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- Genre: Doctoral Dissertation
Description
Humans' ability to perform fine object and tool manipulation is a defining feature of their sensorimotor repertoire. How the central nervous system builds and maintains internal representations of such skilled hand-object interactions has attracted significant attention over the past three decades. Nevertheless, two major gaps exist: a) how digit positions and forces are coordinated during natural manipulation tasks, and b) what mechanisms underlie the formation and retention of internal representations of dexterous manipulation. This dissertation addresses these two questions through five experiments that are based on novel grip devices and experimental protocols. It was found that high-level representation of manipulation tasks can be learned in an effector-independent fashion. Specifically, when challenged by trial-to-trial variability in finger positions or using digits that were not previously engaged in learning the task, subjects could adjust finger forces to compensate for this variability, thus leading to consistent task performance. The results from a follow-up experiment conducted in a virtual reality environment indicate that haptic feedback is sufficient to implement the above coordination between digit position and forces. However, it was also found that the generalizability of a learned manipulation is limited across tasks. Specifically, when subjects learned to manipulate the same object across different contexts that require different motor output, interference was found at the time of switching contexts. Data from additional studies provide evidence for parallel learning processes, which are characterized by different rates of decay and learning. These experiments have provided important insight into the neural mechanisms underlying learning and control of object manipulation. The present findings have potential biomedical applications including brain-machine interfaces, rehabilitation of hand function, and prosthetics.
ContributorsFu, Qiushi (Author) / Santello, Marco (Thesis advisor) / Helms Tillery, Stephen (Committee member) / Buneo, Christopher (Committee member) / Santos, Veronica (Committee member) / Artemiadis, Panagiotis (Committee member) / Arizona State University (Publisher)
Created2013
Description
Sensory gating is a process by which the nervous system preferentially admits stimuli that are important for the organism while filtering out those that may be meaningless. An optimal sensory gate cannot be static or inflexible, but rather plastic and informed by past experiences. Learning enables sensory gates to recognize stimuli that are emotionally salient and potentially predictive of positive or negative outcomes essential to survival. Olfaction is the only sensory modality in mammals where sensory inputs bypass conventional thalamic gating before entering higher emotional or cognitive brain regions. Thus, olfactory bulb circuits may have a heavier burden of sensory gating compared to other primary sensory circuits. How do the primary synapses in an olfactory system "learn"' in order to optimally gate or filter sensory stimuli? I hypothesize that centrifugal neuromodulator serotonin serves as a signaling mechanism by which primary olfactory circuits can experience learning informed sensory gating. To test my hypothesis, I conditioned genetically-modified mice using reward or fear olfactory-cued learning paradigms and used pharmacological, electrophysiological, immunohistochemical, and optical imaging approaches to assay changes in serotonin signaling or functional changes in primary olfactory circuits. My results indicate serotonin is a key mediator in the acquisition of olfactory fear memories through the activation of its type 2A receptors in the olfactory bulb. Functionally within the first synaptic relay of olfactory glomeruli, serotonin type 2A receptor activation decreases excitatory glutamatergic drive of olfactory sensory neurons through both presynaptic and postsynaptic mechanisms. I propose that serotonergic signaling decreases excitatory drive, thereby disconnecting olfactory sensory neurons from odor responses once information is learned and its behavioral significance is consolidated. I found that learning induced chronic changes in the density of serotonin fibers and receptors, which persisted in glomeruli encoding the conditioning odor. Such persistent changes could represent a sensory gate stabilized by memory. I hypothesize this ensures that the glomerulus encoding meaningful odors are much more sensitive to future serotonin signaling as such arousal cues arrive from centrifugal pathways originating in the dorsal raphe nucleus. The results advocate that a simple associative memory trace can be formed at primary sensory synapses to facilitate optimal sensory gating in mammalian olfaction.
