Beginner
Statistics of spike trains
Level: beginner Type: user documentation
This notebook provides an overview of the functions provided by the elephant statistics module.
Advanced
Spike Pattern Detection and Evaluation (SPADE)
Level: advanced Type: user documentation
SPADE is a method to detect repeated spatio-temporal activity patterns in parallel spike train data that occur in excess to chance expectation. In this tutorial, we will use SPADE to detect the simplest type of such patterns, synchronous events that are found across a subset of the neurons considered.
The Unitary Events Analysis
Level: advanced Type: user documentation
The Unitary Event analysis detects coordinated spiking activity that occurs significantly more often than predicted by the firing rates of neurons alone. It’s therefore superior to simple statistics. This tutorial will show you how to use this analysis in Elephant.
Gaussian Process Factor Analysis (GPFA)
Level: advanced Type: user documentation
This tutorial illustrates the usage of the gpfa.GPFA() class implemented in elephant, through its applications to synthetic spike train data, of which the ground truth low-dimensional structure is known.
Time-domain Granger Causality
Level: advanced Type: user documentation
The Granger causality is a method to determine functional connectivity between time-series using autoregressive modelling.
Parallel
Level: advanced Type: user documentation
elephant.parallel module provides a simple interface to parallelize multiple calls to any user-specified function. We showcase a typical use case in this tutorial which is calling a function many times with different parameters.