Available tutorials:

Statistics of spike trains

Level: beginner

This notebook provides an overview of the functions provided by the elephant statistics module.

ASSET: Analysis of Sequences of Synchronous Events in Massively Parallel Spike Trains

Level: advanced

The tutorial demonstrates a method of finding patterns of synchronous spike times (synfire chains) which cannot be revealed by measuring neuronal firing rates only.

Gaussian Process Factor Analysis

Level: advanced

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.

Parallel

Level: advanced

elephant.parallel module provides a simple interface to parallelize multiple calls to any user-specified function.

Spike Pattern Detection and Evaluation (SPADE)

Level: advanced

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

The analysis detects coordinated spiking activity that occurs significantly more often than predicted by the firing rates of neurons alone. It’s superior to simple statistics.

Time-domain Granger Causality

Level: advanced

The Granger causality is a method to determine functional connectivity between time-series using autoregressive modelling.