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- Creators: Hindemith, Paul, 1895-1963
- Creators: Ravel, Maurice, 1875-1937
ContributorsHindemith, Paul, 1895-1963 (Composer)
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
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
With the new independence of adulthood, college students are a group susceptible to adopting unsupported, if not harmful, health practices. A survey of Arizona State University undergraduate students (N=200) was conducted to evaluate supplement use, trust in information sources, and beliefs about supplement regulation. Of those who reported using supplements, college students most frequently received information from friends and family. STEM majors in fields unrelated to health who were taking a supplement were found to be less likely to receive information about the supplement from a medical practitioner than those in health fields or those in non-STEM majors (-26.9%, p=0.018). STEM majors in health-related fields were 15.0% more likely to treat colds and/or cold symptoms with research-supported methods identified from reliable sources, while non-health STEM and non-STEM majors were more likely to take unsupported cold treatments (p=0.010). Surveyed students, regardless of major, also stated they would trust a medical practitioner for supplement advice above other sources (88.0%), and the majority expressed a belief that dietary supplements are approved/regulated by the government (59.8%).
ContributorsPerez, Jacob Tanner (Author) / Hendrickson, Kirstin (Thesis director) / Lefler, Scott (Committee member) / College of Liberal Arts and Sciences (Contributor) / School of Molecular Sciences (Contributor) / Department of Physics (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
ContributorsChandler, N. Kayla (Author) / Neisewander, Janet (Thesis director) / Sanabria, Federico (Committee member) / Olive, M. Foster (Committee member) / Barrett, The Honors College (Contributor) / College of Liberal Arts and Sciences (Contributor)
Created2013-05
Description
I propose that norms regulate behaviors that negatively impact an individual's survival and reproduction. But because monitoring and enforcing of norms can be costly, individuals should be selective about which norms they police and under what circumstances they should do so. Two studies tested this idea by experimentally activating fitness-relevant motives and having participants answer questions about the policing of norms. The first study examined a norm prescribing respect for status and another proscribing sexual coercion. Results from Study 1 failed to support the hypotheses; activating a status-seeking motive did not have the predicted effects on policing of the respect-status norm nor did activating a mating motive have the predicted effects on policing of the respect-status norm or anti-coercion norm. Study 2 examined two new norms, one prescribing that people stay home when sick and the other proscribing people from having sex with another person's partners. Study 2 also manipulated whether self or others were the target of the policing. Study 2 failed to provide support; a disease avoidance motive failed to have effects on policing of the stay home when sick norm. Individuals in a relationship under a mating motive wanted less policing of others for violation of the mate poaching norm than those in a baseline condition, opposite of the predicted effects.
ContributorsSmith, M. Kristopher (Author) / Neuberg, L. Steven (Thesis director) / Presson, Clark (Committee member) / Hruschka, J. Daniel (Committee member) / Barrett, The Honors College (Contributor) / College of Liberal Arts and Sciences (Contributor)
Created2013-05
Description
Literature in public administration emphasizes a growing dissatisfaction with government on the part of residents. Where there tends to be a lack in the literature is in terms of solutions to this problem. We would like to argue that the engagement process itself has the power to foster a profound attitudinal shift on the part of both residents and government. This paper explores the structural and cultural barriers to satisfactory public engagement both from literature and a combination of policy analysis, semi-structured interviews and participatory observation within the City of Tempe. We then provide recommendations to the City of Tempe on how to overcome these barriers and effect authentic public engagement practices. With these new suggested practices and mindsets, we provide a way that people can have the power to create their own community.
ContributorsRiffle, Morgan (Co-author) / Tchida, Celina (Co-author) / Ingram-Waters, Mary (Thesis director) / Grzanka, Patrick (Committee member) / King, Cheryl (Committee member) / Barrett, The Honors College (Contributor) / College of Liberal Arts and Sciences (Contributor)
Created2013-05
Description
This thesis examines the relationship between unofficial, official, and parallel Islam in Uzbekistan following the end of the Soviet Union. Key touchstone moments in Uzbekistan during the twentieth-century show the history between unofficial and official Islam and the resulting precedents set for Muslims gathering against the government. This historical analysis shows how President Karimov and the Uzbek government view and approach Islam in the country following independence.
ContributorsTieslink, Evan (Author) / Batalden, Stephen (Thesis director) / Kefeli, Agnes (Committee member) / Saikia, Yasmin (Committee member) / Barrett, The Honors College (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Politics and Global Studies (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor)
Created2013-05
Description
Through this creative project, I executed a Distracted Driving Awareness Campaign at Arizona State University to raise awareness about the dangers of distracted driving, specifically texting while driving. As an Undergraduate Student Government Senator, my priority is the safety and success of students, both in and out of the classroom. By partnering with State Farm and AT&T, we were able to raise awareness about the dangers of distracted driving and collected over 200 pledges from students to never text and drive.
ContributorsHibbs, Jordan Ashley (Author) / Miller, Clark (Thesis director) / Parmentier, Mary Jane (Committee member) / Barrett, The Honors College (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Politics and Global Studies (Contributor) / Department of Psychology (Contributor) / Graduate College (Contributor)
Created2014-05
Description
Teen dating violence is a significant problem in the U.S., with approximately 1 out of 3 teens experiencing some form of dating violence. BLOOM is a not-for-profit organization created by Donna Bartos. BLOOM's educators enter high schools in Arizona and present their educational program on dating abuse prevention. BLOOM's primary goal is to educate teens on how to prevent teen dating violence and empower them with the skills leading to healthy relationships. After participants complete their educational program, a feedback card is filled out with an open-response section. This project focused on the open response section to analyze feedback cards through a process of code development, coding, and tallying. Information provided by this project could assist BLOOM in re-evaluating their curriculum, appealing to future investors, and growing their program to reach more students. With a coding system in place, BLOOM will also be able to better assess the impact they have on the participants of their program.
ContributorsHarmon, Ashley Nicole (Author) / Bodman, Denise (Thesis director) / Dumka, Larry (Committee member) / T. Denny Sanford School of Social and Family Dynamics (Contributor) / College of Liberal Arts and Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05