Version 33.1 by abonard on 2025/06/13 16:08

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adavison 1.1 1
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abonard 3.1 3 * ((( ==== **[[Beginner >>||anchor = "HBeginner-1"]]** ==== )))
jessicamitchell 2.1 4
abonard 32.1 5 * ((( ==== **[[Advanced >>||anchor = "HAdvanced-1"]]** ==== )))
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abonard 3.1 7 === **Beginner** ===
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abonard 3.1 9 === [[Statistics of spike trains>>https://elephant.readthedocs.io/en/latest/tutorials/statistics.html||rel=" noopener noreferrer" target="_blank"]] ===
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abonard 3.1 11 **Level**: beginner(%%) **Type**: user documentation
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abonard 3.1 13 This notebook provides an overview of the functions provided by the elephant statistics module.
abonard 32.1 14 === **Advanced** ===
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abonard 32.1 16 === [[Spike Pattern Detection and Evaluation (SPADE)>>https://elephant.readthedocs.io/en/latest/tutorials/spade.html||rel=" noopener noreferrer" target="_blank"]] ===
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18 **Level**: advanced(%%) **Type**: user documentation
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20 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.
abonard 33.1 21 === [[The Unitary Events Analysis>>https://elephant.readthedocs.io/en/latest/tutorials/unitary_event_analysis.html||rel=" noopener noreferrer" target="_blank"]] ===
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abonard 33.1 23 **Level**: advanced(%%) **Type**: user documentation
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25 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.
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