Generative Simulations and Statistical Inference with Elephant
This unit introduces the Electrophysiology Analysis Toolkit, Elephant to simulate neurons as Poisson processes, study their statistical properties and apply statistical inference. Learn how to generate spike trains from simulated neurons and compare the observed distribution of spikes and the intervals between them to theoretical Poisson and exponential distributions. The subsequent units focus on two advanced algorithms for detecting patterns of activity in multi-unit recordings: Unitary Event Analysis (UEA) and Spike Pattern Detection and Evaluation (SPADE). While UEA is designed to detect synchronous firing among small ensembles of neurons, SPADE aims at finding recurring patterns among large numbers of simultaneously recorded neurons. Generative simulations allow exploration of how these algorithms perform under different conditions before applying them to actual neural recordings.
Tools
Sessions
Simulating Neurons as Poisson Processes
Use non-stationary Poisson processes to simulate neural spike trains, analyze spike time variability with the coefficient of variation
Detecting Synchronicity with Unitary Event Analysis (UEA)
Detect statistically significant synchronous spiking events across multiple neurons with Unitary Event Analysis
Mining Statistical Patterns with SPADE
Use SPADE to discover recurring patterns of synchronous firing across large populations of neurons with statistical significance testing