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Creators/Authors contains: "Bergin, David"

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  1. ; ; ; ; (, 2021 10th International IEEE/EMBS Conference on Neural Engineering (NER))
    Herein, we describe the implementation of virtual labs that simulate central nervous system functions. The virtual labs use Jupyter Notebooks as a method of distribution. The underlying physiology is implemented using NEURON [8]. Python is used to implement interactive portions of the code without the need to know how to write code. Together, these tools provide a method for engaging students in inquiry-based exploration of neuroscience processes. Additionally, we report that computational tools have potential to engage students and promote inclusion in the research community similarly to students who have a traditional laboratory experience. 
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  2. ; ; ; ; (, IEEE Transactions on Education)
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  3. ; ; ; ; (, Journal of undergraduate neuroscience education)
    We developed an interdisciplinary course in computational neuroscience to address the need for students trained in both biological/psychological and quantitative sciences. Increasingly, exposure to advanced math and physics is important to stay on the cutting edge of developments and research in neuroscience. Additionally, the ability to work in multidisciplinary teams will continue to be an asset as the field develops. This course brings together students from biology, psychology, biochemistry, engineering, physics, and mathematics. The course was designed to highlight the importance of math in understanding fundamental neuroscience concepts and to prepare students for professional careers in neuroscience. They learn neurobiology, via a ‘biology to model and back again’ approach involving wet- and software/modeling-labs, with the latter being the focus of this paper 
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    Accepted Manuscript Full Text Available