Matching Items (87)
Description
A direct Magnetic Resonance (MR)-based neural activity mapping technique with high spatial and temporal resolution may accelerate studies of brain functional organization.
The most widely used technique for brain functional imaging is functional Magnetic Resonance Image (fMRI). The spatial resolution of fMRI is high. However, fMRI signals are highly influenced by the vasculature in each voxel and can be affected by capillary orientation and vessel size. Functional MRI analysis may, therefore, produce misleading results when voxels are nearby large vessels. Another problem in fMRI is that hemodynamic responses are slower than the neuronal activity. Therefore, temporal resolution is limited in fMRI. Furthermore, the correlation between neural activity and the hemodynamic response is not fully understood. fMRI can only be considered an indirect method of functional brain imaging.
Another MR-based method of functional brain mapping is neuronal current magnetic resonance imaging (ncMRI), which has been studied over several years. However, the amplitude of these neuronal current signals is an order of magnitude smaller than the physiological noise. Works on ncMRI include simulation, phantom experiments, and studies in tissue including isolated ganglia, optic nerves, and human brains. However, ncMRI development has been hampered due to the extremely small signal amplitude, as well as the presence of confounding signals from hemodynamic changes and other physiological noise.
Magnetic Resonance Electrical Impedance Tomography (MREIT) methods could have the potential for the detection of neuronal activity. In this technique, small external currents are applied to a body during MR scans. This current flow produces a magnetic field as well as an electric field. The altered magnetic flux density along the main magnetic field direction caused by this current flow can be obtained from phase images. When there is neural activity, the conductivity of the neural cell membrane changes and the current paths around the neurons change consequently. Neural spiking activity during external current injection, therefore, causes differential phase accumulation in MR data. Statistical analysis methods can be used to identify neuronal-current-induced magnetic field changes.
The most widely used technique for brain functional imaging is functional Magnetic Resonance Image (fMRI). The spatial resolution of fMRI is high. However, fMRI signals are highly influenced by the vasculature in each voxel and can be affected by capillary orientation and vessel size. Functional MRI analysis may, therefore, produce misleading results when voxels are nearby large vessels. Another problem in fMRI is that hemodynamic responses are slower than the neuronal activity. Therefore, temporal resolution is limited in fMRI. Furthermore, the correlation between neural activity and the hemodynamic response is not fully understood. fMRI can only be considered an indirect method of functional brain imaging.
Another MR-based method of functional brain mapping is neuronal current magnetic resonance imaging (ncMRI), which has been studied over several years. However, the amplitude of these neuronal current signals is an order of magnitude smaller than the physiological noise. Works on ncMRI include simulation, phantom experiments, and studies in tissue including isolated ganglia, optic nerves, and human brains. However, ncMRI development has been hampered due to the extremely small signal amplitude, as well as the presence of confounding signals from hemodynamic changes and other physiological noise.
Magnetic Resonance Electrical Impedance Tomography (MREIT) methods could have the potential for the detection of neuronal activity. In this technique, small external currents are applied to a body during MR scans. This current flow produces a magnetic field as well as an electric field. The altered magnetic flux density along the main magnetic field direction caused by this current flow can be obtained from phase images. When there is neural activity, the conductivity of the neural cell membrane changes and the current paths around the neurons change consequently. Neural spiking activity during external current injection, therefore, causes differential phase accumulation in MR data. Statistical analysis methods can be used to identify neuronal-current-induced magnetic field changes.
ContributorsFu, Fanrui (Author) / Sadleir, Rosalind (Thesis advisor) / Kodibagkar, Vikram (Committee member) / Kleim, Jeffrey (Committee member) / Muthuswamy, Jitendran (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2019
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
Abstract. The term "sex trafficking" can mean many different things, depending on who uses it. To some, it may be synonymous with prostitution. To others, it may equate to slavery. And some may find that sex trafficking differs from both slavery and prostitution. But I find that the term "sex trafficking" is used improperly when referring to phenomena that may not entail the violation of rights of any individual involved. For this reason, various definitions of "sex trafficking" may inappropriately conflate sex trafficking with prostitution. In this essay, I argue against such a conflation through supporting a rights-based approach of defining "sex trafficking," in which every instance of true sex trafficking necessitates a violation of someone's rights. First, I begin by laying the foundation of my discussion with definitions and various government and non-government uses of the term "sex trafficking." Then, I argue for the rights-based approach. I proceed to explore how the rights-based approach relates to consent, force, coercion, deception, and competence. Then, I compile my findings, synthesize a definition, and elaborate on a few questions regarding my definition. Using the term "sex trafficking" correctly, as I argue, means that we necessarily use the term in a context of a violation of rights.
