This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students. 

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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

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
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Description
Lower-limb prosthesis users have commonly-recognized deficits in gait and posture control. However, existing methods in balance and mobility analysis fail to provide sufficient sensitivity to detect changes in prosthesis users' postural control and mobility in response to clinical intervention or experimental manipulations and often fail to detect differences between prosthesis

Lower-limb prosthesis users have commonly-recognized deficits in gait and posture control. However, existing methods in balance and mobility analysis fail to provide sufficient sensitivity to detect changes in prosthesis users' postural control and mobility in response to clinical intervention or experimental manipulations and often fail to detect differences between prosthesis users and non-amputee control subjects. This lack of sensitivity limits the ability of clinicians to make informed clinical decisions and presents challenges with insurance reimbursement for comprehensive clinical care and advanced prosthetic devices. These issues have directly impacted clinical care by restricting device options, increasing financial burden on clinics, and limiting support for research and development. This work aims to establish experimental methods and outcome measures that are more sensitive than traditional methods to balance and mobility changes in prosthesis users. Methods and analysis techniques were developed to probe aspects of balance and mobility control that may be specifically impacted by use of a prosthesis and present challenges similar to those experienced in daily life that could improve the detection of balance and mobility changes. Using the framework of cognitive resource allocation and dual-tasking, this work identified unique characteristics of prosthesis users’ postural control and developed sensitive measures of gait variability. The results also provide broader insight into dual-task analysis and the motor-cognitive response to demanding conditions. Specifically, this work identified altered motor behavior in prosthesis users and high cognitive demand of using a prosthesis. The residual standard deviation method was developed and demonstrated to be more effective than traditional gait variability measures at detecting the impact of dual-tasking. Additionally, spectral analysis of the center of pressure while standing identified altered somatosensory control in prosthesis users. These findings provide a new understanding of prosthetic use and new, highly sensitive techniques to assess balance and mobility in prosthesis users.
ContributorsHoward, Charla Lindley (Author) / Abbas, James (Thesis advisor) / Buneo, Christopher (Committee member) / Lynskey, Jim (Committee member) / Santello, Marco (Committee member) / Artemiadis, Panagiotis (Committee member) / Arizona State University (Publisher)
Created2017
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Description
Object manipulation is a common sensorimotor task that humans perform to interact with the physical world. The first aim of this dissertation was to characterize and identify the role of feedback and feedforward mechanisms for force control in object manipulation by introducing a new feature based on force trajectories to

Object manipulation is a common sensorimotor task that humans perform to interact with the physical world. The first aim of this dissertation was to characterize and identify the role of feedback and feedforward mechanisms for force control in object manipulation by introducing a new feature based on force trajectories to quantify the interaction between feedback- and feedforward control. This feature was applied on two grasp contexts: grasping the object at either (1) predetermined or (2) self-selected grasp locations (“constrained” and “unconstrained”, respectively), where unconstrained grasping is thought to involve feedback-driven force corrections to a greater extent than constrained grasping. This proposition was confirmed by force feature analysis. The second aim of this dissertation was to quantify whether force control mechanisms differ between dominant and non-dominant hands. The force feature analysis demonstrated that manipulation by the dominant hand relies on feedforward control more than the non-dominant hand. The third aim was to quantify coordination mechanisms underlying physical interaction by dyads in object manipulation. The results revealed that only individuals with worse solo performance benefit from interpersonal coordination through physical couplings, whereas the better individuals do not. This work showed that naturally emerging leader-follower roles, whereby the leader in dyadic manipulation exhibits significant greater force changes than the follower. Furthermore, brain activity measured through electroencephalography (EEG) could discriminate leader and follower roles as indicated power modulation in the alpha frequency band over centro-parietal areas. Lastly, this dissertation suggested that the relation between force and motion (arm impedance) could be an important means for communicating intended movement direction between biological agents.
ContributorsMojtahedi, Keivan (Author) / Santello, Marco (Thesis advisor) / Greger, Bradley (Committee member) / Artemiadis, Panagiotis (Committee member) / Helms Tillery, Stephen (Committee member) / Buneo, Christopher (Committee member) / Arizona State University (Publisher)
Created2017
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Description
Neural interfacing applications have advanced in complexity, with needs for increasingly high degrees of freedom in prosthetic device control, sharper discrimination in sensory percepts in bidirectional interfaces, and more precise localization of functional connectivity in the brain. As such, there is a growing need for reliable neurophysiological recordings at a

Neural interfacing applications have advanced in complexity, with needs for increasingly high degrees of freedom in prosthetic device control, sharper discrimination in sensory percepts in bidirectional interfaces, and more precise localization of functional connectivity in the brain. As such, there is a growing need for reliable neurophysiological recordings at a fine spatial scale matching that of cortical columnar processing. Penetrating microelectrodes provide localization sufficient to isolate action potential (AP) waveforms, but often suffer from recorded signal deterioration linked to foreign body response. Micro-Electrocorticography (μECoG) surface electrodes elicit lower foreign body response and show greater chronic stability of recorded signals, though they typically lack the signal localization necessary to isolate individual APs. This dissertation validates the recording capacity of a novel, flexible, large area μECoG array with bilayer routing in a feline implant, and explores the ability of conventional μECoG arrays to detect features of neuronal activity in a very high frequency band associated with AP waveforms.

Recordings from both layers of the flexible μECoG array showed frequency features typical of cortical local field potentials (LFP) and were shown to be stable in amplitude over time. Recordings from both layers also showed consistent, frequency-dependent modulation after induction of general anesthesia, with large increases in beta and gamma band and decreases in theta band observed over three experiments. Recordings from conventional μECoG arrays over human cortex showed robust modulation in a high frequency (250-2000 Hz) band upon production of spoken words. Modulation in this band was used to predict spoken words with over 90% accuracy. Basal Ganglia neuronal AP firing was also shown to significantly correlate with various cortical μECoG recordings in this frequency band. Results indicate that μECoG surface electrodes may detect high frequency neuronal activity potentially associated with AP firing, a source of information previously unutilized by these devices.
ContributorsBarton, Cody David (Author) / Greger, Bradley (Thesis advisor, Committee member) / Santello, Marco (Committee member) / Buneo, Christopher (Committee member) / Graudejus, Oliver (Committee member) / Artemiadis, Panagiotis (Committee member) / Arizona State University (Publisher)
Created2018