ContributorsLi, Monica (Author) / Tyler, William J (Thesis advisor) / Smith, Brian H. (Thesis advisor) / Duch, Carsten (Committee member) / Neisewander, Janet (Committee member) / Vu, Eric (Committee member) / Arizona State University (Publisher)
Created2012
Description
To address the need of scientists and engineers in the United States workforce and ensure that students in higher education become scientifically literate, research and policy has called for improvements in undergraduate education in the sciences. One particular pathway for improving undergraduate education in the science fields is to reform undergraduate teaching. Only a limited number of studies have explored the pedagogical content knowledge of postsecondary level teachers. This study was conducted to characterize the PCK of biology faculty and explore the factors influencing their PCK. Data included semi-structured interviews, classroom observations, documents, and instructional artifacts. A qualitative inquiry was designed to conduct an in-depth investigation focusing on the PCK of six biology instructors, particularly the types of knowledge they used for teaching biology, their perceptions of teaching, and the social interactions and experiences that influenced their PCK. The findings of this study reveal that the PCK of the biology faculty included eight domains of knowledge: (1) content, (2) context, (3) learners and learning, (4) curriculum, (5) instructional strategies, (6) representations of biology, (7) assessment, and (8) building rapport with students. Three categories of faculty PCK emerged: (1) PCK as an expert explainer, (2) PCK as an instructional architect, and (3) a transitional PCK, which fell between the two prior categories. Based on the interpretations of the data, four social interactions and experiences were found to influence biology faculty PCK: (1) teaching experience, (2) models and mentors, (3) collaborations about teaching, and (4) science education research. The varying teaching perspectives of the faculty also influenced their PCK. This study shows that the PCK of biology faculty for teaching large introductory courses at large research institutions is heavily influenced by factors beyond simply years of teaching experience and expert content knowledge. Social interactions and experiences created by the institution play a significant role in developing the PCK of biology faculty.
ContributorsHill, Kathleen M. (Author) / Luft, Julie A. (Thesis advisor) / Baker, Dale (Committee member) / Orchinik, Miles (Committee member) / Arizona State University (Publisher)
Created2013
Description
Intracortical microstimulation (ICMS) within somatosensory cortex can produce artificial sensations including touch, pressure, and vibration. There is significant interest in using ICMS to provide sensory feedback for a prosthetic limb. In such a system, information recorded from sensors on the prosthetic would be translated into electrical stimulation and delivered directly to the brain, providing feedback about features of objects in contact with the prosthetic. To achieve this goal, multiple simultaneous streams of information will need to be encoded by ICMS in a manner that produces robust, reliable, and discriminable sensations. The first segment of this work focuses on the discriminability of sensations elicited by ICMS within somatosensory cortex. Stimulation on multiple single electrodes and near-simultaneous stimulation across multiple electrodes, driven by a multimodal tactile sensor, were both used in these experiments. A SynTouch BioTac sensor was moved across a flat surface in several directions, and a subset of the sensor's electrode impedance channels were used to drive multichannel ICMS in the somatosensory cortex of a non-human primate. The animal performed a behavioral task during this stimulation to indicate the discriminability of sensations evoked by the electrical stimulation. The animal's responses to ICMS were somewhat inconsistent across experimental sessions but indicated that discriminable sensations were evoked by both single and multichannel ICMS. The factors that affect the discriminability of stimulation-induced sensations are not well understood, in part because the relationship between ICMS and the neural activity it induces is poorly defined. The second component of this work was to develop computational models that describe the populations of neurons likely to be activated by ICMS. Models of several neurons were constructed, and their responses to ICMS were calculated. A three-dimensional cortical model was constructed using these cell models and used to identify the populations of neurons likely to be recruited by ICMS. Stimulation activated neurons in a sparse and discontinuous fashion; additionally, the type, number, and location of neurons likely to be activated by stimulation varied with electrode depth.
