Pandemic Teaching: Using the Allen Cell Types Database for Final Semester Projects in an Undergraduate Neurophysiology Lab Course

We designed a final semester research project that allowed students to apply the electrophysiological concepts they learned in a lab course to propose and answer experimental questions without access to laboratory equipment. We created the activity based on lesson plans from Ashley Juavinett and the Allen Institute for Brain Science (AIBS) Allen SDK online examples. An interactive graphic interface was added for students to explore and easily quantify subtle neuronal voltage changes. Before starting the final project, students had experience with conventional extracellular and intracellular recording techniques to record and analyze extracellular action potential firing patterns and intracellular resting, action, and synaptic potentials. They demonstrated their understanding of neural signal transmission in required lab reports using data they gathered before the pandemic shutdown. After students left campus, they continued to analyze data and write lab reports focused on neuronal excitability in snail and fly neurons with data supplied by the instructors. For their final project, students were challenged to answer questions addressing neuronal excitability at both the single neuron and neuronal population level by analyzing and interpreting the open-access, patch clamp recording data from the Allen Cell Types Database using code we provided (Python/Jupyter Notebook). This virtual final semester project allowed students to ask real-world medical and scientific questions from "start to end". Through this project, students developed skills to navigate an extensive online database and gained experience with coding-based data analysis. They chose neuronal populations from human and mouse brains to compare passive properties and neuronal excitability between and within brain areas and across different species and disease states. Additionally, students learned to do simple manipulations of Python code, work remotely in teams, and polish their written scientific presentation skills. This activity could complement other remote learning options such as neuronal simulations. Few online sources offer such a wealth of neuroscience data that students can use for class assignments, and even for research and keystone projects. The activity extends the traditional material often taught in upper-level neuroscience courses, with or without a laboratory section, providing a deeper understanding of the range of excitability properties that neurons express.