Software automation for research and training in neuroscience
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[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Research and training in neural science and engineering is increasingly becoming data-intensive due to the need to integrate and analyze voluminous data being generated at multiple levels including intracellular, cellular, systems, behavior and clinical levels. Effective research also requires the need to access multi-omics data archives, heterogeneous software and computing resources, and seek multi-site interdisciplinary expertise, e.g., engineering, biology and psychology. All this, together with the fact that neuroscience researchers in general lack the background in advanced software tools, makes it important to develop automated and easy to use software tools to aid in both research and teaching in neuroscience. This research proposes software automation tools at both single cell and network levels using several methods. We then use the tools to solve one of the real-world problems involving the coordination of brain waves between two cortical regions.
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