posture, while perturbed by a robot arm. Moreover, the subjects were asked to control the level of their arm muscles' co-contraction, using visual feedback of their muscles' activation, in order to investigate the effect of the muscle co-contraction on the arm impedance. The results of this study showed a very interesting, anisotropic increase of the arm stiffness due to muscle co-contraction. This can lead to very useful conclusions about the arm biomechanics as well as many implications for human motor control and more specifically the control of arm impedance through muscle co-contraction. The study finds implications for the EMG-based control of robots that physically interact with humans.
ContributorsPatel, Harshil Naresh (Author) / Artemiadis, Panagiotis (Thesis advisor) / Berman, Spring (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2013
Description
This research is focused on two separate but related topics. The first uses an electroencephalographic (EEG) brain-computer interface (BCI) to explore the phenomenon of motor learning transfer. The second takes a closer look at the EEG-BCI itself and tests an alternate way of mapping EEG signals into machine commands. We test whether motor learning transfer is more related to use of shared neural structures between imagery and motor execution or to more generalized cognitive factors. Using an EEG-BCI, we train one group of participants to control the movements of a cursor using embodied motor imagery. A second group is trained to control the cursor using abstract motor imagery. A third control group practices moving the cursor using an arm and finger on a touch screen. We hypothesized that if motor learning transfer is related to the use of shared neural structures then the embodied motor imagery group would show more learning transfer than the abstract imaging group. If, on the other hand, motor learning transfer results from more general cognitive processes, then the abstract motor imagery group should also demonstrate motor learning transfer to the manual performance of the same task. Our findings support that motor learning transfer is due to the use of shared neural structures between imaging and motor execution of a task. The abstract group showed no motor learning transfer despite being better at EEG-BCI control than the embodied group. The fact that more participants were able to learn EEG-BCI control using abstract imagery suggests that abstract imagery may be more suitable for EEG-BCIs for some disabilities, while embodied imagery may be more suitable for others. In Part 2, EEG data collected in the above experiment was used to train an artificial neural network (ANN) to map EEG signals to machine commands. We found that our open-source ANN using spectrograms generated from SFFTs is fundamentally different and in some ways superior to Emotiv's proprietary method. Our use of novel combinations of existing technologies along with abstract and embodied imagery facilitates adaptive customization of EEG-BCI control to meet needs of individual users.
Contributorsda Silva, Flavio J. K (Author) / Mcbeath, Michael K (Thesis advisor) / Helms Tillery, Stephen (Committee member) / Presson, Clark (Committee member) / Sugar, Thomas (Committee member) / Arizona State University (Publisher)
Created2013
Description
Microbial electrochemical cells (MXCs) are promising platforms for bioenergy production from renewable resources. In these systems, specialized anode-respiring bacteria (ARB) deliver electrons from oxidation of organic substrates to the anode of an MXC. While much progress has been made in understanding the microbiology, physiology, and electrochemistry of well-studied model ARB such as Geobacter and Shewanella, tremendous potential exists for MXCs as microbiological platforms for exploring novel ARB. This dissertation introduces approaches for selective enrichment and characterization of phototrophic, halophilic, and alkaliphilic ARB. An enrichment scheme based on manipulation of poised anode potential, light, and nutrient availability led to current generation that responded negatively to light. Analysis of phototrophically enriched communities suggested essential roles for green sulfur bacteria and halophilic ARB in electricity generation. Reconstruction of light-responsive current generation could be successfully achieved using cocultures of anode-respiring Geobacter and phototrophic Chlorobium isolated from the MXC enrichments. Experiments lacking exogenously supplied organic electron donors indicated that Geobacter could produce a measurable current from stored photosynthate in the dark. Community analysis of phototrophic enrichments also identified members of the novel genus Geoalkalibacter as potential ARB. Electrochemical characterization of two haloalkaliphilic, non-phototrophic Geoalkalibacter spp. showed that these bacteria were in fact capable of producing high current densities (4-8 A/m2) and using higher organic substrates under saline or alkaline conditions. The success of these selective enrichment approaches and community analyses in identifying and understanding novel ARB capabilities invites further use of MXCs as robust platforms for fundamental microbiological investigations.