ContributorsMiller, Isaac Jonathan (Author) / de Marneffe, Peter (Thesis director) / McGregor, Joan (Committee member) / School of Historical, Philosophical and Religious Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Language, as an abstract, is one of the most sophisticated inventions even devised by human beings. Reading alone is a multi-faceted problem, and understanding how the brain solves it can offer enormous benefits for scientists and language-enthusiasts alike. In order to gain a more complete picture of how language and the brain relate, Chinese, an East Asian logographic language, and English, an alphabetic language, were compared and contrasted using all available scientific literature in both psychology and neuroimaging. Taken together, these findings are used to generalize the processing of written language. It was found that the hypothesis of a neuroplastically adaptable network that recruits brain areas based on the demands of a specific language has stronger support in current research than does the model of a fixed language network that is merely tuned for different languages. These findings reiterate the need for meticulous control of variables in order to reasonably compare language tasks and also demands more precise localization and labeling of brain regions for the purpose of determining function of individual areas.
ContributorsMcCann, Garrett (Author) / Helms Tillery, Stephen (Thesis director) / Azuma, Tamiko (Committee member) / Barrett, The Honors College (Contributor)
Created2014-05
Description
Human subject research is a sensitive ethical topic in today's society, and with good cause. The history of human subject research is full of tragedy and wrongdoing, which is what has led to the firm restrictions we presently have. At the same time, we also acknowledge the value behind human subject research and the information science can obtain from such endeavors. This project analyzes this conundrum through a narrative describing a group of scientists who choose to ignore some of the laws and regulations concerning human subject research in order to pursue neurological based research for a "greater good." In the novella, the scientists end up harming several people while performing their illegal research, but are able to obtain successful results. However, the group is eventually caught, and end up having to face the consequences of their actions. The situations and interactions the story presents are meant to juxtapose both sides of the human subject research ethical argument in a unique way in order to allow the reader to critically think through the argument themselves and form their own opinions on the matter.
ContributorsPirotte, Benjamin Daniel (Author) / Finn, Edward (Thesis director) / Cook, Paul (Committee member) / McGregor, Joan (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor)
Created2015-05
Description
The globalized food system has caused detriments to the environment, to economic justice, and to social and health rights within the food system. Due to an increasing concern over these problems, there has been a popular turn back to a localized food system. Localization's main principle is reconnecting the producer and consumer while advocating for healthy, local, environmentally friendly, and socially just food. I give utilitarian reasons within a Kantian ethical framework to argue that while partaking in a local food system may be morally good, we cannot advocate for localization as a moral obligation. It is true from empirical research that localizing food could solve many of the environmental, economic, social, and health problems that exist today due to the food system. However, many other countries depend upon the import/export system to keep their own poverty rates low and economies thriving. Utilitarian Peter Singer argues that it would be irresponsible to stop our business with those other countries because we would be causing more harm than good. There are reasons to support food localization, and reasons to reject food localization. Food localization is a moral good in respect to the many benefits that it has, yet it is not a moral obligation due to some of the detriments it may itself cause.
ContributorsGulinson, Chelsea Leah (Author) / McGregor, Joan (Thesis director) / Watson, Jeff (Committee member) / Barrett, The Honors College (Contributor) / Department of Psychology (Contributor) / Sandra Day O'Connor College of Law (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor)
Created2015-05
Description
Robotic rehabilitation for upper limb post-stroke recovery is a developing technology. However, there are major issues in the implementation of this type of rehabilitation, issues which decrease efficacy. Two of the major solutions currently being explored to the upper limb post-stroke rehabilitation problem are the use of socially assistive rehabilitative robots, robots which directly interact with patients, and the use of exoskeleton-based systems of rehabilitation. While there is great promise in both of these techniques, they currently lack sufficient efficacy to objectively justify their costs. The overall efficacy to both of these techniques is about the same as conventional therapy, yet each has higher overhead costs that conventional therapy does. However there are associated long-term cost savings in each case, meaning that the actual current viability of either of these techniques is somewhat nebulous. In both cases, the problems which decrease technique viability are largely related to joint action, the interaction between robot and human in completing specific tasks, and issues in robot adaptability that make joint action difficult. As such, the largest part of current research into rehabilitative robotics aims to make robots behave in more "human-like" manners or to bypass the joint action problem entirely.
ContributorsRamakrishna, Vijay Kambhampati (Author) / Helms Tillery, Stephen (Thesis director) / Buneo, Christopher (Committee member) / Barrett, The Honors College (Contributor) / Economics Program in CLAS (Contributor) / W. P. Carey School of Business (Contributor) / School of Life Sciences (Contributor)
Created2015-05
Description
Determining the characteristics of an object during a grasping task requires a combination of mechanoreceptors in the muscles and fingertips. The width of a person's finger aperture during the grasp may affect the accuracy of how that person determines hardness, as well. These experiments aim to investigate how an individual perceives hardness amongst a gradient of varying hardness levels. The trend in the responses is assumed to follow a general psychometric function. This will provide information about subjects' abilities to differentiate between two largely different objects, and their tendencies towards guess-chances upon the presentation of two similar objects. After obtaining this data, it is then important to additionally test varying finger apertures in an object-grasping task. This will allow an insight into the effect of aperture on the obtained psychometric function, thus ultimately providing information about tactile and haptic feedback for further application in neuroprosthetic devices. Three separate experiments were performed in order to test the effect of finger aperture on object hardness differentiation. The first experiment tested a one-finger pressing motion among a hardness gradient of ballistic gelatin cubes. Subjects were asked to compare the hardness of one cube to another, which produced the S-curve that accurately portrayed the psychometric function. The second experiment utilized the Phantom haptic device in a similar setup, using the precision grip grasping motion, instead. This showed a more linear curve; the percentage reported harder increased as the hardness of the second presented cube increased, which was attributed to both the experimental setup limitations and the scale of the general hardness gradient. The third experiment then progressed to test the effect of three finger apertures in the same experimental setup. By providing three separate testing scenarios in the precision grip task, the experiment demonstrated that the level of finger aperture has no significant effect on an individual's ability to perceive hardness.
