Comparing and Visualizing Neural Spiking Across Different Brain Areas
This unit focuses on computing descriptive statistics and visualizations of neural spiking like firing rates, unit counts, resterplots and peri-stimulus time histograms. You’ll learn how to use the Pandas library to efficiently process data from hundreds of neurons and visualize the results using the Seaborn library. The data for this unit comes from a recent study conducted at the Allen Institute for Brain Science and contains single-unit activities from six different visual areas of the mouse brain. Comparing descriptive firing statistics across units from different areas will allow you to draw interesting connections to the organization of the visual system’s functional hierarchy.
Tools
Sessions
Surveying Neural Spiking in Visual Cortex
Explore spike train data from visual cortex by creating rasterplots, comparing firing rates across brain areas, and performing statistical tests
Relating Neural Firing to Stimuli
Relate neural activity to stimuli through aligning spike times to stimulus presentations and identifying stimulus-responsive units