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Articles 1 - 7 of 7
Full-Text Articles in Physical Sciences and Mathematics
A Novel Analytical Method For Studying Pharmacological Treatments For Affective Disorders In Neuroscience, Shane N. Berger
A Novel Analytical Method For Studying Pharmacological Treatments For Affective Disorders In Neuroscience, Shane N. Berger
Theses and Dissertations
Histamine and serotonin are important neurochemicals that maintain crucial brain functions. Both are thought to be altered in affective and neurodegenerative disorders such as depression and Parkinson’s disease. Histamine and serotonin are thought to modulate one another but the exact relationship remains unknown and this gap in knowledge makes diagnosing and treating disorders involving the transmitters difficult. The Hashemi lab studies serotonin neurochemistry to understand serotonin’s role in psychiatric disorders. However, histamine has remained an understudied neurotransmitter due to a lack of analytical tools. In 2015 and 2016, the Hashemi lab pioneered a novel detection method utilizing fast-scan cyclic voltammetry …
Cell Assembly Detection In Low Firing-Rate Spike Train Data, Phan Minh Duc Truong
Cell Assembly Detection In Low Firing-Rate Spike Train Data, Phan Minh Duc Truong
Mathematics Theses and Dissertations
Cell assemblies, defined as groups of neurons forming temporal spike coordination, are thought to be fundamental units supporting major cognitive functions. However, detecting cell assemblies is challenging since they can occur at a range of time scales and with a range of precisions, from synchronous spikes to co-variations in firing rate. In this dissertation, we use a recently published cell assembly detection (CAD) algorithm that is capable of detecting assemblies at a range of time scales and precisions. We first showed that the CAD method can be applied to sparser spike train data than what have previously been reported. This …
Data Assimilation For Conductance-Based Neuronal Models, Matthew Moye
Data Assimilation For Conductance-Based Neuronal Models, Matthew Moye
Dissertations
This dissertation illustrates the use of data assimilation algorithms to estimate unobserved variables and unknown parameters of conductance-based neuronal models. Modern data assimilation (DA) techniques are widely used in climate science and weather prediction, but have only recently begun to be applied in neuroscience. The two main classes of DA techniques are sequential methods and variational methods. Throughout this work, twin experiments, where the data is synthetically generated from output of the model, are used to validate use of these techniques for conductance-based models observing only the voltage trace. In Chapter 1, these techniques are described in detail and the …
Oscillations Via Excitable Cells, Derek Orr, Bard Ermentrout
Oscillations Via Excitable Cells, Derek Orr, Bard Ermentrout
Biology and Medicine Through Mathematics Conference
No abstract provided.
Modeling Of Pmv Neuronal Circuitry In Adaptive Changes Of Energy Balance, Pilhwa Lee, Cristina Saenz De Miera, Nicole Bellefontaine, Kevin W. Williams, Renata Frazao, Carol Elias
Modeling Of Pmv Neuronal Circuitry In Adaptive Changes Of Energy Balance, Pilhwa Lee, Cristina Saenz De Miera, Nicole Bellefontaine, Kevin W. Williams, Renata Frazao, Carol Elias
Biology and Medicine Through Mathematics Conference
No abstract provided.
Geometry-Based Estimates Of Glutamate Transporter Density In Astrocytes, Anca R. Radulescu, Cassandra Williams, Annalisa Scimemi
Geometry-Based Estimates Of Glutamate Transporter Density In Astrocytes, Anca R. Radulescu, Cassandra Williams, Annalisa Scimemi
Biology and Medicine Through Mathematics Conference
No abstract provided.
Mechanisms Of Value-Biased Prioritization In Fast Sensorimotor Decision Making, Kivilcim Afacan-Seref
Mechanisms Of Value-Biased Prioritization In Fast Sensorimotor Decision Making, Kivilcim Afacan-Seref
Dissertations and Theses
In dynamic environments, split-second sensorimotor decisions must be prioritized according to potential payoffs to maximize overall rewards. The impact of relative value on deliberative perceptual judgments has been examined extensively, but relatively little is known about value-biasing mechanisms in the common situation where physical evidence is strong but the time to act is severely limited. This research examines the behavioral and electrophysiological indices of how value biases split-second perceptual decisions and the possible mechanisms underlying the process. In prominent decision models, a noisy but statistically stationary representation of sensory evidence is integrated over time to an action-triggering bound, and value-biases …