SPIKY: A graphical user interface for tracking spike train similarity (Abstract/Poster in rivista)

Type
Label
  • SPIKY: A graphical user interface for tracking spike train similarity (Abstract/Poster in rivista) (literal)
Anno
  • 2014-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1186/1471-2202-15-S1-P201 (literal)
Alternative label
  • Thomas Kreuz; Nebojsa Bozanic (2014)
    SPIKY: A graphical user interface for tracking spike train similarity
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Thomas Kreuz; Nebojsa Bozanic (literal)
Pagina inizio
  • P201 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#altreInformazioni
  • Poster presentation. Part of the supplement: Abstracts from the Twenty Third Annual Computational Neuroscience Meeting: CNS*2014. (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.biomedcentral.com/1471-2202/15/S1/P201 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 15 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 2 (literal)
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  • Suppl1 (literal)
Note
  • Poster (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Institute for Complex Systems, CNR, Sesto Fiorentino, Italy (literal)
Titolo
  • SPIKY: A graphical user interface for tracking spike train similarity (literal)
Abstract
  • Modern electrophysiology is developing fast and it sometimes provides more data than available algorithms and methods can handle and process. In particular, there is an increasing demand for methods which provide the possibility to study similarity patterns of activity across many neurons. Accordingly, a wide variety of approaches to quantify the similarity (or dissimilarity) between two or more spike trains has been suggested. Recently, the ISI- and the SPIKE-distance [1,2] have been proposed as parameter-free and time-scale independent measures of spike train synchrony. The key property of both measures is that they are time-resolved since they rely on instantaneous estimates of spike train dissimilarity. This makes it possible to track changes in instantaneous clustering, i.e., time-localized patterns of (dis)similarity among multiple spike trains. The SPIKE-distance also comes in a causal variant [2] which is defined such that the instantaneous values of dissimilarity are defined from past information only so that time-resolved spike train synchrony can be estimated in real-time. ... ... (literal)
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