ContributorsMaestas, Gabrielle Elise (Author) / Helms Tillery, Stephen (Thesis director) / Tanner, Justin (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2015-05
Description
Currently, assistive robots and prosthesis have a difficult time giving and receiving objects to and from humans. While many attempts have been made to program handover scenarios into robotic control algorithms, the algorithms are typically lacking in at least one important feature: intuitiveness, safety, and efficiency. By performing a study to better understand human-to-human handovers, we observe trends that could inspire controllers for object handovers with robots. Ten pairs of human subjects handed over a cellular phone-shaped, instrumented object using a key pinch while 3D force and motion tracking data were recorded. It was observed that during handovers, humans apply a compressive force on the object and employ linear grip force to load force ratios when two agents are grasping an object (referred to as the "mutual grasp period"). Results also suggested that object velocity during the mutual grasp period is driven by the receiver, while the duration of the mutual grasp period is driven by the preference of the slowest agent involved in the handover. Ultimately, these findings will inspire the development of robotic handover controllers to advance seamless physical interactions between humans and robots.
ContributorsChang, Eric (Author) / Helms Tillery, Stephen (Thesis director) / Santos, Veronica (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2015-05
Description
A previous study demonstrated that learning to lift an object is context-based and that in the presence of both the memory and visual cues, the acquired sensorimotor memory to manipulate an object in one context interferes with the performance of the same task in presence of visual information about a different context (Fu et al, 2012).
The purpose of this study is to know whether the primary motor cortex (M1) plays a role in the sensorimotor memory. It was hypothesized that temporary disruption of the M1 following the learning to minimize a tilt using a ‘L’ shaped object would negatively affect the retention of sensorimotor memory and thus reduce interference between the memory acquired in one context and the visual cues to perform the same task in a different context.
Significant findings were shown in blocks 1, 2, and 4. In block 3, subjects displayed insignificant amount of learning. However, it cannot be concluded that there is full interference in block 3. Therefore, looked into 3 effects in statistical analysis: the main effects of the blocks, the main effects of the trials, and the effects of the blocks and trials combined. From the block effects, there is a p-value of 0.001, and from the trial effects, the p-value is less than 0.001. Both of these effects indicate that there is learning occurring. However, when looking at the blocks * trials effects, we see a p-value of 0.002 < 0.05 indicating significant interaction between sensorimotor memories. Based on the results that were found, there is a presence of interference in all the blocks but not enough to justify the use of TMS in order to reduce interference because there is a partial reduction of interference from the control experiment. It is evident that the time delay might be the issue between context switches. By reducing the time delay between block 2 and 3 from 10 minutes to 5 minutes, I will hope to see significant learning to occur from the first trial to the second trial.
The purpose of this study is to know whether the primary motor cortex (M1) plays a role in the sensorimotor memory. It was hypothesized that temporary disruption of the M1 following the learning to minimize a tilt using a ‘L’ shaped object would negatively affect the retention of sensorimotor memory and thus reduce interference between the memory acquired in one context and the visual cues to perform the same task in a different context.
Significant findings were shown in blocks 1, 2, and 4. In block 3, subjects displayed insignificant amount of learning. However, it cannot be concluded that there is full interference in block 3. Therefore, looked into 3 effects in statistical analysis: the main effects of the blocks, the main effects of the trials, and the effects of the blocks and trials combined. From the block effects, there is a p-value of 0.001, and from the trial effects, the p-value is less than 0.001. Both of these effects indicate that there is learning occurring. However, when looking at the blocks * trials effects, we see a p-value of 0.002 < 0.05 indicating significant interaction between sensorimotor memories. Based on the results that were found, there is a presence of interference in all the blocks but not enough to justify the use of TMS in order to reduce interference because there is a partial reduction of interference from the control experiment. It is evident that the time delay might be the issue between context switches. By reducing the time delay between block 2 and 3 from 10 minutes to 5 minutes, I will hope to see significant learning to occur from the first trial to the second trial.
ContributorsHasan, Salman Bashir (Author) / Santello, Marco (Thesis director) / Kleim, Jeffrey (Committee member) / Helms Tillery, Stephen (Committee member) / Barrett, The Honors College (Contributor) / W. P. Carey School of Business (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05