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