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- Creators: Barrett, The Honors College
- Status: Published
Model Based Automatic and Robust Spike Sorting for Large Volumes of Multi-channel Extracellular Data
Description
Spike sorting is a critical step for single-unit-based analysis of neural activities extracellularly and simultaneously recorded using multi-channel electrodes. When dealing with recordings from very large numbers of neurons, existing methods, which are mostly semiautomatic in nature, become inadequate.
This dissertation aims at automating the spike sorting process. A high performance, automatic and computationally efficient spike detection and clustering system, namely, the M-Sorter2 is presented. The M-Sorter2 employs the modified multiscale correlation of wavelet coefficients (MCWC) for neural spike detection. At the center of the proposed M-Sorter2 are two automatic spike clustering methods. They share a common hierarchical agglomerative modeling (HAM) model search procedure to strategically form a sequence of mixture models, and a new model selection criterion called difference of model evidence (DoME) to automatically determine the number of clusters. The M-Sorter2 employs two methods differing by how they perform clustering to infer model parameters: one uses robust variational Bayes (RVB) and the other uses robust Expectation-Maximization (REM) for Student’s 𝑡-mixture modeling. The M-Sorter2 is thus a significantly improved approach to sorting as an automatic procedure.
M-Sorter2 was evaluated and benchmarked with popular algorithms using simulated, artificial and real data with truth that are openly available to researchers. Simulated datasets with known statistical distributions were first used to illustrate how the clustering algorithms, namely REMHAM and RVBHAM, provide robust clustering results under commonly experienced performance degrading conditions, such as random initialization of parameters, high dimensionality of data, low signal-to-noise ratio (SNR), ambiguous clusters, and asymmetry in cluster sizes. For the artificial dataset from single-channel recordings, the proposed sorter outperformed Wave_Clus, Plexon’s Offline Sorter and Klusta in most of the comparison cases. For the real dataset from multi-channel electrodes, tetrodes and polytrodes, the proposed sorter outperformed all comparison algorithms in terms of false positive and false negative rates. The software package presented in this dissertation is available for open access.
This dissertation aims at automating the spike sorting process. A high performance, automatic and computationally efficient spike detection and clustering system, namely, the M-Sorter2 is presented. The M-Sorter2 employs the modified multiscale correlation of wavelet coefficients (MCWC) for neural spike detection. At the center of the proposed M-Sorter2 are two automatic spike clustering methods. They share a common hierarchical agglomerative modeling (HAM) model search procedure to strategically form a sequence of mixture models, and a new model selection criterion called difference of model evidence (DoME) to automatically determine the number of clusters. The M-Sorter2 employs two methods differing by how they perform clustering to infer model parameters: one uses robust variational Bayes (RVB) and the other uses robust Expectation-Maximization (REM) for Student’s 𝑡-mixture modeling. The M-Sorter2 is thus a significantly improved approach to sorting as an automatic procedure.
M-Sorter2 was evaluated and benchmarked with popular algorithms using simulated, artificial and real data with truth that are openly available to researchers. Simulated datasets with known statistical distributions were first used to illustrate how the clustering algorithms, namely REMHAM and RVBHAM, provide robust clustering results under commonly experienced performance degrading conditions, such as random initialization of parameters, high dimensionality of data, low signal-to-noise ratio (SNR), ambiguous clusters, and asymmetry in cluster sizes. For the artificial dataset from single-channel recordings, the proposed sorter outperformed Wave_Clus, Plexon’s Offline Sorter and Klusta in most of the comparison cases. For the real dataset from multi-channel electrodes, tetrodes and polytrodes, the proposed sorter outperformed all comparison algorithms in terms of false positive and false negative rates. The software package presented in this dissertation is available for open access.
ContributorsMa, Weichao (Author) / Si, Jennie (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / He, Jingrui (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2019
Description
The purpose of this paper is to understand how companies are finding high potential employees and if they are leaving top talent behind in their approach. Eugene Burke stated in 2014 that 55% of employees that are labeled as a High Potential Employee will turn over and move companies. Burke (2014) also states that the average high potential employee tenure is five years. The Corporate Leadership Council says that on average, 27% of a company's development budget is spent on its high potential program (CEB 2017). For a midsize company, the high potential development budget is almost a million dollars for only a handful of employees, only to see half of the investment walking out the door to another company . Furthermore, the Corporate Leadership Council said that a study done in 2005 revealed that 50% of high potential employees had significant problems within their job (Kotlyar and Karkowsky 2014). Are time and resources are being given to the wrong employees and the right employees are being overlooked? This paper exams how companies traditionally select high potential employees and where companies are potentially omitting employees who would be better suited for the program. This paper proposes that how a company discovers their top talent will correlate to the number of turnovers or struggles that a high potential employee has on their job. Future research direction and practical considerations are also presented in this paper.