ContributorsOverstreet, Cynthia K (Author) / Helms Tillery, Stephen I (Thesis advisor) / Santos, Veronica (Committee member) / Buneo, Christopher (Committee member) / Otto, Kevin (Committee member) / Santello, Marco (Committee member) / Arizona State University (Publisher)
Created2013
Description
Consideration of both biological and human-use dynamics in coupled social-ecological systems is essential for the success of interventions such as marine reserves. As purely human institutions, marine reserves have no direct effects on ecological systems. Consequently, the success of a marine reserve depends on managers` ability to alter human behavior in the direction and magnitude that supports reserve objectives. Further, a marine reserve is just one component in a larger coupled social-ecological system. The social, economic, political, and biological landscape all determine the social acceptability of a reserve, conflicts that arise, how the reserve interacts with existing fisheries management, accuracy of reserve monitoring, and whether the reserve is ultimately able to meet conservation and fishery enhancement goals. Just as the social-ecological landscape is critical at all stages for marine reserve, from initial establishment to maintenance, the reserve in turn interacts with biological and human use dynamics beyond its borders. Those interactions can lead to the failure of a reserve to meet management goals, or compromise management goals outside the reserve. I use a bio-economic model of a fishery in a spatially patchy environment to demonstrate how the pre-reserve fisheries management strategy determines the pattern of fishing effort displacement once the reserve is established, and discuss the social, political, and biological consequences of different patterns for the reserve and the fishery. Using a stochastic bio-economic model, I demonstrate how biological and human use connectivity can confound the accurate detection of reserve effects by violating assumptions in the quasi-experimental framework. Finally, I examine data on recreational fishing site selection to investigate changes in response to the announcement of enforcement of a marine reserve in the Gulf of California, Mexico. I generate a scale of fines that would fully or partially protect the reserve, providing a data-driven way for managers to balance biological and socio-economic goals. I suggest that natural resource managers consider human use dynamics with the same frequency, rigor, and tools as they do biological stocks.
ContributorsFujitani, Marie (Author) / Abbott, Joshua (Thesis advisor) / Fenichel, Eli (Thesis advisor) / Gerber, Leah (Committee member) / Anderies, John (Committee member) / Arizona State University (Publisher)
Created2014
Description
Mathematical modeling of infectious diseases can help public health officials to make decisions related to the mitigation of epidemic outbreaks. However, over or under estimations of the morbidity of any infectious disease can be problematic. Therefore, public health officials can always make use of better models to study the potential implication of their decisions and strategies prior to their implementation. Previous work focuses on the mechanisms underlying the different epidemic waves observed in Mexico during the novel swine origin influenza H1N1 pandemic of 2009 and showed extensions of classical models in epidemiology by adding temporal variations in different parameters that are likely to change during the time course of an epidemic, such as, the influence of media, social distancing, school closures, and how vaccination policies may affect different aspects of the dynamics of an epidemic. This current work further examines the influence of different factors considering the randomness of events by adding stochastic processes to meta-population models. I present three different approaches to compare different stochastic methods by considering discrete and continuous time. For the continuous time stochastic modeling approach I consider the continuous-time Markov chain process using forward Kolmogorov equations, for the discrete time stochastic modeling I consider stochastic differential equations using Wiener's increment and Poisson point increments, and also I consider the discrete-time Markov chain process. These first two stochastic modeling approaches will be presented in a one city and two city epidemic models using, as a base, our deterministic model. The last one will be discussed briefly on a one city SIS and SIR-type model.
