Home > Workflow collections > Publication Charges > 3d-SPADE: Significance Evaluation of Spatio-Temporal Patterns of Various Temporal Extents > print

001     864994
005     20240313094936.0
024 7 _ |a 10.1016/j.biosystems.2019.104022
|2 doi
024 7 _ |a 0303-2647
|2 ISSN
024 7 _ |a 1872-8324
|2 ISSN
024 7 _ |a 2128/23043
|2 Handle
024 7 _ |a altmetric:65504483
|2 altmetric
024 7 _ |a pmid:31449837
|2 pmid
024 7 _ |a WOS:000493212900008
|2 WOS
037 _ _ |a FZJ-2019-04571
082 _ _ |a 570
100 1 _ |a Stella, Alessandra
|0 P:(DE-Juel1)171932
|b 0
245 _ _ |a 3d-SPADE: Significance Evaluation of Spatio-Temporal Patterns of Various Temporal Extents
260 _ _ |a Amsterdam [u.a.]
|c 2019
|b Elsevier Science
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1569915118_15941
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a The Spike Pattern Detection and Evaluation (SPADE) analysis is a method to find reoccurring spike patterns in parallel spike train data, and to determine their statistical significance. Here we introduce an extension of the original statistical testing procedure which explicitly accounts for the temporal duration of the patterns. The extension improves the performance in the presence of patterns with different durations, as here demonstrated by application to various synthetic data. We further introduce an implementation of SPADE in form of a sub-module of the Python library Elephant (ELEctroPHysiological ANalysis Toolkit). The code is made publicly available on GitHub, together with detailed documentation, tutorials, and the results presented here.
536 _ _ |a 571 - Connectivity and Activity (POF3-571)
|0 G:(DE-HGF)POF3-571
|c POF3-571
|x 0
|f POF III
536 _ _ |a HBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907)
|0 G:(EU-Grant)785907
|c 785907
|x 1
|f H2020-SGA-FETFLAG-HBP-2017
536 _ _ |a DFG project 238707842 - Kausative Mechanismen mesoskopischer Aktivitätsmuster in der auditorischen Kategorien-Diskrimination (238707842)
|0 G:(GEPRIS)238707842
|c 238707842
|x 2
536 _ _ |a DFG project 322093511 - Kognitive Leistung als Ergebnis koordinierter neuronaler Aktivität in unreifen präfrontal-hippokampalen Netzwerken (322093511)
|0 G:(GEPRIS)322093511
|c 322093511
|x 3
536 _ _ |a GRK 2416 - GRK 2416: MultiSenses-MultiScales: Neue Ansätze zur Aufklärung neuronaler multisensorischer Integration (368482240)
|0 G:(GEPRIS)368482240
|c 368482240
|x 4
588 _ _ |a Dataset connected to CrossRef
700 1 _ |a Quaglio, Pietro
|0 P:(DE-Juel1)164108
|b 1
|e Corresponding author
700 1 _ |a Torre, Emiliano
|0 P:(DE-Juel1)145148
|b 2
700 1 _ |a Grün, Sonja
|0 P:(DE-Juel1)144168
|b 3
773 _ _ |a 10.1016/j.biosystems.2019.104022
|g p. S030326471930053X
|0 PERI:(DE-600)1496359-0
|p 104022
|t Biosystems
|v 185
|y 2019
|x 0303-2647
856 4 _ |u https://juser.fz-juelich.de/record/864994/files/Invoice_OAD0000010690.pdf
856 4 _ |y OpenAccess
|u https://juser.fz-juelich.de/record/864994/files/1-s2.0-S030326471930053X-main.pdf
856 4 _ |x pdfa
|u https://juser.fz-juelich.de/record/864994/files/Invoice_OAD0000010690.pdf?subformat=pdfa
856 4 _ |y OpenAccess
|x pdfa
|u https://juser.fz-juelich.de/record/864994/files/1-s2.0-S030326471930053X-main.pdf?subformat=pdfa
909 C O |o oai:juser.fz-juelich.de:864994
|p openaire
|p open_access
|p OpenAPC
|p driver
|p VDB
|p ec_fundedresources
|p openCost
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)171932
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)164108
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 3
|6 P:(DE-Juel1)144168
913 1 _ |a DE-HGF
|b Key Technologies
|l Decoding the Human Brain
|1 G:(DE-HGF)POF3-570
|0 G:(DE-HGF)POF3-571
|2 G:(DE-HGF)POF3-500
|v Connectivity and Activity
|x 0
|4 G:(DE-HGF)POF
|3 G:(DE-HGF)POF3
914 1 _ |y 2019
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
915 _ _ |a Creative Commons Attribution CC BY 4.0
|0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1040
|2 StatID
|b Zoological Record
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b BIOSYSTEMS : 2017
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
915 _ _ |a WoS
|0 StatID:(DE-HGF)0110
|2 StatID
|b Science Citation Index
915 _ _ |a WoS
|0 StatID:(DE-HGF)0111
|2 StatID
|b Science Citation Index Expanded
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0310
|2 StatID
|b NCBI Molecular Biology Database
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
915 _ _ |a Nationallizenz
|0 StatID:(DE-HGF)0420
|2 StatID
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)INM-6-20090406
|k INM-6
|l Computational and Systems Neuroscience
|x 0
980 1 _ |a APC
980 1 _ |a FullTexts
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)INM-6-20090406
980 _ _ |a APC
981 _ _ |a I:(DE-Juel1)IAS-6-20130828

LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21