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  Correlation detection as a general mechanism for multisensory integration

Parise, C., & Ernst, M. (2016). Correlation detection as a general mechanism for multisensory integration. Nature Communications, 7: 11543, pp. 1-9. doi:10.1038/ncomms11543.

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Parise, CV1, 2, Autor           
Ernst, MO1, 2, Autor           
Affiliations:
1Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
2Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              

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 Zusammenfassung: The brain efficiently processes multisensory information by selectively combining related signals across the continuous stream of multisensory inputs. To do so, it needs to detect correlation, lag and synchrony across the senses; optimally integrate related information; and dynamically adapt to spatiotemporal conflicts across the senses. Here we show that all these aspects of multisensory perception can be jointly explained by postulating an elementary processing unit akin to the Hassenstein-Reichardt detector-a model originally developed for visual motion perception. This unit, termed the multisensory correlation detector (MCD), integrates related multisensory signals through a set of temporal filters followed by linear combination. Our model can tightly replicate human perception as measured in a series of empirical studies, both novel and previously published. MCDs provide a unified general theory of multisensory processing, which simultaneously explains a wide spectrum of phenomena with a simple, yet physiologically plausible model.

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 Datum: 2016-06
 Publikationsstatus: Erschienen
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 Identifikatoren: DOI: 10.1038/ncomms11543
BibTex Citekey: PariseE2016
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Titel: Nature Communications
  Kurztitel : Nat. Commun.
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: London : Nature Publishing Group
Seiten: - Band / Heft: 7 Artikelnummer: 11543 Start- / Endseite: 1 - 9 Identifikator: ISSN: 2041-1723
CoNE: https://pure.mpg.de/cone/journals/resource/2041-1723