ContributorsHarrison, Carrie (Author) / Mizzi, Philip (Thesis director) / Ruediger, Stefan (Committee member) / Department of Management and Entrepreneurship (Contributor) / School of Sustainability (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The purpose of this research is to explore Latina/o students' involvement at Arizona State University West and how it affects their sense of belonging, and thereby, their retention. I operationalize a "sense of belonging" as being able to express and feel comfortable with one's ethnic identity in the context of a higher education institution (Hurtado, 1997). I operationalize student involvement by the extent to which an individual student is devoted to their academic experience, invests time studying on campus, participates in student organizations, and interacts with faculty and their peers (Astin, 1984). I draw from Astin's theory of student involvement and Hurtado's sense of belonging as a base for this inquiry because they are critical components to understanding retention among the Latino/a community at Arizona State University West.
ContributorsGuerra, Luis D. (Author) / Cuadraz, Gloria (Thesis director) / Aska, Cassandra (Committee member) / School of Social and Behavioral Sciences (Contributor) / School of Humanities, Arts, and Cultural Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Researchers suggests that college students' involvement and use of resources on campus are important for success, in the form of satisfaction and GPA, in the first year. College officials invest substantial resources in activities to encourage freshmen students to become involved in campus activities and utilize resources that promote successful outcomes, yet we do not know which activities best relate to success. Using a self-report survey, we sought to corroborate previous research that has shown that overall levels of involvement and use of resources relate to satisfaction/GPA. Furthermore, we disentangled which individual types of involvement and use of resources are most highly correlated with satisfaction and GPA. And finally, we identified the barriers and benefits to involvement and resource use, according to the students themselves. We found evidence that higher levels of involvement were related to satisfaction and attending faculty office hours appears to be particularly important, given a significant relation to both satisfaction and GPA. Implications for program promotion and resource allocation are discussed.
ContributorsPaley, Madeleine (Author) / Foster, Stacie (Thesis director) / Spinrad, Tracy (Committee member) / Sanford School of Social and Family Dynamics (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
Buck converters are a class of switched-mode power converters often used to step down DC input voltages to a lower DC output voltage. These converters naturally produce a current and voltage ripple at their output due to their switching action. Traditional methods of reducing this ripple have involved adding large discrete inductors and capacitors to filter the ripple, but large discrete components cannot be integrated onto chips. As an alternative to using passive filtering components, this project investigates the use of active ripple cancellation to reduce the peak output ripple. Hysteretic controlled buck converters were chosen for their simplicity of design and fast transient response. The proposed cancellation circuits sense the output ripple of the buck converter and inject an equal ripple exactly out of phase with the sensed ripple. Both current-mode and voltage-mode feedback loops are simulated, and the effectiveness of each cancellation circuit is examined. Results show that integrated active ripple cancellation circuits offer a promising substitute for large discrete filters.
ContributorsWang, Ziyan (Author) / Bakkaloglu, Bertan (Thesis director) / Kitchen, Jennifer (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
This project seeks to investigate the ways in which the W.P. Carey School of Business, at Arizona State University, can improve student retention and engagement efforts. The analysis is being completed through an audit of the business school's current efforts towards student engagement, an examination of the internal and external environments of business schools across the nation, and a review of scholarly data/research on student retention risk factors and methods for improving engagement. The study highlights what exactly contributes to the success of the W.P. Carey School of Business, concluding with recommendations for how its engagement and retention efforts can be further improved to continue to serve students at a nationally ranked level.
ContributorsStinger, Rio W. (Author) / Hillman, Amy (Thesis director) / Mader, Michael (Committee member) / Division of Teacher Preparation (Contributor) / Department of Management (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Sex trafficking in the United States is an enormous illegal underground business economy that involves the sexual exploitation of many persons. Due to the large nature of the sex trafficking business and the many different types of sex trafficking, it is helpful for social workers, government agencies, and activists to understand the intricacies of the various types of sex trafficking. This research focused on determining the human resources business structures behind pimp businesses that relied on mental coercion of the victim. The data source used, Pimpfeet.com—an online pimp authored blog—provided data from actual pimps on their business practices that were analyzed to determine trends in recruitment and retention. These trends were compared to human resource management theories from business literature to determine to what extent, or if at all, a pimp’s business recruited and retained workers in a way that was similar to how a legal business would, according to human resources strategies. The data extracted from Pimpfeet.com and used in this study consisted of 69 pimp quotes that were put into three recruitment categories and five retention categories based on human resource management literature in order to see which categories were used for recruitment and retention by pimps. This study found that pimp recruitment and retention followed, to some extent, the same models described in the human resource management literature, with slight modifications. This study showed that job embeddedness theory (Holtom, Mitchel and Lee, 2009) was able to explain much of why sex trafficking victims are retained so well by pimps since they are so embedded in the prostitution lifestyle. These findings show the different business techniques that pimps use for recruitment and retention of sex workers and are useful for understanding how a social worker, government entity or an activist can combat these forces to help remove victims from a pimp’s control, or keep victims from getting recruited in the first place. Further areas of research related to this topic were suggested.
