Learning Objectives

Once you’ve completed this lesson you should be able to:

Spike trains¶

• define spike trains

• explain how spike train data is recorded

• describe two ways of storing spike train data: time series and spike times

• generate two type of visualizations of spike train data: raster plots and peri-stimulus time histograms (PSTHs)

• interpret raster plots and PSTHs with respect to experimental manipulations

• generate 2D heat maps of PSTHs

• work with data sets comprising thousands of rows

• generate correlation matrices of spike train data from multi-unit recordings

Python¶

• create and work with data in lists, NymPy arrays, and pandas DataFrames

• use nested list comprehension

• use subplots to plot multiple levels of data in a single graphic

• generate 2D images from data

Data Visualization¶

• make informed decisions about accessible design in scientific visualization, including color map choice and interpolation methods