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Symposia

A hands-on technical workshop for cognitive neuroscientists

Chair: Bradley Voytek¹; ¹UC San Diego

Data science! GitHub! LLMs and generative AI and scikit-learn and… it feels like there are an overwhelming number of technical skills and technologies to learn in order to succeed in our current data-heavy world. While these technologies are widely used in industry, and are often required for industry data science and research jobs, in this hands-on workshop we will teach how they can be used by cognitive neurosciences. Attendees will be required to bring a laptop so that they can participate in the exercises, where we will show how these technologies can make your scientific research easier to track, make it more efficient, and more reproducible. Specifically, we will introduce Git and explain its esoteric lingo (forking, cloning, pulling, merging, and fetching repos). We will show how GitHub’s project management tools can be used for tracking research projects, and we will demonstrate how GitHub and Jupyter can be used together for scientific reproducibility. Reproducibility will be taught using the “executable papers” model adopted by some publishers, such as eLife, where Jupyter notebooks are published alongside scientific manuscripts. While we will focus on Python, interactive Jupyter notebooks support many programming languages, including Python, R, and Matlab. These notebooks permit the mixture of executable code with graphs and images, as well as detailed textual annotations using Markdown markup language. We will conclude the workshop by walking attendees through a neural data science project, published as an executable notebook, that leverages multiple open neural data sets.

Participants: Quirine van Engen¹, Andrew Bender¹, Eena Kosik¹; ¹UC San Diego