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
Brain-machine interfaces (BMIs) were first imagined as a technology that would allow subjects to have direct communication with prosthetics and external devices (e.g. control over a computer cursor or robotic arm movement). Operation of these devices was not automatic, and subjects needed calibration and training in order to master this

Brain-machine interfaces (BMIs) were first imagined as a technology that would allow subjects to have direct communication with prosthetics and external devices (e.g. control over a computer cursor or robotic arm movement). Operation of these devices was not automatic, and subjects needed calibration and training in order to master this control. In short, learning became a key component in controlling these systems. As a result, BMIs have become ideal tools to probe and explore brain activity, since they allow the isolation of neural inputs and systematic altering of the relationships between the neural signals and output. I have used BMIs to explore the process of brain adaptability in a motor-like task. To this end, I trained non-human primates to control a 3D cursor and adapt to two different perturbations: a visuomotor rotation, uniform across the neural ensemble, and a decorrelation task, which non-uniformly altered the relationship between the activity of particular neurons in an ensemble and movement output. I measured individual and population level changes in the neural ensemble as subjects honed their skills over the span of several days. I found some similarities in the adaptation process elicited by these two tasks. On one hand, individual neurons displayed tuning changes across the entire ensemble after task adaptation: most neurons displayed transient changes in their preferred directions, and most neuron pairs showed changes in their cross-correlations during the learning process. On the other hand, I also measured population level adaptation in the neural ensemble: the underlying neural manifolds that control these neural signals also had dynamic changes during adaptation. I have found that the neural circuits seem to apply an exploratory strategy when adapting to new tasks. Our results suggest that information and trajectories in the neural space increase after initially introducing the perturbations, and before the subject settles into workable solutions. These results provide new insights into both the underlying population level processes in motor learning, and the changes in neural coding which are necessary for subjects to learn to control neuroprosthetics. Understanding of these mechanisms can help us create better control algorithms, and design training paradigms that will take advantage of these processes.
ContributorsArmenta Salas, Michelle (Author) / Helms Tillery, Stephen I (Thesis advisor) / Si, Jennie (Committee member) / Buneo, Christopher (Committee member) / Santello, Marco (Committee member) / Kleim, Jeffrey (Committee member) / Arizona State University (Publisher)
Created2015
Description
The human hand relies on information from surrounding environment to distinguish objects based on qualities like size, texture, weight, and compliance. The size of an object can be determined from tactile feedback, proprioception, and visual feedback. This experiment aims to determine the accuracy of size discrimination in physical and virtual

The human hand relies on information from surrounding environment to distinguish objects based on qualities like size, texture, weight, and compliance. The size of an object can be determined from tactile feedback, proprioception, and visual feedback. This experiment aims to determine the accuracy of size discrimination in physical and virtual objects using proprioceptive and tactile feedback. Using both senses will help determine how much proprioceptive and tactile feedback plays a part in discriminating small size variations and whether replacing a missing sensation will increase the subject's accuracy. Ultimately, determining the specific contributions of tactile and proprioceptive feedback mechanisms during object manipulation is important in order to give prosthetic hand users the ability of stereognosis among other manipulation tasks. Two different experiments using physical and virtual objects were required to discover the roles of tactile and proprioceptive feedback. Subjects were asked to compare the size of one block to a previous object. The blocks increased in size by two millimeter increments and were randomized in order to determine whether subjects could correctly identify if a box was smaller, larger, or the same size as the previous box. In the proprioceptive experiment subjects had two sub-sets of experiments each with a different non-tactile cue. The experiment demonstrated that subjects performed better with physical objects compared to virtual objects. This suggests that size discrimination is possible in the absence of tactile feedback, but tactile input is necessary for accuracy in small size discrimination.
ContributorsFrear, Darcy Lynn (Author) / Helms Tillery, Stephen (Thesis director) / Buneo, Christopher (Committee member) / Overstreet, Cynthia (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2013-05