Statistical evaluation of synchronous spike patterns extracted by Frequent Item Set Mining
We recently proposed frequent itemset mining (FIM) as a method to perform an optimized search for patterns of synchronous spikes (item sets) in massively parallel spike trains. This search outputs the occurrence count (support) of individual patterns that are not trivially explained by the counts of...
Main Authors: | Emiliano eTorre, David ePicado-Muino, Michael eDenker, Christian eBorgelt, Sonja eGrün |
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Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2013-10-01
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Series: | Frontiers in Computational Neuroscience |
Subjects: | |
Online Access: | http://journal.frontiersin.org/Journal/10.3389/fncom.2013.00132/full |
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