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Teaching with Big Data: Report from the 2016 Society for Neuroscience Teaching Workshop
William Grisham1, Joshua C Brumberg2, Terri Gilbert3
1Psychology Department, University of California, Los Angeles (UCLA), Los Angeles, CA 90095-1563.
Summary
This workshop summary highlights open datasets and resources for teaching neuroscience with big data. It explores challenges and opportunities in neuroinformatics education for undergraduate students.
Area of Science:
- Neuroscience Education
- Neuroinformatics
- Computational Neuroscience
Background:
- Workshops at the Society for Neuroscience annual meetings focus on teaching neuroscience.
- The 2016 workshop specifically addressed "Teaching Neuroscience with Big Data."
Purpose of the Study:
- To summarize the 2016 workshop on teaching neuroscience with big data.
- To highlight available open datasets and resources for undergraduate neuroscience courses.
- To discuss the challenges and potential of neuroinformatics education.
Main Methods:
- Overview of open datasets suitable for teaching undergraduate neuroscience.
- Presentation of existing and novel big data resources.
- Discussion of curriculum development and training initiatives in neuroinformatics.
Main Results:
- Several open datasets were presented, including Allen Brain Atlas, Mouse Brain Library, GeneNetwork, NeuroData, OpenFMRI, NeuroVault, and Neurosynth.
- The iNeuro Project aims to develop curriculum for handling big data in neuroscience.
- Training resources from the International Neuroinformatics Coordinating Facility were discussed.
Conclusions:
- Numerous big data resources have potential for neuroscience education.
- Developing curriculum and training programs is crucial for preparing students in neuroinformatics.
- The feasibility of neuroinformatics programs at undergraduate institutions was explored.
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