ContributorsCruz-Aponte, Maytee (Author) / Wirkus, Stephen A. (Thesis advisor) / Castillo-Chavez, Carlos (Thesis advisor) / Camacho, Erika T. (Committee member) / Kang, Yun (Committee member) / Arizona State University (Publisher)
Created2014
Description
Advances in implantable MEMS technology has made possible adaptive micro-robotic implants that can track and record from single neurons in the brain. Development of autonomous neural interfaces opens up exciting possibilities of micro-robots performing standard electrophysiological techniques that would previously take researchers several hundred hours to train and achieve the desired skill level. It would result in more reliable and adaptive neural interfaces that could record optimal neural activity 24/7 with high fidelity signals, high yield and increased throughput. The main contribution here is validating adaptive strategies to overcome challenges in autonomous navigation of microelectrodes inside the brain. The following issues pose significant challenges as brain tissue is both functionally and structurally dynamic: a) time varying mechanical properties of the brain tissue-microelectrode interface due to the hyperelastic, viscoelastic nature of brain tissue b) non-stationarities in the neural signal caused by mechanical and physiological events in the interface and c) the lack of visual feedback of microelectrode position in brain tissue. A closed loop control algorithm is proposed here for autonomous navigation of microelectrodes in brain tissue while optimizing the signal-to-noise ratio of multi-unit neural recordings. The algorithm incorporates a quantitative understanding of constitutive mechanical properties of soft viscoelastic tissue like the brain and is guided by models that predict stresses developed in brain tissue during movement of the microelectrode. An optimal movement strategy is developed that achieves precise positioning of microelectrodes in the brain by minimizing the stresses developed in the surrounding tissue during navigation and maximizing the speed of movement. Results of testing the closed-loop control paradigm in short-term rodent experiments validated that it was possible to achieve a consistently high quality SNR throughout the duration of the experiment. At the systems level, new generation of MEMS actuators for movable microelectrode array are characterized and the MEMS device operation parameters are optimized for improved performance and reliability. Further, recommendations for packaging to minimize the form factor of the implant; design of device mounting and implantation techniques of MEMS microelectrode array to enhance the longevity of the implant are also included in a top-down approach to achieve a reliable brain interface.
ContributorsAnand, Sindhu (Author) / Muthuswamy, Jitendran (Thesis advisor) / Tillery, Stephen H (Committee member) / Buneo, Christopher (Committee member) / Abbas, James (Committee member) / Tsakalis, Konstantinos (Committee member) / Arizona State University (Publisher)
Created2013
Description
This work is an assemblage of three applied projects that address the institutional and spatial constraints to managing threatened and endangered (T & E) terrestrial species. The first project looks at the role of the Endangered Species Act (ESA) in protecting wildlife and whether banning non–conservation activities on multi-use federal lands is socially optimal. A bioeconomic model is used to identify scenarios where ESA–imposed regulations emerge as optimal strategies and to facilitate discussion on feasible long–term strategies in light of the ongoing public land–use debate. Results suggest that banning harmful activities is a preferred strategy when valued species are in decline or exposed to poor habitat quality. However such a strategy cannot be sustained in perpetuity, a switch to land–use practices characteristic of habitat conservation plans is recommended. The spatial portion of this study is motivated by the need for a more systematic quantification and assessment of landscape structure ahead of species reintroduction; this portion is further broken up into two parts. The first explores how connectivity between habitat patches promotes coexistence among multiple interacting species. An agent–based model of a two–patch metapopulation is developed with local predator–prey dynamics and density–dependent dispersal. The simulation experiment suggests that connectivity levels at both extremes, representing very little risk and high risk of species mortality, do not augment the likelihood of coexistence while intermediate levels do. Furthermore, the probability of coexistence increases and spans a wide range of connectivity levels when individual dispersal is less probabilistic and more dependent on population feedback. Second, a novel approach to quantifying network structure is developed using the statistical method of moments. This measurement framework is then used to index habitat networks and assess their capacity to drive three main ecological processes: dispersal, survival, and coexistence. Results indicate that the moments approach outperforms single summary metrics and accounts for a majority of the variation in process outcomes. The hierarchical measurement scheme is helpful for indicating when additional structural information is needed to determine ecological function. However, the qualitative trend between network indicator and function is, at times, unintuitive and unstable in certain areas of the metric space.