ContributorsBadalamenti, Jonathan P (Author) / Krajmalnik-Brown, Rosa (Thesis advisor) / Garcia-Pichel, Ferran (Committee member) / Rittmann, Bruce E. (Committee member) / Torres, César I (Committee member) / Vermaas, Willem (Committee member) / Arizona State University (Publisher)
Created2013
Description
Human activity has increased loading of reactive nitrogen (N) in the environment, with important and often deleterious impacts on biodiversity, climate, and human health. Since the fate of N in the ecosystem is mainly controlled by microorganisms, understanding the factors that shape microbial communities becomes relevant and urgent. In arid land soils, these microbial communities and factors are not well understood. I aimed to study the role of N cycling microbes, such as the ammonia-oxidizing bacteria (AOB), the recently discovered ammonia-oxidizing archaea (AOA), and various fungal groups, in soils of arid lands. I also tested if niche differentiation among microbial populations is a driver of differential biogeochemical outcomes. I found that N cycling microbial communities in arid lands are structured by environmental factors to a stronger degree than what is generally observed in mesic systems. For example, in biological soil crusts, temperature selected for AOA in warmer deserts and for AOB in colder deserts. Land-use change also affects niche differentiation, with fungi being the major agents of N2O production in natural arid lands, whereas emissions could be attributed to bacteria in mesic urban lawns. By contrast, NO3- production in the native desert and managed soils was mainly controlled by autotrophic microbes (i.e., AOB and AOA) rather than by heterotrophic fungi. I could also determine that AOA surprisingly responded positively to inorganic N availability in both short (one month) and long-term (seven years) experimental manipulations in an arid land soil, while environmental N enrichment in other ecosystem types is known to favor AOB over AOA. This work improves our predictions of ecosystem response to anthropogenic N increase and shows that paradigms derived from mesic systems are not always applicable to arid lands. My dissertation also highlights the unique ecology of ammonia oxidizers and draws attention to the importance of N cycling in desert soils.
ContributorsMarusenko, Yevgeniy (Author) / Hall, Sharon J (Thesis advisor) / Garcia-Pichel, Ferran (Thesis advisor) / Mclain, Jean E (Committee member) / Schwartz, Egbert (Committee member) / Arizona State University (Publisher)
Created2013
Description
The efficacy of deep brain stimulation (DBS) in Parkinson's disease (PD) has been convincingly demonstrated in studies that compare motor performance with and without stimulation, but characterization of performance at intermediate stimulation amplitudes has been limited. This study investigated the effects of changing DBS amplitude in order to assess dose-response characteristics, inter-subject variability, consistency of effect across outcome measures, and day-to-day variability. Eight subjects with PD and bilateral DBS systems were evaluated at their clinically determined stimulation (CDS) and at three reduced amplitude conditions: approximately 70%, 30%, and 0% of the CDS (MOD, LOW, and OFF, respectively). Overall symptom severity and performance on a battery of motor tasks - gait, postural control, single-joint flexion-extension, postural tremor, and tapping - were assessed at each condition using the motor section of the Unified Parkinson's Disease Rating Scale (UPDRS-III) and quantitative measures. Data were analyzed to determine whether subjects demonstrated a threshold response (one decrement in stimulation resulted in ≥ 70% of the maximum change) or a graded response to reduced stimulation. Day-to-day variability was assessed using the CDS data from the three testing sessions. Although the cohort as a whole demonstrated a graded response on several measures, there was high variability across subjects, with subsets exhibiting graded, threshold, or minimal responses. Some subjects experienced greater variability in their CDS performance across the three days than the change induced by reducing stimulation. For several tasks, a subset of subjects exhibited improved performance at one or more of the reduced conditions. Reducing stimulation did not affect all subjects equally, nor did it uniformly affect each subject's performance across tasks. These results indicate that altered recruitment of neural structures can differentially affect motor capabilities and demonstrate the need for clinical consideration of the effects on multiple symptoms across several days when selecting DBS parameters.
ContributorsConovaloff, Alison (Author) / Abbas, James (Thesis advisor) / Krishnamurthi, Narayanan (Committee member) / Mahant, Padma (Committee member) / Jung, Ranu (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2013