Neurobiology is founded in animal behavior and neurons are like little animals themselves – behaving in predictable yet almost limitless ways based on fundamental principles of chemistry and physics. Measuring neural activity involves electronics, computing, crafting, and fine motor skills. Describing neural activity can be as simple as a single number or as complex as abstract math theory. Research implements diverse techniques from histology to electrophysiology to computational modeling.
In my teaching philosophy, student learning shapes instructor teaching by using their interests to stoke novel synthesis of information. I work hard to build tools that afford students the opportunity to explore complex concepts using interactive, data-driven visualizations. One of my favorite tools for supporting student-led learning in neurobiology is Jupyter Notebooks written in Python. Check out my growing collection in Notebooks and on my Github.