ContributorsRivera, Kameron (Co-author) / La Benz, Alexis (Co-author) / Roe-Sepowitz, Dominique (Thesis director) / Corley, Kevin (Committee member) / W. P. Carey School of Business (Contributor) / Chemical Engineering Program (Contributor) / T. Denny Sanford School of Social and Family Dynamics (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
This project was centered around designing a processor model (using the C programming language) based on the Coldfire computer architecture that will run on third party software known as Open Virtual Platforms. The end goal is to have a fully functional processor that can run Coldfire instructions and utilize peripheral devices in the same way as the hardware used in the embedded systems lab at ASU. This project would cut down the substantial amount of time students spend commuting to the lab. Having the processor directly at their disposal would also encourage them to spend more time outside of class learning the hardware and familiarizing themselves with development on an embedded micro-controller. The model will be accurate, fast and reliable. These aspects will be achieved through rigorous unit testing and use of the OVP platform which provides instruction accurate simulations at hundreds of MIPS (million instructions per second) for the specified model. The end product was able to accurately simulate a subset of the Coldfire instructions at very high rates.
ContributorsDunning, David Connor (Author) / Burger, Kevin (Thesis director) / Meuth, Ryan (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2014-12
Description
In this paper, it is determined that learning retention decreases with age and there is a linear rate of decrease. In this study, four male Long-Evans Rats were used. The rats were each trained in 4 different tasks throughout their lifetime, using a food reward as motivation to work. Rats were said to have learned a task at the age when they received the highest accuracy during a task. A regression of learning retention was created for the set of studied rats: Learning Retention = 112.9 \u2014 0.085919 x (Age at End of Task), indicating that learning retention decreases at a linear rate, although rats have different rates of decrease of learning retention. The presence of behavioral training was determined not to have a positive impact on this rate. In behavioral studies, there were statistically significant differences between timid/outgoing and large ball ability between W12 and Z12. Rat W12 had overall better learning retention and also was more compliant, did not resist being picked up and traveled more frequently at high speeds (in the large ball) than Z12. Further potential studies include implanting an electrode into the frontal cortex in order to compare neuro feedback with learning retention, and using human subjects to find the rate of decrease in learning retention. The implication of this study, if also true for human subjects, is that older persons may need enhanced training or additional refresher training in order to retain information that is learned at a later age.
ContributorsSpinrad, Amelia (Author) / Si, Jennie (Thesis director) / Thompson, Patrick (Committee member) / Ma, Weichao (Committee member) / Barrett, The Honors College (Contributor)
Created2014-05
Description
Students across the United States lack the necessary skills to be successful college students in Science, Technology and Math (STEM) majors and as a result post-secondary institutions are developing summer bridge programs to aid in their transition. As they develop these programs, effective theory and approach are critical to developing successful programs. Though there are a multitude of theories on successful student development, a focus on self-efficacy is critical. Summer Bridge programs across the country as well as the Bio Bridge summer program at Arizona State University were studied alone and through the lens of Cognitive Self-Efficacy Theory as mentioned in Albert Bandura's "Perceived Self-Efficacy in Cognitive Development and Functioning." Cognitive Self-Efficacy Theory provides a framework for self-efficacy development in academic settings. An analysis of fifteen bridge programs found that a large majority focused on developing academic capabilities and often overlooked development of community and social efficacy. An even larger number failed to focus on personal psychology in managing self-debilitating thought patterns based on published goals. Further, Arizona State University's Bio Bridge program could not be considered successful at developing cognitive self-efficacy or increasing retention as data was inconclusive. However, Bio Bridge was tremendously successful at developing social efficacy and community among participants and faculty. Further research and better evaluative techniques need to be developed to understand the program's effectiveness in cognitive self-efficacy development and retention.
ContributorsTummala, Sailesh Vardhan (Author) / Orchinik, Miles (Thesis director) / Brownell, Sara (Committee member) / Shortlidge, Erin (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2015-05