ContributorsSalau, Kehinde Rilwan, 1985- (Author) / Janssen, Marco A (Thesis advisor) / Fenichel, Eli P (Thesis advisor) / Anderies, John M (Committee member) / Abbott, Joshua K (Committee member) / Arizona State University (Publisher)
Created2013
Description
Colorful ornaments in animals often serve as sexually selected signals of quality. While pigment-based colors are well-studied in these regards, structural colors that result from the interaction of light with photonic nanostructures are comparatively understudied in terms of their consequences in social contexts, their costs of production, and even the best way to measure them. Iridescent colors are some of the most brilliant and conspicuous colors in nature, and I studied the measurement, condition-dependence, and signaling role of iridescence in Anna's hummingbirds (Calypte anna). While most animal colors are easily quantified using well-established spectrophotometric techniques, the unique characteristics of iridescent colors present challenges to measurement and opportunities to quantify novel color metrics. I designed and tested an apparatus for careful control and measurement of viewing geometry and highly repeatable measurements. These measurements could be used to accurately characterize individual variation in iridescent Anna's hummingbirds to examine their condition-dependence and signaling role. Next, I examined the literature published to date for evidence of condition-dependence of structural colors in birds. Using meta-analyses, I found that structural colors of all three types - white, ultra-violet/blue, and iridescence - are significantly condition-dependent, meaning that they can convey information about quality to conspecifics. I then investigated whether iridescent colors were condition-dependent in Anna's hummingbirds both in a field correlational study and in an experimental study. Throughout the year, I found that iridescent feathers in both male and female Anna's hummingbirds become less brilliant as they age. Color was not correlated with body condition in any age/sex group. However, iridescent coloration in male Anna's hummingbirds was significantly affected by experimental protein in the diet during feather growth, indicating that iridescent color may signal diet quality. Finally, I examined how iridescent colors were used to mediate social competitions in male and female Anna's hummingbirds. Surprisingly, males that were less colorful won significantly more contests than more colorful males, and colorful males received more aggression. Less colorful males may be attempting to drive away colorful neighbors that may be preferred mates. Female iridescent ornament size and color was highly variable, but did not influence contest outcomes or aggression.
ContributorsMeadows, Melissa (Author) / McGraw, Kevin J. (Thesis advisor) / Rutowski, Ronald L (Committee member) / Sabo, John L (Committee member) / Alcock, John (Committee member) / Deviche, Pierre (Committee member) / Arizona State University (Publisher)
Created2012
Description
This research investigated using impedance as a minimally invasive oral cancer-screening tool by modeling healthy and diseased tissue. This research developed an ultra-structurally based tissue model for oral mucosa that is versatile enough to be easily modified to mimic the passive electrical impedance responses of multiple benign and cancerous tissue types. This new model provides answers to biologically meaningful questions related to the impedance response of healthy and diseased tissues. This model breaks away from the old empirical top down "black box" Thèvinin equivalent model. The new tissue model developed here was created from a bottom up perspective resulting in a model that is analogous to having a "Transparent Box" where each network element relating to a specific structural component is known. This new model was developed starting with sub cellular ultra-structural components such as membranes, proteins and electrolytes. These components formed the basic network elements and topology of the organelles. The organelle networks combine to form the cell networks. The cell networks combine to make networks of cell layers and the cell layers were combined into tissue networks. This produced the complete "Transparent Box" model for normal tissue. This normal tissue model was modified for disease based on the ultra-structural pathology of each disease. The diseased tissues evaluated include cancers type one through type three; necrotic-inflammation, hyperkeratosis and the compound condition of hyperkeratosis over cancer type two. The impedance responses for each of the disease were compared side by side with the response of normal healthy tissue. Comparative evidence from the models showed the structural changes in cancer produce a unique identifiable impedance "finger print." The evaluation of the "Transparent Box" model for normal tissues and diseased tissues show clear support for using comparative impedance measurements as a clinical tool for oral cancer screening.
ContributorsPelletier, Peter Robert (Author) / Kozicki, Michael (Thesis advisor) / Towe, Bruce (Committee member) / Saraniti, Marco (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2012